In this study, we propose a method for generating highly accurate high-density point clouds of piping facilities using an unmanned aerial vehicle (UAV) laser scanner and a handheld laser scanner. The point cloud for each scanline measured by the UAV scanner is repositioned on the piping axis, and the handheld scanner’s 3D point cloud is subsequently registered so that the center axis of the piping coincides with the UAV point cloud as a reference. The method proposed in this study was used to accurately reconstruct linear piping measured in high winds, which can easily deteriorate measurement accuracy. Whereas the conventional method incurred a deviation of 44.3 mm between the predicted and true values at altitudes of 15 m, the proposed method reduced this deviation to 19.4 mm. An application of the registration method demonstrated that the combined use of the two laser scanners enabled the creation of a high-density point cloud.

The geothermal power plants in Japan have a low plant capacity factor. In the geothermal power plant under study, a problem is that the pressure of the steam production wells frequently drops suddenly. The plant operators have recovered the steam production well to a stable state through the valve operation based on their experience when the well is unstable. However, the same operation, such as opening a valve, may result in a decrease in reservoir pressure which can be accelerated depending on the reservoir recharge conditions. The objective of this study was to examine wellhead valves operation to prevent sudden pressure drop. This study developed a machine learning (ML) model to predict time-series of steam enthalpy from inputs such as valve openings using Temporal Fusion Transformer (TFT) architecture. The ML model was confirmed to function as a simulator to predict the behavior of the steam enthalpy when the valve openings are varied. The ML model was also able to detect the rapid enthalpy decrease from 25 hours before the happened. Furthermore, we confirmed that the ML model can sequentially evaluate whether changing the valve openings stabilized the reservoir conditions. Future studies should validate and extend these findings from diverse perspectives.

Drones, whose applications have been rapidly expanding in recent years, have a wide range of uses, such as transporting goods, spraying pesticides, inspecting structures, and even flying cars, which have become a hot topic in recent years. However, it is difficult to fly in bad weather such as gusty winds. To solve these problems, flight stability has been controlled by manipulating the rotation speed of the propeller. However, it is not desirable to use a propeller for flight stability in bad weather conditions. Therefore, the authors developed a drone equipped with a CMG(Control Moment Gyro), which has the property of rotating in a direction perpendicular to the force applied to the axis of rotation from the outside, and confirmed the suppression effect of pitch angle fluctuation through experiments. In this paper, based on these findings, we developed and tested a drone equipped with two CMGs that can suppress the variation of pitch and roll angles. As a result, the variation of pitch and roll angles without CMGs was 20 degrees and 25 degrees, respectively, while the variation of pitch and roll angles with CMGs was 12 degrees and 16 degrees, respectively. In the case of the CMG, the pitch and roll angles fluctuated by 20 and 25 degrees, respectively. In addition, it is necessary to operate the controller to keep the drone as level as possible before applying disturbance, and we confirmed that the variation of pitch angle and roll angle with CMG is less than that without CMG.

Hydrogen production using variable renewable energy surplus electricity that called Power-to-Gas is attracting attention as a grid stabilization technology. However, there is an issue that Power-to-Gas is low economically viable to use only for stabilizing of variable renewable energy output. The objective of this article is to evaluate the economic efficiency of the Power-to-Gas system based on the optimal operation strategies by using electricity from both an on-site photovoltaic system and an electric power exchange market, assuming a specific situation in Japan in the near future. The Power-to-Gas plant considered in this article consists of a 1 MW proton exchange membrane electrolyser cell, which has already started demonstration tests, a hydrogen storage tank, and a 3 MW photovoltaic system. An operational planning problem of the plant to optimize the annual hydrogen production schedule is formulated as a mixed-integer linear programming problem, and the economic efficiency is evaluated using the optimized unit price of hydrogen production as an evaluation index. The result shows that the hydrogen unit price is improved by using the power exchange market in addition to on-site photovoltaic due to the improvement of the utilization rate of cell. Case 1 with no constraints of hydrogen storage which has a large impact on hydrogen unit price marks 46.8 JPY/NM3 of the best hydrogen unit price, and Case 2-1, in which a fixed amount of hydrogen is produced continuously and transported by gas piping, improves 5.8 JPY/Nm3 of the hydrogen unit price compared to Case 2-2, in which batch transportation by a loader. From the sensitivity analysis of varying the depreciation cost of electrolyser cell and the price of the power market, it was concluded that the target unit cost of hydrogen production of less than 30 JPY/Nm3 can be obtained by decreasing the depreciation cost of the cell by 50% and the price of the market by 30%.

When there is a surplus of electricity from variable renewable energy (VRE), the conversion factor of the grid becomes very low. Therefore, a well-timed conversion of electricity to heat using thermal storage cooling systems driven by surplus electricity is expected to reduce annual cumulative CO2 emissions. Therefore, if the CO2 emission factors for different periods can be obtained explicitly, the operation can be planned to minimize CO2 emissions. In this study, we evaluated how much the district cooling (DC) system which has ice storage tank can contribute to the reduction of CO2 emission by comparing reduction in CO2 emissions with and without the use of an ice storage tank. First, we created a CO2 emission factor that varies on an hourly basis, reflecting the operating conditions of the facilities that make up the energy mix. We then derived the optimal operation strategy for the DC system every 15 min to minimize CO2 emissions. The amount of CO2 emissions reduced by operating the refrigerator at a time when the CO2 emission factor was low and storing the cold heat in the thermal storage tank was clarified. By analysing the results of the optimal operation during the cooling demand period, we found that the CO2 emission reduction effect of heat storage was higher on days when the daily variance of the CO2 emission factor was large. Furthermore, sensitivity analyses suggest that a larger heat source machine is more effective in reducing CO2 emissions than a larger heat storage tank.

The introduction of variable renewable energy (VRE) has been expanded, with the goal of reducing CO2 emissions. In anticipation of the expansion of VRE and increases in demand for hydrogen supplies, demonstration experiments are in progress for power-to-gas (P2G) systems, as these do not emit CO2 during hydrogen production and use surplus VRE power. However, the economic viability of P2G systems is currently poor, hindering their widespread use, and it is necessary to clarify the target value of the equipment costs to make them economically viable. In this study, a P2G system comprising a polymer electrolyte membrane electrolysis cell (PEMEC) using both photovoltaic power and power from the electric power exchange market was used as an example to clarify the cost factors for achieving economic feasibility. The cost of hydrogen production was optimized by setting conditions reflecting the parameters of the demonstration site. The optimal solution was formulated using mixed-integer linear programming, with minimization of the equipment costs and electricity consumption as the objective function. As a result, it was confirmed that a unit cost of hydrogen production of 0.278 USD/Nm3 or less, i.e., the target for Japan by FY2030, can be achieved by reducing the equipment cost of the PEMEC by 50%.

This paper proposes the generalized energy management method responding to demand response (DR) events in which the proposed method eliminates as much prior knowledge about the process as possible. The proposed method has the two functions of multihorizon forecasting and operational planning. The quantile regression by a transformer-based network architecture with interpretable self-attention predicts demand time-series, which is supplied by the energy system, and electricity time-series consumed by the energy system, in the case that DR event does not occur. This electricity time-series is used to consider curtailment potential during DR. The method optimizes the daily ahead dispatching planning of the energy system by a binary quadratic optimization problem solved on quantum-inspired annealing machine. This paper takes into account the water distribution system (WDS) as an energy system in numerical experiments. The proposed method represents a total of 107 controllable pumps belonging to 20 pumping stations by 10,272 binary variables. An operational planning problem for WDS is constructed with pumps grouped in 40 distribution reservoirs and an operational strategy for a DR event that 1 MW curtailment of electricity consumption for three hours is derived. As a result, it is obtained that an operational strategy that successfully completes a given DR event can be derived.

The high-definition (HD) map is widely used in autonomous driving to acquire correct road information during driving. At the same time, the HD map also needs to be updated promptly when road changes happen, such as establishing new traffic signs or the expansion of road lanes. Therefore, building a system that automatically detects road change areas is an essential issue need to be solved. In this paper, we had improved the accuracy of road sign detection then investigated change detection methods. We confirmed a proposed method to correct the position and orientation of the vehicle in real-time using road lanes detected from images with other data.

The introduction of Power-to-Gas systems that actively use renewable energy to produce hydrogen is expected to expand. To achieve this, there is an urgent need to reduce the unit cost of hydrogen production. It is necessary to operate the system under the optimal operation strategy while forecasting the ever-changing spot price and solar power generation. Currently, the method of sequentially deriving and controlling operational measures is computationally burdensome. In this paper, we report the effectiveness of a simple control rule derived by analyzing the annual optimal operation strategy with the technique of decision tree derived for the purpose of cost minimization.

The paper reports a method to improve the accuracy of radiation thermometry by infrared thermo-camera equipped on a small UAV (Unmanned Aerial Vehicle), eliminating the disturbances in the outdoor environment. In this study, the authors are developing a system for detecting anomalies associated with the deterioration of piping equipment in a geothermal power plant. However, it was challenging to obtain accuracy with an infrared thermo-camera due to the significant influence of external radiation disturbance such as solar radiation and sky reflection in an outdoor environment. We proposed models of compensating for those disturbances. Those improved the accuracy to detect anomalies of the facility by considering the characteristics of emissivity and reflected radiation in the measurement. Consequently, by thermal model corresponding to the effect of solar radiation and sky reflection, we confirmed that the infrared thermo-camera on UAV could accurately detect temperature anomalies in plant facilities, even in an outdoor environment.

In a geothermal power plant, the soundness of the pipeline is an essential factor that could influence power generation efficiency. However, it is laborious and dangerous for staff to inspect the condition of the pipeline. Therefore, we have developed a system that can conduct inspections automatically by using a small unmanned aerial vehicle (UAV) equipped with Laser Imaging Detection and Ranging (LiDAR). In this research, we focus on increasing point clouds' accuracy and improving the efficiency of inspection route generation. The experimental results show that our system could detect less than 25 mm misalignment and estimate UAV attitude less than 0.05 deg. Furthermore, the efficient inspection route could improve abnormalities detection accuracy from 66.8% to 75.8%.

The energy transition toward carbon neutrality in 2050 is progressing, and attention is being paid to demand-side energy resources to absorb the fluctuations in the output of variable renewable energy. The objective of this research is to construct an easy-to-adopt methodology for virtual power plants that the method can be adopted for arbitrary demand-side energy resources such as district heating and cooling system and water distribution system by using a part of measured process variable values, to respond against demand response signal in any time. The proposed VPP method is composed of a process modelling method for an optimal operational planning problem and a time series forecasting method as well as an optimization algorithm that fulfils the requirements of a given demand response event. This paper represents the three models to identify input-output characteristics of demand-side energy resources. Quadratic polynomials, piecewise linear approximation and discretization by basis coding are taken up as models and their respective characteristics are discussed.

We started investigation of a proving test equipment development which corresponds to field device tool (FDT (R), IEC62453) ver. 3.0 (FDT 3.0) to study theoretically the issues of field device level requirements for industrial smart system design. We select carbon emission data international trade system using European secure data-sharing platform GAIA-X as the target future production system which utilizes FDT3.0. We created a proving test equipment architecture for all automation industry domain including process automation (PA) and factory automation (FA). Manufacturing Execution Systems (MES) study part of the proving test equipment for FA side is constructed and demonstrated at IIFES2022 in collaboration with IAF. We will continue our research to show the use cases which utilizes device data effectively.

Polymer electrolyte fuel cell cogeneration systems (PEFC-CGSs) provide hot water by utilizing exhaust heat produced in electricity generation process. The energy saving potential of PEFC-CGSs can be maximized by optimal operational plans, and most state-of-the-art approaches implement operational planning function (OPF) based on energy demand time-series prediction by using machine learning techniques. In general, prediction of demand time-series with small expected average errors is regarded as the most important point in obtaining appropriate operational plans; however, several recent studies have revealed that other complex factors such as the direction and timing of forecast errors greatly affect the quality of operational plans in some cases. Core ideas proposed in these previous studies are broadly classified into seven types. The purpose of this study is to characterize these OPFs from the two aspects: the output form of prediction model and prediction target variable, and to clarify "what kind of uncertainty should be focused on" and "how this uncertainty should be handled" in designing OPF. The seven kinds of OPFs were comprehensively evaluated via numerical simulations using real-world data. The results show the significance of OPF based on prediction of expected operational cost surface using multiple output prediction model. (C) 2021 The Authors. Published by Elsevier B.V.

Energy-conversion systems are optimized in three stages: synthesis (structure, configuration), design (operating characteristics at the rated load), and operation. The performance of energy systems, including the thermal efficiency, can be improved by increasing the complexity of the cycle configuration. Therefore, when two thermodynamic cycles are compared, they must be evaluated at the same level of their complexity. The SYNTHSEP methodology, which presents a general procedure to derive a complex thermodynamic cycle configuration operating with a pure working fluid, has been proposed in the literature. In this methodology, a cycle configuration is represented as a superimposition of elementary thermodynamic cycles (ETC), consisting of four basic processes (compression, heating, expansion, and cooling). This methodology has been formulated and codified for the derivation of candidate configurations, which are then narrowed down to the effective candidates. The complexity of the cycle configuration can be expressed by the number of elementary thermodynamic cycles. In previous works, the authors expanded the methodology to cover the absorption refrigeration cycle, which is also represented by superimposing elementary thermodynamic cycles operating with different working fluids. The purpose of this paper is to propose a revised methodology for configuration optimization that can be applied to any absorption cycle, including absorption power cycles, such as the Kalina cycle. The cycle complexity defined using a cycle simplicity index based on the number of ETCs and the number of mixing and splitting points of the ETC. The authors have derived candidate configurations for the simplest absorption cycle, defined by this index. Then, the proposed methodology for configuration optimization is demonstrated by performing a case study on an absorption power cycle and refrigeration cycle. Thus, designers can compare the configurations of absorption power and cooling or heating cycles with certified simplicity. This study establishes a methodology for configuration optimization and maximizes an objective function for an arbitrary absorption cycle. In principle, this methodology can also be applied to the absorption power and cooling cycle.

To achieve increased stability in industrial control systems (ICS) and reduction in maintenance cost, the asset management application in addition to control application is evaluated important. In that situation, device data must be integrated to upper layer in a standardized way under various field networks and field devices environment. FDT (IEC62453) is a standard technology which allows integration of devices and networks to engineering tools, e.g. for ICS asset management systems. FDT can integrate device data to upper layer in a standardized way regardless of process automation or factory automation. Recently FDT technology is upgraded to FDT3.0 (FDT version 3) which enables the FDT IIoT Server™ (FITS™) concept. This paper focuses the device data utilization use case analysis for FDT technology in ICS. We show concrete image of use cases and several benefits obtained from FDT technology in which FDT3.0 realizes attractive role in IIoT for device integration in ICS.

District heating and cooling (DHC) systems have attracted interest in reducing CO2 emissions. A fifth-generation DHC (5GDHC) system that supplies a heat-transport medium at a temperature close to the ground and uses various unused heat sources is proposed. Meanwhile, some DHC systems installed in Japan are first-generation DHC (1GDHC) systems that use fossil fuels as a heat source. Based on these scenarios, this study focuses on the energy-saving effects of introducing a CO2 network system in Tokyo, which is based on the same concepts as the 5GDHC systems. The purpose of this study is to estimate the utility value of unused heat sources for the CO2 network system. An analytical model is developed that calculates the energy consumption of the system under exogenous conditions, such as those for energy consumers and heat sources. Applying a model to a domestic urban area in Tokyo, where a conventional 1GDHC system was introduced, it was confirmed that for a total head of groundwater of 50 m, river water of 10 m, and sewage water of 10 m, the potential annual CO2 reduction is approximately 5,000 ton/y compared with the 1GDHC system. These values are feasible in Tokyo, and therefore, this system looks promising.

This paper proposes a method for detecting non-line-of-sight (NLOS) multipath, which causes large positioning errors in a global navigation satellite system (GNSS). We use GNSS signal correlation output, which is the most primitive GNSS signal processing output, to detect NLOS multipath based on machine learning. The shape of the multi-correlator outputs is distorted due to the NLOS multipath. The features of the shape of the multi-correlator are used to discriminate the NLOS multipath. We implement two supervised learning methods, a support vector machine (SVM) and a neural network (NN), and compare their performance. In addition, we also propose an automated method of collecting training data for LOS and NLOS signals of machine learning. The evaluation of the proposed NLOS detection method in an urban environment confirmed that NN was better than SVM, and 97.7% of NLOS signals were correctly discriminated.

In a geothermal power plant, the soundness of steam-pipeline is an essential factor that could influence power generation efficiency. However, it is laborious and dangerous for staff to inspect the state of pipes. Therefore, authors have developed a system that automatically conducts inspections using a small unmanned aerial vehicle (UAV) equipped with Laser Imaging Detection and Ranging (LiDAR) and RGB/Infrared Rays camera. In this research, authors focus on misalignment, deformation, surface colour change, temperature change detection on piping. The authors propose a piping model in the 3D-map generated by the UAV to detect these abnormal sections in pipes. The experimental results show that our system could detect misalignment less than 25 mm in horizontal view on the straight pipeline and deformation larger than 2 cm. Recall of colour-changing detection on the test was 96.2%, and the result of temperature-changing detection on dummy data also show the effectiveness of our methods.

This study aimed to apply the essence of human navigation methodology to autonomous vehicles with an abstracted schematic floor map image without using a high-precision pre-map such as SLAM. First, we transformed the captured floor map image into a cognitive feature map represented by cognitive features. Self-position estimation and path planning should be done efficiently with the cognitive feature map. Next, we converted the sensing data of the moving object into cognitive features and mapped the position and posture of the moving object in the moving space to the position and posture in the cognitive feature map. In addition, after extracting the branches to be passed to the destination using the attribute information obtained from the floor map, we appropriately placed the sub-goals in the moving space and drove along the road. In the virtual environment, a virtual vehicle equipped with a stereo camera and an encoder was used for navigation using the proposed method. Even if the self-position estimation is inaccurate temporally, the proposed method does not interfere with the navigation because it controls the vehicle by running along the road.

The 5th-generation district heating and cooling (5GDHC) system has been attracting attention as a district heating and cooling system that contributes to the integrated use of energy to realize a decarbonized society. 5GDHC system transports a heat transport medium near ambient temperature to specific areas, enabling the bi-directional exchange of energy between the supply and demand sides. In this paper, the value of unused heat resources that can be used as a heat source of 5GDHC system is organized as temporal and spatial characteristics of exergy to be used as design information of 5GDHC system. The results are reported as the conditions for matching the demand characteristics with the unused heat resources that can reduce the annual CO₂ emissions the most in a specific area where 5GDHC system is to be installed.

The introduction of variable renewable energy (VRE) has been increasing to reduce CO2 emissions. With the rapid introduction of VREs, it is necessary to take measures against excess power generation to stabilize the power system. Hydrogen production using VRE surplus electricity that called Power-to-Gas (P2G), is attracting attention as a new means. However, it has been reported that P2G is low economically viable when introduced as a countermeasure for VRE surplus power, and improving the economics of P2G systems is the issue. In this study, two methods of procuring electricity to the P2G plant will be used: one is electricity generated by photovoltaic (PV) panels annexed the P2G plant, and the other is electricity purchased from the Electric Power Exchange (EPX). By using these two methods together, the authors will increase the operating ratio of the P2G plant and study the economics when producing hydrogen in a stable manner. The target P2G plant consists of a 1 MW proton exchange membrane electrolyzer cell (PEMEC), a hydrogen storage tank, and 3 MW PV. In this study, three conditions are assumed for the power used for P2G: only EPX, only PV, and the combination of EPX and PV. For each case, the economically optimal operation that minimizes the operating cost is derived using mixed integer linear programming. Results of Japan's FY2019 estimates, it was confirmed that the hydrogen production by using both PV and EPX to procure electricity for the P2G system has the effect of lowering the unit price of hydrogen production by 1.51-15.1 yen/Nm3 compared with the case of PV only. Based on the results for FY2019, the authors derived the assumed unit cost of hydrogen in 2030 when electricity is procured using both PV and EPX and confirmed that it can be kept below the target of 30 yen/Nm3

The smart energy grid is expected to have a mechanism that demand-side and supply-side get managed onto the whole energy grid to balance. The research question is which energy management architecture is suitable to operate a large-scale energy system within a specific limited time step for computing and communicating. The previous work has proposed a hierarchical management method, which handles local status in the demand-side Energy Management System layer and global status in the aggregation layer. The hierarchical method appeals to scalable, robust, and privacy protection merits compared to a centralized method. The performance of hierarchical management, including demand forecast, is still an open question. This article shows on incorporating energy demand forecast into the hierarchical management method. The paper also evaluates the energy storage capacity needed to balance under the effect on forecast error of energy demand.

Some production wells of geothermal power plants sometimes shut down unintentionally. Before the unintentional shutdown, unstable fluctuations in pressure and flow rate at the wellhead are observed. Because of the difficulties in observing the ground, it is constrained to predict the performance of the steam at the wellhead. If the abrupt shutdown symptoms can be detected and the shutdown prevented, then the power generation continuation can be achieved. The authors have proposed a method for detecting anomalies using 1-Dimensional convolutional neural networks (1D-CNN) to predict this phenomenon. There is an empirical rule that opening the bypass valve can prevent a sudden pressure drop. It is necessary to conduct a comparative experiment between cases relevant to valve operation. This comparative experiment is difficult to conduct because the condition of the well differs from case to case, and therefore the authors could not measure it. Thus, the authors proposed another 1D-CNN model to predict the pressure at the wellhead. It was verified that this model steadily predicts the pressure performance several hours in advance. Consequently, the authors can virtually compare the past measured data with the predicted data to investigate the validity of the valve operation.

Virtual Power Plant (VPP) is a power grid stabilization technology which responds demand response (DR) signal for management of demand-side energy resources. Our research group has intended to construct widely applicable VPP system to several types of demand-side energy resources such as generator, load, and storage. From those resources, existing heat pump (HP) and thermal storage tank (TST) onto residential, commercial, and industrial sectors are attractive energy resources to DR because it is easy to shift peak power by storage. The difficulty of VPP depends on system configuration to compensate for forecast error, for example, whether the system has a backup power source, whether the system has enough buffer or not. In this context, the difficulty of the system consisting of HP and TST is that it generally does not have a backup power source, so it is necessary to improve the accuracy of demand forecast and to develop operational strategy with sufficient supply capacity. The paper shows the concept that extending our previous works on VPP management method, the paper proposes to add a function block of operation guidance to help operator's decision making in DR periods.

District heating and cooling (DHC) systems have attracted interest in reducing CO2 emissions, and a 5th-generation DHC (5GDHC) is being proposed in Europe, which supplies a heat-transport medium at ambient temperature and utilizes various unused heat sources. 5GDHC systems have the characteristics of being nonlinear, bi-directional and decentralized. The CO2 network system has similar concepts in these aspects, but the system adopts CO2 refrigerant as heat-transport medium and uses the latent heat of vaporization of CO2 refrigerant to transport and exchange unused heat to specific areas via decentralized heat pumps (DHPs). Previous studies have confirmed that the CO2 network system can reduce the total annual energy consumption by up to 80% compared to the conventional 1st-generation DHC (1GDHC) system using fossil fuels as heat source in Japan. In this study, evaluation of the CO2 network system, properly storing surplus variable renewable energy (VRE) into storage tanks (STs), is clarified by a flexible grid operation. In addition, it is confirmed that the “zero CO2 emission” can be achieved by the CO2 network with STs in optimal operation. The effectiveness of the CO2 network system with STs is quantified compared to the 1GDHC system.

In this study, we develop a system for efficiently measuring detailed information of trees in a forest environment using a small unmanned aerial vehicle (UAV) equipped with light detection and ranging (lidar). The main purpose of forest measurement is to predict the volume of wood for harvesting and delineating forest boundaries by tree location. Herein, we pro-pose a method for extracting the position, number of trees, and vertical height of trees from a set of three-dimensional (3D) point clouds acquired by a UAV lidar system. The point cloud obtained from a UAV is dense in the tree’s crown, and the trunk 3D points are sparse because the crown of the tree obstructs the laser beam. Therefore, it is difficult to extract single-tree information from 3D point clouds because the characteristics of 3D point clouds differ significantly from those of conventional 3D point clouds using ground-based laser scanners. In this study, we segment the forest point cloud into three regions with different densities of point clouds, i.e., canopy, trunk, and ground, and process each region individually to extract the target information. By comparing a ground laser survey and the proposed method in an actual forest environment, it is discovered that the number of trees in an area measuring 100 m × 100 m is 94.6% of the total number of trees. The root mean square error of the tree position is 0.3 m, whereas that of the vertical height is 2.3 m, indicating that single-tree information can be measured with sufficient accuracy for forest manage-ment.

The lunar surface is directly and continuously exposed to Galactic Cosmic ray (GCR) particles and Solar energetic particles (SEPs) due to the lack of atmosphere and lunar magnetic field. These charged particles interact with the lunar surface materials producing secondary radiations such as neutrons and gamma rays. In a departure from precise GCR and SEP data, we estimated the effective dose equivalent at the lunar surface and in a lunar lava tube in this paper by using PHITS, a Monte Carlo simulation tool. The effective dose equivalent due to GCR particles at the lunar surface reached 416.0 mSv yr-1 and that due to SEPs reached 2190 mSv/event. On the other hand, the vertical hole of the lava tube provides significant radiation protection. The exposure by GCR particles at the bottom of the vertical hole with a depth of 43 m was found to be below 30 mSv yr-1 while inside a horizontal lava tube, the value was less than 1 mSv yr-1 which is the reference value for human exposure on the Earth. We expect that the lunar holes will be useful components in the practical design of a lunar base to reduce radiation risk and to expand mission terms.

© 2020 The Society of Instrument and Control Engineers - SICE. The supply-demand adjustment market in Japan will be opened in 2021, and it is expected to contribute to a virtual power plant (VPP) to gather distributed energy resources even from residential sector. The problem is to integrate residential sector that respond differently depending on the characteristics of each household, with keeping protecting consumer privacy. This article proposes a hierarchical management method that realizes VPP in residential sector. The proposed framework meets the requirements to join a market. The proposed method gets evaluated in numerical experiments. We aim to aggregate 1 MW controllable electricity with 4, 000 detached household. The results show that the proposed method could achieve an amount of electricity of the procurement target in computing time of 10 minutes.

© 2020, Springer-Verlag GmbH Germany, part of Springer Nature. Urban environments present significant challenges to global navigation satellite system (GNSS) positioning. GNSS signals are often obstructed by buildings and other obstacles, leading to reflection and diffraction, which cause major line-of-sight (LOS) and non-line-of-sight (NLOS) multipath positioning errors. We propose a new, precise GNSS positioning technique that can simultaneously mitigate LOS and NLOS multipath errors by rotating the GNSS antenna arm horizontally at a certain angular velocity. The key idea behind this technique is to use the antenna motion to mitigate the LOS multipath effect and detect the NLOS multipath signals. The relative carrier phase between the direct signal and the multipath signal frequently changes when a GNSS antenna is moving. As a result, the effect that the strong reflected signal affects the direct signal can be reduced. We use this characteristic to mitigate LOS multipath errors by generating antenna motion. By rotating a GNSS antenna, the Doppler frequency is produced by the antenna motion. If the received GNSS signal is the NLOS signal, the direction of incoming signals is different from that of direct signals. In this situation, the phase of the generated Doppler frequency will be different, and NLOS signals can be detected by comparison with the ideal Doppler frequency. We conducted an experiment to evaluate the proposed method. The positioning error of the proposed method using LOS multipath mitigation and NLOS exclusion by the rotating antenna was decreased from 18.96 to 2.83 m. In addition, the availability of GNSS positioning increased from 44.29 to 100%.

The purpose of this study is to examine the feasibility of 100 % renewable energy systems in the residential area. The boundary of the residential area was a set of “all-electric houses” that have electric vehicles, photovoltaic and heat pump water heaters. In each case, we derive the power self-sufficiency ratio and power self-consumption ratio by photovoltaic defined by the boundary. Comparing the presence or absence of power interchange, in the case of electricity interchange, the photovoltaic surplus in a home that does not stay the electric vehicle in the daytime can be charged to another home's electric vehicles and used for power supply at night. It was confirmed that the power interchange in residential areas has the effect of increasing the self-sufficiency ratio by up to 14.0 % and the self-consumption ratio of electricity by up to 15.7 % and reducing the annual CO2 emission by up to 18.3 %. In comparison with regional characteristics, in areas where there are many commuting electric vehicles such as the sub-urban area, the electric vehicle does not stay home in the daytime, and the photovoltaic power generation cannot be charged. Therefore, the effect of the photovoltaic - electric vehicles system on the realization of RE100 is small. When there are multiple electric vehicles in one household as in the rural area, it was confirmed that the photovoltaic - electric vehicles system was effective in realizing RE100 by introducing mega solar in the area.

Localization and navigation are an important factor for autonomous mobile robots. As progress in CPU and GPU performance has been made, scan matching can be the major method of localization. Before scan matching, a dense map of the activity area is necessary, and to do path planning, the coordinate value of self-position and goal is efficient. However, we don’t need such map nor coordinate value. Even in environment never been to, we can reach to the destination if there are sign symbols showing the direction of the destination in the route even if the sign does not show the precise direction. This paper proposes a method using the name and direction of the destination, scan data of the wall, and odometry calculated from encoder and IMU. This method was tested in 2 courses in a 3D simulation environment representing Shinagawa station made by Gazebo. As a result, the robot model was able to reach goal-1 without any help, and goal-2 with 0.8 times help by human in average.

The use of GNSS(Global Navigation Satellite System) has become common worldwide. However, in urban environment, the positioning accuracy of GNSS is lowered by the effect of multipath. There are two types of multipath, LOS multipath and NLOS multipath, and effective countermeasures are required for both. We propose a method using a rotating antenna or antenna switching. The arrival direction of the satellite signal is obtained from the doppler shift generated with the movement of the antenna. Then, the direction of arrival of the signal and the arrangement of the satellite are compared to judge the NLOS, and reject from the positioning calculation. The effect of LOS multipath is averaged by moving the antenna. As an experimental equipment, in the rotating antenna technique, GNSS antenna and receiver are mounted on the rotating arm. In the antenna switching technique, multiple GNSS antennas are switched by elements. By using this technique, the positioning rate of the rotating antenna increased from 0.23% to 100%. In another test, the positioning rate increased from 40.74% to 93.86% using the switching antenna.

In order to contribute to electricity supply and demand adjustment, consolidation of household responses is essential. A typical example of adjustment power is the preheating/precooling operation of air conditioners in houses. The operation model of an air conditioner requires an understanding of the insulation and heat storage characteristics of a housing. However, it is difficult to precisely model the detailed energy use of each household. In this study, we propose a framework to derive an optimal operation plan for residential air conditioner pre-heating and pre-cooling operation using a system identification method. The purpose of this study is to estimate the coordinating electricity for 500 households and to clarify the combination of the insulation and heat storage characteristics of the equipment and the housing, which contribute to the adjustment of power supply and demand, from the power saving plan selected by the aggregator. As a result, it was shown that the load estimation model of the residential air conditioner identified could derive a response to demand response while maintaining the comfort of level of residents. Also, the results of consolidation of 500 households showed that the pre-heating and pre-cooling of the air conditioner was selected secondarily after the heat pump water heater and that the higher the heat insulation performance, the lower the power saving and the lower the incentive price.

Positioning accuracy of global navigation satellite system (GNSS) is deteriorates when non-line-of-sight (NLOS) multipath signals are received in urban environments. Therefore, it is important to determine satellite visibility and reject NLOS satellites from positioning calculation to improve positioning accuracy. In this paper, we focus on a correlation waveform which is affected by multipath signals. To detect NLOS multipath signals, we use convolutional neural networks (CNN) for machine learning to generate the NLOS discriminator. From the evaluations of proposed method, the global positioning system (GPS) accuracy of satellite visibility determination by using the CNN was 98.0 %. In addition, the GPS accuracy of NLOS satellites determination by using the CNN was 97.9 %. Similarly, GLONASS, Galileo and BeiDou accuracy of it were about 90 %. We confirmed the effectiveness of the proposed method with experiments in urban environments by comparing with conventional method.The positioning accuracy without NLOS signals is also improved compared with the conventional positioning method in urban environments.

This paper describes a small unmanned aerial vehicle (UAV) attitude estimation method using multiple global navigation satellite system (GNSS) doppler. In 3D measurement by a UAV with light detection and ranging (LiDAR), it is most important to estimate UAV attitude precisely. We have been developed a UAV with a LiDAR and six GNSS receivers to generate a 3D map. By using the developed method, we can estimate UAV attitude with 0.2 deg accuracy. And we also have been developed a UAV attitude estimation method with six GNSS receivers and inertial measurement unit (IMU). By using this method, we can estimate UAV attitude with 0.1 deg accuracy. However, in these previous researches, system configuration tends to be complicated by using IMU other than six GNSS receivers. Therefore, we now propose a UAV attitude estimation method with about same accuracy without using IMU by using only six GNSS receivers. In proposed method, we focus on GNSS doppler that we did not use in previous method. By calculating UAV angular velocity using multiple GNSS doppler and using it with Kalman Filter, we achieved 3D measurement in 55.4 mm horizontal Root Mean Square (RMS) error. In addition, by using six GNSS antenna positions that we did not use in the previous method with Extended Kalman Filter (EKF), we achieved 3D measurement in 54.3 mm horizontal RMS error.

In recent years, “CO2 network system” has been proposed by researchers in EPFL, Switzerland. The system uses the latent heat of CO2 refrigerant to transport and exchange unused heat to specific areas by employing distributed heat pumps on demandside. The purpose of this study is to derivate of optimum equipment configuration of the decentralized heat pump and the CO2 temperature supplying to the network from the central plant for the cooling/heating ratio of demand. In this report, first, we analyzed the effect of the cooling/heating ratio of demand and the temperature of CO2 refrigerant on the performance of CO2 network system. As a result, we found that when the cooling/heating ratio of demand is 1.13 or more, the connection pattern in which CO2 supplied from the network and indoor air exchange heat directly was optimal for the air conditioner for cooling. In other cases, the connection pattern in which CO2 supplied from the network was directly used as the refrigerant for the decentralized heat pump was suitable. Second, we calculated the annual energy consumption using the derived optimal CO2 temperature supplying to the network from the central plant for typical energy demand in urban areas in Japan where a district heating and cooling system using steam and chilled water as a heat transport medium was introduced. It was clarified that when the CO2 temperature supplying to the network from the central plant was constant at 12 °C for a year, the electricity consumption was almost the same as that when the CO2 temperature was set optimally.

The SYNTHSEP methodology that presents a general procedure to derive a complex system configuration of thermodynamic systems operating with a pure working fluid has been proposed by A.Lazzaretto and A.Toffolo et., al. Designers focus on a set of fundamental thermodynamic processes (compression, heating, expansion, cooling) in the flowsheet which is called “basic configuration” in this methodology. The basic configuration is defined by aggregating certain elementary thermodynamic cycles. In previous studies, this technology was applied to absorption refrigeration cycle by K.Seki et., al, in case of waterlithium bromide system as working fluids pair. By aggregating certain elementary thermodynamic cycles, the cycle configuration and operating point equivalent to the absorption refrigerator which had been considered optimal were demonstrated by case study. Based on these works, this research aims to apply the SYNTHSEP methodology to generate basic configurations of an absorption power cycle. In a case study, elementary cycles are operated with an ammonia-water mixture. Demonstration of the proposed method for optimization is shown by performing a case study for an absorption power cycle in which thermal efficiency is regarded as a system product. Calculated solutions are evaluated by comparing with publicly available solutions of an existing design.

Demand Response (DR) that controls energy consumption based on a margin of power supply capability has been drawing increasing attention. In the residential sector, however, aggregators have to aggregate saving power because the capacity of saving power per customer is less than the industrial sector. Because of this, improving the calculation time that is spent on deriving an operation plan is necessary. Therefore, we derive operation plans using Convolutional Neural Network (CNN). And then, we analyze the classifier to clear up the efficient operational logic of residential energy equipment. We target a household that an air conditioner and polymer electrolyte fuel cell co-generation system (PEFC-CGS) are installed. To create CNN that reduces operational cost, we added a term for the operational cost to the loss function which is used during learning. After that, we analyze constructed CNN by LIME (Local Interpretable Model-agnostic Explanations). As a result, an average relative error rate from the optimal result is decreased to 5.67 %. We found that the hot water demand, the amount of remaining hot water and operation state have a big impact on the operation plan of PEFC while the electricity demand has no impact on it.

To reduce CO₂ emissions in the residential sector, the installation of high-efficiency energy supply equipment and the development of smart residential buildings are progressing. It is important to appropriately select energy system configuration, such as the number of installing equipment and capacity, for rational energy use. The purpose of this study is to analyze the trends of the relationship between optimal configuration and household characteristics. After that, we evaluate and analyze the derived configuration from a long-term perspective. We assumed the smart residential building consisted of 50 dwelling units, installs photovoltaics and battery as shared assets, and can power-sharing. Also, we assumed each household must install any one of 3 types of thermal equipment, which is a gas-fired water heater, heat pump water heater (HPWH), and solid oxide fuel cell cogeneration systems (SOFC). As a result, all the households select HPWH after 2025. Focusing on the number of occupants, the increased tendency to install HPWH before 2025 correlates with the number of occupants. In the long-term evaluation, the system configuration consisted of 35 HPWH and 15 SOFC is best from the viewpoint of CO₂ emissions. The configuration can reduce 21.9 % CO₂ emissions from 2020 to 2030.

In japan, robot technology for efficient tunnel inspection is required. MIMM is one of the tunnel inspection systems using robot technology. To find the deformation of the tunnel surface, it is required to analyze the difference between the two periods survey result. For that purpose, it is necessary to aligns two point clouds in precisely. But the cumulative error is caused by GNSS/IMU positioning system make it difficult to align two point clouds. Hence, there are needs for more precise positioning system for tunnel survey. Our purpose is to perform high-accuracy positioning system for tunnel survey. We proposed a new positioning method using tunnel facilities. Through evaluation test, it was confirmed that the accuracy of the proposed method was higher than that of the conventional method. In this paper, we detail to the method and evaluation test result.

Reducing CO₂ emissions by the effective use of renewable energy is one of the most important issues around the world. Therefore, many researchers have analyzed not only the development of individual high-performance equipment, but also the area-wide energy utilization systems. One of the area-wide energy utilization systems is a district heating and cooling system. However, conventional systems that utilize the steam and chilled water produced by the boiler and the chiller have some issues. Hence, the CO₂ network system has been proposed by researchers in EPFL, Switzerland. The system uses the latent heat of CO₂ refrigerant to transport and exchange unused heat to specific areas by employing decentralized heat pumps on demand-side. The proposed system is expected to significantly reduce energy consumption compared with the conventional system. In this paper, we analyzed the energy-saving effect by introducing the system to Japan based on CO₂ emissions reduction in 2030. As a result, it was confirmed that the annual energy consumption and CO₂ emissions resulting from equipment operation could be reduced by about 80% and 60% compared with the conventional system. By using the surplus electric power from renewable energy as the power supply source of the proposed system, it contributes to the construction of the optimal system for energy interchange.

This study analyzes a temperature condition that produces maximal power from a non-isothermal heat source under a finite number of heat-recovery thermodynamic cycles. Some previous studies have theoretically analyzed a system utilizing thermal energy from heat sources under multiple thermodynamic cycles assuming a constant heat-source temperature. However, many heat sources for heat-recovery thermodynamic cycles are non-isothermal, where the temperature changes considerably during heat exchange with the cycles. Therefore, it is necessary to consider the temperature change of the heat source. First, a condition that maximizes the power generated by a combination of single/multiple Carnot cycles from constant-specific-heat heat sources is analyzed, and the optimal temperature is derived analytically. Subsequently, simulations of the Rankine cycle and several patterns of the Kalina cycle are compared with those of the analytical model. These comparisons reveal that the proposed model effectively estimates the condition for heat-recovery cycles that produce maximal power from a non-isothermal heat source. Using the proposed method, the required number of cycles and their operating conditions under a given heat source condition are estimated, without any information about cycle configurations, types of working fluids, and iteration of simulation calculation under inappropriate conditions. In addition, a systematic exploration of the optimal system can be started from the proper initial condition.

This study proposes a novel operational planning method for polymer electrolyte fuel cell cogeneration systems (PEFC-CGSs). PEFC-CGSs provide hot water by utilizing waste heat produced in the electricity generation process, and hot water is stored in an attached tank. Generating and storing hot water based on an optimal operational plan according to household demand leads to further energy saving; therefore, operational planning methods based on household demand prediction have received significant attention. However, the improvement in the demand prediction accuracy does not necessarily lead to efficient PEFC-CGS operation in terms of operational costs; in other words, the accuracy in the demand prediction does not directly indicate the resulting operational efficiency. In this study, the authors propose a novel approach based on a surrogate model for deriving an appropriate plan that minimizes the expected operational costs among the operational plan candidates. In the proposed scheme, the error between expected and actual operational costs explicitly represents the relevance of the operational plan, so that the optimal operational plan can be selected directly from the perspective of the resulting operational efficiency. The practicality of the proposed approach is evaluated with the existing demand prediction-based approach via numerical simulations using real-world measurements of multiple customers in Japan. The proposed method reveals 30% reduction of the excessive operational costs by avoiding the inefficient operation of the auxiliary gas-heater in the experiments and will further enhance the value of introducing highly efficient residential fuel cell system that contributes to a low-carbon society.

© ECOS 2020.All right reserved. The demand response (DR), which balances power supply and demand, is attracting attention as a method of absorbing fluctuations in renewable energy when output is unstable. Since the Great East Japan Earthquake in 2011, Japan has made progress toward the liberalization of electricity and the introduction of renewable energy. In 2021, a supply and demand adjustment market will be opened. Unlike companies and factories, which can control large amounts of power for long periods, household demand has a small capacity and is short term. However, household demand is expected to be able to respond quickly to emergencies and to secure capacity by consolidating multiple households via an aggregator. This study concerns two problems in assessing town-scale residential DR capability. First, we evaluate residential DR response capacity. This capacity is assumed to be pre-cooling heating by an air conditioner according to thermal insulation and heat capacity characteristics, and energy storage by a hot water storage tank and a power storage device. Next, we investigate implementing the optimization of the town-scale DR by an aggregator. Optimal town-scale aggregation proposals are often formulated in large-scale combinatorial optimization problems. The challenge is that the calculation tends to be time-consuming and difficult to solve. In this research, we propose a framework that can be solved at high speed using digital annealer. Finally, we evaluate the possibility of town-scale residential DR in specific areas of Tokyo.

© ECOS 2020.All right reserved. The utilization of "100% renewable energy" has recently attracted considerable interest in view of the objective of achieving a low-carbon society. An approach that seems effective to realize this goal is the purchase of renewable electricity from the power grid. However, the amount of renewable electricity that the power grid can supply at various seasons and periods is limited. In view of this, it is necessary to consider the use of energy systems that can exploit renewable energy, such as the installation of photovoltaics in households. The purpose of this study is to investigate the feasibility of 100% renewable energy systems in residential areas and multi-dwelling buildings. The area and building examined are limited to a set of "all-electric houses" with electric vehicles, photovoltaics, and heat pump water heaters. In each case, the electricity self-sufficiency ratio and electricity self-consumption ratio resulting from the use of photovoltaics are derived. In this study, an operation that minimizes CO2 emissions during the evaluation period is developed. It is found that the use of 100% renewable energy in residential areas without relying on the renewable electricity from the power grid is possible as demonstrated by the high feasibility of using 100% renewable energy in rural areas. In multidwelling buildings, this feasibility is lower than that in residential areas. To achieve the utilization of 100% renewable energy using the renewable electricity from the power grid, the grid should increase its supply of renewable electricity at dawn and in the evening. In winter, the renewable electricity from the photovoltaic power alone is insufficient; hence, the power grid requires other renewable electricity sources, such as windgenerated power. To improve the electricity self-sufficiency ratio of multi-dwelling buildings, the use of an energy system that allows electricity sharing from the residential areas to multi-dwelling buildings is found effective.

© ECOS 2020.All right reserved. The article develops and demonstrates the fractional optimization to evaluate the environmental efficiency of the regional-scale energy system with heat pumping and thermal storage. The fractional optimization gets converted into the equivalent quadratic one via the proposed iterative algorithm. The proposed method makes converting a fractional equation into a different one with an auxiliary variable, and it makes us free from heuristic parameter tuning that makes balancing the weight of objective coefficient when the objective function is composed of some terms. We consider the operational planning problem of the mixed energy grid, including electricity and heat. It manages power generations and a heat pump with thermal storage as an application. The numerical studies take into account the open data measured by the most western region of Japan, where the region gets applied the installation/connection of variable renewable energy sources of 25.7 GW at the moment even not every capacity starts operation. As a result, the CO2conversion factor reaches 0.21 kg-CO2/kWh in the best case. It is confirmed that a heat pump with thermal storage can absorb the electrical output from variable renewable energy sources up to 2.72 TWh/y.

© ECOS 2020.All right reserved. Reducing CO2emissions by the effective use of renewable energy is one of the most important issues globally. Therefore, research has focused on both the development of individual high-performance equipment and also district heating and cooling systems. In Japan, installations of the conventional district heating and cooling system, which utilizes steam and chilled water, are rare. In recent years, a promising alternative, the CO2network system, has been proposed by researchers at Swiss Federal Institute of Technology in Lausanne. The system uses the latent heat of vaporization of the CO2refrigerant to transport and exchange unused heat to specific areas via decentralized heat pumps on the demand-side. The proposed system is expected to significantly reduce energy consumption compared with the conventional system. In this study, we analyzed the energy-saving effects of introducing a CO2network system in Tokyo, with consideration of the environmental conditions and the typical energy demand profiles. The effects of modifying the central unit and the demand-side decentralized heat pump systems were examined in the context of Tokyo. When using the CO2network, the annual energy consumption resulting from equipment operation can be reduced by approximately 80% compared with the conventional system. This effect is almost of the same magnitude as the effect observed in previous research conducted in Switzerland. Furthermore, we examined the optimum connection pattern of the decentralized heat pumps and the optimum temperature of the CO2supplied to the network.

© ECOS 2020.All right reserved. The objective of the research is to develop an optimal management and control framework to contribute to improving the capacity factor of the geothermal power plant. As the initial consideration of the study, the article aims to identify the phenomenon that causes to decrease capacity factor from the analysis of a process data, to detect the phenomenon to support the decision-making of operators. For achieving the latter goal, we construct the framework that announces the operator to how much anomaly with a convolutional neural network model, which can capture non-stationary and nonlinearity of process data. Through the literature survey and the analysis of the process data, we confirmed that the steam flow rate and pressure of wellbore having two feed zones oscillate, and the wellbore reached the spurts stop of the steam due to oscillation growth. We confirmed that the pressure-drop events occurred six times in 2018, and it would be one of the causes to decrease capacity factor. As numerical results of the proposed framework, before the pressure-drop happens, they are increased that the amplitude of the second harmonic wave, the period of the first harmonic wave, and the anomaly score we derived. We could conclude that the pressure-drop, as mentioned above indexes made by the proposed method, could predict the pressure-drop at the one minute ahead, even in the case that pressure time-series have the nature of non-stationarity and nonlinearity.

© ECOS 2020.All right reserved. The SYNTHSEP methodology that presents a general procedure to derive a complex system configuration of thermodynamic systems operating with a pure working fluid was proposed by A. Lazzaretto and A. Toffolo et al. In this methodology, the designers focus on a set of fundamental thermodynamic processes (compression, heating, expansion, and cooling) in the flowsheet, which is called as the "basic configuration", and it is defined by aggregating certain elementary thermodynamic cycles. In previous studies, this methodology was applied to the absorption refrigeration cycle by Seki et al. for a water-lithium bromide system used as a working fluid pair. By aggregating certain elementary thermodynamic cycles, the cycle configuration and operating point equivalent to the absorption refrigerator that had been considered optimal were demonstrated by a case study. Based on these works, this study redefines a part of the bottom-up synthesis methodology to apply to an absorption power system. In a case study considered for this research, elementary thermodynamic cycles were operated with an ammonia-water mixture. The proposed methodology for optimization is demonstrated by performing a case study for an absorption power cycle with thermal efficiency as an objective function.

© 2020 Proceedings of the 33rd International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2020. All rights reserved. In global navigation satellite system (GNSS) positioning, GNSS satellites are often obstructed by buildings, leading to reflected and diffracted signals, which are known as non-line-of-sight (NLOS) signals. Such signals cause major GNSS positioning (also known as “NLOS multipath”) errors. In this paper, a novel NLOS multipath detection technique using a machine-learning approach to improve the positioning accuracy in urban environments is proposed. The key idea behind this technique is to construct a classifier that discriminates NLOS multipath signals from the output of the multiple GNSS signal correlators of a software GNSS receiver. In the case of an NLOS signal, there are no direct signals; the first reflected signal has low power compared to a direct signal. Hence, the correlation function is expected to be more distorted in the case of an NLOS signal correlation. We use this phenomenon to detect NLOS signals. To consider the change in shape of the correlation values of NLOS signals and their temporal variation, we propose a method for constructing a convolutional neural network (CNN)-based NLOS discriminator. Furthermore, we propose a method for applying the NLOS probability, which is the output of the CNN, to the positioning calculation. To evaluate the proposed technique, we conducted NLOS classification experiments using signal correlation data acquired at different locations in the Shinjuku area of Japan. We compared the proposed method with a method using a simple NN. As the experiment results indicate, the proposed method can correctly discriminate approximately 98% of NLOS multipath signals, and the discrimination rate of the proposed CNN-based method is higher than that of the simple NN-based approach. Furthermore, we improved the positioning accuracy from 34.1 to 1.6 m using the proposed method and concluded that the proposed approach can increase the positioning accuracy in urban environments.

© 2019 IEEE. This study proposes a hot water demand prediction method for operational planning of polymer electrolyte fuel cell cogeneration systems (PEFC-CGSs). PEFC-CGSs provide hot water by utilizing waste heat produced in the electricity generation process. An optimal operational plan according to household demand leads to further energy saving. Therefore, operational planning methods based on household demand prediction have received intense focus. In particular, the prediction of the amount of hot water demand is important for efficient operation. The authors have attempted to improve the hot water prediction method based on multivariate random forest (MRF), which uses the average of many decision trees' outputs as the prediction result. However, some experimental results show that a prediction strategy based on averaging the outputs of decision trees does not always lead to the best solution. In this study, the authors propose a novel prediction method utilizing the quantile of the estimation results derived in MRF. By setting the appropriate quantile, we can evade the demand underestimation, which has a higher negative impact on operational efficiency than overestimation. The usefulness of the proposed approach is evaluated via numerical simulations using real-world demand data.

© 2019 IEEE. Small-sized unmanned aerial vehicles (UAVs) have been widely investigated for use in a variety of applications such as remote sensing and aerial surveying. Direct three-dimensional (3D) mapping using a small-sized UAV equipped with a laser scanner is required for numerous remote sensing applications. In direct 3D mapping, the precise information about the position and attitude of the UAV is necessary for constructing 3D maps. In this study, we propose a novel and robust technique for estimating the position and attitude of small-sized UAVs by employing multiple low-cost and light-weight global navigation satellite system (GNSS) antennas/receivers. Using the 'redundancy'' of multiple GNSS receivers, we enhance the performance of real-time kinematic (RTK)-GNSS by employing single-frequency GNSS receivers. This method consists of two approaches: hybrid GNSS fix solutions and consistency examination of the GNSS signal strength. The fix rate of RTK-GNSS using single-frequency GNSS receivers can be highly enhanced to combine multiple RTK-GNSS to fix solutions in the multiple antennas. In addition, positioning accuracy and fix rate can be further enhanced to detect multipath signals by using multiple GNSS antennas. In this study, we developed a prototype UAV that is equipped with six GNSS antennas /receivers. From the static test results, we conclude that the proposed technique can enhance the accuracy of the position and attitude estimation in multipath environments. From the flight test, the proposed system could generate a 3D map with an accuracy of 5 cm.

© 2019 John Wiley & Sons, Ltd. This paper deals with the development and operation of a mechanical vapor recompression (MVR) desalination system with improved energy efficiency in harnessing wind energy, which is non-dispatchable. Its design, construction, and operation details are presented in this paper. Especially, the main focus of developing the system was on the operation of the system in conjunction with variable loads of new and renewable power sources, in particular, varying wind power. That is, the present work has been carried out to assess the feasibility of its operation in light of capacity modulation to match the power generated under various wind speeds. Optimal operation modes of the system were studied, in which single- and double-effect operations were analyzed for their improvement in energy efficiency. The compression ratio of the proposed MVR system was 1.55 at an inverter speed of 55 Hz, which agreed well with its design value. Operation of the main heat exchanger remained stable within the limits of its operable range, although the temperature differences in the main heat exchanger did not remain constant because of the pressure variations in the evaporator. The daily freshwater yield was between 28 and 51 tons. The power consumption per ton of freshwater produced was about 43 kW for a single effect and about 23 kW for a double effect, which is about twice as efficient.

© 2019 IEEE. This study proposes an operation planning method for polymer electrolyte fuel cell cogeneration systems (PEFC-CGSs). PEFC-CGSs provide hot water by utilizing waste heat produced in the electricity generation process. An appropriate operation plan according to household demand will lead to further energy saving. The authors have discussed a framework for estimating expected operation costs of individual operation plans to select an appropriate candidate that minimizes the cost. In this scheme, the expected cost under each corresponding operation was independently estimated. This approach can be expected to provide accurate prediction of costs under individual operations. However, one open issue remains; it may not work well in estimating relative goodness compared to other operations. In this study, the authors propose a new cost estimation approach, focusing on relative appropriateness in candidate plans based on a multiple output prediction. The usefulness of the proposed approach is proved via a numerical simulation.

© 2019 by the authors. Optimal design of energy systems ultimately aims to develop a methodology to realize an energy system that utilizes available resources to generate maximum product with minimum components. For this aim, several researches attempt to decide the optimal system configuration as a problem of decomposing each energy system into primitive process elements. Then, they search the optimal combination sequentially from the minimum number of constituent elements. This paper proposes a bottom-up procedure to define and explore configurations by combining elementary processes for energy systems with absorption technology, which is widely applied as a heat driven technology and important for improving system’s energy efficiency and utilizing alternative energy resources. Two examples of application are presented to show the capability of the proposed methodology to find basic configurations that can generate the maximum product. The demonstration shows that the existing absorption systems, which would be calculated based on the experience of designers, could be derived by performing optimization with the synthesis methodology automatically under the simplified/idealized operating conditions. The proposed bottom-up methodology is significant for realizing an optimized absorption system. With this methodology, engineers will be able to predict all possible configurations and identify a simple yet feasible optimal system configuration.

To achieve a goal of CO₂ emissions reduction by 2030, the installation of high-efficiency energy supply equipment is progressing in Japan. Thus, many researchers have analyzed replacing scenario of such equipment that maximizes the effect of installing it. For example, the effects of efficiency and cost of energy supply equipment on diffusion process were reported. However, sensitivity analysis of scale of demand is insufficient. The purpose of this study is to derive the optimal configuration of energy systems in a household of the various scale of demand for the minimization of annual CO₂ emissions from 2016 to 2030. In addition, we analyze the effects of replacing year on CO₂ emissions from 2016 to 2030. As a result, polymer electrolyte fuel cell (PEFC) is the optimal equipment reducing CO₂ emissions in regardless of the demand scale when CO₂ conversion factor of the electrical grid is 0.474 kg-CO₂/kWh. So as the heat pump water heater (HPWH) is the optimal equipment reducing CO₂ emissions regardless of the demand scale when CO₂ conversion factor of the electrical grid is 0.370 kg-CO₂/kWh. In addition, replacing gas boiler with HPWH and installation of photovoltaics can reduce approximately 60 % of CO₂ emissions in 2030.

This paper describes a method of azimuth angle estimation using RTK-GNSS and gyroscope on a small unmanned aerial vehicle (UAV). Recently, a power line and steel tower inspection using UAV is attracted at electric power companies. However, azimuth angle cannot be estimated due to the high magnetic field in the vicinity of the power line. We propose a method to estimate azimuth angle by combining RTK-GNSS and gyroscope with Kalman filter. As a result, the proposal method has the same azimuth angle estimation accuracy as the method using the magnetic sensor in the static test. In the high magnetic field environment, the proposed method could stably estimate the azimuth angle. We implemented an autonomous flight test with a UAV incorporating our proposed method. As a result, even during the flight, the proposed method was able to estimate the azimuth angle equivalent to that using a magnetic sensor.

Real-time kinematic (RTK) positioning is a GNSS positioning technique that can provide precise position within several centimeters of accuracy. In general, it is more difficult to solve GNSS carrier-phase ambiguities using RTK-GNSS in multipath environments with a low-cost single-frequency GNSS receiver than with an expensive dual-frequency GNSS receiver. The purpose of this work is to improve the accuracy of single-frequency RTK-GNSS positioning. The proposed technique consists of two approaches. The first approach is the autonomous selection of the GNSS signals used for RTK-GNSS positioning. We select satellite signals depending on their quality, which can be identified by signal strength. The second approach combines the GNSS Doppler velocity to resolve the integer ambiguities. To estimate more precise initial position and covariance of RTK-GNSS, we use the previous fixed solution and the Doppler velocity. Extending the open-source RTKLIB software for RTK-GNSS positioning, we confirm the effectiveness of the proposed technique.

This paper describes a real-time 3D measurement technique using multiple global navigation satellite system (GNSS) receivers and antennas on a small unmanned aerial vehicle (UAV). At disaster sites, rapid 3D measurement is highly required. However, in our previous research, it took time to generate a 3D map because the computation process after a flight of the UAV was needed. In addition, this technique needs 30 position calculations to estimate the UAV attitude. Accordingly, it is difficult to estimate the attitude using an onboard computer in real time. Therefore, we propose a method using six GNSS antenna positions to estimate the UAV attitude. Because the proposed method can reduce position calculations, it can be used for real-time UAV attitude estimation. Then in the proposed system, we use robot operating system (ROS) to build distributed system. By using the proposed system, we achieved real-time 3D measurement in 151.7 mm horizontal root mean square (RMS) error and 4.8 mm vertical RMS error.

In most cases, many sensors are used in autonomous robots for self-position estimation to acquire detailed coordinate values, create a dense map, and implement map-matching. However, though human being doesn’t use coordinate values, it is easy to head toward the destination. There are many parameters human being uses for self-position estimation. Among them, we focus on scenery change in this paper, and propose a method of self-position estimation using sparse scenery information. In order to detect scenery change, we quantitated scenery information by using SegNet and named the value VQ (Visual Quality). First, we verified that the similarity of a VQ wave would be high in the same rout. Next, we used VQ and classes of semantic segmentation, and SIFT (Scale-Invariant Feature Transform) to implement selfposition estimation. As a result, the accuracy was enough and VQ can be used as a parameter for self-position estimation.

In this paper, we aim to build a citywide energy system evaluation platform to build a decentralized energy management system. The built evaluation platform automatically build a mixed-integer optimization model based on the information of each household from the scenario settings to be evaluated, and derive the optimal operation plan and the optimal operation result. The optimization problem is constrained by heat, energy and mass balance entering and leaving the equipment installed in the home and binary variables that indicate the operating conditions. The energy demand of a house is given as an exogenous variable, but the demand for electricity and hot water is generated from household composition information. And the demand for heating and cooling is estimated from the heat network model consisting of the thermal characteristics of the house. Using this evaluation platform, we conducted a concrete case study on 4,383 detached houses in Komae, Tokyo. We set a basic scenario in which only a part of households was introduced solar power and a scenario in which all households were introduced solar power toward 2030. As a result, it was shown that CO₂ emissions can be reduced by about 45.6% compared to fiscal 2017 in the scenario of 100% photovoltaic power generation penetration rate.

© ECOS 2019 - Proceedings of the 32nd International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems. All rights reserved. For a daily-basis scheduling of an energy system, energy management system often enough to use not a global optimal scheduling but a near optimal scheduling. The article proposes an online scheduling framework without online optimization. The framework is built from two encoder-decoder architectures to extract features of time series; a multi-layer long short-term memory regression model for multi-step time-series forecasting, and multi-class and single-label classification model for on/off scheduling of a device. The models are estimated at offline, and return scheduling from historical time series as input, at online. We evaluate the accuracy of scheduling from the viewpoint of Kullback-Leibler divergence which measures the dissimilarity between two probability distributions. Through the numerical experiments, we demonstrate the usefulness of the proposed framework.

© 2019 Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems.All rights reserved. It is extremely difficult to conduct fundamental research on optimizing the system configuration and design parameters of energy conversion systems because many parameters need to be considered. This study ultimately aims to develop a methodology for realizing an energy system that utilizes available resources to generate a maximum product that employs the minimum number of components. Several studies have been conducted to find an optimal system configuration by decomposing energy systems into primitive process elements and sequentially searching for the optimal combination that uses the minimum number of constituent elements. This paper proposes a bottom-up methodology for defining and exploring configurations that combine elementary processes of energy systems with absorption technology. Absorption technology is a widely applied heat driven technology that is important for improving the energy efficiency of systems and also utilizes alternative energy resources. A specific procedure using a codification method is presented that generates new candidate configurations for the absorption system with respect to the optimization problem and enables an optimization algorithm to be used to implement the organized rules. When applying the proposed methodology to optimization, designers should narrow promising solutions by conducting the optimization under simplified and/or idealized conditions, and then adjusting the solutions by considering certain real conditions. One example of applying this optimization is shown to reveal the capability of the proposed methodology in clarifying a basic configuration that generates the maximum product under constant heat source capacity conditions. The demonstration shows that the existing absorption system, which is calculated based on the experience of designers, could be derived by automatically performing the optimization using this methodology. The proposed methodology is significant for use in realizing an optimized absorption system, and it allows designers to predict all possible configurations in advance and clarify a simple and feasible optimal system configuration.

2019 © International Journal of Thermodynamics. All Rights Reserved. Energy management is a systematic activity for improving energy performances of a target system, and an energy management system is expected to solve operational planning problems and report or suggest opportunities for performance improvement. An equipment model is required to reflect the characteristics of the actual equipment’s performance and to have a simple structure to apply to operational planning problems. The model should be able to diagnose changes with performance degradation over time. In this study, we proposed a thermodynamically-sound model of a CO2 heat pump water heater, suitable for solving operational planning problems and diagnosing degradation of equipment. The proposed model consists of a heat pump unit (HP) and a hot water storage tank (ST). The HP model is a status-transition model, constructed based on the Lorentz efficiency, which is identified by experimental values and a theoretical maximum coefficient of performance (COP) for a trans-critical heat pump cycle. The ST model is simplified and can describe temperature distribution in the ST because the unit COP of the HP influences the thermal stratification of the ST. The proposed model is preferable in its simplicity and robust performance for a wide temperature range by comparison with a conventional statistical regression model.

© ECOS 2019 - Proceedings of the 32nd International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems. All rights reserved. To reduce CO2 emissions in the residential sector, the installation of high-efficiency energy supply equipment and development of zero energy house are progressing in Japan. It is important to appropriately select energy system configuration, such as the number of installed equipment and capacity when designing the system configuration. There are various studies on the configuration of energy systems. The purpose of this study, we analyze the trends of the relationship between optimal configuration and household characteristics. Then, based on the derived configuration, we evaluate the system configuration from a long-term perspective. We assume a smart residential building consisting of multiple households that introduces photovoltaics (PV) and battery (BT) as common assets and has variations in the number of occupants and demand profile. In addition, we consider various thermal devices, which is a gas-fired water heater (GH), heat pump water heater (HPWH), and solid oxide fuel cell cogeneration systems (SOFC). Deriving the optimal configuration of energy systems over the year is difficult from the viewpoint of calculation load. Therefore, we select 7 representative days for each month and derive optimal configuration such as minimizing CO2 emissions in each evaluation period. Then, we aggregate the results and decide the optimal configuration of the residential building in the target year. As a result, when the CO2 conversion factor for electricity is 0.400 kg/kWh or more, installing SOFC to the few-person household is effective. On the other hand, in the case of the many-person household, the SOFC installation effect is lower than the HPWH from the viewpoint of CO2 emissions.

© ECOS 2019 - Proceedings of the 32nd International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems. All rights reserved. In this paper, an analysis of the temperature condition producing maximal power from a sensible heat source by finite heat-recovery thermodynamic cycles is presented. Some studies have been conducted that theoretically analyzed a system utilizing thermal energy from heat sources by multiple thermodynamic cycles in cascade with the assumption of constant heat-source temperature. However, many heat sources for heat-recovery thermodynamic cycles are sensible, in which the temperature changes considerably with the cycles during heat exchange. Therefore, it is necessary to consider the temperature change of the heat source. First, a temperature condition that maximizes the power generated by a combination of single/multiple Carnot cycles from constant-specific-heat heat sources is analyzed, and the optimal temperature is derived analytically. Subsequently, simulations of the Rankine cycle and several patterns of the Kalina cycle are compared to the analytical model. These comparisons reveal that the Carnot cycle model provides an effective estimation of the temperature conditions for the heat-recovery cycles that produce maximal power from a sensible heat source.

© 2018 Elsevier B.V. Home energy management systems (HEMSs) are the system to manage the energy usage in houses. The use of HEMSs, and especially those which are capable of automatically controlling home energy appliances such as air-conditioners (ACs), is expected to manage energy utilized in domestic field effectively. In the present study, we focused on automatic AC operation by HEMS with the combined goal of improving thermal comfort while reducing electricity costs. In general, the room temperature and electricity consumption of an AC are highly dependent on the characteristics of the installation environment, so that the derivation of an appropriate AC operation plan is generally a difficult task. To tackle this problem, an energy management method to provide AC operation plan tailor-made for the target AC installation environmental by learning the characteristics of the installation environment (CIE) from the historical operation result data is proposed. The efficacy of the proposed method is verified via numerical and real-world experiments.

© 2017 IMEKO This study presents optimal design conditions by considering the cost effectiveness and operability of a single-stage ammonia/water absorption refrigerator (AAR) via exergy analysis. Chemical exergy change constitutes complexity with respect to exergy analysis of absorption systems. In the study, Gibbs free energy is considered in exergy analysis to precisely evaluate absorption and rectification processes including chemical exergy change. The theoretical maximum exergy efficiency of AAR and the influence of its design/operating conditions on exergy efficiency/destructions are investigated in an ideal condition. The analysis indicates the importance of the evaporator outlet liquid (bleed) ammonia mass fraction and desorber temperature. A condition of bleed mass fraction control is illustrated. The study also involves performing sensitivity analysis of design parameters (pinch temperatures) with respect to exergy efficiency and optimal desorber temperature. Finally, design conditions that maximize exergy efficiency per cost are derived relative to the sum of thermal conductance as a cost parameter. The study demonstrates the potential for downsizing of AAR without reducing exergy efficiency. The results indicate that approximately 39% total thermal conductance reduction, maintaining nominal efficiency, or 19% total thermal conductance reduction with an exergy efficiency increase of 16% are expected when compared to those in a commercial AAR.

© 2018, Fuji Technology Press. All rights reserved. Our goal is to automatically classify objects from Mobile Mapping System data to enable the automatic construction of dynamic maps. We aimed at the extraction of curbstones and classification of curb types. Although there is much research about curbstones being recognized from laser-scanned point clouds, there are few methods to classify curb types. In this paper, we propose a method to extract curbstones from low-density-type laser scan data. We also propose a method to distinguish whether curbstones allow access to off-road facilities. Evaluation tests give an F-measure of ≥94.4% and an accessibility classification accuracy of ≥99.6%. Moreover, the results of applying multiple filters to noise removal are compared.

自動運転の実現に必要とされるダイナミックマップの整備に向けて，MMSにより取得された点群から様々な道路周辺の情報を自動で抽出することが求められている．これまで我々は，スキャンラインごとの変化点を抽出することで縁石に照射された点群の検出を行っていた．しかし，ダイナミックマップには縁石のベクトルデータが必要である．本報では抽出した点群をモデル化し，精度の検証を行った．

We describe recognition of deviating from the route method by monocular camera image. Recently major self-position estimation methods of autonomous mobile system(AMS) use accurate map and observation information (distance, coordinates, etc.). However, these has some problems, high generating map cost, recognition miss matching and deviating from the route etc. We propose the self-position estimation method like human. This method uses monocular camera image. AMS detection distinctive features in surrounding environment from image and estimate self-position. Moreover, when it is different from the assumed route, it returns to the correct spot and route using parameter of correctness of self-position. The result of a simulation shows this method is possible to return correct route.

This paper describes a method of generating 3D colored point clouds using a light detection and ranging (LiDAR) and a camera on a small unmanned aerial vehicle (UAV). Recently, the 3D measurement using small UAVs have attracted attention because of its highly usefulness. In the previous research, 3D point clouds can be generated using multiple global navigation satellite system (GNSS) antennas/receivers and LiDAR. To increase the amount of information of the 3D point clouds, we propose a method to add color information to 3D point clouds using a camera. Precise camera mounting angle must be estimated to add color information into 3D point clouds. We propose a method to estimate maximum likelihood of camera mounting angle using white circle markers. As the result of the evaluation, the accuracy of colored 3D point clouds is 0.41 m after camera mounting angle estimation.

Positioning accuracy of global positioning system (GPS) is deteriorates when non-line-of-sight (NLOS) GPS multipath signals are received in urban environments. Therefore, it is important to determine GPS satellite visibility and reject NLOS satellites from positioning calculation to improve positioning accuracy. In this paper, we focus on a GPS correlation waveform which is affected by multipath signals. To detect NLOS multipath signals, we use machine learning of GPS correlation waveforms. We use neural networks for machine learning to generate the NLOS discriminator. From the evaluations of proposed method, the accuracy of GPS satellite visibility determination by using the neural networks is 96.8 %. The positioning accuracy without NLOS signals is also improved compared with the conventional positioning method.

This paper describes a real-time position and attitude estimation technique using multiple global navigation satellite system (GNSS) receivers and antennas on a small unmanned aerial vehicle (UAV). At disaster sites, a rapid 3D measurement is highly required. However, in the previous research, it takes time to generate 3D map because the computation process after a flight of the UAV is needed. In addition, in the previous research, it needs 6 position calculations to estimate UAV positions, and it needs 30 position calculations to calculate baseline vectors between 6 antennas to estimate the UAV attitude. Accordingly, it is difficult to estimate the position and attitude using onboard computer in real-time. Therefore, we propose a method using 6 GNSS antenna positions to estimate the UAV attitude. The proposed method can reduce position calculations from 36 to 6. By using the proposed method, we achieved the real-time position and attitude estimation within 0.1 s delay time.

© 2018 University of Minho. All rights reserved. There is a high demand that aggregating Home Energy Management System (HEMS) as demand response service. Aggregation scheme is divided into the centralized and decentralized approach. On the one hand, in a centralized fashion, a controller manages all device. On the other hand, in a decentralized fashion, a local controller manages own devices and exchanges information for achieving the global optimum. Our previous work has proposed decentralized HEMS aggregation with Alternating Direction Method of Multipliers (ADMM) to address scalability and privacy issue. The main idea of this method is that we decompose the large-scale aggregated scheduling problem into individual HEMS scheduling problem by introducing local upper limit which stands for the maximum purchasable electricity from an electrical grid. This article reports that we extend the previous decentralized HEM method to asynchronous fashion in order to improve convergence time efficiency from the practical implementation perspective. We propose the waiting ratio which represents the minimum HEMS number for updating the next local upper limit. We also evaluate the algorithm processing time with changing waiting ratio and the number of households. As a result, it is confirmed that though the result shows 53% of acceleration at the most accompanied by barely 2% increase cost, the asynchronous process does not always accelerate the processing time. It may be reasonable to suppose that the degree of acceleration is decreased, as the degree of asynchrony increases, because iteration number until fulfilling converging criteria is increased.

© 2018 University of Minho. All rights reserved. Energy management is systematic activity to improve energy performances of target system, and it has already been introduced in the industrial and commercial field. Energy management system is expected to solve operational planning problem and report or suggest opportunities for performance improvement. In recent years, CO2 heat pump water heater (HPWH) is attracting attention as one of the high-efficiency devices to meet domestic hot water demand. Equipment model is required to reflect the characteristics of the actual equipment’s performance and to have a simple structure to apply to operational planning problem and should diagnose the changes with the performance degradation overtime. However, few studies have been reported which proposes the thermodynamically-sound model of HPWH for energy management. In this paper, we proposed a simple model suitable for solving operational planning problem and diagnosing aging deterioration or degradation of equipment in energy management system. Firstly, we constructed function model consisting of a heat pump unit (HP) and a hot water storage tank (ST). HP model is simply composed of start-up, steady state, and shut-down status-transition model. The steady state model is constructed based on the Lorentz efficiencyand theoretical maximum coefficient of performance (COP) for trans-critical heat pump cycle. The Lorentz efficiency is identified by experiment on typical domestic hot water demand with variation of ambient temperature, inlet/outlet water temperature at the gas-cooler. While the heat pump system is operating, unit COP of the HP is influenced on the thermal stratification of ST. The ST model is a simplified model that can describe temperature distribution in ST. Secondly, we validated the model. Proposed model reproduced experimental values with sufficient accuracy for day-ahead planning problem. Finally, we confirmed that the proposed model is preferable in its simplicity and robust performance for wide temperature range by comparing with a conventional statistical regression model.

© 2018 University of Minho. All rights reserved. Some general procedures for optimizing energy systems have previously been presented. However, it is practically difficult to obtain an optimal design of thermodynamic systems that have several system parameters. The optimization is considered at three levels: synthesis (configuration), design (component characteristics), and operation. In this paper, the syntheses of two absorption heat pump systems are evaluated and their design/operation optimization is performed efficiently based on an energy-utilization diagram (EUD) for performance improvement. Cycle models of an absorption heat pump system, including an absorber heat exchanger (AHX) and a solution heat exchanger (SHX), are constructed. These models consider exergy destruction caused by heat transfer and pressure loss. The exergy analysis is performed to evaluate the system performance, and an EUD is drawn to evaluate the margins for improvement. The design parameters and operating points are improved for reducing the exergy destruction in the components where dominant exergy destruction occurs, based on an EUD. Before improvements, COP and exergy efficiency are higher in the SHX cycle, while the margin for improvement is larger in the AHX cycle. In the absorber, exergy destruction is reduced by adjusting the operating point to make the temperature slopes at the hot and cold sides coincide. In other components, exergy destruction is reduced by adjusting the design parameters to improve the heat transfer performances. The results show that exergy efficiency is improved by the distribution of exergy destruction of each component. After these improvements, COP is higher in the SHX cycle, while exergy efficiency is higher in the AHX cycle. It is concluded that we can efficiently realize the design/operation optimization of a thermodynamic system using an EUD. This is because an EUD presents both exergy destruction and margin for improvement at the components comprehensively, as well as the operating point of the system.

© 2018 IEEE. With growing attention to sustainability and recognition of the impact of global warming problems, energy supply and consumption have become critically important. This paper presents the construction of a modeling platform accommodating cooperative energy management systems (EMSs), which virtually produces the model of a smart city with a distribution network (DN) by using a wide range of data obtained from the real world. The platform involves models of various EMSs, governing the operation of a power system or controlling consumer-installed devices, and simulating the power flow, electrical losses, and voltage in the DN. In addition, indices measuring the sustainability of the model city, such as CO2 emission, are estimated from scenarios, for example, photovoltaic system installation, electric vehicle penetration, etc. The results can be visually displayed and the platform is highly versatile and applicable to various types of issues associated with smart cities. Two case studies are presented in detail.

© 2016 IEEE. The introduction of photovoltaic power systems is being significantly promoted. This paper proposes the implementation of a distributed energy management framework linking demand-side management systems and supply-side management system under the given time-of-use pricing program for efficient utilization of photovoltaic power outputs; each system implements a consistent management flow composed of forecasting, operation planning, and control steps. In our framework, demand-side systems distributed in the electric distribution network manage individual energy consumption to reduce the residential operating cost by utilizing the residential photovoltaic power system and controllable energy appliances so as not to inconvenience residents. On the other hand, the supply-side system utilizes photovoltaic power maximally while maintaining the quality of electric power. The effectiveness of the proposed framework is evaluated on the basis of an actual Japanese distribution network simulation model from both the supply-side and demand-side viewpoints.

© 2017 Elsevier B.V. As demand-side energy management system (EMS) has not only a function to maximize owner's utility by automatic control but also a potential capability to respond a demand activation, demand-side EMS is expected to fulfill the key role for intelligent control of community energy management. To achieve the stable control result of EMS against the uncertain environment, it needs approach from both forecast and operation sides. The objective of this study is to construct a control scheme for a home EMS from a practicable implementation perspective and to evaluate the control performance of the scheme proposed. The scheme is composed of operational planning with receding horizon and energy demand forecasting. The goal of the scheme is to maximize householder's utility only by retrofitting the home EMS to a residential household. Throughout numerical results, it is revealed that the better control performance comes from the conservative operational strategy derived from the multiple scenarios.

© 2017 IEEE. The world is more aware of the need for saving energy because of increasing world energy consumption and environmental problems. To promote saving energy in the domestic field, the use of home energy management systems (HEMSs) is rapidly spreading. The HEMS which has automatically controlling function can control domestic electrical appliances including air-conditioners (ACs). In this research, we focus on AC operation plans to improve thermal comfort and reduce electricity costs for residents. However, AC control planning is generally a difficult task because the operation results greatly depend on the environmental characteristics in which the HEMS is installed. To solve this problem, we proposed an AC planning method that accounts for environmental characteristics and uncertainty in prediction by using historical data.

The main objective of this study is to realize the Photovoltaic (PV) power generation short-period forecasting with high accuracy using the neural network predictors learned by sky image features as input to detect PV power generation abrupt change. For extracting the features correlated with PV power generation abrupt change, we segmented the sky images into clear and cloudy areas and calculated the ratio clear areas of the whole image. For estimating the PV power generation, we calculated the averaged saturation of the sky image. We clustered the sky condition based on the extracted features and constructed the neural network predictors corresponding to each sky condition. For evaluating the proposed method, the one predictor for all sky conditions as a reference method forecasts PV output. As a result, we found that the proposed method for 20 minutes ahead PV output forecasting in the case that corresponds to “cloudy”, which is defined by Japan meteorological agency, decrease 18.3 % of mean-absolute error compared with reference method.

CO₂ heat pump water heater is one of the high-efficiency apparatus to meet hot water demand. Energy management in residential and commercial sector is one way to keep the system operation efficiently. Energy management system (EMS) might measure the unit performance and is expected to derive a day-ahead optimal operational planning and then report or suggest opportunities for performance improvement. Since the heat pump model presented in energy conservation law (ECL) is designed for calculating daily performance, it is not appropriate for deriving an operational planning in several tens of minutes' intervals. Thus, in this paper, we will propose a model suitable for solving day-ahead operational planning optimization problems in EMS. The CO₂ heat pump model is simply composed of Lorentz efficiency and theoretical maximum coefficient of performance (COP) for trans-critical heat pump cycle. The Lorentz efficiency is identified by a series of experiments for typical residential hot water demand with variation of ambient temperature, inlet/outlet water temperature at gas-cooler of the heat pump unit. Comparing with the base case derived by ECL model, we confirmed that the proposed model is preferable in its simplicity and robust performance for wide temperature range.

Vapor compression and condensation system (VCC) can dehydrate wet wastes such as biomass with high efficiency, using same principle as heat pump. However, mass flow of treated steam decreases as time goes on. The causes of this problem are the lack of heat transfer area, the sediment of solid materials in the evaporator on the heating surface and the existence of non-condensable gas in the condenser. In addition, excessive superheated vapor causes breakdown of compressor or scorching of biomass. Thus, we constructed the VCC simulation model in order to investigate the effect of the factor obstructing heat transfer and the water injection at the inlet of compressor on overall system performance. Also, the method to select optimal design parameters is proposed for the improvement of machine performance or downsizing. In this paper, we defined objective function, in which weighting factor is applied to the size of heat exchanger and the input power to VCC, and specified design parameters to minimize the objective function. Then, we performed parametric analysis to investigate the effect of mass flow of water injection and the heat transfer coefficient on the objective function, under the different weighting factor. As the result, it was concluded that the discharging means of heat transfer obstructive factor with high capability was necessary for optimal design of VCC.

<p>This paper describes an extrinsic parameter calibration of light detection and ranging (LiDAR) for a 3D measurement system using an unmanned aerial vehicle (UAV). Recently, the use of small UAVs becomes widespread in 3D measurements because small UAVs are highly useful. We target 10 cm accuracy of 3D measurement aiming for use in disaster environments. 3D measurements using small UAV need estimating not only accurate position and attitude of UAV but also accurate extrinsic parameters of the LiDAR. We propose a calibration method of extrinsic parameters of the LiDAR using reflectors. The proposed method estimates the angle of the LiDAR that minimizes the RMS error of the distance between the reference points of the reflectors and the measured 3D points. As the result of the calibration, vertical RMS error of 3D measurements was 0.0408 m and horizontal RMS error was 0.0472 m.</p>

<p>This paper describes a precise attitude estimation method for a 3D measurement system using LiDAR on a small unmanned aerial vehicle (UAV). Recently, the use of small UAVs becomes widespread in 3D measurements because small UAVs are highly useful. In 3D measurement using LiDAR, the precise attitude of the UAV is necessary because attitude estimation errors influence the 3D measurement accuracy. However, it is difficult to estimate the attitude of small UAVs because they are too small to be equipped with large and precise inertial measurement unit (IMU). Therefore, we proposed a method using six global navigation satellite systems (GNSS) receivers and a low-cost and light-weight IMU to estimate the precise attitude. The method combines Euler angles calculated statistically using six GNSS receivers with angular velocities measured by the IMU. As a result of evaluation, the proposed method is effective on improvement of the attitude estimation accuracy.</p>

© 2017 IMEKO As communication standard, such as SEP 2.0 and ECHONET Lite, for digital communication of home appliances has been established, the research of networked control system is progressing in the domain of residential house. Instead of building new power station to fulfil new electricity requirement, such as electric vehicle charging, the concept, that an aggregator coordinates massive amount of home energy management system (HEMS) to supply negawatt power, is proposed. The aggregator requires to manipulate electricity consumption through massive amount of HMES as networked control system. As fundamental study for control algorithm of distributed architecture, this paper constructed one of the networked supervisory control system formulated as stochastic model predictive control scheme, and analysed primary energy consumption sensitivity against update interval of energy demand forecasting and operational strategy in addition to changing number of scenarios. The mainly results are concluded that: as the energy saving ratio in the case of 6 hours update interval has enough high point, which is 9.5% in comparison with the case of 24 hours update interval, the stochastic model predictive control scheme proposed in the case using six scenarios can downsample until 6 hours update interval.

© 2017 IMEKO In order to reduce energy consumption, the installation of combined heat and power (CHP) has been promoted. However, when the heat to power ratio of CHP and the energy demand do not match, performance of CHP is depreciated. As one of the solutions to improve performance of the CHP and to reduce the energy consumption, energy interchanges have attracted attention and gradually increased in importance in the commercial sector. The objective of this study was to analyze the impact of the difference between demand profiles in buildings employing power and heat interchanges on energy saving. Specifically, we formulated the optimal planning problem of building energy systems by Mixed Integer Linear Programming (MILP) from the viewpoint of energy consumption minimization. The analysis was applied to three model areas with different demand profiles by changing the component ratio of each building in a city with the same total floor area. The main results showed that the energy reduction effects of three model areas with different demand profiles were due to power and heat interchanges. We also found that employing power and heat interchanges increased both the installed capacity of CHPs in buildings and the contributing ratio of CHPs for electricity demand.

© 2017 IMEKO This paper presents the design method for an ejector-absorption heat pump based on entropy generation minimization (EGM). This cycle is driven by low-temperature waste heat below 90 °C. A cycle model of the ejector-absorption heat pump with an ammonia-water mixture as the working fluid has been constructed. The required model parameters to represent the thermodynamic and geometric characteristics were determined from an experimental study. Cycle simulation specifies the dominant locations of irreversibility and operability. Parametric analysis is performed to investigate the effects of the geometry of the cycle components on entropy generation. This study considers the entropy generation from two components: one associated with the frictional pressure drop and the other including heat transfer in each heat exchanger. The geometric parameter for each component is set based on the results of the parametric analysis. The performance of the designed heat pump is evaluated by its modified coefficient of performance (COP) based on the primary energy consumption. The results show that the dominant entropy generation occurs in the solution heat exchanger and absorber, and the design using EGM produces an improved COP. The results of the sensitivity analysis for the overall unit size of the designed heat pump are also shown.

© 2017 IMEKO As a replacement for conventional sources, which cause CO2 emissions, the installation of photovoltaics (PV) has increased extensively in residential sectors. However, large-scale PV installation causes voltage violations of low-voltage distribution grids, particularly in the residential sector. According to previous studies, energy storage systems and power interchange methods are effective in utilizing PV surplus electricity and saving energy. The objective of this study is to derive the optimal configuration of energy systems in multiple households under power interchange for the minimization of total CO2 emissions. Two methods for solving this complicated and large-scale problem are proposed. First, we considered a calculation of the optimal configuration of energy systems in multiple households as an optimal unit sizing of energy systems in a single household. Second, we examined the operational planning problem as mixed integer linear programming (MILP) with an enumeration method. We found that a heat pump water heater (HP) can be installed as the heat supply equipment regardless of the PV installation ratio by the year 2030 in Japan, when the CO2 conversion factor of the electrical grid will be 0.37 kg/kWh. In addition, the maximum impact of power interchange on CO2 emissions will lead to its reduction by 85 kg, at 75 % of PV installation ratio.

Copyright © 2017 ASME. In order to reduce CO2 emissions in the residential sector, the installation of photovoltaics (PV) has been increasing extensively. However, such large-scale PV installations cause problems in the low-voltage distribution grid of the residential sector, such as PV related voltage surges. In this study, the utilization of suppressed PV output through energy storage devices was proposed. Using demand side energy storage devices reduces voltage surge, transmission loss, and CO2 emissions from the residential buildings. The objective of this study was to add voltage constraints of the low-voltage distribution grid to an operational planning problem that we developed for the residential energy systems, and to quantitatively evaluate the potential of heat pump water heater (HP) to utilize the PV surplus electricity, while considering the electrical grid constraints based on the minimization of CO2 emissions. We found that when a 4.5 kW HP with 370 L storage, which utilizes PV output, was added to the system, the reduction in CO2 emissions was more than twice compared with that in the case of adding 4 kWh battery (BT) to a PV and gas fired water heater configuration. Further, the effect of utilizing the suppressed PV electricity by HP was almost equivalent to that by the BT. Therefore, the potential of HP in utilizing PV surplus electricity is higher than that of the BT in terms of CO2 emissions reduction in the residential sector.

There are a lot of hot springs in Fukushima. The thermal energy of the hot spring is a valuable energy resource. In this paper effectiveness as the heat source for power generation systems is investigated. The temperature of 70 ℃ or more and enough flowrate are necessary as the heat source for power generation systems of 10kW class. However there are few regions where this condition is satisfied in Fukushima. Because the potential heat of the hot spring water in Fukushima is not low, it is proposed to use the hot spring water as the heat source of power generation systems by compensating for shortfall energy.

In recent years, demands of indoor positioning for analyzing human behaviors are increasing; various positioning methods have been proposed. However, the adequate system to analyze the human behavior based on the precise position information has not been established yet. This paper describes a high precision and a simple system of indoor positioning by combining wearable and monitoring cameras. To estimate the position, we use the visual odometry (VO) using the wearable camera. In the VO, the positioning error is accumulated. Therefore, the VO's error is compensated using the monitoring camera when the target person is captured in the monitoring camera. From the result of evaluation, we found that VO's error was compensated by the monitoring camera and combined system can estimate the accurate position.

We develop Rush or Evacuate Judgment System referring for the lesson from Fukushima Daiichi Nuclear Power Plant. In this study, we developed obstacle detection method by deep learning for autonomous control on uneven ground. In this paper, we describe this proposed method and the result of test learning using laser-scanned point cloud images and camera images. These images divided into two data, no or movable obstacles images and immovable obstacles images. As a result, the percentage of correct answers of our classifier for self-test images was 85.04%, and it was found that learning from point cloud images has a possibility of being used for obstacle detection.

Drying process consumes great amount of energy, but, by attaching the evaporation-dehydration system called VRC (Vapor Re-Compression), energy consumption can be reduced significantly. In this study, authors take up a biomass power plant that burns EFB (Empty Fruit Bunches) as fuel. These are reference processes called as P-VRC and P-opt. P-VRC is a process that attached SSD (Super-heated Steam Dryer) and VRC to original biomass power plant. P-opt is a process that studied by Nakamura, designed by minimizing utility and matches of heat exchanges, and optimizing operating point based on P-VRC. However, the phase changes of water were not consider in both processes, so we designed a process called P-HEN.opt by proposing a new optimization technique as a solution. As a result, generating efficiency of P-HEN.opt is 2.23 points higher than P-VRC. In calculation of annual profit, P-HEN.opt saves 68 million yen than P-VRC, and 63 million yen than P-opt.

The main objective of this study is to clarify the impacts of partial load characteristics in industrial energy supply system on optimal operating planning and capacity of storage tanks through a numerical experiment. In order to analyze effects of non-linearity of partial load characteristics of the equipment, we calculate operational planning problems with various demand pattern adopting optimal approach based on Mixed Integer Quadratic Programming. In this paper, the industrial energy system consists of combined heat and power generator, absorption heat pump, gas-fired water heater, vapor compression refrigerator, storage tanks of hot and cold water, photovoltaic power generator and circulation pumps. As a result, it is found that equipment with strong non-linear partial load characteristic is operated at part-load operating point rather than rated point. Additionally, primary energy consumption can be reduced by 1.19% compared to regardless of non-linearity of partial load characteristic. Furthermore, method for regression of partial load characteristics affects optimal capacity of storage tanks. Each capacity corresponded to about 10 % of the cumulative daily load of peak day.

In the agricultural sector, huge amount of energy were comsumed for heating green house. This paper proposes combined system of GHP (Gas Heat Pump) for agriculture and AHP (Absorption heat pump) driven by waste heat of GHP and comperes with new system and conventional system of heating and cooling greenhouse. As a result, the annual running cost of heating is reduced 52% by using combined system than using oil heater and combined system reduced 35% costs compared with GHP system in winter. The annual cooling costs is reduced 17% by using combined system compared with GHP system in summer.

This paper describes a precise positioning method for autonomous driving system. Global navigation satellite system (GNSS) is widely used to estimate the vehicle position. The purpose of this paper is improving the accuracy of single-frequency real time kinematic (RTK)-GNSS positioning. In general, it is difficult to solve GNSS carrier phase ambiguity using a single-frequency GNSS receiver in multipath environments. Therefore, we propose a method consists of two approaches to solve this problem. First, reliable GNSS satellites are selected based on the difference of the signal to noise ratio (SNR) between the vehicle and the base station. Second, inertial navigation system (INS) is integrated in least-squares ambiguity decorrelation adjustment (LAMBDA) method to improve the ambiguity resolution performance. As a result of evaluation, the proposed method is effective on improvement of GNSS positioning accuracy.

This paper presents a method of a position estimation for planetary rovers by using “skyline matching”. Skyline matching is the method that can estimate the position and attitude by comparing two types of skylines; the simulated skyline from a digital elevation model (DEM) and the extracted skyline from a camera. To improve the accuracy of the skyline matching, we propose the integration of the multiple skyline matching results using the relative position estimated by the odometry. We conducted field experiments in Oshima Island. As a result, it can be concluded that the proposed method can improve the positioning accuracy of the normal skyline matching.

© 2016 University of Ljubljana. The degree of operational freedom of home appliances is increasing with introducing controllable demand-side appliances by using Home Energy Management System with some communication standard. This situation increases the demands on methodology achieving customer utility maximization, which is able to plan operational strategies of a variety of appliances under various exogenous variables such as energy demand, outlet temperature, and power output of Photovoltaic power generator. Energy demand and photovoltaic output have some uncertainty or variation in the parameter. The objective of this study is to analyze a solution behavior of an operational planning problem adapting Mixed Integer Second-Order Cone Programming extended from traditional Mixed Integer Linear Programming model. The objective function of the mathematical optimization involves mean and its variance by extracting naturally Markowitz model. Above proposed model is intended to sophisticate robust operational planning method, and is also evaluated on the EMS simulation platform that we are developing. As a result, it is found that involving variance to objective function affects to computational time meaning computational load rather than robustness of planned schedule. Additionally, using several scenario results in more robust schedule than using plausible one scenario.

© Copyright 2016 by ASME. This paper proposes an optimal predictive control of 0.75 kW PEM fuel-cell cogeneration with home appliances. This paper also models fuel cell system for design and operation evaluation of building equipment based on actual measurement of residential fuel cell system on sale. As one application of constructed model and proposed control method, this paper discusses concerning home EMS for efficient PV utilization.

This paper presents a motion-stereo device using the GPS/DR (dead reckoning) combination along with omnidirectional cameras to reconstruct 3-D environments by means of sensors small enough to be installed on a mobile robot. The proposed technique is based on the fact that it is possible to determine epipolar lines by using the precise positions and heading angles measured by a combination of GPS and various sensors; high-precision stereo matching may then be performed by means of geometrical restrictions. Furthermore, in comparison to the other stereo techniques, it is also possible to establish longer baselines for peripheral objects and simultaneously provide a higher precision in calculating the distances to far objects by applying voting processing to a series of distant motion-stereo images, which can be attained by using more than one baseline length, in 3-D spaces based on the precise positions and heading angles. In short, the proposed technique provides a substantial increase in measurement precision as compared to that with the well-known SFM (structure from motion) technique for reconstructing 3-D environments with monocular cameras; this is because the proposed technique utilizes a greater number of mobile parameters, which are determined using precise cameras. In this experiment, the measurement precision of the proposed technique has been evaluated in reconstructing the shapes of vehicles parked alongside a road; the measurements were found to have a standard deviation of 140 mm within a range of 10 m. It can be stated that the proposed omnidirectional motion-stereo technique is robust to environmental perturbations and can accurately estimate distances in the case of highly textured objects. © 2007 SAGE Publications.

This paper describes the localization method based on global navigation satellite systems (GNSS) technology for autonomous navigation of mobile robots. The accurate and robust position estimation of the robot is the key to the autonomous navigation. GNSS was usually not used in localization in urban environments because its positioning has multipath errors and problems in availability. In this paper, we propose the GNSS positioning technique that is suitable for the autonomous navigation of mobile robots. We use an open source GNSS positioning library to compute the GNSS fix solutions. The techniques, which select the GNSS observations using the GNSS signal strength and validate GNSS fix solutions, are proposed. Then the GNSS fix solutions are integrated with inertial sensors and an odometer through the extended Kalman filter. From the experiment in the &quot;Real World Robot Challenge (RWRC)&quot;, it was confirmed that the effectiveness of our proposed technique and the feasibility of its highly accurate positioning.

© 2016, Fuji Technology Press. All rights reserved. In recent years, global navigation satellite systems (GNSSs) have been widely used in intelligent transport systems (ITSs), and many countries have been rapidly improving the infrastructure of their satellite positioning systems. However, there is a serious problem involving the use of kinematic GNSS positioning in urban environments, which stems from significant positioning errors introduced by non-line-of-sight (NLOS) satellites blocked by obstacles. Therefore, we propose the method for positioning based on NLOS satellites detection using a fish-eye camera. In general, it is difficult to robustly extract an obstacle region from the fish-eye image because the image is affected by cloud cover, illumination conditions, and weather conditions. We extract the obstacle region from the image by tracking image feature points in sequential images. Because the obstacle region on the image moves larger than the sky region, the obstacle region can be determined by performing image segmentation and by using feature point tracking techniques. Finally, NLOS satellites can be identified using the obstacle region on the image. The evaluation results confirm the GNSS positioning accuracy without the NLOS satellites was improved compared with using all observed satellites, and confirm the effectiveness of the proposed technique and the feasibility of implementing its highly accurate positioning capabilities in urban environments.

© 2016 ICIC International. This paper presents a technique to optimize the communication schedules generated for synchronization of Foundation Fieldbus H1 devices in cascade control loop. A level-to-flow cascade control operated by the Harmonas-DEO host system is examined as an illustrative case study. Major objectives of the optimization are not only to minimize the latency of the control loop but also to maximize the availability of the network bandwidth. The proposed technique can be applied for H1 segment macrocycle schedules performing the control functions in both of the host controller and the field devices. Three examples for optimizing communication schedules generated from different control block assignments are described. The validation of the optimization methods can be determined by using two metrics: control loop latency improvement and publication gap availability improvement. Experimental results confirm that the proposed technique works effectively to operate the studied H1 segment for cascade control without any problems.

© 2015 Elsevier B.V. All rights reserved. In Japan, a feed-in tariff scheme has been implemented to promote the use of photovoltaic power generators in combination with electric batteries. Although many researchers have assessed the operation of grid-connected photovoltaic systems with electric batteries, little attention has been paid to the impact of the electric batteries' degradation characteristics. This paper evaluates the operation of a grid-connected photovoltaic/electric-battery system in a house in terms of cost savings and energy savings. We constructed a long-term operational optimization model considering the degradation characteristics of the electric battery. This model contains two objective functions: energy savings and operating costs. We create a scenario of power rates and photovoltaic/battery system configurations. To reveal the optimal operational strategy for the photovoltaic/battery system, the multi-objective optimization problem was solved. As a result, Pareto-optimal solutions were obtained, and trade-off relationships between cost and energy savings are presented. In this study, the utilization of a grid-connected photovoltaic system with an electric battery was expected to be most effective in energy-saving priority operation.

This paper describes an accurate attitude determination technique using multiple global navigation satellite system (GNSS) receivers and antennas for small unmanned aerial vehicles (UAVs). A laser survey using a small UAV needs highly accurate attitude information for reconstructing 3D models. The proposed technique uses the multiple GNSS antenna&#039;s positions computed by the GNSS carrier phase measurements to estimate the UAV&#039;s attitude. To solve the GNSS carrier phase ambiguity, the reliable ambiguity search is performed with a couple of constraints for the base line vector. The performance of the proposed technique is evaluated in the static test. From the test, the proposed technique could estimate UAV&#039;s yaw angle in 0.1 degree accuracy.

The main objective of this study is to clarify the impact of energy demand prediction accuracy on optimal operating result of residential energy supply system. In this paper, the energy system consists of polymer electrolyte fuel cell cogeneration system and electrical-driven heating, ventilating and air conditioning system. Primary energy of operational results with various demand prediction patterns are calculated in order to analyze the effect of demand prediction error. As a result, it is concluded that prediction error of energy demand causes 54.3 MJ/day increase of daily primary energy in the worst case, and annual primary energy consumption can be reduced by 13.2% with the best prediction in comparison with the worst one. Furthermore, the impact of energy demand prediction accuracy on daily primary energy has relationship with the amount of hot water demand. Therefore, the effectiveness of using the amount of hot water demand as a parameter for demand prediction is suggested in terms of energy saving.

The objective of this paper is to identify the model parameter of PEM fuel cell cogeneration in order to contribute to the building performance simulation for design and operation. As cogeneration system has many operational alternative strategies, the simulation using the mathematical model of cogeneration needs to predict accurate prime mover's thermal and electrical output, and also needs to represent characteristics of both steady state and transient state, for the aim of evaluate accurate energy performance and CO2 emissions. We made a test environment for parameter identification of PEM fuel cell cogeneration, and examined operational characteristics on steady state and transient state. As a result, the model parameter of PEM fuel cell cogeneration was identified, and was also validated.

This paper presents that the skyline matching algorithm with considering camera tilt. Skyline matching is the method that estimating position and attitude by comparing two skylines. One skyline is simulated one from a digital elevation model (DEM). The other one is gotten from camera images taking around view. We conducted field experiments in Oshima Island. As a result, we conclude that considering camera tilt has a significant influence.

Drying process consumes great amount of energy, but, by attaching the evaporation-dehydration system called VRC (Vapor Re-Compression), energy consumption can be reduced significantly. In this study, authors take up a biomass power plant that burns empty fruit bunches (EFB) as fuel. In this paper, an original process is called P-org. Ho et.al. proposed a process (P-Ho) attached SSD (Super-heated Steam Dryer) and HAD (Hot Air Dryer) to P-org. The authors proposed a process (P-VRC) replaced with VRC instead of HAD in P-Ho. Then, P-VRC.HEN is derived by optimizing HEN (Heat Exchanger Network) in P-VRC. P-Ho and P-VRC.HEN are processes optimized in operating point. As a result, net thermal efficiency is maximized in P-VRC.HEN, 30.1%, which is 2.2 points higher than that of P-Ho.

This paper describes a Non-Line-of-Sight (NLOS) satellites detection method for improving GNSS (Global Navigation Satellite System) positioning accuracy in urban area. In general, NLOS satellites which are shielded by obstacle such as buildings and elevated bridges cause large multipath errors in positioning results. Therefore, our method extracts obstacle area in a fish-eye camera image by projecting 3D map on it, and detects NLOS satellites existed on obstacle area. However, camera's position and orientation on 3D map coordinate are essential in projecting 3D map, and we estimate them using particle filter. As a result of evaluation test in urban area, it is confirmed the proposed method is effective on improving positioning accuracy.

We propose and develop Attack Judgment System referring the lesson from Fukushima Daiichi Nuclear Power Plant. In this study, we developed path planning method for autonomous control on uneven ground in Attack Judgment System. In this paper, I describe proposed algorithm and the result of simulation supposed on uneven ground. This algorithm consists of six processes. I have just tested at uneven dirt road, sloop, and bush growing tall weed. As a result, I succeed at the former two.

This paper proposes four cycles driven by low temperature waste heat. Four cycles are modified from Absorption Heat Pump cycle - Absorber Heat Exchanger cycle. First cycle is installed compressor between pre cooler and absorber heat exchanger (AHX) to increase pressure of absorber. Second cycle is changed AHX to solution heat exchanger (SHX). Third cycle is installed compressor between pre cooler and SHX. Last cycle is installed ejector between pre cooler and SHX. All of these cycles were carried out with NH_3-H_2O. The cycles are compared with coefficient of performance (COP) and exergetic efficiency. Results of the simulation show that installing compressor with AHX increases COP_H 0.15 point on heating mode and COP_C 0.18 point on cooling mode at rate point (T_<H,in>=88). Installing ejector with AHX increases COP_H 0.1 point on heating mode and increases COP_C 0.18 point on cooling mode at rate point. In addition, installing compressor decreases heat source temperature.

The multi-stage renewal planning problem is studied here for an energy supply system installed into a hospital from the long- Term economic viewpoint by applying the mathematical optimization method. This problem is mathematically formulated as a large-scale mixed-integer linear programming one, and the average annual total cost during the evaluation period is set as the objective function to be minimized. In this problem, by taking the deterioration of performance efficiency of the existing pieces of equipment, the renewal system is assumed to be composed by installing new pieces of equipment with improved efficiency by reflecting technical progress. By optimizing the system's operational policy for hourly and seasonally changing energy demands through years of the evaluation period, the renewal years and the system's configurations at each multi-stages are determined optimally. A numerical study is carried out for a really existing hospital with total floor area of 25000m2, and many comprehensive and useful results are obtained by comparing 13 alternative renewal plans by using the CPLEX solver.

Demand-side electricity saving is an important factor in the reduction of the installed capacity of power-supply facilities. In order to save electricity automatically while maintaining comfort levels, home energy management systems (HEMS) have attracted attention. These systems can control residential energy equipment cooperatively to reduce electricity consumption while considering benefits to consumers. Although many researchers have evaluated HEMS, no one has conducted a study which considers the control of various types of residential energy equipment in real time along with the uncertainties of energy demands. This paper proposes a single HEMS method which connects prediction, operational planning and control steps and enables the evaluation of operational planning methods of HEMS connected with many kinds of residential energy equipment currently in use in Japan while considering the uncertainties. The purpose of this study is to evaluate the economic potential of residential energy systems based on the proposed method with the uncertainties of energy demands and photovoltaic (PV) output under time-of-use prices. The results allowed us to establish a framework to quantitatively evaluate the operational planning methods of HEMS with the uncertainties of energy demands and PV output. In addition, the usability of the proposed method was confirmed by comparing the operational costs to those of a reference method.

Residential houses are in the process of introducing power generators such as photovoltaic (PV) power generators and fuel cell cogeneration systems. Under current laws in Japan, surplus electricity from a residential PV system can be sold by feeding it back into the electrical grid. However, when a lot of neighboring power generators make and feed back electricity at the same time, there is an issue of an upper voltage violation of the provisions of the laws and regulations relating to the Electricity Business Act in the distribution system of the electrical grid. The issue has been solved by stopping power generators when they reach an upper voltage limit, 107V. Another solution is to acknowledge demand response signal from electrical grid operator to store electricity in residential batteries using Home Energy Management System (HEMS). The research question is that how to collaborate HEMS and Grid Energy Management System (GEMS). This paper developed an evaluation framework for the cooperative behavior between HEMS and GEMS. Using this evaluation framework, this paper demonstrated the optimal operational strategy of HEMS including PV in the case that HEMS is informed voltage profile from GEMS, and also assessed amount of PV suppression quantitatively in residential sector in practical aspect.

© 2015 Elsevier B.V. All rights reserved. The Active X-ray Spectrometer (AXS) is considered as one of the scientific payload candidates for a future Japanese mission, SELENE-2. The AXS consists of pyroelectric X-ray generators and a Silicon Drift Detector to conduct X-Ray Fluorescence spectroscopy (XRF) on the Moon to measure major elements: Mg, Al, Si, Ca, Ti, and Fe; minor elements: Na, K, P, S, Cr and Mn; and the trace element Ni depending on their concentration. Some factors such as roughness, grain size and porosity of sample, and the geometry of X-ray incidence, emission and energy will affect the XRF measurements precision. Basic studies on the XRF are required to develop the AXS. In this study, fused samples were used to make homogeneous samples free from the effect of grain size and porosity. Experimental and numerical studies on the XRF were conducted to evaluate the effects from incidence and emission angles and surface roughness. Angle geometry and surface roughness will be optimized for the design of the AXS on future missions from the results of the experiment and the numerical simulation.

An optimal operational planning problem of residential energy system has been formulated by Mixed Integer Linear Programming (MILP). The decision variables of optimal operational planning problem are energy and mass flows, equipment's operating statuses, and energy level of storage. Many kinds of energy supply equipment are available for householders in Japan. Of course, in operational planning problem, the increase of integer variables which means equipment's on/off status, is linked to the increase of calculation time. It is important to assess the impact of introducing an energy system for a house based on the suitable planning horizon of this problem. Energy storage brings the energy in the form of hot water and electricity to the next d a y. The operational strategy of energy system including storage should be evaluated through few days toward various energy demand. The optimal planning problems become large scale because many pieces of equipment to introduce and long evaluation period are required. This paper analyzes characteristics of energy systems caused by planning horizon. Additionally, we propose a hierarchical method as heuristic method for solving large MILP problem easily, and the proposed method is tested the effectiveness. Our finding shows that the proposed search method for better feasible solution has good performance in comparison with default settings of conventional MILP solver in terms of calculation time.

The main objectives of this study are to consider both thermal comfort and energy consumption on operational planning problem of residential energy system, and to handle uncertainty of energy demand and PV output for the future as a scenario-based stochastic programming problem. The energy system consists of photovoltaic power generator, electrical-driven room air-conditioner and PEM type fuel-cell cogeneration system. We introduce mathematical optimization theory for operational planning problem, because the targeted system has many alternative operations. As a result, the optimal operational planning problem, which is extended by considering PMV and future scenarios as constraints, concludes that the residential energy system achieves 33% of energy saving ratio in the case of 1.0 of PMV.

Three configurations of power and refregiration hybrid cycle with ammonia-water mixture are evaluated based on the theoretical optimum cycle. The first cycle is APC by D. Zheng et al, which is complicated configuration. The second is CPC by J. Wang et al, which is most simpliest configuration of the three. The last is PRPC by N. Zhang et al, whose configuration is atacched two heat exchangers and booster pump to CPC. For each cycle, investigated operating points which maximize the net power or cooling capacity on each heat source temperature with a unit mass flow rate of heat source. The cycles are compared with the theoretical optimum cycle on T-S diagram. From the diagram, the effects of configuration differences on system performance are confirmed and validated with numerical simulation.

The main objective of this study is to evaluate energy saving potentials of polymer electrolyte fuel cell cogeneration systems integrated with solar cell and battery installed into residential houses. There exist many alternative operational policies in the above systems, and the mathematical planning approach is taken to derive the rational system's operational solution based on the mixed-integer linear planning method. In the numerical analysis of this study, energy saving characteristics of 12 alternative systems are compared respectively, and as one of main obtained results, it become clear that the energy saving effects to install battery into the systems depend largely on the operational policy of the system together with the evaluation criterion of adverse electricity from the solar cell to the electric grid. In other words, in the case of giving high priority to the self-consumption of electricity from the solar cell within the house, the energy saving potential to install battery increases largely, but few effects are noticed in other cases.

Drying process consumes great amount of energy, but, by attaching the evaporation-dehydration system called VCC (Vapor Compression and Condensation), energy consumption can be reduced significantly. VCC is an open-type heat pump cycle uses water. ln this study, authors take up a granulating-drying system for sewage disposal process. It is called as case-A as a reference. The adaptability of the VCC to the system is evaluated by comparing two sets of process, case-B and C. Case-B is the cascading combination of the VCC and the granulating-drying system. VCC preprocess the dehydrating process in order to relaxing the drying-load of existing centrifugal hydro-extractor. Then, to enhance the energy recovery in the process, the integrated process was derived by pinch method; that is case-C. These three cases are compared with primary energy consumption. As a result, compared with Case-A, primary energy consumption of Case-B is reduced 42.8%, and Case-C is reduced 50.5%.

The subject of this study is to plan the operation of residential energy system with uncertain parameters based on ex-ante decision before uncertain parameters are realized. This paper applies a scenario-based stochastic programming framework to the operational planning problem having uncertain energy demand as parameters. Based on predicted energy demand scenarios, the operational strategies, which indicates the prime mover's start-stop status and the level of hot water tank, are decided. The decided operational strategies and realized values of energy demand are input to optimal control problem, which is formulated by dynamic programming. Finally we consider the operational performance of dynamic programming using the decided operational strategies based on predicted demand scenarios. As a result, the proposed stochastic programming framework decided the optimal strategies, and showed that effectiveness.

Nowadays, PEFC-CGS is getting attention as a distributed energy system. It has high efficiency, and a lot of studies of PEFC-CGS were reported. But almost of them didn't consider energy prediction error. In this study, in order to evaluate energy-saving performance of PEFC-CGS for residential use with energy prediction error, I made PEFC-CGS control low input optimal operational plan based on energy prediction value. Consequently, operational plan to start PEFC-CGS in the morning or avoiding unneeded power runup and low load operation of PEFC-CGS can make control low of PEFC-CGS improved.

This paper presents that the method of position error correction for planetary rovers by using skyline matching azimuth estimation. Skyline matching is the method that estimating position and attitude by comparing two skylines. One skyline is simulated one from a digital elevation model (DEM). The other one is gotten from camera images taking around view. We focus on using azimuth attitude estimated by skyline matching to correct accumulation error of IMU. We modeled IMU angular velocity bias increases linearity. We conducted field experiments in Oshima Island and Chiba. As a result, estimated relative azimuth errors are lower than 1 degree. IMU azimuth errors decreased by 67% (6.25 deg to 2.15 deg ) and IMU position errors decreased by 70% (3.33m to 1.04m).

This paper describes a method of obstacle detection in the fish-eye camera image for GPS-Non-Line-Of-Sight(NLOS) satellites detection. Recently the development of the autonomous mobile system(AMS) is more expected for example an auto-pilot car. A GPS measurement is widely used for estimating self-position for such AMS. It can measure the position without premeasured emvironmental data like a map-matching. However, in the urban canyon, GPS measurement accuracy deteriorates seriously using NLOS satellite. Because of obstacles between NLOS satellites and GPS antenna, electrical waves omitted from GPS satellites are reflected or diffracted by obstacles. We propose the method to detect the obstacle using a fish-eye camera image to detect NLOS satellite. Firstly fish-eye image is parted into various small segments by k-means clustering method. And the segments are divided into sky and obstacle areas according to its movement using SIFT matching. The result of a field experiment shows the proposed method is effective to detect GPS-NLOS satellites.

When the nuclear accident at Fukushima Daiichi Nuclear Power Plant happened, TOKYO Fire Department member were send for cooling the nuclear reactor. But there isn't means to get information of disaster site by unmanned and fire fighter had to rush into Nuclear Power Plant with taking a risk of radiation exposure. Therefore in this study, we propose Attack and Retreat Judgment System Referring the Lesson from Fukushima Daiichi Nuclear Power Plant. In this paper, we mainly describe Attack Judgment System, consisting of remote-control information gathering system and geographical information system. Remote-control information gathering system gets disaster site information with remote-control unmanned ground vehicle and geographical information system registers the information.

This paper describes a new positioning method which improves the availability and accuracy of multi-GNSS positioning in urban canyon environment using QZSS satellite. In our proposal method, we use GNSSs including GPS, QZSS, GLONASS, Galileo, and Beidou. Furthermore, we use the QZSS as an only master satellite. We conducted a static evaluation test in a narrow-sky environment with many obstacles above the GNSS antenna.The results of the static evaluation test show that our proposal method is highly available and has accurate positioning (fixed ratio: 92.7%, horizontal RMS error: 4.2cm) in urban canyon. In contrast, the number of DD measurements of the conventional multi-GNSS positioning method is 4 or less nearly all the time, indicating that this positioning does not work most of the time.

The Active X-ray Spectrometer (AXS) for the Japanese SELENE-2 rover has been proposed for elemental analysis on the lunar surface to measure the major elements: Mg, Al, Si, Ca, Ti, and Fe; the minor elements, Na, K, P, S, Cl, Cr, and Mn and the trace element Ni, all depending on their concentrations at a landing site. The elemental data of the AXS allow us to not only classification but also quantification of surface rocks on the Moon. The AXS is a compact low-weight instrument for elemental analysis based on the principle of X-ray fluorescence spectrometry using an X-ray spectrometer and two (four) pyroelectric crystals as X-Ray Generators (XRG). This paper introduces the current status of the pre-project to develop an AXS for the SELENE-2 Rover including the investigations on the generation of X-ray flux of the XRG, required surface roughness for the XRS measurement, and a thermal design of the AXS.

This paper describes the development of a mobile robot system and an outdoor navigation method based on global navigation satellite system (GNSS) in an autonomous mobile robot navigation challenge, called the Tsukuba Challenge, held in Tsukuba, Japan, in 2011 and 2012. The Tsukuba Challenge promotes practical technologies for autonomous mobile robots working in ordinary pedestrian environments. Many teams taking part in the Tsukuba Challenge used laser scanners to determine robot positions. GNSS was not used in localization because its positioning has multi-path errors and problems in availability. We propose a technique for realizing multipath mitigation that uses an omnidirectional IR camera to exclude "invisible" satellites, i.e., those entirely obstructed by a building and whose direct waves therefore are not received. We applied GPS/dead reckoning (DR) integrated based on observation data from visible satellites determined by the IR camera. Positioning was evaluated during Tsukuba Challenge 2011 and 2012. Our robot ran the 1.4 km course autonomously and evaluation results confirmed the effectiveness of our proposed technique and the feasibility of its highly accurate positioning.

Copyright © (2014) by the Institute of Navigation All rights reserved. This paper describes a new positioning method that improves the availability and accuracy of Multi-global navigation satellites system (GNSS) positioning by using QZSS satellites in urban canyon environments. Standard multi-GNSS is problematic because one satellite is defined as the master satellite in each GNSS, leaving insufficient numbers of satellites for positioning roles. Our new method uses QZSS as the sole master satellite. To this end, we solve the ambiguity of QZSS by the wide- lane method and the QZSS LEX signal, and preserve that double-difference (DD) ambiguity is integral number. We also estimate the inter system bias (ISB). The GNSS used in our method includes GPS, QZSS, GLONASS, Galileo, and BeiDou satellites. Static evaluation tests were conducted in open-sky and narrow-sky environments. The open-sky evaluation confirmed the accurate positioning ability of our proposed method (horizontal RMS error: 1.6 cm), whereas the narrow-sky evaluation confirmed that our proposed method operates with accurate positioning and high availability in urban canyon environments (fixed ratio: 92.7%, horizontal RMS error: 4.2 cm). In conclusion, our method realizes high accuracy and availability high-coverage positioning.

© 2014 SPIE. The chemical element abundance on planetary surface is essential for planetary science. We have been developing an active X-ray spectrometer (AXS), which is an in-situ chemical element analyzer based on the X-ray uorescence analysis for future planetary landing missions. The AXS consists of an X-ray detector and multiple X-ray sources. Although a pyroelectric X-ray generator is promising for the AXS as an X-ray source, the raise of emission X-ray intensity is necessary for short-time and precise determination of elemental composition. Also, in order to enhance the detection efficiency of light major elements such as Mg, Al, and Si, we have tested the low energy X-ray emission by changing the target material. In this study, the X-ray emission calculation at the target by Monte Carlo simulation and the X-ray emission experiments were carried out. More than 106 cps of the time-averaged X-ray emission rate was achieved in maximum using a LiTaO3 crystal with 4 mm thickness and Cu target with 10 μm thickness. The performance of pyroelectric X-ray generator is presented in this paper.

Copyright ©2014 by ASME. The purpose of this study is to evaluate the maximum energy-saving potential of residentia energy supply systems consisting of a solid oxide fuel cell (SOFC) cogeneration syste (CGS) combined with a solar cell (SC) and a battery (BT), compared with reference system (RS). This study applies an optimization theory into an operational plannin problem to measure actual energy demands over the course of 1 year. Eight differen types of energy supply system were compared with each other by changing the component of the SOFC-CGS, SC, BT, and RS. Meaningful numerical results are obtained indicating the maximum potential energy savings.

In Japan a feed-in tariff scheme has promoted the utilization of photovoltaic power generators in combination with electric batteries. Although many researchers have assessed the operations of grid-connected photovoltaic systems with electric batteries, little attention has been paid to the impact of the electric batteries' degradation characteristics. This paper presents an evaluation of the operation of a grid-connected photovoltaic/electric battery system in a house from energy saving and economy viewpoints. We constructed a long-term operational optimization model considering the degradation characteristics of the electric battery. This model contains two objective functions: energy saving and operating cost. We set a scenario of power rate and photovoltaic/battery system configurations. In order to reveal the optimal operational strategy of the photovoltaic/battery system, the multi-objective optimization problem was solved. As a result, pareto optimal solutions were obtained, and trade-off relationships between economy and energy saving are presented. In this study, the utilization of the grid-connected photovoltaic system with an electric battery was expected to be effective in an energy saving priority operation.

Various residential cogeneration systems have been studied and developed as parts of distributed energy supply system. A residential fuel cell cogeneration system is composed of three units: a fuel cell unit, a thermal storage unit and a back-up boiler. Those three-parts are necessary to compensate a gap between system output with a rigid heat-to-power ratio and heat and power demand. It is difficult to operate the fuel cell system with frequent starts and stops. The peak thermal load is far greater than the maximum thermal output capacity of the fuel cell unit alone. Generally, a cogeneration system performs effectively when all of the recovered heat was utilized in a day. The common issues in promoting residential fuel cell cogeneration systems are the unit price and size. The size must be reduced for use in apartment houses, which constitute about half of the households in Japan. The objectives of this study are to evaluate the rational hot water tank capacity for individual households in order to provide a guide for hot water tank capacity sizing. Sensitivity analysis on the hot water tank capacity from energy saving and economic viewpoints based on an optimal operational planning problem was carried out. Additionally, residential energy demand profiles with different climate conditions are analysed. Our findings show that, in Japan, commutative duration of hot water demand is about 10% or less of the time in one year, and domestic hot water demand rarely observed above 4 kWh in any quarter of an hour. Annual primary energy consumption and operating costs rarely fell when the hot water tank capacity was 7 kWh or more. Additionally, reducing the hot water tank capacity to 5 kWh had only a small effect on the objective values. This suggests that the hot water tank could be smaller than that currently in use. The daily hot water demand gives an excellent estimation of the maximum stored heat of the hot water tank. It was found that the hot water tank capacity can be estimated from the regression lines, or from the fraction of daily hot water demand.

Two configurations of power/cooling cycle with ammonia-water mixture are evaluated. At first, an ammonia-absorption hybrid cycle (AAH), which is one of the simplest configurations, is evaluated on temperature entropy diagram to introduce the insight for enhancement. The other configuration, which was proposed by Goswami, is also evaluated. It is a candidate for an enhanced in producing power. The multi-objective optimization for net-work output, refrigerating capacity and total thermal conductance are carried out to derive the pareto front. The optimization is carried out by epsilon-constraint method. The results show that T-S diagram is a good tool for derive the enhancement. Goswami cycle has about quarter cooling capacity while 123.8% net output power comparing with AAH.

In this paper, three conventional energy supply systems are compared from economic and energy saving characteristic points of view for an office building with total floor area of 5000m^2. These systems are consuming mainly electricity (E-system), heavy oil (D-system), and city gas (G-system) as primary energy source, respectively. For hourly and daily changing energy demands, the daily input energy cost or primary input energy is minimized through one year for these systems by considering disaster occurring three days, respectively. As a result, economic and energy saving superiorities of E-system are resulted to those of respective D- and G-ones. For disaster occurring situation, effects of installing solar cell and battery are also evaluated by changing capacities of them numerically.

To implement and design an application of a real time fieldbus segment, engineers are obliged to estimate the communication load factor of the communication to secure the operation. According to the recent increase of the node number per segment, communication load management becomes a real issue. This paper gives the definition of the communication load and the procedure to estimate and measure the communication load of a real time fieldbus: FUNDATION^TM fieldbus and thus establish the theoretical and experimental base of the guidance to keep the periodical/stationary communication load less than 70%.

This paper describes an outdoor localization method by matching skyline. On a surface of the moon, we cannot use either the GNSS (Global Navigation Satellite System), information of artificial landmark or map matching. However a lot of planetary probe's missions need absolute coordinates. Therefore we propose a method that uses DEM (Digital Elevation Model) and panoramic photo image, and compares skylines made by them. Extracting skylines from image uses k-means clustering method with color information. A skyline made by panoramic photo image is determined uniquely by 4 parameters. However the proposed method fixes 2 parameters and uses a rough calculation, assuming that the place to get the photo image is horizontality. As the result of experiments at Oshima Island, it was confirmed that it is possible to estimate location in error by 65 m or 19 m by using the proposed method. One of prospective causes of an error is the assumption of horizontality in the place getting photo images, so we expect to improve accuracy of estimating location if this method is used with attitude sensor.

The steam compressors are usually developed for the purpose of large size and special VRC (vapor re-compression) application. However, it seems to have a considerable ripple effect on the various purposes if the small size and high performance steam compressor are practical use. In this study, the authors suggest the two-phase compression process models which are based on the various assumptions. In addition, an experimental set-up which uses 7.5kW - wing type compressor is made to validate calculation results and enabled to confirm reduced discharge temperature and effect of compression work reduction. An effect of two-phase compression of the steam is reported by comparing calculation results with experimental results.

Promoting utilization of photovoltaic (PV) cell, for residential use has become urgent issue recently. One approach is to use an electrical battery (BT) in the house in order to maximize consuming the electricity generated by the photovoltaic power generator. The energy systems including energy buffer like electrical batteries have a lot of operational flexibility. The mathematical optimization technique is useful for rational energy use The objective of this study is to making operational optimization models considering degradation characteristic of a battery. As a result, the four types of operational optimization models, which consider degradation characteristics caused by battery cycle life, were formulated on the mixed integer linear programming problems. Consequently, it was found that the appropriate optimal operational strategy should be derived from the model including the degradation characteristics on DOD.

Simple firefly luciferin analogs emitting blue, green, and red light were developed. The longest emission maximum was observed at 675 nm, which belongs to the NIR biological window (650-900 nm), useful for deep site bioimaging of living animals. The analogs showed a slow rise of emission intensity compared with the rapid emission of natural luciferin. The light emission of the adenylated analogs was strongly enhanced compared with those of analogs themselves. (C) 2013 Elsevier Ltd. All rights reserved.

本研究では，MMSで計測された大規模三次元点群を用いて電線などの空中架線を効率的に管理することを目的とし，空中架線の自動抽出手法について提案する．本手法では，まず柱状物体をSVMにより認識し，次に認識された柱状物体と空中架線との位置関係から架線の認識を行う．本論文では，本手法の詳細と実際のMMS点群に本手法を適用した結果について述べる．

The operational degree of freedom in a residential energy system has dramatically increased recently because an energy system tends to be composed of many devices including some energy buffers. It is challenging to construct the framework of the operational planning problems, which update the plan based on the short-span predictions. This framework has to plan the operation before uncertain demand and PV output are realized; hence the plan is based on ex-ante decisions. The aim of this paper is to apply a stochastic programming framework to the operational planning of a residential energy system considering the prediction, and is to show basic directions for the planning. The residential energy system includes a fuel cell cogeneration system with a hot water tank, the photovoltaic system with an electrical battery. The parameters of the numerical experiments are three kinds of temporal precision and the number of predicted scenarios. The operation means the timing of the fuel cell's start-stop, and the stored energy levels of the battery and the hot water tank. As a result, the expected value based on scenarios was 21% greater than the minimized value based on perfect information in terms of daily primary energy consumption. The number of predicted scenarios was reasonable around 10 at 15-min temporal precision, because the great number of input scenarios made a decision not to operate the fuel cell cogeneration system for the entire day, and needed a great deal of the computational time.

An active X-ray spectrometer (AXS) is now being developed as a payload candidate for the rover on SELENE-2, the next Japanese lunar exploration mission. The AXS will determine the chemical compositions of lunar rocks and regolith around the landing site. The surface of lunar rock samples will be ground using a rock abrasion tool. Thus, fundamental studies on the X-ray fluorescence analysis for lunar rocks and regolith are required to design and develop the AXS. In this study, we have investigated the X-ray fluorescence analysis in order to evaluate the effects of surface roughness of samples and the angle of incident and emergent X-rays. It was found that the fluorescent X-ray yield for low energy X-rays, i.e. the light elements, decreases at rough surface samples. This effect of surface roughness becomes small for smooth surface samples. It was also found that the fluorescent X-ray yield depends on the incident angle, which is attributed to the fact that the X-ray fluorescence occurs closer to the sample surface at larger incident angles. Since the emergent X-rays are affected by the detection geometry and surface roughness, the incident angle effect also depends on the above conditions. © 2013 SPIE.

In conventional vehicle teleoperation systems, using low-bandwidth, high-delay transmission links causes a serious problem for remote control of the vehicles. To solve this problem, a proposed teleoperation system employs 3D maps and GPS time synchronization. Two GPS receivers measure the transmission delay, which the system uses to estimate the vehicle's location and orientation. Field experiments show that the 3D-map-based interface lets users easily comprehend the remote environment while navigating a vehicle. The experiments also show that taking communication delays into account improves maneuverability. © 2013 IEEE.

In this paper, we propose a path planning method for a Mobile Mapping System (MMS) considering GPS geometry for the purpose of increasing GPS availability. We calculate Position Dilution of Precision (PDOP) using aerial laser survey data that provides geography and height of buildings near roads. PDOP is used for weighting road network data. By using the Chinese postman problem, we then calculate the optimum path that passes through all routes at least once. We describe currentMMS operation first and clear up problems with the current method. We then describe the proposed method in detail. Finally, we conduct evaluation tests and describe results in detail. The evaluation test verifies that the proposed method increases the GPS FIX ratio by 5% under the same GPS geometry and proves the effectiveness of the proposed method.

When evaluating residential energy systems like co-generation systems, hot water and electricity demand profiles are critical. In this paper, the authors aim to extract basic time-series demand patterns from two kinds of measured demand (electricity and domestic hot water), and also aim to reveal effective demand patterns for primary energy saving. Time-series demand data are categorized with a hierarchical clustering method using a statistical pseudo-distance, which is represented by the generalized Kullback-Leibler divergence of two Gaussian mixture distributions. The classified demand patterns are built using hierarchical clustering and then a comparison is made between the optimal operation of a polymer electrolyte membrane fuel cell co-generation system and the operation of a reference system (a conventional combination of a condensing gas boiler and electricity purchased from the grid) using the appropriately built demand profiles. Our results show that basic demand patterns are extracted by the proposed method, and the heat-to-power ratio of demand, the amount of daily demand, and demand patterns affect the primary energy saving of the co-generation system. © 2013 by the authors; licensee MDPI, Basel, Switzerland.

This paper describes a path planning method that uses the Quasi-Zenith Satellites System (QZSS) and a satellite visibility map for autonomous vehicles. QZSS is a positioning system operated by Japan that has an effect similar to an increase in the number of GPS satellites. Therefore, QZSS can be used to improve the availability of GPS positioning. A satellite visibility map is a special map that simulates the number of visible satellites at all points on the map. The vehicle can use the satellite visibility map to determine the points that receive more satellite signals. The proposed method generates the artificial potential fields from the satellite visibility map and obstacle information around the vehicle, and it generates the path following the potential fields. Thereby, the vehicle can select the path that has more satellite signals, improving the availability of GPS fixed solutions. Hence, the vehicle can reduce the accumulated error by dead reckoning, and it can improve the safety of self-control. In this study, we evaluate the satellite visibility maps and the path planning method. The results show that the proposed method does improve the availability of GPS fixed solutions.

This paper describes a GNSS (Global Navigation Satellite System) precise point positioning (PPP) technique that can be applied to mobile robots in urban environments. The multipath signals, which from invisible satellites in urban area, cause serious effect on the GNSS positioning. Our proposed technique mitigates GNSS multipath signals by means of an omnidirectional infrared (IR) camera that can eliminate the need for invisible satellites by using IR images. With an IR camera, the sky appears distinctively dark. This facilitates the detection of the borderline between the sky and the surrounding buildings, which are captured in white, because of the difference in the atmospheric transmittance rates between visible light and IR rays. Positioning evaluation was carried out only with visible satellites that have less multipath errors. The evaluation results confirm the effectiveness of the proposed technique and the feasibility of its highly accurate positioning.

本研究では，モバイルマッピングシステムにより取得した大規模三次元点群からの道路周辺地物の自動認識を目的としている．本研究の従来手法では，柱状物体の認識において壁面の誤認識が多いことが課題であった．そこで本論文では壁面の誤認識低減のために，従来の認識手法に加え，局所領域の点群孤立度に着目した認識手法を提案する．また，本手法を実環境の大規模三次元点群に適用した結果や課題について述べる．

In recent years, many types of energy supply systems have come into use in various buildings for spaceheating/ cooling and hot water supply. Lifetimes of buildings are generally more than 60 years, but those of energy supply systems are around 15~25 years. Therefore, these systems must be renewed several times during lifetimes of buildings. In the study, this renewal planning problem is formulated mathematically as an optimization one, in which the objective function to be minimized is the average value of annual total cost during system's evaluation period. Namely, this optimization problem is formulated as a large-scale mixed-integer linear programming problem, and the programming language AMPL solver is adopted here as the solving tool to derive the numerical solution. A numerical study is carried out for a hospital with the total floor area of 25 000m2, where electrical (e.g., heat pump) and gas (e.g., gas engine cogeneration) systems are compared together with their hybrid system. The analysis is particularly focused on the influence of initial system's difference on the renewal planning of energy supply system. Through this study, the following results are mainly obtained: a) If the initial system is gas one, it is better to renew it to the electrical one as soon as possible due to relatively low energy efficiency of gas utilizing pieces of equipment, the high price of gas input energy in Japan, and so on. b) If the initial system is electrical one, the optimal renewal year becomes relatively later year, because it is economically better to use the initially installed high efficiency system as long as possible. c) Theoretically, the hybrid system is of course the best renewal one. However, there is no economic difference between the hybrid and the electrical systems.

This paper describes an outdoor positioning system for vehicles that can be applied to an urban canyon by using an omnidirectional infrared (IR) camera and a digital surface model (DSM). By means of omnidirectional IR images, this system enables robust positioning in urban areas where satellite invisibility caused by buildings hampers high-precision GPS measurements. The omnidirectional IR camera can generate IR images with an elevation of 20-70° for the surrounding area of 360°. The image captured by the camera is highly robust to light disturbances in the outdoor environment. Through the IR camera, the sky appears distinctively dark; this enables easy detection of the border between the sky and the buildings captured in white due to the difference in the atmospheric transmittance rate between visible light and IR rays. The omnidirectional image, which includes several building profiles, is compared with building-restoration images produced by the corresponding DSM in order to determine the self-position. Field experiments in an urban area show that the proposed outdoor positioning method is valid and effective, even if high-rise buildings cause satellite blockage that affects GPS measurements. © 2008 VSP.

Residential energy demand varies widely in terms of time-series behaviors, amounts consumed between families, and even within one family. Residential energy demand profiles have a high degree of uncertainty in their essentials because the demand profile is entirely based on the occupant-driven load. When evaluating residential energy systems like co-generation systems, hot water and electricity demand profiles are critical. In this paper, in order to clarify rational energy system selection guidelines and rational operation strategies, authors aim to extract basic demand time-series patterns from two kinds of measured demand (electricity and domestic hot water), measured over 26307 days of data in Japan. Authors also aim to reveal the relationship between primary energy consumption and demand patterns. Demand time-series data are categorized by means of a kind of "unsupervised" learning, which is a hierarchical clustering method using a statistical pseudo-distance. The statistical pseudo-distance is calculated from the generalized Kullback-Leibler divergence with the Gaussian mixture distribution fitted to the demand time-series data. The classified demand patterns are built using a hierarchical clustering and then a comparison is performed between the optimal operation of the two systems (a polymer electrolyte membrane fuel cell co-generation system, and a CO2 heat pump system) and the operation of a reference system (a conventional combination of a condensing gas boiler and electricity purchased from the grid) using the demand profiles appropriately built. Our results show that basic demand patterns are extracted by the proposed method. The demand patterns, the amount of daily demand and heat-to-power ratio of demand affect the primary energy reduction ratio of the polymer electrolyte membrane fuel cell co-generation system.

In this paper, we have evaluated the performance and availability enhancement of Quasi-Zenith Satellite System (QZSS) in urban environments. In urban environments, QZSS can be expected to be fairly effective because of the high elevation angle of satellite and enhancement functions. Therefore, we conducted performance and availability enhancement evaluation tests to verify thus. In performance enhancement evaluation test, in order to evaluate the improvement of GPS accuracy by L1 Submeter-class Augmentation with Integrity Function (L1-SAIF) broadcasted by QZSS satellite, we compared the positioning errors of only GPS positioning and L1-SAIF positioning in open sky environment. In availability enhancement evaluation test, we performed the static and kinematic observation test. In static observation test, in order to evaluate the improvement of GPS accuracy by availability enhancement, we observed GPS and QZSS statically in narrow-sky environment. And we compared the positioning errors of only GPS positioning and positioning using availability enhancement. In kinematic observation test, in order to evaluate the availability of QZSS based on the visibility of QZSS satellite in urban environment, we observed QZSS and SBAS from moving vehicle. And we compared the visibility of QZSS and SBAS satellites. From these evaluation tests, it was confirmed that the performance and availability enhancement of QZSS have high availability and effectiveness.

MMSの計測データには対向車など不要なデータが計測される。そのため、使用用途によっては対向車の除去が必要である。筆者らは、これまでに進行方向を向いたカメラとレーザを用いた対向車除手法を提案してきた。本報では、前後方向を計測できる複数のレーザを搭載したMMSに着目し、１回の走行の中で複数のレーザで計測された対向車の点群を検出し、除去する手法を提案する。

大規模災害からの復興の際に，支援物資の輸送や新たな街づくり等において道路は重要なインフラである．そのため航空写真などを用いた広域な被災状況の収集に加えて，道路周辺環境の詳細な被災状況の把握が，迅速な災害復興に結びつく．本論文では，道路周辺環境の詳細な情報収集が可能なMobileMappingSystemを活用した災害復興の支援手法を提案し，さらに東日本大震災への適用の展望について述べる．

In this paper, a method of rationally determining an optimal renewal plan is proposed for energy supply systems based on the optimization approach. In the planning of this proposed method, it becomes necessary to consider many factors such as the deterioration of each pieces of existing equipment, candidate pieces of equipment with upgraded efficiency reflecting technology improvement in the proper renewal year, the structure of renewal system, and so on. It is also necessary to determine the system's operational policy to match energy demands, which change daily and hourly through the year. A numerical study is carried out for a hospital with the total floor area of 25 000m2, where electrical (e.g., heat pump) and gas (e.g., gas engine cogeneration) systems are compared together with their combination of gas and electricity driven equipment (hybrid) system. Through this numerical study, the following results are obtained: a) Theoretically, the hybrid system is, of course, the best renewal system. However, the economic difference between the hybrid and the electrical systems is very small. b) The gas system is worse economically than the electrical one relatively due to the low energy efficiency of the related equipment, the high price of energy, and so on.

A next-generation digital road map (DRM) is expected to be an effective technology for achieving detailed navigation and driving safety assistance. As certain precise road information is required to make the next-generation DRM, the mobile mapping system (MMS) has attracted considerable attention as an efficient and precise survey method to gather such information. Since the MMS is a vehicle equipped with a GPS/inertial measurement unit along with a navigation system, cameras, and laser scanners, it can acquire precise, detailed 3D road information. However, when the MMS surveys are carried out during a GPS blockage, the positioning precision is reduced. In such a case, the MMS corrects its position by observing landmarks (LMs) which is surveyed its position by conventional method to calculate the precise position. In this study, we performed simulations of the positioning correction method to evaluate optimum landmark intervals and estimated the acceptable observation errors. We also conducted a field test to evaluate the effectiveness of the abovementioned positioning correction method. © 2011 SICE.

In this paper, we have evaluated the L1 submeter-class augmentation with integrity function (L1-SAIF) broadcasted by the Quasi-Zenith Satellite System (QZSS) in an urban environment for vehicle positioning. In urban environments, the augmentation of QZSS can be expected to be fairly effective because of the high elevation angles. Therefore, we conducted static and kinematic evaluation tests to verify thus. In the static evaluation test, for evaluating the positioning accuracy, we compared the positioning errors for only GPS positioning and augmentation of QZSS positioning. In the kinematic evaluation test, for evaluating the availability, we compared the visibility of QZSS and SBAS satellites. From the evaluation tests, it was confirmed that the QZSS augmentation has better availability and effectiveness than the SBAS augmentation. © 2011 SICE.

This paper describes a precision positioning technique that can be applied to vehicles or mobile robots in urban or leafy environments. The availability of satellite positioning is currently expected to improve due to the presence of positioning satellites such as US GPS, Russia's Glonass and Europe's Galileo. Due to the serious multipath impact on positioning accuracy in urban or leafy areas, however, improvements in satellite positioning availability do not necessarily facilitate highprecision positioning. Our proposed technique mitigates the GPS and Glonass multipath using an omnidirectional infrared (IR) camera that can eliminate the need for invisible satellites using IR images. With an IR camera, the sky appears distinctively dark. This facilitates the detection of the borderline between the sky and surrounding buildings and foliage due to the difference in atmospheric transmittance between visible light and IR rays, since buildings and foliage appear white. The proposed technique can automatically and robustly mitigate the GPS and Glonass multipath by excluding invisible satellites. Positioning was evaluated with visible satellites, which have less multipath error and without using invisible satellites. Evaluation results confirmed the effectiveness of the proposed technique and the feasibility of its highly accurate positioning.

This paper describes a precision positioning technique that can be applied to vehicles or mobile robots in urban environments. Currently, the availability of satellite positioning is anticipated to improve because of the presence of various positioning satellites such as U.S.'s GPS, Russia's GLONASS and Europe's GALILEO systems. However, because of the serious impact of multipath on their positioning accuracy in urban areas, such improvements in the availability of satellite positioning do not necessarily also facilitate high precision positioning. In this study, we propose a precision positioning technique that can be applied to vehicles or mobile robots in urban environment using a single frequency GNSS receiver, and we propose a technique to realize code multipath mitigation that uses an omnidirectional IR (infrared) camera to exclude invisible satellites. With the IR camera, the sky is distinctively dark. This makes it easy to detect the borderline between the sky and the obstacles such as the buildings, which are captured in white, due to the difference in the atmospheric transmittance rates between visible light and far-IR rays. Moreover we apply a tightly coupled GPS/INS (inertial navigation system) integration based on code and carrier phase from visible satellites determined by the omnidirectional IR camera. In a situation of degraded GNSS availability because of elimination of invisible satellites however a tightly coupled configuration is capable of updating the filter with only one visible satellite. Positioning evaluation was carried out only with visible satellites that have less multipath errors and without using invisible satellites. The evaluation results confirm the effectiveness of the proposed technique and the feasibility of its highly accurate positioning.

This paper describes a precision positioning technique that can be applied to vehicles or mobile robots in urban or leafy environments. Currently, the availability of satellite positioning is anticipated to improve because of the presence of various positioning satellites such as GPS of the U.S., GLONASS of Russia and GALILEO of Europe. However, because of the serious impact of multipath on their positioning accuracy in urban or leafy areas, such improvements in the availability of satellite positioning do not necessarily also facilitate high precision positioning. Our proposed technique mitigates GPS and GLONASS multipath by means of an omnidirectional infrared (IR) camera that can eliminate the need for invisible satellites by using IR images. With an IR camera, the sky appears distinctively dark. This facilitates the detection of the borderline between the sky and the surrounding buildings, which are captured in white, because of the difference in the atmospheric transmittance rates between visible light and IR rays. The proposed technique can automatically and robustly mitigate GPS and GLONASS multipath by excluding the invisible satellites. Positioning evaluation was carried out only with visible satellites that have less multipath errors and without using invisible satellites. The evaluation results confirm the effectiveness of the proposed technique and the feasibility of its highly accurate positioning. © 2011 IEEE.

This paper describes a Simultaneous Localization And Mapping (SLAM) algorithm using a monocular camera for a small Unmanned Aerial Vehicle (UAV). A small UAV has attracted the attention for effective means of the collecting aerial information. However, there are few practical applications due to its small payloads for the 3D measurement. We propose extended Kalman filter SLAM to increase UAV position and attitude data and to construct 3D terrain maps using a small monocular camera. We propose 3D measurement based on Scale-Invariant Feature Transform (SIFT) triangulation features extracted from captured images. Field-experiment results show that our proposal effectively estimates position and attitude of the UAV and construct the 3D terrain map.

This paper describes low-cost flexible vegetation monitoring and compares it to with conventional remote sensing systems such as airplanes and satellites. The small lightweight Unmanned Aerial Vehicle (UAV) we have developed has visible and near-infrared cameras that create a high-resolution wide-area mosaic image for observing vegetation. We propose integrating a GPS receiver, inertial sensors, and an image sensor to accurately estimate the UAV location and altitude to generate a mosaic image. The vegetation index is then calculated from the generated mosaic image to evaluate vegetation status. Monitoring experiment results at the Yawata moor in Hiroshima Prefecture showed that our small UAV both effectively and usefully provided low-cost flexible vegetation monitoring.

This paper describes outdoor localization for a mobile robot using a laser scanner and three-dimensional (3D) point cloud data. A Mobile Mapping System (MMS) measures outdoor 3D point clouds easily and precisely. The full six-dimensional state of a mobile robot is estimated combining dead reckoning and 3D point cloud data. Two-dimensional (2D) position and orientation are extended to 3D using 3D point clouds assuming that the mobile robot remains in continuous contact with the road surface. Our approach applies a particle filter to correct position error in the laser measurement model in 3D point cloud space. Field experiments were conducted to evaluate the accuracy of our proposal. As the result of the experiment, it was confirmed that a localization precision of 0.2 m (RMS) is possible using our proposal.

In this paper, based on the multi-objective optimization approach, a renewal planning method is proposed for an air-conditioning system, by which the optimal renewal system can be determined by selecting the optimal renewal year and the system's structure from both economic and environmental viewpoints simultaneously. In this method, one objective function is the average annual total cost of the system, which is the summation of the annual capital, operational and maintenance costs based on the annualized cost method during the evaluation years. The other objective function is the average annual total amount of CO_2 emission during the evaluation years. The numerical optimal solution is derived for the system of an office building by the mixed-integer linear programming algorithm together with the ε-constraint method. As a result, the set of Pareto optimal solutions is derived, and the trade-off relationship between economy and environment is analyzed. Through the result of the set of Pareto optimal solutions, tolerating the increase of the average system's annual total cost up to 1%, we can reduce the average amount of CO_2 emission from the system up to 15%. One another main result obtained shows that it is necessary to introduce electrically-driven heat pump to reduce CO_2 emission.

This paper describes a way to generate mosaic image using a small lightweight UAV for effective remote sensing. Payload limits are the source of most error in small lightweight UAVs to generate accurate mosaic images. We have overcome inherent small lightweight UAV drawbacks by providing them with integration of a GPS receiver, inertial sensors, and an image sensor to generate a large mosaic image. Position and attitude data of a UAV is estimated using onboard sensors and image correlation from SIFT features between overlapped images. A nonlinear optimization algorithm is used to optimize the position and attitude of the UAV. We demonstrated that our proposed mosaic image effectively enables low-cost remote sensing using a small lightweight UAV. © 2010 SICE.

This paper describes outdoor localization for a mobile robot using a laser scanner and a three-dimensional (3D) voxel map that is based on outdoor point clouds. A mobile mapping system (MMS) measures outdoor 3D point clouds easily and precisely. The complete 6D state of a mobile robot is estimated by combining dead reckoning and the 3D voxel map. The 2D position and orientation are extended to 3D by using the 3D voxel map and by assuming that the mobile robot remains in continuous contact with the road surface. Our approach applies a particle filter to correct position errors in the laser measurement model for a 3D point cloud space. Field experiments were performed to evaluate the accuracy of our proposed method. Our results confirmed that it is possible to achieve a localization precision of 0.2 m (RMS) using our proposed method. ©2010 IEEE.

An optimal planning method is proposed for the renewal-planning problem of an energy supply system installed into building from economic viewpoint. In this method, the objective function to be minimized is the average annual total cost during the evaluation period of the objective system based on the annualized costs method, and the renewal year is considered as a decision variable together with the renewal system's structure, equipment capacities, and system's operational strategy. This problem is formulated as one of the mixed-integer linear programming problem, and a numerical study is carried out for an office building with the total floor area of 15,000 m2 by using the GAMS/CPLEX solver. Impact analysis of the carbon tax introduction is mainly studied on the renewal planning mentioned above, and the following results are obtained:. (a) The optimal renewal strategy is not affected by the future carbon tax introduction at the standard rate such as 655 Japanese Yen/t-CO2 (=4.1 €/t-CO2) argued presently in Japan. (b) By increasing the above tax rate more than 13 times higher, structure of the optimal renewal system changes suddenly, and equipment with high energy conversion efficiency becomes to be installed in spite of its expensive initial cost. © 2009 Elsevier Ltd. All rights reserved.

This paper describes a tunnel cross-section measurement system using a mobile mapping system (MMS). The MMS features a GPS/Dead Reckoning (DR) combined navigation system, a three-axis GPS-Gyro/Inertial Measurement Unit (IMU), laser scanners, cameras, and the Network-based Positioning Augmentation Services (PAS). As GPS cannot be used in the tunnel, so the position estimation is done using IMU and Odometer. In this paper the result of comparison between the conventional tunnel cross-section measurement methods using 3D laser scanner and total station, and the proposed method using the MMS is described. And the examination result of the MMS's positioning accuracy that doesn't use GPS is described. The evaluation result proves that the tunnel cross-section measurement accuracy using the MMS is 7.0 mm, the MMS's measurement accuracy is not different from conventional method using a 3D laser scanner and a total station. The MMS tunnel measurement efficiency is also confirmed in this paper.

This paper describes a low-cost and flexible vegetation monitoring system and compares it with traditional remote sensing systems such as airplanes and satellites. We have developed a small unmanned aerial vehicle (UAV) equipped with visible and infrared cameras for vegetation observation. This system can automatically generate widespread high-resolution mosaic image and calculate the vegetation index from the multiple aerial images collected by an autonomous flight of the UAV. We performed monitoring experiments at Yawata moor in Hiroshima Prefecture. From the experimental results, we concluded that the small UAV system was effective and useful for carrying out low-cost and flexible vegetation monitoring. © 2009 SICE.

A multi-stage optimal renewal planning method is proposed for an energy supply system installed into building from economic viewpoint. Based on the annualized costs method, the average annual total cost during the total evaluation period is formulated as the objective function to be minimized. This is formulated as one of the mixed-integer linear programming problem, and the numerical solution is carried out by using the GAMS/CPLEX solver. A numerical study is carried out for an energy supply system installed into an office building with total floor area of 15 000m2, and the optimal renewal system is proposed as the one of installing high performance equipment properly at each optimal renewal year.

This paper describes a precision positioning technique that can be applied to vehicles in urban areas. The proposed technique mitigates Global Positioning System (GPS) multipath by means of an omnidirectional infrared (IR) camera that can eliminate the need for invisible satellites [a satellite detected by the receiver but without line of sight (LOS)] by using IR images. Some simple GPS multipath mitigation techniques, such as the installation of antennas away from buildings and using choke ring antennas, are well known. Further, various correlator techniques can also be employed. However, when a direct signal cannot be received by the antenna, these techniques do not provide satisfactory results because they presume that the antenna chiefly receives direct signals. On the other hand, the proposed technique can mitigate GPS multipath, even if a direct signal cannot be received because it can recognize the surrounding environment by means of an omnidirectional IR camera. With the IR camera, the sky appears distinctively dark; this facilitates the detection of the borderline between the sky and the surrounding buildings, which are captured in white, due to the difference in the atmospheric transmittance rate between visible light and IR rays. Positioning is performed only with visible satellites having fewer multipath errors and without using invisible satellites. With the proposed system, static and kinematic evaluations in which invisible satellites are discriminated through observation using an omnidirectional IR camera are conducted. Hence, signals are received even if satellites are hidden behind buildings; furthermore, the exclusion of satellites having large errors from the positioning computation becomes possible. The evaluation results confirm the effectiveness of the proposed technique and the feasibility of highly accurate positioning. © 2006 IEEE.

This paper presents the disaster prevention and mitigation system using a small unmanned aerial vehicle (UAV) . Immediate assessments of damage information and continuous collection of information for constructing a revival plan are important for damage mitigation when natural disasters such as huge earthquakes occur. In this study, we divide the period that follows a natural disaster on the basis of three processes, and propose the use of the small UAV for gathering information in such situations. The field experiments were conducted to evaluate the proposed system employing the small UAV. From the results of our experiments, it can be concluded that the small UAV system is effective for disaster prevention and mitigation.

Phenolic oxidation of 4-hydroxyphenylpropionic acid (5) with electrochemically generated hypervalent iodine oxidant, was performed using a variety of iodobenzene derivatives. Iodobenzene derivatives carrying electron-deficient aromatic moieties showed oxidant activity comparable to that of bis(2,2,2-trifluoroethoxy)phenyliodine(III) 1, and better than those carrying electron-donating groups with the exception of a methyl group. In our electrochemical procedure, the oxidant from 1-iodo-4-nitrobenzene was obtained as a stable solid, while other oxidants that did not precipitate from the reaction mixture, were used in situ. Conversion of the methoxyamide 7 into the corresponding azaspiro derivative 3 was also performed by the oxidants carrying aromkatic substitutions.

The public water supply line is required to build depth underground in an urban district in recent years. However the construction method has not been completely established especially for a large diameter water tunnel built in the congested urban district. As the latest water tunnel structure the separated-type water tunnel structure composite of steel liner and RC segments linings has been proposed in Japan. However the buckling of steel liner has not been solved which is obstructing the application of new water tunnel structure considering the high hydrostatic pressure is inevitably built up in the void between RC lining and liner during an operation period. In this article the study on buckling of locally supported steel liner encased in RC linings is carried out using the numerical analysis. The encased liner fails in single-lobe buckling and the critical pressure is related to not only the geometries of steel liners but also the initial gap are identified. Meanwhile the existing buckling equations are examined and discussed and the design procedure for locally supported steel liner is presented.

This paper presents a measurement method of refrigerant mass faction in an ammonia-absorption refrigerator. The proposed method is modified from conventional sampling method In the conventional method, a certain volume of solution from the outlet of condenser is sampled under the atmospheric pressure. With the nature of the high volatility of ammonia, it is difficult to measure the solution volume with high precision. Therefore, authors modified experimental set-up with pressurized chamber in which the solution volume is measured with high precision. The experimental results showed good match with results of a prediction method developed by authors.

In this paper, based on the multi-objective optimization approach, a renewal planning method is proposed for the energy supply system to determine the optimal renewal one by selecting optimal renewal year and system's structure from both economic and environmental viewpoints simultaneously. In this method, one objective function is the annual total cost of the system, which is the summation of the annual capital, operational and maintenance costs based on the annualized cost method during the evaluation years. The other objective function is the average annual total amount of CO2 emission during the evaluation years. The numerical optimal solution is derived for the system of an office building by the conventional mixed integer linear programming algorithm together with the ε-constraint method. As a result, the set of Pareto optimal solutions is derived, and the trade-off relationship between economy and environment is analyzed. Through the result of the set of Pareto optimal solutions, tolerating the increase of the system's annual total cost up to 1%, we can reduce the amount of CO2 emission from the system up to 15%. One main result also obtained shows that it is necessary to introduce different types of electrically-driven equipment such as heat pumps to reduce CO2 emission.

This paper presents a disaster mitigation system that uses a small unmanned aerial vehicle (UAV). The immediate assessment of damage and the continuous collection of information when natural disasters such as large earthquakes strike are important for developing a disaster recovery plan for damage mitigation. In this study, we develop a small prototype UAV and onboard software using a GPS navigation system and propose a unique disaster mitigation system that generates digital real-time hazard maps with the aid of the UAV. The effectiveness of the proposed system is confirmed by a flight experiment. © 2008 SICE.

This paper presents a disaster prevention system using aerial images obtained by a small unmanned aerial vehicle (UAV). The immediate assessment of damage information and the continuous collection of information for constructing a revival plan are important for damage mitigation when natural disasters such as large earthquakes occur. In this study, we develop a small prototype UAV and onboard software using a GPS navigation system and propose a unique disaster prevention system that employs the small UAV and a geographical information system (GIS). We divide the period that follows a natural disaster on the basis of three processes, and we propose the use of the small UAV for gathering and integrating information into the GIS. We conducted field experiments to evaluate the proposed system employing the small UAV. From the results of our experiments, we concluded that the system is effective in disaster prevention.

This paper describes a precision positioning technique that can be applied to vehicles in urban areas. The proposed technique mitigates GPS multipath by means of an omnidirectional infrared (IR) camera that can eliminate the need for invisible satellites (a satellite detected by the receiver but without LOS (Line Of Sight)) by using IR images. Some simple GPS multipath mitigation techniques such as installation of antennas away from buildings and using choke ring antennas are well known. Further, various correlator techniques can also be employed. However, when a direct signal cannot be received by the antenna, these techniques do not provide satisfactory results because they presume that the antenna chiefly receives direct signals. On the other hand, the proposed technique can mitigate GPS multipath even if a direct signal cannot be received because it can recognize the surrounding environment by means of an omnidirectional IR camera. With the IR camera, the sky appears distinctively dark; this facilitates the detection of the borderline between the sky and the surrounding buildings, which are captured in white, due to the difference in the atmospheric transmittance rate between visible light and the IR rays. Positioning is performed only with visible satellites having less multipath errors, and without using invisible satellites. With the proposed system, static and kinematic evaluations in which invisible satellites are discriminated through observation using an omnidirectional IR camera are conducted. Hence, signals are received even if satellites are hidden behind buildings; furthermore, exclusion of satellites having large errors from the positioning computation becomes possible. The evaluation results confirm the effectiveness of the proposed technique and the feasibility of highly accurate positioning. ©2008 IEEE.

Precise highway alignment data to be used in car navigation and ITS to increase driving safety must be kept up-to-date and accurate. A Mobile Mapping System (MMS) provides a highway alignment database and offers unparalleled productivity when combined with navigation and videogrammetry tools. The MMS we propose features a GPS/Dead Reckoning (DR) combined navigation system, a three-axis GPS-Gyro/ Inertial Measurement Unit (IMU), laser scanners, nearly horizontal cameras, and network-based Positioning Augmentation Services (PAS (TM)) (Mit-subishi Electric Corporation) and measures centerline and side-line locations precisely based on a 3D road surface model. The carrier-phased D-GPS/DR navigation system and GPS-Gyro/IMU conducts highly accurate positioning in centimeters and posture estimation at 0.073 degrees rms for heading, 0.064 degrees rms for pitch, and 0.116 degrees for roll. It provides 0.095 m rms accuracy for both center-line and side-line measurement when GPS visibility is sufficient. A comparison of accuracy between static RTK-GPS measurement and MMS measurement on the Tateyama Kurobe alpine route confirmed MMS dynamic measurement accuracy and effectiveness.

This paper discusses a hot spring power generation system using the thermal energy obtained from the temperature difference between the hot water drawn up and the hot water supply to the hot spring facilities. In order to clarify the feature of a hot spring power generation system using ammonia (NH_3) as the working fluid, the thermal efficiency, required hot water flow rate, and sizes of heat exchangers and turbine rotor are calculated compared with the conventional system using chlorofluorocarbon (R134a, R123, R22 ) as the working fluid. As the results, it shows the effectiveness of a hot spring power generation system using NH_3.

The energy saving potential of micro-scale gas engine cogeneration systems installed in detached residential houses was studied experimentally and theoretically. First, the energy demands for electricity and hot water were measured experimentally, with a 1-minute sampling time interval, in two houses for one year. Based on these measured data, a simulation model was built to analyse and compare the energy saving characteristics of the cogeneration systems with a corresponding conventional system. The estimated results show that the total primary energy consumption of the cogeneration system in the two houses was 4.5% and 10.1% higher than that of conventional system. Therefore it did not contribute to energy saving in these houses. Next, the maximum potential energy saving characteristics of the cogeneration system was investigated by constructing a mathematical model which optimises the system's operation to minimise total primary energy consumption. It became clear that under theoretically optimal conditions the above total primary energy consumption ratios could be decreased by up to 5.5% and 6.6% in the two houses.

In order to empirically study a cogeneration system, an advanced co-generation system (ACGS) was built in Waseda University in 1999. The ACGS consists of a gas turbine system, a steam turbine system, an ammonia-water mixture turbine system, an ammonia absorption refrigerator system and an ice storage system. In the bottoming stage of ACGS, by activating an ammonia-water mixture turbine system and an ammonia absorption refrigerator system, both of which are effective for heat recovery of low temperatures, the system is made up positively using the heat cascade, which is unique compared to other systems. At present, for the introduction of the co-generation system, its practicality is not fully considered and a method has not yet been established which would lead to an operating method fitting the characteristics of the customer requirements. So it is considered very important to propose the most suitable system construction, taking an overall view of the annual earnings and cost of energy for the customers. In this paper, we cover an assumed system which changed the part of composition of ACGS and, in order to find out the initial advantages of the system, seek the most suitable composition and the most suitable operational planning of a system for cooling, electricity and heat demand of a typical hotel, and then propose an example of the system design guide.

In the near future, precise digital map data is said to be applied to the next generation car navigation system as well as ITS to increase the driving safety. It is important to maintain digital map data's freshness and accuracy. A MMS (Mobile Mapping System) can acquire this highway database, while offering unbeatable productivity with the combination of navigation and videogrammetry tools. The proposed MMS, featuring a GPS/DR combined navigation system, a GPS-Gyro/IMU, nearly horizontal cameras, laser scanners, high sampling rate road data measurement logger, and the network-based RTK-GPS PASTM can acquire road feature location like snow-poles, guard-rails, road signs and road line precisely at normal cruising speed considering 3D road surface model. The carrier phased D-GPS/DR combined navigation system and GPS-Gyro/IMU performs highly accurate positioning performance at a few centimeter and posture estimation at 0.073 [deg rms] for heading and 0.064 [deg rms] for pitching, and 0.116 [deg rms] for rolling. Furthermore, the proposed road feature digitizing method, featuring 2D camera image projection to the 3D road surface model, allows users to understand complicated 3D point-cloud data intuitively and to designate desired road feature with few mistakes. The accuracy comparison between the static RTK-GPS/Total-Station measurement with the dynamic MMS mobile measurement reveal that the system allows 0.3 [m] road feature measurement accuracy with unbeatable productivity when sufficient GPS visibility is obtained. ©2007 IEEE.

This paper describes an outdoor positioning system that can be applied for an urban canyon by using an omni-directional IR camera and the DSM (Digital Surface Model). The image captured by an IR camera has high robustness to light disturbances in the outdoor environment. The omni-directional image, which includes several building profiles, is compared with building-restoration images that are calculated from the corresponding DSM in order to identify the self-position. Field experiments at Fujisawa City show that the proposed outdoor positioning method is valid and effective even if high-rise buildings cause satellite blockages affecting GPS measurements. ©2007 IEEE.

In order to empirically study a cogeneration system, an advanced co-generation system (ACGS) was built in Waseda University in 1999. The ACGS consists of a gas turbine system, a steam turbine system, an ammonia-water mixture turbine system, an ammonia absorption refrigerator system and an ice storage system. In the bottoming stage of ACGS, by activating an ammonia-water mixture turbine system and an ammonia absorption refrigerator system, both of which are effective for heat recovery of low temperatures, the system is made up positively using the heat cascade, which is unique compared to other systems. At present, for the introduction of the co-generation system, its practicality is not fully considered and a method has not yet been established which would lead to an operating method fitting the characteristics of the customer requirements. So it is considered very important to propose the most suitable system construction, taking an overall view of the annual earnings and cost of energy for the customers. In this paper, we cover an assumed system which changed the part of composition of ACGS and, in order to find out the initial advantages of the system, seek the most suitable composition and the most suitable operational planning of a system for cooling, electricity and heat demand of a typical hotel, and then propose an example of the system design guide.

Drying of wet wastes is expected to be effective in reduction and recycling of them. However, water-evaporation operations of concentration and drying are typical energy-intensive processes because the latent heat of vaporization of water is quite a lot. Therefore, an unique technology to achieve energy savings is studied. In this system, the output steam generated in drying wet wastes is compressed, and the heat of the steam is utilized to heat the material itself. This paper describes the basic characteristics of this system. Experiments in which water was used as the heated material, availability analyses to estimate which components cause bigger losses, and calculations to estimate the effects of the efficiency changes of each components to the system were conducted.

In recent years, automation system based on IT technology becomes very popular not only for manufacturing industries but also for the construction and civil engineering industries. The conventional location survey method in the civil engineering construction site is pinpoint location survey for a broad objective area. The conventional method has severe constraints when it comes to measure the broad objective area as macro or to estimate general distinctive geometrical features. In this study, a unique vehicle-mounted mobile measurement system which can measure dense 3D point-cloud data for wide construction site is presented. The proposed MMS (Mobile Mapping System) is equipped with the carrier phased D-GPS/DR combined navigation system, the GPS gyro, and a laser scanner. The MMS, which measures unleveled round surface at 40 [km/h] using laser scanner's range data and vehicle attitude stabilization algorithm, can construct continuous dense road surface 3D model. The functional and performance test as a mobile measurement instrument is revealed.

In the near future, precise road line location data is said to be applied to car navigation system and ITS to increase the driving safety. It is important to maintain road data freshness and accuracy. A MMS(Mobile Mapping System) can acquire this road database, while offering an unbeatable productivity with the combination of navigation, and videogrammetry tools. The proposed MMS, featuring a GPS/DR(Dead Reckoning) combined navigation system, the 3 axes GPS-Gyro/IMU(Inertial Measurement Unit) , laser scanners, and nearly horizontal cameras, can measure centerline and side-line location precisely considering 3D road surface model based on a laser scanner. The carrier phased D-GPS/DR combined navigation system and GPS-Gyro/IMU performs highly accurate position and posture estimation at a few centimeter and 0.1 degree order. It can be said that the proposed MMS and its unique road signs positioning method is valid and effective as the road sign location error is within 100[mm] even in the slanted road by considering the 3D road surface model.

This paper reports on the demonstration of a hybrid power generation and refrigeration cycle in a turbine system which employs ammonia-water mixture as the working fluid. The hybrid cycle is the one in which the ammonia-water mixture turbine cycle and the ammonia absorption refrigerator are combined. To demonstrate the performance enhancement of the hybrid cycle, its steady state characteristics were experimentally investigated. The increase of the coefficient of performance (COP) and the performance improvement of the cycle are mainly due to a reduction of the heat of rectification at the ammonia absorption refrigerator. Therefore, the authors especially focused on the COP, the heat source steam consumption rate, and the heat of rectification when the ammonia mass fraction at the rectifier inlet increased. Results showed the COP and heat source steam consumption rate improved about 20% in hybrid operation, compared with normal operation which drives the ammonia absorption refrigerator and the ammonia-water mixture turbine cycle separately. Copyright © 2006 by ASME.

In this paper, a unique dense 3D shape reconstruction method featuring GPS/DR coupled omni-direction multi-baseline motion stereo system is presented. The epipolar plane equation between two Omni Directional Vision images is computed from the GPS/DR s position and posture information. Then, the precise epipolar lines can be obtained robustly by projecting the intersection line between the epipolar plane and the ODV s image plane. The robust matching method featuring hybrid use of the future based matching and the area based matching, as well as the bi-directional matching which chose common mutual matching points to improve robustness is also presented. Voting process using multi-baseline is used to reduce distance error of motion stereo. Hundreds of dense range images are unified based on the precise position/posture information to generate the successive dense 3D outdoor model. The range estimation accuracy within 10 [m] area is 140 [mm], which is equal to a laser radar. It can be said that the propos d omni-directional stereo vision has robustness toward environmental complication and accurate distance estimation performance for rich textured object. ©2006 IEEE.

The development of road telematics requires the management of continuously growing road database. A MMS(Mobile Mapping System) can acquire this road database, while offering an unbeatable productivity with the combination of navigation, and videogrammetry tools. The proposed MMS, featuring a GPS/DR(Dead Reckoning) combined navigation system, a GPS-Gyro/IMU(Inertial Measurement Unit) , laser scanners, nearly horizontal cameras and high sampling rate road data measurement logger, can measure centerline and side-line location precisely considering 3D road surface model based on a laser scanner. The carrier phased D-GPS/DR combined navigation system and GPS-Gyro/IMU performs highly accurate position and posture estimation at a few centimeter and 0.1 degree order. It can be said that the proposed MMS and its unique road signs positioning method is valid and effective as the road sign location error is within 100[mm] even in the slanted road by considering the 3D road surface model©2006 IEEE.

This paper describes phased earthquake data collection system by cooperation of mobile robots and the Temporal Spatial GIS. This proposed method features three phased data update and the change region modeling as KIWI+ building object data. The first stage sends the robot position and the omni-directional images as soon as possible. On the second stage, 3D environmental data with image texture which is obtained by omni-directional motion stereo augmented by the RTK-GPS/INS, is sent as the VRML format. Finally, “change region”, which is recognized by difference operation between the obtained 3D environmental data and the GIS database, can be recognized as new KIWI+ object data. Field experiments and analyses have proved that the proposed system can provide sufficient data collection/update performance under complicated outdoor environment.

This paper reports the effectiveness evaluation of a power and refrigeration hybrid cycle which is driven by a sensible heat source. The hybrid cycle employs ammonia-water mixture (AWM) as working fluid; in the configuration with which the ammonia absorption refrigerator and the AWM turbine cycle are connected by several pipelines. The authors carried out the simulation calculation, and investigate the performance of the hybrid system when the heat source flow rate ratio changes. In order to compare the consequences of the calculations, the exergy efficiency and the exergy availability are defined. The exergy efficiency or the exergy availability increase correspond the effect of hybridization. The increase of the exergy efficiency becomes maximum (5.1%) when the flow rate ratio is 0.25, and that of the exergy availability becomes maximum (2.9%) when the flow rate ratio is 0.75.

Generally, it takes a lot of time for us to solve the liner programming that is modeled in the round to plan a optimal co-generation system. In this paper, we suggest one method to handle demand data in advance according with a frequency data of the demand. Preliminary calculation of the cost implies us some possible choice of the optimal system size and structure, before solving the optimal plan in co-generation system.

This paper reports results from experimental investigations of the dynamics of an ammonia-water mixture turbine system. The mixture turbine system features Kalina Cycle technology [1]. The working fluid is an ammonia-water mixture (AWM), which enhances the power production recovered from the low-temperature heat source [2], [3]. The Kalina Cycle is superior to the Rankine Cycle for a low temperature heat source [4], [5].
The ammonia-water mixture turbine system has distillation-condensation processes. The subsystem produces ammonia-rich vapor and a lean solution at the separator, and the vapor and the solution converge at the condenser. The mass balance of ammonia and water is maintained by a level control at the separator and reservoirs at the condensers. Since the ammonia mass fraction in the cycle has a high sensitivity to the evaporation/condensation pressure and vapor flow rate in the cycle, the pressure change gives rise to a flow rate change and then level changes in the separators and reservoirs and vice versa. From the experimental investigation of the ammonia-water mixture turbine system, it was observed that the sensitivity of the evaporating flow rate and solution liquid density in the cycle is very high, and those sensitivity factors are affected by the ammonia-mass fraction. This paper presents the experimental results of a study on the dynamics of the distillation process of the ammonia-water mixture turbine system and uses the results of investigation to explain the mechanism of the unstable fluctuation in the system.

This paper presents the results of a preliminary investigation into the effect of installing an ejector in an ammonia-water mixture turbine cycle, also called a Kalina cycle. To enhance the availability of the cycle, we focus on the pressure difference in the cycle. The temperature difference between the heat source and sink enhances the efficiency of the thermodynamic cycle, as does the pressure difference in the cycle. To improve the heat recovery in the cycle, other heat exchangers are required, and to utilize the pressure difference in the cycle, an ejector is a reasonable choice. From the viewpoint of the impact on the initial cost of the plant, the heat exchanger option is more costly than the ejector option. The authors investigated a simple AWM turbine cycle with an ejector driven by the high-pressure solution stream to vacuum the turbine exhaust. Simulations of several AWM turbine cycle configurations, with or without heat recovery exchangers and ejectors were performed. The specific power, which is the output power per unit mass flow rate of the heat source, of the proposed cycle EJT34 was 103% that of the WMTS. The thermal conductance is only about 24% of that of the WMTS, which is almost the same as the value of the KCS34. The results shows that the EJT34 produced as much power as that from the WMTS with 24% of the heat transfer area.

This paper presents the optimal plan in an assumed co-generation system based on Advanced Co-generation system built in Kikui-cho campus and suggests the introductory technique of co-generation system. At first, we analyzed the annual change of the electric power and cooling demand for a typical consumer and completed the assumed model by formulating. In hospital, hotel, etc., it was checked that electric power and cooling demand have the high correlation with outside temperature, and the daily maximum temperature is effective as an explaining variable especially. We verified the optimal planning according to the consumer using this assumed demand.

This study describes mobile robot surveillance system using spatial temporal GIS. This paper specially describes the method of collecting spatial temporal data by an autonomous mobile robot system used in a factory premises with some high-rise buildings. This system consists of a wireless LAN network, a base station and an autonomous vehicle. The vehicle is equipped with a GPS/INS navigation system using the network-based Real-Time Kinematic GPS (RTK-GPS) with Positioning Augmentation Services (PAS™, Mitsubishi Electric Corporation 2003), an Area Laser Radar (ALR), a slaved camera, and an Omni-Directional Vision (ODV) sensor for surveillance and reconnaissance. The vehicle switches control modes according to the vehicle navigation error. It has three modes, "Normal", "Road tracking", and "Crossing recognition". A field test result shows that the vehicle can track the planned-path within 0.10 [m] accuracy at straight paths and within 0.25 [m] for curved paths even if RTK fixed solutions are not available. Field experiments and analyses have proved that the proposed navigation method can provide sufficient navigation and guidance accuracy under poor satellite geometry and visibility. Omni-directional image and ALR's scan data, which is synchronized with both position and GPS time, is memorized as spatial temporal. This spatial temporal data enables the operator to search everywhere in the factory premises efficiently by way of arbitrary position or measured time. The field test reveals that the spatial temporal database is confirmed to be useful for remote surveillance. © 2005 IEEE.

In this paper, the unique omni-directional motion stereo method featuring robust epipolar estimation and hybrid use of the feature/area based matching, and the change-region recognition technique which uses dense color-textured depth map and 3D-GIS data for segmentation, are presented. The dense stereo imaging data, which is acquired by the coupled use of an ODV (Omni-Directional Vision) and a GPS/INS (Inertial Navigation Systems) by the motion stereo method, is classified in "change region" or "registered region" by the 3D-GIS's geometric model of the building. Hence, the changeable region like a parking-vehicle on the road is modeled as a hexahedron through surface recognition process, the position of vertexes and the image texture of three surfaces are measured, and are additionally registered in the Spatial Temporal GIS (Geographic Information System) as new object data. The proposed method can be applicable to a mobile robot surveillance system which is used in a site immediately after a disaster. © 2005 IEEE.

In this study, an advanced cogeneration system (ACGS) composed of three turbine systems and an ammonia absorption refrigerator is presented. The overall system configurations and some experimental results of the steady state are shown. The effectiveness of the bottoming stage that employs an ammonia-water mixture (AWM) as the working fluid is confirmed by experimental investigation. The experimental investigation shows that the AWM bottoming power-refrigeration cycles contributes to a higher bottoming efficiency, which is about 7.0% in electric power. Otherwise. the efficiency at the middle stage in conventional combined gas and steam turbine power plants is 4.6%. The cogeneration efficiency at the bottoming reached about 26.5% which is the heat and power ratio to the heat input from the heat recovery steam generator. (C) 2004 Elsevier Ltd. All rights reserved.

This paper presents an experimental investigation of the effectiveness of an AWM (Ammonia-Water Mixture) turbine system with low temperature heat sources. The AWM turbine system (AWMTS) features Kalina cycle technology, namely, it employs an ammonia-water mixture as the working fluid and includes a separation / absorption process of NH3-H2O. Since AWM is a non-azeotropic mixture, its temperature changes during evaporation and condensation. This behavior gives AWMTS the advantage of heat recovery from a sensible heat source such as exhaust gas. It is known that an AWMTS can generate more power than a Rankine cycle system from 250-650 °C sensible heat sources. The authors constructed a 70 KW-experimental facility and investigated the practical applications of AWMTS. It is located at the bottoming stage below a conventional combined cycle composed of a gas turbine and a steam turbine. Its heat source is the exhaust steam from a back pressure steam turbine at the middle stage of the system. The experiment was carried out with changing the back pressure of the steam turbine. The experimental results show that power generation is possible from 138 to 162 °C heat source steam.

In this paper, authors propose and investigate an Ammonia-Water Mixture (AWM) turbine system with ejector. The AWM turbine system is a power cycle which is similar to a Kalina cycle. The AWM turbine system without ejector has high pressure solution which is led to the condenser through the reducing valve without using potential of the pressure. For using the pressure difference effectively, a new cycle configuration which installs ejector is proposed. The results of simulations show that the turbine system with ejector generates larger output power than that without ejector under the same condition. And the simple configuration cycle can be expected to generate almost as much output as more complicated cycle by installation of ejector.

This paper presents an experimental investigation on effectiveness of the AWM (Ammonia-Water Mixture) turbine system to the lower temperature heat sources. The system features two subsystems: a distillation/condensation subsystem (DCSS) and a vapor generator subsystem (VGSS). The experimental result and calculation results show that DCSS functions when the heat source is higher than 100 [℃], and VGSS functions when the heat source is over than 180 [℃]. Since the main application of the AWM turbine system is the heat recovery and there are abundant 100-200 [℃] exhaust heats as unused heat sources, effectiveness of the system to the lower temperature heat source, especially from 100 to 200 [℃], is very important. The experiment was carried out with changing the back pressure of the steam turbine.

This paper reports about the mechanism of pump error at starting-up of ammonia-absorption refrigerator, and the countermeasure for it. First, the authors analyzed relations between the pump error and the transitional change of state at the absorber. Then, the starting-up experiments to evaluate the countermeasure for the pump error are carried out. Consequently, there is the optimum ammonia-water solution flow rate through the spray nozzle of the absorber. And no pump error occurs at the solution flow rate.

This paper presents the optimal plan in an assumption co-generation system based on Advanced Co-generation system built on Kikui-cho campus and suggest the introductory technique of co-generation system. At first, we analyzed the change in a year of the electric power and cooling demand in a typical consumer and completed the assumption model by formulizing. In the hospital, the hotel, etc., it was checked that electric power and cooling demand have the high correlation with outside temperature, and the maximum temperature in one day is effective as an explanation variable especially. We verified about the optimal planning according to the consumer using this assumption demand.

The performance of the rectifying column affects the coefficient of performance (COP) of an ammonia absorption refrigerator. Ammonia mass fraction of refrigerant is one of the key parameters indicating the performance of the rectifying column. We propose a method to estimate the refrigerant mass fraction with mass and energy balance equations around the separator at the inlet of the evaporator, and describe the results of experiments which measured the refrigerant mass fraction by sampling from the refrigerant receiver. Throughout these investigations, the refrigerant mass fraction turned out to be lower than the expected value calculated from the condition of dry-saturated vapor at the top of the rectifying column. The refrigerant mass fraction can be estimated within an accuracy of 0.3% by the estimation method based on mass and energy balance equations.

This paper presents the experimental study of a unique co-generation system which the authors call the "Advanced Co-Generation System (ACGS)". It mainly consists of three turbine systems and an ammonia absorption refrigerator (AAR). The specialty of the ACGS is the bottoming stage employing an ammonia-water mixture (AWM) as the working fluid. First, the overall system configuration and some experimental results at the steady state are shown. The experimental investigation shows that the AWM bottoming cycles contribute to a higher efficiency of the system. An increase of 5-10% in electric power compared to a conventional co-generation system (CGS) is confirmed. Next, a hybrid configuration of the AWM turbine (AWMT) cycle and the AAR is investigated. A simulation model is constructed. The results of the simulation show that the hybrid configuration performs at about 14% higher efficiency.

The advanced co-generation system (ACGS) was built at Waseda University in 1999. We used MILP as the mathematical plan that has shown the example of an operation plan. In this paper, optimal operation planning of the bottoming stage of the ACGS with practical cases of the cooling demands 'such as a hotel and a hospital' in a day is discussed. The difference between the continuous operation cases (of 24 hours), and the daily start/stop operation cases is also discussed.

This paper is an additional report to the paper by Amano (2001). In this paper, the authors report the additional experimental results of the effect of an ammonia mass fraction at the inlet of the AWM (Ammonia-Water Mixture) vapor generator in the AWM turbine system. The AWM turbine system features the Kalina Cycle technology. The 70KW-experimental facility was built in order to gain knowledge for practical applications. The heat source is the exhaust steam from a back-pressure steam turbine. The AWM turbine system is installed at the bottoming stage of a combined cycle which has a gas turbine, a steam turbine and an AWM turbine for cascade utilization of heat. The authors designed and constructed an experimental facility, the ACGS (the Advanced Co-Generation System), to investigate various energy-saving technologies for a distributed energy supply system in the Advanced Research Institute for Science and Engineering at Waseda University. One of the main targets is a hybrid combined heat and power supply system that uses AWM as its working fluid. The AWM turbine system was developed for the bottoming stage of a "trinary turbine cycle system" which is composed of a gas turbine, a steam turbine and the AWM turbine systems. The experimental results of the ammonia mass fraction to the cycle efficiency are investigated with a range of the ammonia mass fraction between 0.4 [NH3kg/kg] to 0.7 [NH3kg/kg]. It shows that there are optimal operating conditions depending on the heat source temperature with an ammonia mass fraction of the cycle. The simulation model of the AWM turbine system shows good agreement with the experimental data.

In this paper, authors propose a hybrid power and refrigeration system which employs ammonia-water mixture (AWM) as the working fluid. The hybrid system is composed of an AWM turbine system and an ammonia absorption refrigerator. The AWM turbine system is a power cycle which is similar to a Kalina cycle. The ammonia absorption refrigerator is a single-stage absorption chiller. The results of the simulations show that the hybrid system generates larger output power than that of separate configuration of the AWM turbine system and the ammonia absorption refrigerator under the condition of the same refrigerating capacity.

The advanced co-generation system (ACGS) was built at Waseda University in 1999. The ACGS consists of a gas turbine, a steam turbine, an ammonia-water mixture turbine, an ammonia absorption refrigerator and an ice storage system. These turbine systems have a cascade relation upon the utilization of energy. Meanwhile, the ammonia-water mixture turbine and the ammonia absorption refrigerator located in the bottoming stage of the ACGS to utilize the lower temperature steam. In this paper, a mathematical model of the bottoming stage of the ACGS is established according to the experimental data. And, the operational planning of the bottoming stage with three cases of the cooling demand during the nighttime is also discussed.

The Advanced Research Institute for Science and Engineering at Waseda University designed and constructed an experimental facility, the ACGS (the Advanced Co-Generation System), to investigate various kinds of energy-saving technology for a distributed energy supply system. One of the main targets is a hybrid combined heat and power supply system that uses AWM (ammonia-water mixture) as its working fluid (Amano et. al., 1999). The AMW turbine system was developed for the bottoming stage of "trinary turbine cycle system." The trinary cycle system is the main part of the ACGS and consists of a gas turbine cycle in the topping stage, a steam turbine cycle in the middle stage and the AWM turbine cycle in the bottoming stage. The AWM turbine system is capable of simulating various vapor mixture conditions observed in the heat exchangers proposed for use in the Kalina cycle and other thermodynamic cycles that use AWM as their working fluid. We call the AWM turbine system the Waseda Ammonia-Water Mixture Turbine System (W-MTS). The ACGS project team has constructed an experimental facility for the AWM turbine system and carried out the first trial run. This paper discusses the basic characteristics of the AWM turbine cycle and describes its input/output characteristics. Steady state characteristics experiments were carried out on the W-MTS to investigate the following: (1) the effect on the distillation/condensation subsystem (DCSS), namely, the effect of temperature at the inlet of the separator in the DCSS and the effect of the reflux loop, which enhances heat transfer in the condensing process, and (2) the effect on the vapor generator subsystem, (VGSS), namely, the effect of evaporating pressure and the effect of changes in the heat source. From the experimental results, we derived the basic characteristics of the turbine cycle as an input/output model, and the planning and control guide to be used in the turbine system in the bottoming stage.

Our previous binary turbine system, which employs steam as the primary working fluid, used R11 as the secondary working fluid because R11 has good characteristics as a working fluid in power plants. However, substitute LBMs (Low Boiling temperature Mediums) are being developed because of the ozone layer depletion by CFCs. We investigated the system using R123 in the next stage. Because R123 is also controlled, in the previous paper, modeling of the dynamics of a directly combined binary turbine system using a mixture of R134a and R123 are described. In this paper, the steady state characteristics and dynamic behavior of the system using a mixture of R134a and R123 are investigated taking into account the mole fraction of the mixture. In addition to the investigation using the experimental system, the following are clarified using our model: In the steady-state characteristics, there are remarkable differences in pressure based on the thermodynamic properties and in the load allotment of the two turbines. However, in the dynamic characteristics, the effect of the mole fraction could hardly be observed on the response characteristics of the rotating components to the load change.

An ammonia-water mixture (AWM) turbine system, the so-called Waseda ammonia-water Mixture Turbine System (W-MTS), is described. Results of cycle simulation are discussed which show that the W-MTS is superior to the other simple Kalina cycles (KCS1 and KCS34) to pressurized hot water and steam as a latent and a sensible heat source at a temperature of 160°C.

The binary turbine system that employs steam as the primary working fluid has used R11 as the secondary working fluid, because R11 has good characteristics as a working fluid in power plants. However, substitute LBMs (low boiling-temperature mediums compared with water) are being developed because of the destruction of the ozone layer by CFCs. In this paper, modeling and experimental investigations into the dynamics of a directly combined binary turbine system using R123 instead of R11 are described. The system consists mainly of a steam- and an R123-turbine, an R123 vapor generator, and an AC generator. The dynamic behavior of the system is discussed from the viewpoint of the network theory. The components of the system are represented as two- or three-port elements of the network and the vapor flow rate and shaft torque are appropriated as the through variable, and the vapor pressure and rotational speed as the across variable. As a result, a very simple network model based on the dynamics of various turbine systems like this was derived. The validity of the model was proven through comparison with our experimental results, which are the frequency responses examined with respect to generator load changes. In addition, we demonstrate that the model is very effective in predicting the dynamic behavior and power generation mechanism of directly combined binary turbine systems.

This paper shows the effects of the thermodynamic properties of several working fluids and operating conditions on the dynamics of condensing process from the network theoretic viewpoint. The authors have presented an approach to modeling of the dynamics of shell-and-tube type heat exchangers. These models are integrated to apply a wide variety of heat transfer modes, namely, condensing, evaporating, and heat transfer without phase change. We now present a more specific version of the condensing process. Investigation of the effects of thermodynamic property and confirmation of the validity of an approximation of internal energy with enthalpy are presented. As working fluids, R11, R12, R22, R123, R134a, ammonia and water (steam) are examined.

In this paper we present a model for the dynamics of a two-heat-exchanger network connected in parallel. The model is represented using the inner admittances, which represent the dynamics of each heat exchanger, in series. The series connection of the inner admittances indicates the complexity of the two-heat-exchanger network. The complexity mainly depends on the characteristic of the confluent process. The fluid temperature behavior in the pipe between the heat exchangers and the confluent junction markedly influences the characteristic of the confluent process. We investigate the dynamics of the two-heat-exchanger network with respect to the effect of the piping and the confluence. © 1998 Scripta Technica.

The results of the theoretical and experimental investigations on the dynamic characteristics of two shell-and-tube heat exchangers connected in parallel are presented. The relationship between the size and flow rate ratio of the heat exchanger and the difference between transportation times from the heat exchanger outlet to the confluence influence the dynamics of the system under the specified parameters. This suggests the importance of matching the size and operating condition of each heat exchanger and the piping arrangement to the confluent junction.

This paper presents a network-theoretical approach to the modeling on the dynamic characteristics of the shell-and-tube heat exchangers. Taking into account the phase conditions of hot and cold fluids upon heat-exchange, the shell-and-tube heat exchangers are classified into four types. At the same time, not only the steady state but also dynamic characteristics of the heat exchangers are classified into four types. Therefore they are usually considered and treated as different heat exchangers. In this paper, the dynamic characteristics of the four types of shell-and-tube heat exchangers are investigated theoretically. As a result, we derived the model on the dynamic characteristic of each type of the heat exchangers from the viewpoint of the network theory. In this model, the hot and cold fluid processes are represented as 2-port network elements interconnected, and each process consists of through variable sources and admittances in parallel. According to this model, the investigation on these admittances gives us important information on the dynamic characteristics of the shell-and-tube heat exchangers.