Power outage caused by natural disasters such as earthquakes and typhoons is likely to take a few days to restore service and has been one of the issues for social infrastructure. As climate change could make weather events severer and more frequent, it is getting more important to reinforce resilience against the malfunction of power system. Distributed Energy Resources (DERs), represented by integrated systems of photovoltaic power (PV) and batteries, are supposed to be effective to improve reliability of power supply as a part of Business Continuity Plans (BCPs) for consumers whose business needs continuous energy. However, clarifying the bene t of DERs in case of power outage is not easy due to variety of causes and uncertainty of occurrence. The objective of this study is to develop a process of evaluating the ‘resilience value’ of DERs. This process is expected to help reduce costs to reinforce overhead power lines against natural disasters by boosting DER installation on the demand-side. The evaluation process mainly consists of ve steps: evaluation condition setup, probabilistic risk assessment, resilience curve analysis, risk curve construction, and resilience value calculation. For the evaluation condition setup, speci cations of power supply equipment including DERs and daily load patterns of consumers changing with weather are collected to set evaluation conditions. Probabilistic risk assessment identi es likely combinations of component states in the demand-side energy system exposed to hazards by event tree analyses. In the resilience curve analysis, transient balance between consumer load and available DER supply during power outage is calculated for each combination of component states by optimizing objective functions to minimize costs considering the penalty for lost load which is divided according to three importance levels. Risk curves are drawn with lost load associated with each combination of component states and cumulative probabilities for its occurrence, providing expected values of lost load caused by the hazards. Eventually, ‘resilience value’ is acquired as the difference between values of lost load (VoLL) with DERs and without any demand-side countermeasures. As a case-study, the resilience values of a single ve-storied building in case of an earthquake were evaluated. The building had been originally equipped with an emergency diesel generator (EDG) for its critical load demand and was assumed to add PV power system with batteries at the roof oor in the evaluation. For the risk analysis, fragility values of six system components by an earthquake leading to seven-day power outage were determined, and occurrence probabilities for combinations of component states were acquired. Resilience values were calculated from the difference in the area formed by the risk curves. The results showed that resilience values for the total service life of the equipment would increase if the renewable DERs were added to the building. The application of the evaluation process will be extended to complex facilities with multiple buildings and DERs connected with each other.

The peak demand for railway power occurs when trains operate at full capacity, which calls for the need of facilities that can handle such peaks. These expansive railway power facilities, which cover vast areas, result in increased maintenance and management costs while affecting the power supply to traction substations (TSs). Herein, we investigated the load leveling of TSs using energy storage systems (ESSs). Most of the studies that have been conducted on the use of ESSs in electric railways have focused on high‐speed railways and urban lines. The application of ESSs to local lines is expected to be highly effective in reducing the capacity of power facilities using the load leveling of TSs. However, the introduction of ESSs to such local lines has not yet been discussed in detail. Hence, we focused on the relationship between ESS specifications (battery capacity, kWh) and load peak reduction (kW) and proposed a method to determine the ESS specifications by simultaneous optimization using linear programming. Numerical calculations were performed based on measured data from a real line, and the proposed method was verified in terms of battery capacity, load peak reduction, and ESS operation ratio. The numerical results indicate that the maximum load of the TS can be reduced by 98.7% and 91.1% using 380 kWh and 65.42 kWh ESS, respectively, considering its cooling time. This highlights the potential of Energy Storage Systems (ESSs) to balance TS (Time‐of‐Use) loads and consequently reduce power facility requirements. © 2024 The Authors. IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Increasing renewable energy (RE) penetration is indispensable for achieving a carbon-neutral society. In particular, a methodology to ensure profitability through the electricity market is a crucial technology for RE producers with unstable output, such as wind power, and a decision-making framework for bidding based on the uncertainty of generation and market prices is essential. This study proposes a day-ahead bidding scheduling method for RE generation targeting two Japanese markets. The proposed method includes functionalities to select appropriate bidding for markets from the viewpoint of maximizing expected revenues calculated based on probabilistic forecast results considering the uncertainty of RE generation and market transaction prices. The usefulness of the proposed method was evaluated through a numerical experiment using real-world historical data.

In recent years, there has been an emerging trend towards aggregation businesses in the distributed energy resources (DERs) that consumers utilise, where aggregators bundle their balancing power values for the balancing market. Therefore, this study proposes a three-stage optimization market bidding strategy for DERs. It incorporates a bidding strategy that considers the balancing market's characteristics and the conventional function of supplying electricity to consumers. The proposed method comprises three optimization stages. First, a bidding plan is devised. Second, a plan is formulated accounting for the execution results. Third, the plan is modified based on the output command value. The approach incorporates formulations accommodating DER activation and availability costs alongside simultaneous optimization by an energy service provider and aggregator. The effectiveness is evaluated based on market transaction simulations utilising real market data.

In this paper, a method for determining line drop compensator (LDC) parameters for step voltage regulators and on-load tap changers is proposed to avoid voltage violations in distribution systems with voltage fluctuations due to photovoltaic (PV) generation and electric vehicle (EV) charging. Distribution system operators need to effectively solve voltage problems caused by the widespread installation of distributed energy resources with the existing voltage regulators to construct an efficient and rational infrastructure. Our focus was on improving the method for determining the LDC parameters for the existing voltage regulators based on LDC control. A mechanism to dynamically change the LDC parameters depending on the situations in the distribution system was developed by using a mixture of experts, one of the machine learning techniques, and real-time voltage and power flow information from information technology switches. The power flow calculations were performed using a distribution system model constructed based on the topology, loads, and generation characteristics of an actual distribution system in the Hokuriku region. The effectiveness of the proposed method was evaluated in terms of its improved effect on PV and EV hosting capacity, as well as the impact on the frequency of tap operations of voltage regulators. © 2024 The Author(s). IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

The widespread introduction of functionally-smart inverters will be an indispensable factor for the large-scale penetration of distributed energy resources (DERs) via the power system. On the other hand, further smartization based on the data-centric operation of smart inverters (S-INVs) is required to cost-effectively achieve the same level of power system operational performance as before under circumstances where the spatio-temporal behavior of power flow is becoming significantly complex due to the penetration of DERs. This review provides an overview of current ambitious efforts toward smartization of operational management of DER inverters, clarifies the expected contribution of machine learning technology to the smart operation of DER inverters, and attempts to identify the issues currently open and areas where research is expected to be promoted in the future.

Distributed energy resources (DERs) such as photovoltaics (PV) and battery energy storage system (BESS) are effective for improving the target renewable energy (RE) rate in a region. Furthermore, it is expected that distribution system operators (DSOs) will promote their installation in the future. However, it is not enough for DSOs to simply install large-capacity PV and BESS. They need to determine these capacities by taking into account the cost reduction of equipment and the constraints on grid operation. In this paper, we propose a DER installation capacity optimization method based on linear programming using annual data and a layout method from the operator's perspective. This method determines the capacity of DERs based on the target RE utilization rate in a controlled area of a distribution system. Furthermore, we report the results of an analysis of power flow when the DER is introduced. Moreover, we estimate the actual required capacity of DERs for a real 2-feeder distribution system model. In addition, power flow calculations are performed for a typical day where that amount of DERs were installed. The results were evaluated in terms of grid voltage, thermal capacity of line, and distribution losses, and the necessary controls were discussed.

This study proposes an output curtailment method for determining the output curtailment of renewable energy sources (REs) to mitigate grid congestion in transmission systems with a significant influx of REs. To manage congestion, minimizing the total REs output curtailment while avoiding the concentrated output curtailment on a specific RE is crucial. As a means of identifying effective curtailment targets for congestion mitigation, sensitivity analysis is being used for quantifying the congestion mitigation effect with curtailment. Furthermore, equality in output curtailment can be ensured by grouping REs of similar sensitivity and uniformly curtailing each group. Minimizing the curtailment of REs under the grouping-based approach requires forming a group of REs that is sensitive to frequently congested lines, considering the tendency of congestion occurrence in the whole grid. Consequently, this study proposes a method for determining the output curtailment rate of REs using grouping based on weighted sensitivity, considering the sensitivity of each RE and grid congestion. The effectiveness of the proposed method was evaluated by numerical simulation of congestion management over one year on a grid in the northern area of the Tohoku region in Japan. The results indicated that the proposed method was superior in terms of total REs curtailment and equality compared to the comparison method that does not consider the grid congestion amount.

Voltage violations in distribution systems (DS) with large photovoltaic (PV) installations must be cleared. To regulate the voltage, Chubu Electric Power Grid has implemented a grid control system (GCS) that aggregates measurement information from switches with sensors, smart meters, step voltage regulators (SVRs), and on-load tap changers (OLTCs) to determine their control parameters. The GCS is characterized by its function to separate measured currents into load and PV currents for the consideration of measured power flow conditions with and without PV generation. Based on the results of numerical simulations using a real grid model, we evaluated the effect of separating functions on increasing the PV hosting capacity in this study.

In this study, we comprehensively evaluated the impacts of popularizing electric vehicles (EVs) and the time shift of EV charging on voltage regulation in distribution systems. Although the popularization of photovoltaics (PVs) and EVs is required to realize a sustainable society, the generation from PVs and the charging demand of EVs may cause voltage violations in distribution systems. To combat these challenges, distribution system operators (DSOs) must upgrade the facilities and management of distribution systems. To verify the strategies for future operations, DSOs evaluate the impact of distributed energy resources (DERs) installation and the effectiveness of the countermeasure candidates on voltage regulations. Therefore, this study assesses the impacts of EV popularization on voltage regulation using an actual distribution system model in the Hokuriku area of Japan. In the numerical simulation, EV and PV popularization levels are set from 0 % to 100 % in 20 % increments. Additionally, the effectiveness of the time shift of EV charging as a countermeasure for voltage regulations is evaluated. To validate the effectiveness, ratios of time-shift EVs are set to 20 % and 50 %. The results reveal the effectiveness and limitation of the time shift of EV charging.

The short-term frequency stability of power systems has decreased with the replacement of synchronous generators (SGs) with inverter-based resources. Grid-forming inverters (GFMIs), developed to maintain power system stability, are also effective for frequency stability. Virtual synchronous generators (VSGs) and droop controls (Droops) are major algorithms of GFMIs. VSGs are considered to outperform Droops in terms of frequency stability because of the existence of the inertia emulation block in the active power controller. However, few studies have identified the quantitative effect of the inertia emulation block of GFMIs on frequency stability. This study analyzes the effect by deriving the relationship between the inertial response and the frequency based on the swing equation of SGs. The method of the analysis is verified by the simulation by the PSCAD/EMTDC. As indicated in this study, after a disturbance, the inertia emulation block immediately increases the load share of the VSG and decreases that of the SG, resulting in improved frequency stability. Moreover, it is implied that the Droop, i.e., the GFMI without inertia emulation block, can improve frequency stability as the VSG by increasing the droop gain, although the Droop requires larger energy provision from the direct-current side than the VSG. This study clarifies the better performance of the VSG in frequency stability by quantifying short-term load sharing among GFMIs and SGs that are significantly related to the short-term frequency stability.

This paper proposes a distribution network operation scheme referred to as the zero emission grid (ZEG) in which all demand is met by renewable energy to reduce the environmental burden. In addition, we propose and evaluate a method for planning and controlling distributed energy resources (DERs) under this scheme. To meet the entire demand with renewable energy, it is necessary to install photovoltaic (PV) and battery energy storage system (BESS), and to control them appropriately to satisfy the grid operation constraints such as voltage and thermal line capacity. Therefore, we propose a PV capacity determination method to achieve ZEG and a BESS charging/discharging method to satisfy the grid constraints under the PV installation of the calculated capacity. Furthermore, we performed numerical simulation using a two-distribution-line model with the calculated capacity of PV to evaluate the effectiveness of the proposed DER management method. The results demonstrated that the proposed method could satisfy the power flow constraints and utilize the BESS efficiently.

With the recent introduction of renewable energy sources, the shortage of the transmission line capacity (i.e., grid congestion) in Japan is a major concern. To maximize the output of wind turbines (WTs), the installation area is determined by considering the grid congestion frequency and wind conditions when installing new WTs. However, determining the appropriate area may be challenging for some power producers in terms of the limitation of accessible information and construction of an evaluation platform as detailed information on the power system and power flow calculations is required. Therefore, this study assumes that the system operator shares the information of acceptable additional generation in each area without grid congestion based on past actual power flow data. Furthermore, using this information, a simple evaluation method is proposed for power generators to evaluate the frequency of grid congestion after the introduction of new WTs. To verify the usefulness of the proposed method, numerical experiments are conducted for several scenarios introducing WTs in a simplified power system model of the northern area of the Tohoku region. The results indicate that the proposed method can accurately estimate the frequency of grid congestion in the evaluation scenarios.

The amount of power generated by wind farms (WFs) varies depending on the wind conditions, and its use as the main power source within a power system is thus uncertain. This study proposes a balancing group (BG) scheme that combines the power from WFs with an existing variable-speed pumped-storage hydro generator (PSHG), which possesses a large capacity that can compensate for the variability in WF output. To maximize revenue, power suppliers need to schedule and operate the BG by considering the uncertainty in WF output and the PSHG's operational constraints. In the proposed method, probability density predictions (PDPs) are used to estimate WF uncertainty, and the BG output is scheduled to maximize the expected revenue. The PSHG water-level transition is managed within an operational limit using WF output scenarios derived from PDP results and historical WF output trends. The effectiveness of the proposed scheme was assessed based on revenue for three weeks with characteristic wind conditions, and the results of numerical simulations conducted using several operational schemes were compared using real-world WF output data. The results indicate that higher revenues can be achieved using the proposed operational scheme, thus validating the usefulness of the proposed method.

In distribution networks, grid operators need to prevent voltage violations when photovoltaic generation increases. As a countermeasure, they apply sophisticated updating of the control parameters of on-load tap changers (OLTCs). Furthermore, to upgrade the grid operation, the measurement granularity of smart meters has been altered from 30-minute increments to shorter times. However, in terms of data communication load reduction, only a few smart meters need changes. In this study, we evaluate the effect of smart meter data with short measurement granularity on the voltage control performance of an OLTC. As a method of programming consumers to acquire data every 5 min, we selected the consumers measuring the high or low voltage among the past measured database. The numerical simulations showed that voltage violations occurred with control parameters using 30minute measurement data. However, this could completely be avoided by using 5-minute data.

As the number of photovoltaic (PV) power generators connected to the distribution grid increases, applications of on-load tap changers (OLTCs), power conditioning systems, and static reactive power compensators are being considered to mitigate the problem of voltage violation in low voltage distribution systems. The reactive power control by power conditioning systems and static reactive power compensators can mitigate steep voltage fluctuations. However, it creates losses in generation opportunities. On the other hand, OLTCs are installed at the bases of distribution lines and can collectively manage the entire system. However, the conventional voltage control method, i.e., the line drop compensation (LDC) method, is not designed for the case in which a large number of PV systems are installed in the distribution network, which results in voltage violations above the limit of the acceptable range. This study proposes a method to determine the optimal LDC control parameters of the voltage regulator, considering the power factor of PV systems to minimize the magnitude of voltage violations based on the voltage profile analysis of low-voltage (LV) distribution networks. Specifically, during a measurement period of several days, the voltages at some LV consumers and pole transformers were measured, and the optimal parameters were determined by analyzing the collected data. The effectiveness of the proposed method was verified through a numerical simulation study using the actual distribution system model under several scenarios of PV penetration rates. Additionally, the difference in the effectiveness of voltage violation reduction was verified in the case where all the LV consumer’s consumer voltage data measured per minute were used as well as in the case where only the maximum and minimum values of the data within the measurement period were used. The results reveal that the proposed method, which operates within the parameters determined by the voltage analysis of the LV distribution network, is superior to the conventional method. Furthermore, it was found that even if only the maximum and minimum values of the measurement data were used, an effective voltage violation reduction could be expected.

As the Japan's feed-in tariff scheme, a renewable energy surcharge is charged in proportion to the grid power consumption. Authors proposed to replace this with a "CO₂ reduction surcharge" which is charged in proportion to CO₂ emissions. This paper evaluates nationwide effects of introducing this surcharge and storage battery when renewable energy is largely introduced. By optimizing hourly thermal power generation output of each type, PV/wind energy curtailment, charge/discharge amount and tie line power flow, the annual thermal power cost in Japan is minimized with linear programming methods. Then the CO₂ emissions and costs are evaluated. Results show the introduction of storage battery decreases PV/wind energy curtailment, but CO₂ emissions are not decreased because the energy share of coal-fired power generation is increased. When the surcharge unit price is increased, the availability and capacity of lower efficiency coal-fired power generation are decreased. Results also show that CO₂ emission intensity can be decreased to 0.2kg-CO₂/kWh when most of coal-fired plants are abolished, but then more capacity of LNG combined cycle power generation and more fuel costs are required.

Loss minimum reconfiguration technology has been studied well from the theoretical and computational perspectives in the past decades and is expected to implement to the real-world distribution systems. In the real-world implementation of loss minimum reconfiguration technology, one of the barriers is the preprocessing cost for modeling the physical characteristics of the distribution networks and grasping the spatio-temporal dynamics of the load in order to derive the expected energy loss based on the power flow simulation though it is desirable that this technology is applied to the site with high expected energy loss reduction effect preferentially, the above laborious preprocess for prioritization which requires to be conducted for all the existing distribution networks becomes a problem of rapid implementation. In this study, the authors discuss several statistical approaches for prioritization of distribution networks with high expected loss reduction effect, that does not require the exhaustive preprocess. Numerical experiments based on data acquired from the real-world demonstration test reveal pros and cons depending on the application situation of these prioritization methods.

To utilize renewable energy systems (RES) as main generators in power system, power system operators need to maintain reserve power to compensate the uncertain output of RES, such as wind farms (WF). This paper focuses on the balancing group (BG) composed of WF and a pumped-storage hydro generator (PSHG). In the BG operation, power system operators need to schedule the operation of PSHG to minimize the imbalance risk caused by the prediction error of WF output while considering the system specific constraints of PSHG, e.g. the mechanical constraint on pump-up/down switching. This paper proposes a method to schedule the PSHG operation using the interval prediction results of the WF output for alleviating the imbalance risk the proposed scheduling scheme is formulated based on the linear programming. To verify the effectiveness of the proposed method, the amount of imbalance and the net generation of the BG were evaluated based on numerical experiments under two types of situations with different characteristics in WF output. The experimental results reveal the effectiveness of the proposed method.

Off-grid is the power system that is completely separated from the commercial grid, and the system is introduced in remote areas such as islands. Currently, power is mainly supplied from diesel generators, but there are some problems that operation and management costs such as fuel and transportation costs are enormous, and that CO2 emissions are very large. Therefore, off-grid systems that have installed renewable energy are attracting attention. In this paper, the power system composition of off-grid mainly based on renewable energy, operation methods that enable efficient power supply, the generator capacity determination method that enables stable power supply are proposed and economical and environmental performances, generator capacities and operational parameters are evaluated. In addition, this study uses the data acquired on the actual island and is carried out by simulation.

This study evaluates the operational potential of pumped-storage hydro generators (PSHGs) as a regulating power source for the stable use of wind power generation. In recent years, the concept of a balancing group (BG), consisting of multiple generators, has been considered to alleviate the imbalance, defined as a discrepancy between planned and actual power supply values. Combining unstable power sources, such as wind power with controllable sources such as PSHG, is expected to reduce the imbalance in BG. For the effective utilization of PSHG, power system operators need to determine a schedule of operation considering the uncertainty in the wind farm (WF) output on the preceding day. In this study, the operation scheduling of PSHG, based on the interval prediction results of wind power generation, is discussed and the potential contribution of PSHG operation is assessed from the perspective of the imbalance reduction within this framework. The operational potential is evaluated from the viewpoint of the types of PSHG, that is, fixed-speed and variable-speed PSHGs, by the annual operational simulation using real-world WF output data. The results show that the appropriate operational scheduling of a single variable-speed PSHG can contribute to a reduction in imbalance comparable to the reduction achieved by two fixed-speed PSHGs.

This paper proposes a novel planning model for electricity-hydrogen energy system in consideration of imported hydrogen, hydrogen demand and renewable energy that is largely penetrated. The model is designed to reveal the optimal ratio of domestic and imported hydrogen production and uses non-linear variables such as start-up costs and partial load efficiency of thermal power generation plants with linear programming in an approximation manner. By using this model, the optimal power supply mix and hourly operation of the energy system in Kyushu, Japan in 2030 are explored. As the introduction of domestic renewable energy increases, domestically produced hydrogen will become more competitive than imported hydrogen, though the use of imported hydrogen is important for thorough decarbonization. The results show that the optimal solution is to use domestic or imported hydrogen up to the amount of surplus renewable energy and the hydrogen price.

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.

Forecasting the electricity spot market price (i.e., the price of electricity traded for the next day) is important in planning efficient power generation and demand schedules. This research aims to discuss the following two points in the forecasting task: an explicit scheme for estimating high and low-price situations and an effective weighted integration of given multiple forecast products depending on the estimated situations. The authors propose an adaptive method of combining market price forecasts (ADAPTIVE) to utilize several types of given forecast results efficiently and improve forecasting accuracy. The method aims to capture the features of the component models' results considering high- and low-prices situations. To evaluate the effectiveness of the proposed ADAPTIVE, numerical experiments were conducted on electricity spot market prices in the Japan Electric Power Exchange. The results indicate that the proposed method is a promising way to improve the accuracy of the conventional method of combining forecasts.

The vehicle electrification, the replacement of engine vehicles by hybrid (HV), electric (EV) and fuel cell vehicles (FCV) is expected to reduce CO₂ emissions in transport sector. However, the reduction amount by EV and FCV is largely affected by CO₂ emission intensity of power system and the way to make hydrogen. Authors simulate a power system in 2030 where a large amount of PV is implemented, and PV generated energy must be curtailed on many days. The annual cost is minimized by optimizing the hourly output of coal fired and LNGCC plants, when the 16% of passenger vehicle mileage is replaced by EV charged at midnight and/or daytime. In FCV case, the capacity of water electrolysis and hydrogen tank, and the hourly electrolysis output as well as thermal power plant output are optimized. Results show CO₂ emissions decrease particularly when EVs are charged at daytime and the charging power is controlled to contribute frequency stability. The electrolysis demand decreases the PV energy curtailment but increases the CO₂ emission because of the lower energy converting efficiency and higher facility cost. The energy chain including whole power system, demand and fuel is analyzed to see the power flow and CO₂ emission.

© 2020 Architectural Institute of Japan. All rights reserved. This study proposes operational strategies for combinations of equipment, including an electric vehicle (EV), in a house using self-consumption. The aim of this is to attain both comfort and efficient energy management under several household and regional conditions, focusing on the frequency of the EV's use as well as the residents' schedules. As operational strategies for self-consumption of surplus power, storage battery (BT) charging, EV charging and daytime operation of heat pump water heater (EC) were assumed. Moreover, the amount of self-consumption, CO2 emissions, and the cost-effectiveness of different equipment combinations were calculated and compared.

A District Heating and Cooling system (DHC) with Combined Heat and Power (CHP) is able to not only satisfy regional heat and cold demand but also generate and control electricity by CHP. Therefore, a DHC with CHP has potential as control reserve for electricity adjustment (EA). In Japan, an EA auction was established to secure control reserve efficiently. In our previous research, potential of EA by a DHC for this auction has already evaluated. Furthermore, it was found that kW and kWh costs of a DHC for EA mainly depend on the heat and cold demand. Operators of DHCs need to comprehend the exact costs for EA when they bid on the auction. Therefore, fluctuations in costs for EA due to changes in heat and cold demand have been a critical issue for operators in decision making for the bid. However, costs for EA of a DHC with comprehensive assumption of various heat and cold demands has not been evaluated. Therefore, in this paper, the kW and kWh costs of an existing DHC are quantified and visualized as a multidimensional function based on the conditions of heat and cold demands. In addition, the factors behind those results are discussed. As a result, this research made it possible to predict the costs for EA of the DHC with heat and cold demand forecasts, and the operator could use it as auxiliary information in decision making for the bid.

This paper proposes a method to determine the Line Drop Compensator (LDC)-control parameters of an On-load Tap Changer (OLTC) and step voltage regulator (SVR) using a database with measured data from offline IT-switches. In a conventional determination method, the parameters are calculated based on the relationship between the sending voltage and the absolute value of current at the secondary side of the OLTC/SVR with a fixed power factor. However, the power factor changes with the interconnection of the photovoltaic (PV) system. Hence, in the proposed method, LDC-control parameters are determined by the relationship between active current, reactive current, and sending voltage. In other words, the parameters are determined from the plane by taking these values as axes. The plane is determined by four measured data extracted from the database which have large voltage fluctuations in response to severe power flow. The effectiveness of the proposed method is verified by numerical simulations using a distribution system model with PV systems. Our results show that the proposed method can improve the amount of voltage violation by 35% compared to a conventional method.

Large-scale and regionally intensive introductions of renewable energy sources (RES) requires greater control capacity from frequency control generators (FCGs). To solve this problem, cross-regional operation, which integrates multiple control areas, is widely studied. However, this involves more complicated power flow, due to the wider control area. Thus, a transmission system operator should adjust output of FCGs to compensate for RES fluctuations, considering system indices and power system constraints in various power flow conditions such as day or night. We have proposed a multi-objective optimizing method for FCG dispatches to compensate for RES fluctuations in one case in the daytime. A simulation was needed, under various load and RES output conditions, to evaluate the validity of the method. In this study, a simulation is conducted, using a power system model base on the power system of East Japan under seven power flow conditions. The results support the validity of the proposed method for determining a dispatch, considering multiple system indices in all cases.

To reduce CO2emissions in transport sector, it is a hopeful way to replace gasoline vehicles (GV) by electric vehicles (EV) and fuel cell vehicles (FCV). However, the reduction is largely affected by CO2emission intensity of power system and the way to make hydrogen. Authors simulate a power system in 2030 where a large amount of PV is implemented and 16% of PV generated energy must be curtailed. The annual cost is minimized by optimizing the hourly output of coal fired and LNGCC plants, when the 16% of passenger GV mileage is replaced by EV charged at midnight and/or daytime. In FCV case, the capacity of water electrolysis and hydrogen tank, and the hourly electrolysis output as well as thermal power output are optimized. Results show CO2emissions decrease particularly when EVs are charged at daytime using a part of surplus PV energy and the charging power is controlled to contribute frequency stability. The electrolysis demand decreases the PV energy curtailment but increases the CO2emission because of the lower energy converting efficiency and higher facility cost. Constraint conditions of the minimum ratio of non-synchronous generation and frequency control ability affect the results too.

This study proposes a nonintrusive appliance load monitoring framework for estimation of the power consumptions of individual residential appliances by using aggregated total consumption based on Gaussian-softmax restricted Boltzmann machine with temporal reservoir. The proposed method is expected to estimate the hidden states of the appliances well by coding the current situation in the nonlinear temporal dynamics of the power consumption in the reservoir units so as to estimate the appliance-wise consumptions well. The accuracy of the proposed framework is evaluated by using real-world power consumption data sets.

© 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 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.

© 2020 Architectural Institute of Japan. All rights reserved. Renewable energy is the focus of the 5th Strategic Energy Plan in Japan. Electric load management systems such as Demand Response (DR) are necessary to increase renewable energy usage. The focus of this study is pre-cooling operations in the daytime, during summer, to reduce electric load during DR. The aim of this study is to evaluate (1) the effectiveness of electric demand shift by "Pre-cooling", and (2) the effect on comfort and health of the residents who switch to "Pre-cooling".

This paper proposes a method to determine an optimal radial-loop configuration to minimize power loss in a distribution network with photovoltaic (PV) systems and evaluates the effectiveness of this configuration. Due to the disaggregation of transmission and distribution in a deregulated power system, stable and efficient operations in terms of voltage regulation and power loss reduction utilizing existing equipment is becoming more important for distribution system operators (DSOs). Japanese DSOs operate distribution networks in a radial configuration while supplying power to customers with high reliability. One method to reduce further power loss is to upgrade the network topology to a radial-loop configuration, which achieves partial loop structures by closing the tie-switches of the radial configuration. To implement a radial-loop configuration, DSOs must first evaluate the reliability, as a loop configuration can cause a feeder circuit breaker (FCB) malfunction and an expansion of the nonsupplied area during fault conditions. However, the impact of a radial-loop configuration on reliability and effectiveness has not been verified. Therefore, this paper proposes a method to determine an optimal radial-loop configuration that minimizes active power loss and maintains high reliability. In a numerical simulation, the reliability of radial-loop configurations is verified, and the effectiveness of the configuration is analyzed in terms of active power loss and voltage regulation under several PV system penetration conditions. A 6.6 kV distribution network consisting of 6 feeders and 11 tie-switches is modeled based on an existing Japanese distribution network and used for numerical simulation.

<p>This paper proposes a decentralized charging and discharging control method of a battery energy storage system (BESS) to prevent the over-capacity of a pole transformer (Pole-Tr) in low-voltage (LV) distribution systems due to reverse power flow from the photovoltaic generation (PV) system. A distribution system operator (DSO) provides the charging/discharging parameters determined by using only the LV-distribution system configuration and the PV/BESS capacity to the customers and each BESS automatically controls the charging/discharging power according to the provided parameters. The charging parameter is defined in the relationship between the state-of-charge (SoC) and the charging threshold ε as the SoC-ε curve, and a total of three SoC-ε curves for the different objectives are prepared. In the charging phase, the BESS selects one SoC-ε curve every minute and determines the charging power based on the charging threshold ε and the present SoC. In the discharging phase, the BESS operates in the load-following discharging and SoC control discharging to adjust the SoC for the prevention of the over-capacity of Pole-Tr. The proposed method is tested on several types of LV-distribution systems, and the numerical simulation results demonstrate that the proposed method can prevent the over-capacity of Pole-Tr and maintain the high charging amount of BESSs.</p>

<p>Transmission system operators (TSO) are responsible to manage the power quality within a proper range and to reduce power loss. Voltage reactive power control (VQC) is mainly utilized to manage the power flow. In the conventional VQC scheme, the static condenser (SC) and shunt reactor (ShR) is generally adjusted based on the target value determined for the heavy load condition in each voltage class. On the other hand, the installation of the massive photovoltaic (PV) systems into transmission systems cause the complex power flow such as the short-term fluctuation of power flow and reverse power flow from the lower transmission system to the upper transmission system. Thus, in the future power system with PV systems, the target values of the VQC devices need to be updated in the short-time period considering the interaction between the upper and lower transmission system to manage the power quality and to the reduce power loss efficiently. This paper proposes the optimization methodology for VQC devices in two-voltage class of transmission system using tabu-search and optimal power flow based on the central VQC methodology. To verify the effectiveness of the proposed methodology, the numerical simulation was performed based on the revised IEEJ EAST 30-machine system model.</p>

This paper proposes a CO₂ reduction surcharge which is charged proportional to customers' CO₂ emission, instead of FIT surcharge proportional to the grid power consumption. When this new surcharge is slightly over 10,000yen/ton-CO₂, the operating unit cost of coal fired plants is over that of LNGCC plants, and the capacity factor decreases as well as CO₂ emission. Authors simulated a power system in 2030 where a large amount of PV is implemented and the 18% of PV generated energy must be curtailed. The annual cost is minimized by optimizing LNGCC and battery energy storage systems (BESSs) capacity, hourly output of coal fired and LNGCC plants, hourly charge and discharge power of BESSs, and PV curtailment. Results show this surcharge is effective to change fuel and decrease CO₂ emission, and BESSs moderate this fuel change but decrease PV curtailment and CO₂ emission. The energy chain including whole power system, demand and fuel is analyzed to see the power flow and CO₂ emission. It is also discussed to apply this surcharge to every fossil fuel usage in order to realize the almost CO₂ free society with a reasonable cost increase.

© 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.

In the Cyber Physical System or the Digital Twin, the control strategy generates multiple scenarios in the cyber world with optimization of future models and objective functions, and these scenarios are utilized to determine an optimal strategy, which is then applied to the physical world. In these procedures, the decision-making to select and fix a future scenario and its time limit are important factors. In this study, considering the scenario decision time limit, a procrastination strategy is introduced and formulated as a new model predictive control framework. It is to postpone the decision and preserve the freedom of scenario choice for the future. In the proposed method, the concept of a common admissible set for control trajectory and its branch point are introduced. A simple numerical example and an application to an energy management problem are shown to illustrate and verify the effectiveness of the proposed method.

© 2019 In Japan, low thermal insulation performance in existing houses is a considerable issue that may lead to health problems. Therefore, it is necessary to acquire technologies and knowledge regarding thermal insulation renovation. On the other hand, with the spread of photovoltaic panels, urban scale energy management and self-consumption have become important. The purpose of this study is to introduce a net-zero energy house which was designed, built, and analyzed by the team of Waseda University and Shibaura Institute of Technology in the ENEMANE HOUSE 2017 competition. The team proposed a renovation method which insert highly insulated walls into the existing structure, creating not only highly insulated areas but also non-insulated areas called “loggias.” By opening and closing the windows of the loggia according to the season, it functions as a passive system and enables residents’ behavioural adaptation to the environment. On the other hand, to aim for self-consumption and leveling of reverse power flow, a heat pump water heater and a storage battery were operated according to solar radiation prediction. Actual measurements confirmed the implementation and effect of this operational method. Moreover, the energy consumption was greatly reduced, while thermal comfort was maintained by thermal insulation and efficient equipment introduction.

We consider enhancing cyber security in voltage regulation of distribution systems in the presence of malicious attacks. Due to the increase in distributed generation, the regulation of voltage has become more complicated, requiring more sensor data to be used for control. Recently, we have developed an attack detection algorithm to find data falsification attacks on voltage measurements transmitted by sectionizing switches in the feeders to a centralized controller. In this paper, the security level of the system is further improved by introducing a controller that is capable of operating the regulation in the presence of attacks by utilizing the detection results. In particular, it identifies abnormal behavior in the sensor data and ignores measurements taking extreme values among those received. Through detailed simulation studies on a small scale distribution system, we show the effectiveness of the proposed control and analyze the relation between the number of attacks and the detectability of the attacks.

Voltage ride-through (VRT) and dynamic voltage support (DVS) are advanced functions of photovoltaic (PV) systems that are expected to improve future power system stability. Toward the improvement in system stability, it is valuable for power system operators (PSOs) to evaluate the effects of these functions. However, it is not straightforward to evaluate the amount of volt-ampere reactive (var) injection from PV systems because var injection depends on weather conditions and on the terminal voltages of the PV systems during voltage sag. In addition, it is equally important to analyze var support from distribution systems (DSs) to accurately determine the amount of var injection in a power system since numerous PV systems are connected to DSs. In this study, we evaluate the var support at a substation of a DS with PV during a voltage sag under various weather conditions. The var injection was analyzed for several time zones and seasons to consider a change in solar radiation. A numerical simulation was conducted based on IEEE 13 Node Test Feeder Model with PV systems. The results indicated that there is a large variation in var support depending on seasons or time zones with different solar irradiance.

This paper proposes a decentralized charging control method of a battery energy storage system (BESS) that can prevent the over-capacity of a pole transformer in low-voltage (LV) distribution systems due to reverse power flow from the photovoltaic generation system. The distribution system operator provides the charging parameters defined as the relationship between the state-of-charge (SoC) and the charging threshold determined by using only the LV-distribution system configuration and the demand-side information to customers. Each BESS charges the power according to the provided parameters. A high charging amount can be maintained by automatically changing the charging mode based on the change in SoC. Results of the numerical simulation demonstrate that the proposed method can prevent the over-capacity of PTr and maintain the high charging amount of a BESS in LV-distribution systems. Further, the maximum power flow at the distribution substation and the distribution losses in MV-distribution system can be reduced.

© 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.

The installation of photovoltaic system (PV) is increasing rapidly across the world. However, the fluctuation of PV output causes serious challenges in the power grid operation. Among the fluctuation, a quick part of fluctuation is mainly caused by the change of cloud coverage. A total-sky imager (TSI), measuring device to take sky and cloud, could be useful for short-term solar irradiance forecasting. In this paper, a convolutional neural network (CNN) is applied to forecasting model (called CNN model) to forecast 5-20 min ahead of global horizontal irradiance (GHI) using total-sky images and lagged GHI. To verify the effectiveness of CNN, three forecasting models are compared. They are the persistence model, the CNN model using only total-sky images, and the CNN model using both total-sky images and lagged GHI. From the computation, the proposed CNN model using both total-sky images and lagged GHI performs root-mean-square error (RMSE) of 49-177W/m2, 93-146W/m2, 71-118W/m2 in sunny day, partly cloudy day and overcast day, respectively. From these results, the proposed method is shown to be suitable for short-term solar irradiance forecasting.

Saving energy in the residential is required under the influence of global warming and electricity shortage caused by natural disaster in Japan. For the purpose of promoting zero energy house, “ENEMANE HOUSE 2017”, a competition of Zero-Energy House was held. This paper shows the overview of the building and equipment planning, and also the evaluation of thermal environment and energy in the zero energy house which the consortium of Waseda University and Shibaura Institute of Technology proposed in the competition. This zero energy house demonstrates a method of renovation of housing using low-insulated outer wall of an existing industrialized house. The aim of the facility planning was not only the compatibility of energy-saving and comfort but also the increase in self-consumption of surplus power.

With the increase of wind power penetration in power system, the uncertainty caused by wind farm forecast error is enlarged which results in deterioration of wind power curtailment. In order to optimize the capacity of battery storage for mitigating forecast error, firstly it is necessary to improve the accuracy of forecast error model. This paper proposed a modeling method of forecast error time series in usage of beta distribution. Varying with forecast output, parameters of the beta distribution are estimated by maximum likelihood estimation. Autocorrelated forecast error obeying beta distribution is generated by correlated Monto-Carlo simulation. Based on the forecast error model, an optimization method is proposed to determine the optimum size of battery storage for mitigating forecast error. Through maximizing the total profit composed of electricity sales revenue, penalty and battery cost, the optimum size of battery storage is calculated. The results show that the forecast error model proposed in this paper is able to simulate both probability density function and autocorrelation correctly, which is beneficial to improving the accuracy and economy of battery storage sizing.

The housing section in Japan is promoting the introduction of renewable energy. However, it has problems such as surplus generation during a low load period and there could be a rise in voltage due to reversed power flow. Therefore, there is a need to use the generated surplus energy effectively. The aim of this study is to evaluate the effects of the precooling and preheating operation. To this end, we measured indoor environmental factors, energy consumption, and skin surface temperature and heat loss using a thermal manikin under ten conditions with different air conditioning in house with higher heat capacity.

Because of the increasing promotion of renewable energy such as photovoltaic (PV) panels in Japanese houses, the voltage increase and frequency adjustment of a city electrical distribution network sys-tem will be of concern. Therefore, self-consuming surplus electricity and leveling the reverse power flow is important in terms of reducing the smart grid network load and reducing the peak load of the smart grid network. The aim of this study was to acquire knowledge regarding methods of self-consuming surplus power as well as leveling the reverse power flow. An equipment operation method, termed “schedule control,” was proposed that changes the operational time of a heat pump water heater and the charging time of a storage battery according to solar radiation prediction. Because PV power fluctuates depending on weather and time zone, this method helps in self-consuming as much PV power generation as possible. By actual measurement and simulation results, it was confirmed that the schedule control of the heat pump water heater and storage battery was useful in self-consuming surplus power and leveling reverse power flow.

© 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.

<p>This paper presents economic evaluation of storage battery systems which increase the self-use of PV output at houses and buildings. The selling price of PV generated energy is decreasing. Battery energy storage systems (BESS) can increase the self-use of PV output, and decrease the volume of buying electric power. So, the introduction of BESS to houses and buildings equipped with PV systems will be economical when the price of BESS is decreased enough. Authors investigated the optimum BESS capacity and hourly charge-discharge pattern for a year, then evaluated annual cost. Daily load pattern of each house and building, and time-of-use electric rates affect the conditions to make BESS cost-effective. Such conditions are shown in this paper.</p>

The popularity of rooftop solar and home-scale batteries brings a fantastic opportunity to homeowners for using energy more flexibly and achieving benefits from trading electricity. This paper narrates a research work of how home energy management systems (HEMSs) maximize profits from buying electricity at a fixed price from utility and selling the surplus energy to an aggregator. Appropriate optimization problems are formulated with technical constraints of household devices and from connection requirements including a volt-watt function installed in the inverter of the rooftop solar-battery system. HEMS responses are optimized in two stages. The first stage is a stochastic program for planning an optimal energy commitment to an aggregator considering forecast errors and the predicted power curtailment. On the day of operation, each HEMS tries to follow the committed energy plan when determining optimal responses in the real-Time condition. Effectiveness of the proposed method is well illustrated through a simulation of a Japanese low-voltage system. Results show that forecast errors and power limitation due to volt-watt functions should be addressed to improve home benefits.

Recently, a multiarea system operation utilized a tie-line has been verified to resolve a shortage of a control capacity of frequency control generators output due to a widespread penetration of renewable energy systems (RES). In order to determine the proper dispatch of the generators output to compensate RES fluctuation in the multiarea system operation, the power system operators should consider power flow constrains and indexes of power system conditions such as the speed of dispatch, the balance of reserved control capacity in each area, and the stability of power supply. In this paper, we propose a methodology to determine multiobjective dispatch candidates of frequency control generators output to compensate RES fluctuation in multiarea system operation considering three indexes, a speed of dispatch, a reserved control capacity, and a transient stability based on optimal power flow and multiobjective particle swarm optimization. The methods determine the dispatch based on Euclidean norm of the indexes in the calculated candidates in order to consider all indexes well-balanced. The effectiveness of the proposed methodology is verified by a numerical simulation used IEEJ EAST 30-Machine Grid Model with much RES, and the effectiveness of the dispatch minimized Euclidean norm is confirmed by comparison to single-objective solution in each index among the calculated candidates.

<p>In this paper, waiting effects of photovoltaic generation (PV) output curtailment by power conditioning system (PCS) on voltage management in a distribution network are quantitatively evaluated, and an appropriate waiting time is determined based on the evaluated results. PV output generation can be categorized to 5 groups based on the weather characteristics, and the waiting effects are evaluated in terms of PV output curtailment amount, cumulative voltage violation amount, maximum voltage violation, and the number of tap operations as the impacts on a distribution system operator and customers. Through a numerical simulation, we found that the waiting time effects in cloudy groups were higher than other groups with keeping the maximum voltage violation lower than the allowable voltage limit. Also, the appropriate waiting time for PCS control was determined based on the relationship between the waiting time and PV output curtailment reduction rate. The results also represent that we do not need to set a longer waiting time from the viewpoints of PV output curtailment reduction rate though the waiting time should be set larger than the time delay of voltage regulators.</p>

In this paper, we propose a comprehensive scheme to determine a suitable method and timing for upgrading the voltage control method. Voltage control methods are expected to be upgraded in accordance with the photovoltaic (PV) penetration in distribution systems. The suitable method and timing detailed in this paper are based on the limit of the PV penetration rate, which is constrained by the regulated voltage deviation. The upgrade process involves moving the on-load tap changer (OLTC) control method from the conventional scalar line drop compensator (LDC) method to the vector LDC method or centralized control method. Then, a static var compensator (SVC) or step voltage regulator (SVR) is installed. The locations of the SVR and SVC are determined to maximize the PV penetration rate. The suitable method and timing are demonstrated using a general distribution system. In addition to the numerical simulations, experiments are performed using an active network system with energy resources. The experimental results are consistent with the numerical simulation results, thus validating the proposed scheme. The maximum PV penetration rate obtained using the OLTC control method is 55%. Whereas, the installation of the SVR and SVC increased the rate to 95% and 100%, respectively.

This paper proposes a hierarchical battery energy storage system (BESS) management in a residential town. The proposed management improves an electric power self-supply ratio (EPSR) with charge/discharge operation of BESSs and a time shift operation of heat-pump water heaters installed in the households, and reduces power flow amount by hierarchically BESSs operation. The proposed management is verified in the residential town, and the results of numerical simulations clearly represent that the proposed management could improve EPSR through a year and drastically reduce the total power flow amount in the residential town compared with conventional self-operation.

In this study, updating parameters of smart inverters (SI) based on the change of PV penetration rate and weather conditions was evaluated. Among a wide variety of functionalities of SI, we focused on Volt-VAR control and comprehensively investigated the voltage profile in distribution network (DN) for various parameters. For the scenario in which PV penetration rate or weather condition was changed, we compared the total energy loss for the updated and fixed parameters, while avoiding voltage violation. We found that the maximum reduction rate of energy loss by appropriately changing the Volt-VAR parameters was 14.4% and 13.7%, respectively for the two cases, and that the parameters should be preferably updated according to the condition of DN from the view point of reducing energy loss. Quantitative results of Volt-VAR parameters survey were summarized, which can be a guide for how to use the functionality when PV is heavily installed in DN.

© 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.

© 2017 IEEE. A low-voltage regulator (LVR) is investigated as a countermeasure for voltage violation caused by the integration of photovoltaic (PV) systems in distribution systems. To achieve appropriate voltage control by the LVR, the appropriate control parameters need to be determined. We have proposed schemes to determine the appropriate control parameters using PV forecast profiles. In a previous work, the control parameters were determined on the basis of one-scenario PV forecast, which derives one forecast value in each time step. However, voltage violation could not be avoided by this method in a time step with a large forecast error. In this paper, we propose a method for determining the voltage control parameters of the LVR based on the forecast interval of the PV outputs to quantitatively consider the PV forecast error. The numerical simulation results show that the proposed method can reduce the amount of voltage deviation compared with the conventional method.

Future declines in the selling price of surplus electric power, and the cost of PV systems and storage batteries are expected. Autonomous operations like self-consumption of surplus electric power may, therefore, become cost-effective. In addition, self-consumption may reduce excessive power backflow, which can reduce the power generation efficiency in cities. Both energy savings and improvements to thermal comfort are important to support the spread of zero energy houses (ZEH). This study aims to understand the utility of autonomous operations. Through measurements and simulations, we show that thermal comfort is improved, and peak load reduced by precooling. In addition, we show that using a heat pump water heater during the day is efficient. We proposed different combinations of PV systems and storage capacity for different regions and household composition and confirmed their economic efficiency. Finally, we confirmed the possibility that using surplus electric power can improve quality of life during low load periods.

Because of the promotion of renewable energy in Japan, it is expected that house with solar panels installed will be approximately 7.5 million in 2030. The aim of this study was to evaluate the effect of the precooling operation. To this end, we measured indoor environmental factors, energy consumption, and skin surface temperature and heat loss using a thermal manikin under four conditions with different air conditioning operations in a zero-energy house. As a result, we found that a 6-h precooling operation is more effective than a 3-h precooling operation, and the radiant cooling system is more effective than the air conditioner to increase the photovoltaic (PV) generation self-consumption and to decrease the sales power from PV generation. Furthermore, we learned that the heat loss of the radiant cooling system was less than that of the convection cooling system (air conditioner).

Under the large penetration of photovoltaic systems, the voltage control in a distribution system will contain a difficulty due to the fluctuated reverse power flow, so that the appropriate deployment of voltage regulators is required to suppress the voltage violation. However, derivation of an appropriate long-term deployment plan of voltage regulators is a difficult task because of the uncertainties in spatial-temporal penetration scenario of the photovoltaics systems connected to the distribution system. This paper focuses on a simple approach for deploying step voltage regulators considering uncertainties in penetration transition of photovoltaic systems in order to discuss the necessity of long-term plan. The impact of long-term deployment plans is evaluated by numerical experiments.

Recently, a multi area system operation utilized a tie-line has been verified to resolve a shortage of a control capacity of frequency control generators output due to a widespread penetration of renewable energy systems (RES). In order to determine the proper dispatch of the generators output to compensate RES fluctuation in the multi area system operation, the power system operators should consider power flow constrains and indexes of power system conditions such as the speed of dispatch, the balance of reserved control capacity in each area and the stability of power supply. In this paper, we propose a methodology to determine multi-objective dispatch candidates of frequency control generators output to compensate RES fluctuation in multi area system operation considering three indexes, a speed of dispatch, a reserved control capacity and a transient stability based on OPF and MOPSO. The methods determine the dispatch based on Euclidean norm of the indexes in the calculated candidates in order to consider all indexes well-balanced. The effectiveness of the proposed methodology is verified by a numerical simulation used IEEJ EAST 30-machine system model with much RES, and the effectiveness of the dispatch minimized Euclidean norm is confirmed by comparison to single-objective solution in each index among the calculated candidates.

In this study, we evaluate the Volt-VAR and Volt-VAR-Watt functions of smart inverters based on the PV penetration level (PVPL) and the photovoltaic (PV) curtailment. The Volt-VAR and Volt-VAR-Watt functions are compared with the optimal control parameters that maintain the distributed network voltage within an admissible range and minimize PV curtailment. The study results at each PVPL (0-100%) with a typical distribution network model highlight the following points within our conditions. (1) Optimal control parameters vary with the PVPL and two weather conditions; (2) The maximum PVPL does not reach 100% with the Volt-VAR function, whereas the Volt-VAR-Watt function enables the maximum PVPL to reach 100%; and (3) the Volt-VAR-Watt function curtails PV generation, and the average ratio of PV curtailment on cloudy and sunny days is about 12.1% and 0.16%, respectively.

© 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.

© 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.

© 2018 The Institute of Electrical Engineers of Japan. This paper presents an evaluation of economical capacity of storage batteries equipped with residential PV systems. In around 2019, many of power companies' ten-year contracts with PV system owners will come to expire, pushing down the selling price of PV generated energy. This, if combined with a declining battery price, would make it more economical to self-consume PV generated energy than selling the electricity to the utilities. The authors explore the optimized storage battery capacity and charge-discharge pattern by using load and PV output data of 200 houses, and by linear programming. Results show 5.8 kWh battery is suitable for an average house with 4.5 kW PV system when the battery system price is about Y60,000/kWh. The authors analyze the daily storage start timing's impact on reverse power which affects power system operation, the optimum combination of PV and battery capacity, and each house's deciding factors for optimum storage capacity and so on.

© 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.

There is a danger of output suppression of high-penetration residential PV systems due to voltage increase. It is necessary to install new technology to prevent the occurrence of such phenomenon. Therefore, we focused our attention on heat pump water heaters (HPWHs). HPWHs are usually used to heat water during night time because electricity prices are cheaper than during the daytime for the load leveling in Japan. So they can be used as a countermeasure without additional cost if they are operated during the daytime. However, HPWHs do not have sufficient capacity to absorb inverse energy at each residence. Thus HPWH operation must be optimized to minimize output suppression loss. In this research, we selected four typical sunny days in spring, summer, autumn and winter. The optimal HPWH operation was calculated by numerical simulation. The optimal monthly HPWH operation was investigated using the weather forecast assuming actual operation in each season.

© 2017 IEEE. In order to coordinate controlling devices of utilities in medium-voltage networks with large-scale photovoltaic (PV) inverters, a revelation of clustered impacts of rooftop solar panels in PV dominated low-voltage networks is necessary. This paper first investigates impacts of smart functions on system performance if they are installed in rooftop solar inverters. An optimization is then formulated based on conflicts that have been revealed. Through simulations in a typical Japan low-voltage system with real data, investigation and optimization results show that optimal inverter settings for rooftop solar are feasible and they could help improve system performance.

© 2017 The Authors Power grids connected to renewable energy sources must cope with fluctuating output by those sources. One method to do so is for the power grid company to accept bids to increase grid stability. These bids are accepted via capacity market auction of increasing grid stability. These offers are to increase the maximum power capacity by using power stations (both utility and non-utility stations) and by reducing electricity consumption via demand response. One candidate for achieving this is a district heating and cooling (DHC) system installed with combined heat and power. However, the electricity adjustment (EA) operation needed by the DHC for the auction is complicated because the system consists of boilers, water heaters, chillers, generators, and other items. To investigate the possibility of using DHC systems for capacity market auctions, this paper proposes two models for operating a DHC system: electricity-adjustment capacity (EAC) provision and EA operation. In addition, to develop methods for evaluating the cost of the proposed operational methods, a model DHC system is formulated with an actual DHC system as a basis. Using the models, numerical simulations are conducted by particle swarm optimization. Then, the running costs of EAC, EA, and normal operation are calculated. The results show that the running costs of the proposed operations are relatively stable by day and season, not varying beyond the range of ±10%. Nevertheless, the running costs in spring and fall are be lower than those in summer and winter. The cost of providing EAC is no more than 1% the cost of normal operation, and the cost of EA itself is no more than 2% that of normal operation.

© 2017 Wiley Periodicals, Inc. There is a danger of output suppression of high-penetration residential photovoltaic systems due to voltage increase. It is necessa1ry to install new technology to prevent the occurrence of such phenomenon. Therefore, we focused our attention on heat-pump water heaters (HPWHs). HPWHs are usually used to heat water during nighttime because electricity prices are cheaper than during the daytime for the load leveling in Japan. So they can be used as a countermeasure without additional cost if they are operated during the daytime. However, HPWHs do not have sufficient capacity to absorb inverse energy at each residence. Thus, HPWH operation must be optimized to minimize output suppression loss. In this research, we selected four typical sunny days in spring, summer, autumn, and winter. The optimal HPWH operation was calculated by numerical simulation. The optimal monthly HPWH operation was investigated using the weather forecast assuming actual operation in each season.

This paper presents an enhanced centralized voltage control method utilizing real-time satellite-observed solar radiation data for distribution networks with PVs. Conventional centralized voltage control methods cannot prevent voltage deviation between data acquisition periods when large voltage fluctuation occurs because of PV output fluctuation. This is because the tap positions are determined regardless of PV output although there is few risk of large voltage rise/drop when PV generates full/no power. The proposed method forecasts voltage fluctuation width by utilizing the real time solar radiation data, which are acquired every 30 minutes at grid points with a 1 km resolution, and determines tap positions of an on-load tap changer and step voltage regulators to maximize the minimum voltage margin between the forecasted voltage and the voltage limits. The numerical simulation utilizing actual measured PV output profile and solar radiation data will show that the proposed method enhanced the voltage control effectiveness.

© 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.

© 2017 IEEE. As more photovoltaic systems (PVs) are allocated to both transmission and distribution systems, it has been required to consider constraints of both transmission and distribution systems, such as power shortages and surpluses in transmission systems and voltages and current in distribution systems. This research proposes the framework to consider these constraints, and formulates the optimal allocation of PVs and energy storage systems (ESSs) to prevent the violation of the above constraints.

Visualizations that depict a consumer's utilization of domestic appliances aid them in effectively thinking about energy conservation. Energy disaggregation aims to break down the total power consumed into the amount consumed by each individual appliance through the use of a single smart meter. This estimation technique provides detailed information about energy consumption and is cheaper than techniques that directly measure each appliance. In order to improve the accuracy of disaggregation, we utilize the consumer feedback information without placing any special burden on the consumer. We propose a semi-supervised shift-invariant weighted non-negative matrix factorization method with auxiliary feedback that records the on or off status of each individual appliance. The experimental results obtained by applying our proposed method to household datasets show that our proposed method and the associated auxiliary information generated contribute to the improvement of the disaggregation accuracy.

Wind power prediction is necessary for stable operation of a power grid under the introduction of significant wind power generation. Wind power prediction approaches based on the results of numerical weather prediction (NWP) have been developed successfully in recent years. However, the high dimensionality of NWP results can be a major obstacle when training models. This paper proposes a feature extraction scheme based on convolutional neural networks to compress high-dimensional NWP results by deriving critically important low-dimensional information for wind power prediction. The experimental results show that the proposed feature extractor can contribute to the improvement of wind power prediction accuracy.

© 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. The incorporation of photovoltaic (PV) inverters makes the management of voltage difficult for power system operators. One solution is to consider these inverter-based devices as controllable reactive power (VAr) sources and to coordinate them with other voltage regulating devices in the distribution system. This paper proposes some acceptable approximations to quickly formulate and solve a mixed-integer quadratic programming problem to periodically determine the optimal voltage coordination of a load tap changer, voltage regulators, capacitor banks, and PVs on a smart grid platform. The solution to the optimization problem is aided by an iteration-based algorithm. By using the MATLAB software to carry out the simulation and computation, the method is well verified by comparing its generated result with a trustworthy solution obtained from examining all possible coordinating combinations of voltage regulating devices and PVs in a modified IEEE 34-bus system. The effectiveness and features of the method are clearly illustrated on that test system by considering a time-varying load and PV generation. The obtained results demonstrate the practical application of this work to medium-voltage systems. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

© 2016 American Society of Civil Engineers. This paper proposes a voltage control method during service restoration in the distribution networks with photovoltaic (PV) generator systems. In the current distribution automation system (DAS) process in Japan, voltage dips and surges occur during service restoration because PVs are disconnected simultaneously after a fault and subsequently reconnected after service restoration. However, in the current DAS, voltage regulators such as an on-load tap changer (OLTC) and step voltage regulators (SVRs) are not controlled during service restoration. The proposed DAS estimates the voltage in a distribution network during service restoration, and it controls the tap position of OLTC and/or SVRs according to the predicted voltage. The numerical simulation results using a real-world distribution system model on a real map and PV output profiles derived by actual square kilometer solar radiation data will be shown. Those results indicate that the proposed DAS prevents voltage deviation that occurs as long as the current DAS is used. The results also show high spatial resolution PV output data are needed to prevent voltage deviation absolutely.

Because of the rapid growth of wind power, an electric grid company set the maximum change rate in a time window to share its fluctuation; this set maximum change rate in a time window is called the grid code. Large fluctuations of wind power may cause deviation from the grid code, but no studies discuss how to control an energy storage system (ESS) so that it quickly goes back to satisfying the grid code. The authors proposed three control methods for an ESS when the wind power output deviates; they are (1) ‘restart’, (2) ‘continuance without operation’, and (3) ‘continuance with operation’. One year numerical simulations with two types of grid codes and two wind power output data have been performed to evaluate the methods. From the studies, control method (3) is found to be the best control method for an ESS to minimize capacity when the wind power output deviates from the grid code, and is verified by the numerical simulations. These results help to answer questions on how to reduce deviation time and ESS capacity using the control method when the wind power output deviates from the grid code.

© 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. The incorporation of photovoltaic (PV) inverters makes the management of voltage difficult for power system operators. One solution is to consider these inverter-based devices as controllable reactive power (VAr) sources and to coordinate them with other voltage regulating devices in the distribution system. This paper proposes some acceptable approximations to quickly formulate and solve a mixed-integer quadratic programming problem to periodically determine the optimal voltage coordination of a load tap changer, voltage regulators, capacitor banks, and PVs on a smart grid platform. The solution to the optimization problem is aided by an iteration-based algorithm. By using the MATLAB software to carry out the simulation and computation, the method is well verified by comparing its generated result with a trustworthy solution obtained from examining all possible coordinating combinations of voltage regulating devices and PVs in a modified IEEE 34-bus system. The effectiveness and features of the method are clearly illustrated on that test system by considering a time-varying load and PV generation. The obtained results demonstrate the practical application of this work to medium-voltage systems. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

© 2016 IEEE. Maintaining voltage levels in distribution networks (DNs) with photovoltaic systems (PVs) is a complicated task for conventional voltage control schemes that only use a load ratio control transformer (LRT) and step voltage regulators (SVRs), because of local voltage fluctuation caused by the introduction of PVs. This paper proposes a coordinated voltage control scheme consisting of multiple kinds of load tap changers (LTCs). The proposed scheme determines the location at which to introduce low-voltage regulators (LVRs) and provides control parameters for the LTCs by considering the behavior of the other LTCs. We carried out numerical simulations using a DN model including PVs to verify the validity of the proposed scheme. The results specify the characteristics of the voltage deviation that cannot be prevented by a conventional voltage control scheme, and the proposed scheme significantly reduces such local voltage deviation.

© 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.

Waseda University and various enterprises proposed a Zero-Energy-House(ZEH) called &ldquo;Nobi-Nobi HOUSE&rdquo; in ENEMANEHOUSE2014. In this ZEH, we carried out a design for the ZEH technology, and was build in Tokyo at January 2014. After the relocated in Shizuoka, it was measured every four seasons in energy consumption, electric-generating capacity and indoor environment. This report shows design of &ldquo;Nobi-Nobi HOUSE&rdquo; for ZEH and result of measurement.

Waseda University and various enterprises proposed a Zero-Energy-House(ZEH) called "Nobi-Nobi HOUSE" in ENEMANEHOUSE2014. In this ZEH, we carried out a design for the ZEH technology, and was build in Tokyo at January 2014. After the relocated in Shizuoka, it was measured every four seasons in energy consumption, electric-generating capacity and indoor environment. This report shows design of "Nobi-Nobi HOUSE" for ZEH and result of measurement.

Maintaining voltage levels in distribution networks
(DNs) with photovoltaic systems (PVs) is a complicated task for
conventional voltage control schemes that only use a load ratio
control transformer (LRT) and step voltage regulators (SVRs),
because of local voltage fluctuation caused by the introduction of
PVs. This paper proposes a coordinated voltage control scheme
consisting of multiple kinds of load tap changers (LTCs). The
proposed scheme determines the location at which to introduce
low-voltage regulators (LVRs) and provides control parameters
for the LTCs by considering the behavior of the other LTCs. We
carried out numerical simulations using a DN model including
PVs to verify the validity of the proposed scheme. The results
specify the characteristics of the voltage deviation that cannot be
prevented by a conventional voltage control scheme, and the
proposed scheme significantly reduces such local voltage
deviation.

© 2016 Power Systems Computation Conference.The maximization of distributed generation (DG) hosting capacity that takes into account network configuration is a complex, non-linear combinatorial optimization problem. The search space of the configurations becomes massively large in practical-size networks with several hundreds of switches. For this reason, no existing method can handle such large-scale networks. In this paper, we propose a novel exact solution method. Our method consists of two stages. In the first stage, the method divides the entire problem into a set of small subproblems. In the second stage, it converts all subproblems into a compressed data structure called a zero-suppressed binary decision diagram (ZDD), which expresses the combinatorial sets compactly. The proposed method avoids any combinatorial explosion by using the ZDD to enable operations of the weighted combinatorial item sets. We conducted experiments on a large-scale network with 235 switches. As a result, our method obtained the global optimal solution in 49 hours.

© 2016 IEEE.This paper presents a method for enumerating the feasible load drop compensator (LDC) parameters of on-load tap changer (OLTC) and step voltage regulators (SVRs) in distribution networks utilizing data acquired by SCADA. Deriving the feasible combinations of LDC parameters is becoming important because voltage control is becoming difficult due to the introduction of photovoltaic generation systems, and the voltage control effectiveness of OLTC and SVRs depends on their three LDC parameters: the target voltage, the dead-band, and the impedance. However, an exhaustive search takes a lot of time and heuristics or metaheuristics provide no guarantee on the quality of the solution. The proposed method derives all the feasible LDC parameters, with which tap operation keeping voltage within the proper range is performed, within practical time. To evaluate the performance of the proposed method, the numerical simulation results of the proposed method will be compared with those of the metaheuristics.

In this paper, we consider the impact of cyber attacks on voltage regulation in distribution systems. We employ a centralized control scheme which utilizes voltage measurements from sectionizing switches equipped with sensors for connecting distributed generation. Through detailed case studies by simulations, it is demonstrated that if measurements are falsified by an attacker, voltage violation can occur in the system. However, by equipping the control with a detection algorithm, we verify that the damage can be limited especially when the number of attacked sensors is small. Further discussion is provided on how to enhance the security level of the proposed algorithm.

© 2016 IEEE.This paper presents an enhanced centralized voltage control method of on-load tap changer (OLTC) and step voltage regulators (SVRs) in distribution systems with photovoltaic (PV) and evaluates its effectiveness. A conventional centralized voltage control is effective when its data acquisition period is short because tap operations of OLTC and SVRs are performed after the voltage values in the distribution lines are acquired. However, in distribution systems with high penetration rate of PVs, voltage deviation occurs between the data acquisition intervals because the tap positions can be changed only at the timing when the data are acquired. The proposed centralized voltage control method forecasts voltage fluctuation between the data acquisition intervals and changes to the tap position which maximizes the minimum voltage margin from the voltage limits. The numerical simulation results will be shown to compare the voltage control effectiveness of the proposed method with that of the conventional method.

© 2010-2012 IEEE.In this paper, we consider the impact of cyber attacks on voltage regulation in distribution systems when a number of photovoltaic (PV) systems are connected. We employ a centralized control scheme that utilizes voltage measurements from sectionizing switches equipped with sensors. It is demonstrated that if measurements are falsified by an attacker, voltage violation can occur in the system. However, by equipping the control with a detection algorithm, we verify that the damage can be limited especially when the number of attacked sensors is small through theoretical analysis and simulation case studies. In addition, studies are made on attacks which attempt to reduce the output power at PV systems equipped with overvoltage protection functions. Further discussion is provided on how to enhance the security level of the proposed algorithm.

The subject of this study is to propose a power interchange system in a collective housing with residential solid oxide fuel cells (SOFCs) and a robust operation planning method for integrated SOFCs against uncertain energy demand forecast. In this method, the future operation plan for multiple SOFCs is optimized and determined to minimize the expected total primary energy consumption in the collective housing considering uncertainty in demand forecast. If the forecast energy demand includes forecast errors, the result of SOFCs operation will corrupt from the viewpoint of the primary energy consumption. Thus, the output decision problem for SOFCs is formulated by considering the corruption caused by forecast errors, so that the decided SOFC outputs have the robustness against uncertainty in demand forecast. The validity of the proposed method is examined based on numerical simulations from the perspective of the robustness.

The subject of this study is to propose a power interchange system in a collective housing with residential solid oxide fuel cells (SOFCs) and a robust operation planning method for integrated SOFCs against uncertain energy demand forecast. In this method, the future operation plan for multiple SOFCs is optimized and determined to minimize the expected total primary energy consumption in the collective housing considering uncertainty in demand forecast. If the forecast energy demand includes forecast errors, the result of SOFCs operation will corrupt from the viewpoint of the primary energy consumption. Thus, the output decision problem for SOFCs is formulated by considering the corruption caused by forecast errors, so that the decided SOFC outputs have the robustness against uncertainty in demand forecast. The validity of the proposed method is examined based on numerical simulations from the perspective of the robustness.

© 2016 Wiley Periodicals, Inc. Photovoltaic (PV) systems have recently attracted considerable attention in the context of environmental problems, antinuclear power movements, and energy problems. Therefore, the large-scale introduction of PV systems is expected in the near future. But the connection of many PV systems to the power system leads to problems. For example, the system voltage often drifts from the norm when reverse power flows increase. Accordingly, optimal system operation is required in order to make maximum use of solar energy to the maximum by installing energy buffers such as storage batteries. In particular, in forecast information, knowledge of the reliability as well as the predicted solar irradiance is essential for effective operation. In this paper, we propose a way of estimating the prediction interval of solar irradiance as an index of reliability by using just-in-time modeling. We consider the accuracy of the prediction interval under many conditions and derive a high-precision estimation method. In addition, we also discuss about the future subjects of study.

Recently home energy management system (HEMS) has been spread due to increase in awareness of save energy after Great East Japan Earthquake. HEMS consists of photovoltaic power system (PV), battery energy storage system (BESS) and heat pump water heater (HPWH), etc. Residential PV implementation rate has been increasing due to feed in tariff from 2009. So there is a danger of output suppression loss due to voltage increase on a distribution line due to reverse power flow from each residential PV. So we try to study how to reduce output suppression loss using BESS and HPWH optimally. One of the main purpose to implement BESS and HPWH is for economy using the difference in electricity charges between during nighttime and daytime. So in this research, we optimize how to operate BESS and HPWH to improve the benefit of the electric power selling charges and electricity charges considering reduction of output suppression loss and the difference in electricity charges between during nighttime and daytime.

Voltage deviation in distribution networks and photovoltaic (PV) output restriction, caused by a large amount of PV systems installation, have been issued recently. BESS (Battery Energy Storage System) is one of the solutions. However, the detailed evaluation of the voltage control effect of BESS has not been carried out, because its effect varies according to BESS placement, its output and configuration of distribution, etc. Therefore, the amount of PV introduction limits in several distribution networks were evaluated and effective BESS arrangement and output control were examined in this paper. The effectiveness of the proposed BESS cooperating voltage control method with LRT, SVR was verified using numerical simulation and experiment of distribution system simulator.

© 2016 American Society of Civil Engineers. An increased penetration of wind energy into the power system will lead to instability of local voltage and global frequency in Japan. Power flow simulation is a powerful tool for understanding the electrical behavior in the power system caused by wind energy; however, plausible and various wind power profiles are required to perform a meaningful simulation to evaluate the effect of wind generators. This paper proposes a procedure of generating synthetic wind power profiles that involve the plausible short-term fluctuation for a power flow simulation based on the spatial kriging method and the bootstrap method.

<p>PMVを用いて熱的快適性を考慮した上で、窓・日射遮蔽ブラインド・断熱ブラインドなどの窓システムとエアコンを協調制御した場合とエアコンのみを単体制御した場合のシミュレーション解析を行い、エアコン単体制御に対する協調制御の電力消費量削減分を求めた。各制御システムに対して、それぞれ異なる気象条件下で解析、PMVの快適範囲を変化させた解析を行った。結果として、熱的快適性と省エネルギー性を両立した窓システムとエアコンの協調制御の有効性を示した。</p>

The subject of this study is to propose a power interchange system in a collective housing with residential solid oxide fuel cells (SOFCs) and a robust operation planning method for integrated SOFCs against uncertain energy demand forecast. In this method, the future operation plan for multiple SOFCs is optimized and determined to minimize the expected total primary energy consumption in the collective housing considering uncertainty in demand forecast. If the forecast energy demand includes forecast errors, the result of SOFCs operation will corrupt from the viewpoint of the primary energy consumption. Thus, the output decision problem for SOFCs is formulated by considering the corruption caused by forecast errors, so that the decided SOFC outputs have the robustness against uncertainty in demand forecast. The validity of the proposed method is examined based on numerical simulations from the perspective of the robustness.

Demand response can achieve peak-cut and peak-shift of the electric demand by delivering the load restraint of customers, based on Demand Response (DR) signal sent by an electric power company. However, the demand response restrains the load amount of many consumers simultaneously, so the voltage of the whole distribution system is greatly fluctuated depending on the distribution form such as line length, amount of load restraint, etc. Therefore, we propose the voltage control methods which can avoid voltage deviation in consideration of a time constant of demand response. Furthermore, we propose the BESS cooperating voltage control methods with LRT, SVR and verify the effectiveness using experiment of distribution system simulator.

Recently home energy management system (HEMS) has been spread due to increase in awareness of save energy after Great East Japan Earthquake. HEMS consists of photovoltaic power system (PV), battery energy storage system (BESS) and heat pump water heater (HPWH), etc. Residential PV implementation rate has been increasing due to feed in tariff from 2009. So there is a danger of output suppression loss due to voltage increase on a distribution line due to reverse power flow from each residential PV. So we try to study how to reduce output suppression loss using BESS and HPWH optimally. One of the main purpose to implement BESS and HPWH is for economy using the difference in electricity charges between during nighttime and daytime. So in this research, we optimize how to operate BESS and HPWH to improve the benefit of the electric power selling charges and electricity charges considering reduction of output suppression loss and the difference in electricity charges between during nighttime and daytime.

Voltage deviation in distribution networks and photovoltaic (PV) output restriction, caused by a large amount of PV systems installation, have been issued recently. BESS (Battery Energy Storage System) is one of the solutions. However, the detailed evaluation of the voltage control effect of BESS has not been carried out, because its effect varies according to BESS placement, its output and configuration of distribution, etc. Therefore, the amount of PV introduction limits in several distribution networks were evaluated and effective BESS arrangement and output control were examined in this paper. The effectiveness of the proposed BESS cooperating voltage control method with LRT, SVR was verified using numerical simulation and experiment of distribution system simulator.

© 2010-2012 IEEE.In distribution network management, switch reconfiguration is an important tool for reducing energy loss. Recently, a variety of annual reconfiguration planning methods considering energy loss have been studied. However, no conventional methods address the reconfiguration periods in fine granularity. Practically, switch durability does not support high-frequency switching. Therefore, this paper proposes a new optimization method for annual reconfiguration scheduling. This method determines switch configurations and their reconfiguration periods with a constraint on the permissible reconfiguration times. In addition, this paper reveals the annual energy loss reduction effect of this optimization. Our method is based on partial network optimization with exhaustive enumeration of all feasible configurations. Experiments were conducted using a standard Japanese distribution network model with 468 switches. The results show that optimizing the reconfiguration periods reduces energy loss by up to 2.1 times, relative to that in a simulated conventional operation, which considers reconfiguration at equal intervals. We believe that this is the first quantitative report to address the difference between optimal reconfiguration scheduling and conventional reconfiguration.

© Springer International Publishing Switzerland 2016.The large-scale introduction of renewable energy resources will cause instability in the power supply. Residential energy management systems will be even more important in the near future. An important function of such systems is visualization of appliance-wise energy consumption; residents will be able to consciously avoid unnecessary consumption behavior. However, visualization requires sensors to measure appliance-wise energy consumption and is generally a costly task. In this paper, an unsupervised method for nonintrusive appliance load monitoring based on a semi-binary non-negative matrix factorization model is proposed. This framework utilizes the total power consumption patterns measured at the circuit breaker panel in a house, and derives disaggregated appliance-wise energy consumption. In the proposed approach, the energy consumption of individual appliances is estimated by considering the appliance-specific variances based on an aggregated energy consumption data set. The authors implement the proposed method and evaluate disaggregation accuracy using real world data sets.

© 2015 IEEE.In this study, we determine the suitable method and timing for the renewal of the voltage control method using voltage control performance evaluated by the maximum photovoltaic (PV) installation rate possible without voltage deviation. The voltage control method is renewed when the voltage of a distribution system deviates with an existing voltage control method. We determine the most suitable voltage control method, which extends the most PV systems, and define its renewal timing as the moment when the PV installation causes voltage deviation. For the renewal of the voltage control method, changing the control operation of a load ratio control transformer (LRT) and the additional installation of a static VAR compensator (SVC) are considered. A numerical simulation is performed to calculate the limit of PV installation rate of each voltage control method to determine the suitable one and its renewal timing.

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, demandside 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

© 2016 The Institute of Electrical Engineers of Japan. Demand response can achieve peak-cut and peak-shift of the electric demand by delivering the load restraint of customers, based on Demand Response (DR) signal sent by an electric power company. However, the demand response restrains the load amount of many consumers simultaneously, so the voltage of the whole distribution system is greatly fluctuated depending on the distribution form such as line length, amount of load restraint, etc. Therefore, we propose the voltage control methods which can avoid voltage deviation in consideration of a time constant of demand response. Furthermore, we propose the BESS cooperating voltage control methods with LRT, SVR and verify the effectiveness using experiment of distribution system simulator.

© 2015 IEEE. In this study, as a new index of facilities, business continuity capability on occasion of an energetically isolated operation, was defined and evaluated for the facility with a rich amount of resources such as private generators, a battery energy storage system and a PV generation system. A methodology was proposed to evaluate a duration during which the facility is self- sustaining regarding energy use. An effect of reducing the capacity of PV or battery was also examined.

© 2015 IEEE. This paper studied power and hour capacity requirement for energy storage by two approaches. First one is evaluations without constrained condition of power and hour capacity with 80 sets of maximum ramp rates and time windows. And second one is evaluations with constrained condition of power and hour capacity for 2 grid codes (less than 0.1pu change of wind farm (WF) capacity in 20min time window, showing 0.1pu/20min in this paper, and 0.3pu/360min) to see details. The first evaluation in case of 3a resulted 1.0 pu power capacity (charge plus discharge capacity for all result) and 1.3 to 2.2 pu-h hour capacity are required to satisfy maximum ramp rate in time window of 0.1pu/20min. And 1.2 to 1.3 pu and 13 to 18 pu-h are required for 0.3pu/360min. And from the second evaluation in case of 3a, 0.7 to 0.8 pu power capacity and 1 to 2 pu-h for 0.1pu/20min and 1.0 pu and 10 to 15 pu-h are required for 0.3pu/360min. This paper provides relationship between maximum ramp rate in time windows and power and hour capacity requirement. The results help to answer questions whether power and hour capacity requirement satisfy grid codes with simple operating method of an energy storage system.

© 2016 The Institute of Electrical Engineers of Japan. Recently home energy management system (HEMS) has been spread due to increase in awareness of save energy after Great East Japan Earthquake. HEMS consists of photovoltaic power system (PV), battery energy storage system (BESS) and heat pump water heater (HPWH), etc. Residential PV implementation rate has been increasing due to feed in tariff from 2009. So there is a danger of output suppression loss due to voltage increase on a distribution line due to reverse power flow from each residential PV. So we try to study how to reduce output suppression loss using BESS and HPWH optimally. One of the main purpose to implement BESS and HPWH is for economy using the difference in electricity charges between during nighttime and daytime. So in this research, we optimize how to operate BESS and HPWH to improve the benefit of the electric power selling charges and electricity charges considering reduction of output suppression loss and the difference in electricity charges between during nighttime and daytime.

Unexpected fluctuation of wind power output will become serious problems from the viewpoint of stable supply for an electricity grid. Operating a battery system installed in the grid for mitigating the short-term fluctuation is one of the new approaches for grid stabilization. In this paper, we propose a method of generating synthetic wind power profiles with high temporal resolution for power flow simulation which aims to estimate the impact of wind power fluctuation and specify the required battery system. We numerically show the plausibility of the synthetic wind power profiles from the viewpoints of statistical properties. (C) 2016 The Authors. Published by Elsevier Ltd.

© 2015 IEEE. Output of the photovoltaic (PV) system drastically fluctuates depending on weather conditions. Therefore users of PV systems should manage their energy usage with forecast information of the PV output. Due to the reasons above, we have developed an estimation method of X% prediction interval of solar irradiance. We have achieved a high-accuracy prediction interval for any prediction coefficient X%. However, we found that there are some errors in a case where the prediction coefficient is high. In this paper, we improve the estimation algorithm of the prediction interval.

© 2015 IEEE. This paper investigates the operation of various possible standalone power supply configurations for smart houses with a view to preventing inconvenience to residents when blackouts occur. In smart houses, various types of power-generation equipment (such as photovoltaic (PV), battery energy storage system (BESS), electric vehicle (EV), and fuel cell (FC) systems) with different output power, capacity, and response time characteristics are used. Our results indicate that combined use of these equipment and home energy management system (HEMS) control provide the best means of enabling residents to effectively use household appliances even in limited power supply situations.

This paper proposes a dynamic updating method of the optimal control parameters of multiple advanced step voltage regulators (SVRs) in a single feeder considering a massive introduction of photovoltaic (PV) systems. Each advanced SVR can adjust their tap position according to the updated control parameters in a certain period. The main feature of the proposed method is that the optimal parameters which minimize the voltage violation amount from the proper range and the tap operation count of SVR are determined quickly based on greedy algorithm. A numerical simulation is carried out on an actual distribution system model with the measured PV and load data so that the effectiveness of the proposed method can be evaluated.

© 2015 IEEE. Widespread interconnection of Photovoltaic (PV) systems in the distribution system may create voltage rise problem. In this paper, a decentralized voltage control method by use of voltage regulators (VRs) and demand side management using consumer controllable load has been proposed for voltage rise compensation. The proposed method includes a novel determination method to find dynamic line drop compensation (LDC) parameters for a VR that has reverse power flow using the measured line current through VR and an optimal method that determines a dead band for a VR in order to lessens the number of tap operations while minimizing voltage deviation and violation. The obtained results show that voltage violation is extensively mitigated by the proposed method and no significant increment in tap operations of VR is encountered.

© 2015 IEEE. This paper presents a new method for determining the load drop compensator (LDC) parameters of On-load tap changer (OLTC) and step voltage regulators (SVRs) in the distribution system. Introduction of photovoltaic generation systems (PVs) into a distribution system makes determining the appropriate LDC parameters difficult, which may cause voltage deviation because reverse power flow from PVs affects voltage. Especially in the distribution system in which multiple SVRs are installed, determining the appropriate combination of LDC parameters becomes difficult. In the proposed method, the parameters are reset every hour by choosing one LDC parameter from a database including feasible parameters in the past. To create the database, the proposed method hourly enumerates the feasible parameters utilizing data acquired by SCADA. To evaluate the performance of the proposed method, the amount of voltage deviation of the proposed method will be compared with that of a centralized control method.

© 2015 IEEE. This paper presents a distribution automation system (DAS) for service restoration in the distribution network with photovoltaic (PV) generator systems, which are disconnected simultaneously after a fault and subsequently reconnected after service restoration. Because the reverse power flow of PVs affects voltage in the distribution system, voltage dips and surges occur during the service restoration. However, current DAS do not control voltage regulators such as an on-load tap changer (OLTC) and step voltage regulators (SVRs) during the service restoration. The proposed DAS estimates the voltage in a distribution network considering the simultaneous disconnection of PVs by performing power flow calculations, and it controls the tap position of OLTC and/or SVRs according to the predicted voltage deviation. The voltage after the disconnection of PVs is calculated by estimating the PV output utilizing square kilometer solar radiation data calculated using satellite image data in real time.

Compensating the voltage within the appropriate range becomes difficult when a large number of photovoltaic (PV) systems are installed. As a solution to this problem, the installation of a low-voltage regulator (LVR) has been studied. In this paper, we propose a method for rapidly and accurately determining the line drop compensator method (LDC) parameters as a part of a voltage management scheme, which consists of prediction, operation, and control. In the proposed method, candidates of the appropriate LDC parameters are selected with low computational cost by using classifiers that learns the relation between power series data and the properness of LDC parameters. We performed numerical simulations to evaluate the validity from the viewpoints of computational time and classification accuracy for determination of the LDC parameters, and verified the voltage control performance of the proposed method.

© 2015 The Institute of Electrical Engineers of Japan. PV system recently attracts much attention on the back of environmental problems, antinuclear power movements and energy problems. Therefore, a large scale introduction of PV system is expected in the near future. On the other hand, a lot of PV systems connected to the power system bring on some problems. For example, a system voltage often drifts from the norm when the reverse power flow increase. Accordingly, it is necessary to perform an optimal system operation in order to utilize a solar energy to the maximum by installing energy buffers, e.g. storage batteries. Especially, the forecast information i.e., the reliability as well as predicted solar irradiance is essential for the effective operation. In this paper, we propose a way to estimate the prediction interval of the solar irradiance as an index of reliability by using Just-In-Time Modeling (JIT Modeling). We consider the accuracy of the prediction interval under many conditions and derive the high-precision estimation method. In addition, we also talk about the future outlook of this study.

This paper proposes a new method for determining the LDC (Load Drop Compensator) parameters of LRT (Load Ratio Transformer) and SVR (Step Voltage Regulator). Since the voltage control effect of LRT and SVR depends on the LDC parameter, the proper parameters should be chosen in order to control voltage within proper range. When the photovoltaic generation system is installed in the distribution system, voltage control becomes difficult and the optimal parameters in the daytime differ from those in the nighttime. In the proposed method, the parameters are reset every hour. The parameters are determined by choosing from the database including all the optimal parameters for each time period in the past. The database also includes the PV output profiles and load profiles in the past, and the proposed method searches the similar time periods in the database to the next one hour period by comparing forecasted PV output profiles with that in the database. And the common parameters among the similar time periods are chosen for the next one hour. The simulation results will be shown to evaluate the performance of proposed 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.

In this paper, the authors propose an electric power interchange system in collective housing with fuel cells (FCs) and a determination method of operation plan for FCs in the collective housing. In the method, the operation plan for FCs is determined from an evaluation point, primary energy consumption of all houses in the collective housing, based on an enumeration method and particle swarm optimization (PSO) which is one of non-liner optimization methods. In order to examine the validity of the determination method, numerical simulations are carried out for the collective housing model, primary energy consumptions of the model are compared to those of a standard system (without FCs), and the reduction effects are evaluated taking uncertainty into consideration by using 10,000 demand patterns which are represented by 40 observational demand data based on the bootstrap method. In addition, the reduction effects by reducing introduced FCs by half are also evaluated from the point of primary energy consumptions, operating efficiency and running efficiency.

It is well known in the numerical simulations of a synchronous generator that the damper winding contributes to suppressing three-phase circuit unbalance in power systems. However, an experimental study has not been performed yet. In this paper, we verify experimentally the suppression of three-phase unbalance by the damper windings. In order to simulate the three-phase unbalance, a 470-W dispersed generator of single-phase two-line type was connected to a three-phase laboratory-scale power system that included a 6-kVA synchronous generator. We measured and analyzed line voltages and currents as well as damper bar currents both with and without the dispersed generator. The influence of damper windings on the unbalance of the three-phase circuit was also investigated. The results show that the damper winding contributes to improving the three-phase unbalance. © 2013 Wiley Periodicals, Inc.

Determining loss minimum configuration in a distribution network is a hard discrete optimization problem involving many variables. Since more and more dispersed generators are installed on the demand side of power systems and they are reconfigured frequently, developing automatic approaches is indispensable for effectively managing a large-scale distribution network. Existing fast methods employ local updates that gradually improve the loss to solve such an optimization problem. However, they eventually get stuck at local minima, resulting in arbitrarily poor results. In contrast, this paper presents a novel optimization method that provides an error bound on the solution quality. Thus, the obtained solution quality can be evaluated in comparison to the global optimal solution. Instead of using local updates, we construct a highly compressed search space using a binary decision diagram and reduce the optimization problem to a shortest path-finding problem. Our method was shown to be not only accurate but also remarkably efficient; optimization of a large-scale model network with 468 switches was solved in three hours with 1.56% relative error bound.

Total electricity consumption in Japan increased rapidly and the power consumption per household is also continuing to increase. The framework of demand response (DR) to promote the reduction of electricity consumption in the household sector by regulating the price of the electricity will be introduced in the future. In this situation, residents must operate their appliances so as not to affect much to their lifestyles while taking into account the power cost. A home energy management system (HEMS) will have an essential role to control appliances such as air conditioners (ACs), battery energy storage systems (BESSs), electric vehicles (EVs), and heat pump water heaters (HPWHs) and automatically match their operations to the behavior of a resident when the electricity price changes. In this study, a Bayesian network, a fundamental tool of machine learning, is adapted to an HEMS to learn the behavior of the resident and appropriate operations of controllable appliances.

This paper discusses a method for obtaining optimal voltage control in a distribution system with advanced step voltage regulators (SVRs) by determining the optimal control parameters of the SVRs. As the voltage in a distribution system becomes unstable if a massive amount of solar-generated power is introduced, voltage control devices such as load ratio control transformers (LRTs) and SVRs must be used to stabilize power flow. In this paper, a modified method of voltage control based on existing techniques for determining the optimal control parameters of multiple advanced SVRs is proposed as a means of maintaining power flow stability as solar power generation facilities are introduced.

This paper presents a novel method for determining the control parameters and a voltage control method for multiple step voltage regulators (SVRs) in a single feeder. The main purpose of the proposed method is to reduce the amount of voltage violation and the tap operation times and to extend the voltage margin from the upper and lower voltage limits by updating the control parameters of the SVRs. To determine the control parameters of the SVRs, an improved greedy algorithm is used. In order to verify the proposed method, a numerical and experimental simulation study based on an actual distribution model is carried out. The results show that the proposed control method has the capability to reduce the amount of the voltage violation in a distribution system and the tap operation times of the SVRs.

This paper presents a novel method of determining the control parameters and a voltage control method for multiple step voltage regulators (SVRs) in a single feeder. The main feature of the proposed method is the updating of the control parameters at constant intervals to minimize the amount of voltage violations and the tap operation times of the SVRs while maximizing the voltage margin from the proper limits in the distribution system. To determine the SVR control parameters, a combined method of a greedy algorithm and a tabu search is used. To verify the proposed method, numerical and experimental simulation studies based on an actual distribution model with photovoltaic (PV) sources are carried out. The results show that the proposed control method can reduce the amount of voltage violations and tap operation times of the SVRs compared with the conventional voltage control method.

This article has no abstract.

This paper describes dynamic voltage control method using SVC with controllable dead band that changes dynamically to a node voltage in a distribution system installed SVC. Proposed method consists of three systems. First system detects probability of voltage deviation from proper range of node voltage. Second system is used to stabilize output of SVC based on changing dead band. Third system expect voltage trend. In order to verify the validity of the proposed method in comparison with conventional methods, numerical simulation and experiment were carried out using a distribution system model with RES.

Distribution system has huge number of configuration candidates because the network configuration is determined by state of many sectionalizing switches (SW: opened or closed) installed in terms of keeping power quality, reliability and so on. Transmission system also has huge number of configuration candidates and circuit breakers (CB: opened or closed) as same objective as distribution system. Since feeder current and voltage depend on the network configuration, losses of transmission and distribution systems can be reduced by controlling states of CB and SW. So far, various methods to determine the loss minimum configuration of transmission and distribution systems have been researched. However, a method that hierarchically determines the loss minimum configuration of transmission and distribution system with PV has not been proposed. In addition, power flow of whole system is changed by various PV penetration distribution patterns. Therefore, transmission and distribution losses must be evaluated in various PV penetration cases.In this paper, a hierarchy control method to determine a transmission and distribution loss minimum network configuration by controlling on-off states of CB and SW is proposed. The validity of the proposed method is evaluated to calculate the reduction of whole network loss in a transmission and distribution model with 48 CB and 1404 SW in two kinds of PV penetration cases.

Since residential photovoltaic systems trend to increase in low-voltage distribution feeders, it is becoming more important to estimate voltage profile including not only high and middle but low-voltage distribution network to operate distribution systems. In case of using the conventional power flow calculation method based on iterative calculation, it will be taken much time to get voltage values all over low-voltage distribution feeders. This paper presents a new method to calculate voltage quickly keeping the accuracy sufficient for practical operation. In order to check the validity of the proposed method, numerical results are shown by comparing its computation accuracy and time with those of the conventional one.

Voltages in distribution system are maintained within a proper voltage range by adjusting a tap position of Load Ratio control Transformer (LRT) and Step Voltage Regulator (SVR). In Japan, many voltage control methods have been researched. However, these conventional methods do not presuppose the bank fault restoration. Since the main purpose of voltage control of the conventional restoration approach is to reduce the amount of voltage violation in distribution system, the number of customers with voltage violation cannot be reduced to zero during a bank fault restoration. In this paper, the authors propose a cooperation voltage control method of LRT and SVR to minimize the number of customers with voltage violation corresponding to the bank fault restoration in distribution systems with PV systems. In the proposed method, the tap position of SVR is controlled after the control of LRT to avoid frequent tap changes and each tap position of voltage control devices is controlled to minimize the number of customers with voltage violation. In order to check the effectiveness of the proposed method, the simulation using distribution system model with PV systems is performed under various conditions.

Measured data from IT switches are utilized in order to control voltage in distribution systems with photovoltaic generation systems. However, length of period from the data measurement to the data acquisition from IT switches affects voltage control ability in the distribution automation system. In this paper, a voltage control method by LRT and SVR with the periodic data from IT switches is proposed, and using the method, the effect of the length of the data acquisition period for voltage control is evaluated through numerical simulations in a distribution system model. Furthermore, the optimal length of the data acquisition period is determined according to PV penetration rate.

The Great East Japan Earthquake drastically changed Japanese energy management scheme in Japanese electrical grid. Stopped nuclear power plants caused a rise of the electricity costs. Demand side energy management scheme such as demand response is newly needed to reduce the peak of electric power demand by using HEMS (Home Energy Management System) and BEMS (Building Energy Management System). This paper describes Japanese trend of energy management based on demand response and international standardization of communications protocol and indicate the future issues and vision.

The amount of distributed generation (DG) such as photovoltaic systems and wind power generator systems installed in distribution systems has been increasing because of reduction of the effects on the environment. However, harmonic problems in the distribution system are a concern in the context of increased connection of DGs through inverters and the spread of power electronics equipment. This paper proposes a method for the restraint of voltage total harmonic distortion (THD) in a whole distribution network by active filter (AF) operation of multiple power conditioner systems (PCSs). It also proposes a method for determination of the optimal gain of AF operation so as to minimize the maximum value of voltage THD in the distribution network by real-time feedback control with measured data from information technology (IT) switches. In order to verify the validity of the proposed method, numerical calculations are carried out using an analytical model of a distribution network of interconnected DGs with PCSs. (c) 2012 Wiley Periodicals, Inc. Electr Eng Jpn, 182(3): 1929, 2013; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/eej.22354

This paper verifies, for distribution systems with residential photovoltaic generators (PV), the distribution loss reduction effect on the loss minimum configuration selected from all possible configurations. Methods that determine the loss minimum configuration of distribution systems have been developed. However, loss reduction effects and guidelines for future PV deployment to effectively reduce distribution loss have not been discussed extensively, because of difficulties in enumerating possible configurations and in comparing distribution losses for each. We have previously proposed a method for selecting loss minimum configurations from among all possible configurations. In this paper, we use the proposed method to verify the loss reduction effect on loss minimum configurations of a distribution system composed of 468 switches for three PV penetration patterns. We also evaluate the loss minimum configuration by comparing its distribution loss with that of other configurations and provide a guideline for future PV penetration position and system operation. © 2013 IEEE.

Analysis and modeling of electric energy demand is indispensable for power planning, operation, facility investment, and urban planning. Because of recent development of renewable energy generation systems oriented for households, there is also a great demand for analysing the electricity usage and optimizing the way to install electricity generation systems for each household. In this study, employing statistical techniques, a method to model daily consumption patterns in households and a method to extract a small number of their typical patterns are presented. The electricity consumption patterns in a household is modeled by a mixture of Gaussian distributions. Then, using the symmetrized generalized Kullback-Leibler divergence as a distance measure of the distributions, typical patterns of the consumption are extracted by means of hierarchical clustering. The statistical modeling of daily consumption patterns allows us to capture essential similarities of the patterns. By experiments using a large-scale dataset including about 500 houses' consumption records in a suburban area in Japan, it is shown that the proposed method is able to extract typical consumption patterns. © 2010-2012 IEEE.

This article has no abstract.

A fault locator system in a loop-shaped distribution system with inverter based distributed generations is proposed. An algorithm of proposed fault locator system is based on the impedance obtained by the phase-voltage and line-current at the transformer feeder in the power distribution substation. We have proposed the quadratic equation expressed in terms of fault location. The quadratic equation represents the impedance from the substation to the fault location. Inserting the impedance obtained by the voltage and current at the transformer feeder into the quadratic equation, two candidates of the fault location are obtained. We can select the true fault location from the two candidates by using the characteristics of impedance calculated by the voltage and current at the incoming feeder of distributed generation. The validity of the fault locator system was investigated by PSCAD/EMTDC simulations. As a result, it was found that impedance obtained by the information of the substation and distributed generations are useful for searching the fault location in the loop-shaped distribution system. © 2013 The Institute of Electrical Engineers of Japan.

This article has no abstract.

This paper describes the results of an experimental investigation on the effects of the damper winding of a four-pole synchronous generator at a synchronous generator transient. It is known from simulations that the damper winding acts effectively under synchronous generator transient conditions. However, experimental proof has not been obtained yet. Thus, experiments on damper effects were conducted using a laboratory-scale power system. The damper winding of the tested generator consisted of five damper bars for each pole
the number of working damper bars could be changed manually. The damper currents at each bar were measured by a Rogowski coil. FFT analysis was applied to both the damper currents and armature currents under different operating conditions. The relationships between damper currents in the rotor and armature currents in the stator were made clearer than before. © 2012 Wiley Periodicals, Inc. Electr Eng Jpn, 180(2): 33-42, 2012
Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/eej.21278 Copyright © 2012 Wiley Periodicals, Inc.

This paper proposes a computation method to determine a optimal planning and operation of residential Photovoltaic Power Generation systems (PV systems) and Battery Energy Storage Systems (BESS) based on the weather forecast to each customer. In this proposed method, the optimal planning and operation are decided by changing the amount of charge in the BESS in midnight when the electric rate is cheap. This proposed method can determine the optimal planning (determination of optimal rating capacities of PV and BESS) and the optimal operation (determination of three values of the amount of charge at midnight on sunny day, cloudy day and rainy day) so as to minimize the annual cost of the household. In order to check the effectiveness of the proposed method, the optimal planning and the operation are compared on the data of two years.

Electricity consumption in households varies dependent on a lot of possible reasons such as lifestyle, family configuration, and weather. It is of great importance to optimize the electricity generation system to install for each household. In our previous work, we proposed a clustering approach for extracting a small number of basic electricity consumption patterns in a household. In this study, we apply the method to a larger dataset with many households. In the previous work, we determined the number of basic patterns in a heuristic manner. In this work, we use gap statistics to automatically determine an appropriate number of basic patterns, and we obtained a reasonable result on a large-scale data.

Considering recent trends in energy technology development, consumer's energy demand could be influenced by the renewable energy supply in any way. A simple extension of pattern sequence-based forecasting (PSF) enables us to predict demand curves based on the correlated bidimensional time-series by using co-occurrence patterns of energy supply and demand. However, prediction accuracy of PSF deeply depends on the clustering result, which is used for pattern matching. In this paper, a promising clustering method based on nonnegative tensor factorization is applied for this task and evaluated experimentally from the viewpoint of prediction accuracy.

The authors propose voltage control method using centralized control of D-STATCOM with controllable dead band to control all the node voltages dynamically. To maximize the acceptable amount of RES, centralized control system meters each node voltage installed D-STATCOM, and control all the node voltages based on each node voltage. The target voltage of D-STATCOM near a substation is modified by another node voltage to regulate all the node voltages within proper range. The amount of correction for the target voltage is determined by the amount of deviation from a threshold which is set between upper limits of the dead band and proper range. Conventional method has potential to command inappropriate reactive power due to delay time based on communication time and calculation for commands of reactive power. Proposed method compensates for the lack of reactive power based on the delay time using the predictive control.

In the field of electrical power system, various approaches, such as utilization of renewable energy, loss reduction, and so on, have been taken to reduce CO(2) emission. So as to work toward this goal, the total number of distributed generators (DGs) using renewable energy connected into 6.6-kV distribution systems has been increasing rapidly. The DGs can reduce distribution loss by appropriate allocation. However, when a fault occurs such as distribution line fault and bank fault, DGs connecting outage sections are disconnected simultaneously. Since the simultaneous disconnection of DGs influences restoration configuration and normal configuration after the restoration, it is necessary to determine the system configuration in the normal state considering simultaneous disconnection of DGs.
In this paper, the authors propose a computation method to determine the loss minimum configuration in the normal state considering reconnection of DGs after simultaneous disconnection by fault occurrence. The feature of determined loss minimum configuration is satisfying with operational constraints even if all DGs are disconnected from the system. Numerical simulations are carried out for a real-scale distribution system model with 252 sectionalizing switches (configuration candidates are 2(252)) and 120 DGs (total output is 38.46 MW which is 23% of total load) in order to examine the validity of the proposed algorithm. (C) 2011 Wiley Periodicals, Inc. Electr Eng Jpn, 176(4): 7-14, 2011; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/eej.

This paper describes the results of experimental investigation on the effects of damper winding of a 4-pole synchronous generator at the synchronous generator transient. It is known in the simulation that the damper winding acts effectively at the synchronous generator transient condition. However, experimental proof has not been performed yet. Then, experiments on damper effects were conducted in this paper using a laboratory-scale power system. The damper winding of tested generator consists of 5 damper bars each pole and the number of working damper bars can be changed manually. Damper currents at each bar were measured by a Rogowski coil. FFT analysis was applied to both damper currents and armature currents under different operating conditions. Relationships between damper currents in the rotor and armature currents in the stator were made clearer than before.

In the field of electrical power system, various approaches, such as utilization of renewable energy, loss reduction, and so on, have been taken to reduce CO₂ emission. So as to work toward this goal, the total number of distributed generators (DGs) using renewable energy connected into 6.6kV distribution system has been increasing rapidly. However, when a fault occurs such as distribution line faults and bank faults, DGs connecting outage sections are disconnected simultaneously. Since the output of DGs influences feeder current and node voltage of distribution system, it is necessary to determine the optimal system configuration considering simultaneous disconnection and reconnection of DGs.<br>In this paper, the authors propose a computation method to determine the optimal restoration configuration considering many connections of DGs. The feature of determined restoration configurations is prevention of the violation of operational constraints by disconnection and reconnection of DGs. Numerical simulations are carried out for a real scale distribution system model with 4 distribution substations, 72 distribution feeders, 252 sectionalizing switches (configuration candidates are 2²⁵²) and 23.2MW DGs (which is 14% of total load) in order to examine the validity of the proposed algorithm.

In recent years, the power quality of a distribution system is getting worse. In the distribution system, the voltage imbalance and current imbalance or the increase of harmonics has been seen with diversification of the loads by progress of power electronics technology and with increase of the amount of connection of distributed generators for home use with the reduction of the effect on the environment. This paper proposes the suppressing method of harmonics and improvement method of voltage imbalance in the distribution system utilizing the plural power conditioner systems of photovoltaic systems. And it verifies the validity of the proposal method by the numerical calculation using an analytical model of distribution system. © 2011 IEEE.

A distribution network has a huge number of configuration candidates because the network configuration is determined by the states of many sectionalizing switches (opened or closed) installed in terms of keeping power quality, reliability, and so on. Since the feeder current and voltage depend on the network configuration, the distribution loss, voltage imbalance, and bank efficiency can be controlled by changing the states of these switches. In addition, feeder currents and voltages change in response to the outputs of distributed generators (DGs) such as photovoltaic generation systems, wind turbine generation systems, and so on, that are connected to the feeder. Recently, the total number of DGs connected to distribution networks has increased drastically. Therefore, many configuration candidates of distribution networks must be evaluated multiply from various viewpoints such as distribution loss, voltage imbalance, bank efficiency, and so on, considering the power supply from the connected DGs. In this paper, the authors propose a multiobjective optimization method from three evaluation viewpoints, (1) distribution loss, (2) voltage imbalance, and (3) bank efficiency, using Pareto optimal solutions. In the proposed method, after several high-ranking candidates with small distribution loss are extracted by combinatorial optimization, each candidate is evaluated from the viewpoints of voltage imbalance and bank efficiency using the Pareto optimal solution, after which the minimum-loss configuration is chosen as the best configuration among these solutions. Numerical simulations were performed for a real-scale system model consisting of 72 distribution feeders and 234 sectionalizing switches in order to examine the validity of the proposed method. (C) 2010 Wiley Periodicals, Inc. Electron Comm Jpn, 94(1): 7-16, 2011; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/ecj.10271

In tandem with the penetration of Renewable Energy Sources (RES) such as photovoltaic and wind power generation to reduce CO2 emissions and conserve energy, development of advanced smart grid technologies is needed to secure a stable power supply of grid with RES by controlling power quality (voltage and frequency) within each secure range. This paper describes Japanese trend of the advanced smart grid technologies to harmonize RES and conventional bulk power system. Furthermore, several ongoing field tests to try to realize Japanese version of smart grid are briefly introduced.

This paper deals with an experimental investigation of a novel fault location method using air-gap flux distributions of a synchronous generator connected to a power system. Air-gap fluxes are the sum of field fluxes and armature reaction fluxes. Changes in armature current and In field current at a fault contribute directly to the armature reaction fluxes and field fluxes, then resultant air-gap fluxes. Therefore, air-gap fluxes can be utilized to locate a fault. Wavelet analysis is applied to the induced voltages of search coils, which are wound around a stator tooth top for measurement of the air-gap flux. It is shown that the fault type and location can be estimated based oil the change in the search coil voltages measured during the fault. (C) 2009 Wiley Periodicals, Inc. Electr Eng Jpn, 167(3): 20-27, 2009; Published online in Wiley InterScicrice (www. interscience.wiley.com). DOI 10.1002/eej.20707

Recently, the total number of distributed generators (DGs) such as photovoltaic generation system and wind turbine generation system connected to an actual distribution network has increased drastically. The distribution network connected to many distributed generators must be operated keeping reliability of power supply, power quality, and loss minimization. In order to accomplish active distribution network operation to take advantage of many connections of DGs, a new coordinated operation of distribution system with many connections of DGs is necessary. In this paper, the authors propose a coordinated operation of distribution network system connected to many DGs by using newly proposed sectionalizing switch control, sending voltage control, and computation of available DG connection capability. In order to check the validity of the proposed coordinated operation of distribution system, numerical simulations using the proposed coordinated distribution system operation are carried out in a practical distribution network model. © 2009 Wiley Periodicals, Inc.

In a distribution system, in order to enhance the reliability of power supply, the distribution feeder is divided into several sections by installing sectionalizing switches, and then each of the sectionalized sections is connected to a different feeder. For example, one feeder is divided into three sections by two sectionalizing switches, and then each of the divided sections is connected to the other feeder through sectionalizing switch. Since a distribution system with many feeders has many sectionalizing switches, the system configuration is determined by states (opened or closed) of sectionalizing switches. Usually, a power utility tries to obtain distribution loss-minimum configuration among large numbers of configuration candidates. However, it is very difficult to determine the loss-minimum configuration such that the mathematical optimality is guaranteed, because it is well known that determination of a distribution system&apos;s configuration is to decide whether each sectionalizing switch is opened or closed by solving a combinatorial optimization problem.
In this paper, the authors propose a determination method of loss-minimum configuration by which the mathematical optimality is guaranteed for a three-sectionalized three-connected distribution feeder network. A problem to determine the loss-minimum configuration is formulated as a combinatorial optimization problems with four operational constraints ((1)) feeder capacity, (2) voltage limit, (3) radial structure, and (4) three-sectionalization). In the proposed method, after picking up all partial configurations satisfied with radial structure constraint by using enumeration method, optimal combination of partial configurations is determined under the other operational constraints by using conventional optimization method. Numerical simulations are carried out for a distribution network model with 140 sectionalizing switches in order to examine the validity of the proposed algorithm in comparison with one of conventional meta-heuristics (tabu search). (c) 2009 Wiley Periodicals, Inc. Electr Eng Jpn, 167(1): 56-65, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20530

Harmonics bred from loads are mainly odd order because the current waveforms have half-wave symmetry. Since the even harmonics are negligibly small, they generally are not measured in electric power systems. However, even harmonics were measured at a 500/275/154 kV substation in Hokuriku Electric Power Company after a transmission line fault was corrected. The even harmonics caused malfunctions of protective digital relays because the relays used 4th harmonics at the input filter as the automatic supervisory signal.
This paper describes mechanisms of generation of the even harmonics by comparing the measured waveforms with the ATP-EMTP simulation results. Analysis of these results has clearly shown that there are three different mechanisms of generation of even harmonics. The first mechanism is the appearance of a magnetizing current in transformers due to flux deviation by the DC component of the fault current. The second mechanism is harmonic conversion of a Synchronous machine which generates even harmonics when the DC component or the even harmonic current flow into the machine. The third mechanism is an increase of harmonic impedance due to an isolated power system, thus producing the harmonic voltages. The design of the input filter of protective digital relays should take into account even harmonics generation in an isolated power system. (C) 2009 Wiley Periodicals, Inc. Electr Eng Jpn, 167(2): 56-63, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20592

Recently, the total number of distributed generation such as photovoltaic generation systems and wind turbine generation systems connected to a distribution network has drastically increased. Distributed generation using renewable energy can reduce the distribution loss and emission of CO,. However, the distribution network with file distributed generators must be operated while maintaining the reliability of the power supply and power quality. In this paper, the authors propose a computational method to determine the maximum output of a distributed generator under operational constraints [(1) voltage limit, (2) line current capacity, and (3) no reverse flow to bank] at arbitrary connection points and hourly periods. In the proposed method, a three-phase iterative load flow calculation is applied to evaluate the above operational constraints. The three-phase iterative load flow calculation has two simple procedures: (Procedure 1) addition of load currents from the terminal node of the feeder to root one, and (Procedure 2) subtraction of Voltage drop From the root node of the feeder to terminal one. In order to check the validity of the proposed method, numerical simulations are performed I or a distribution system model. Furthermore, the characteristics of locational and hourly maximum output of a distributed generator connected to a distribution feeder are analyzed using several numerical examples. (C) 2009 Wiley Periodicals, Inc. Electr Eng Jpn, 167(2): 38-47, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20610

In the field of electrical power system, various approaches, such as utilization of renewable energy, loss reduction, and so on, have been taken to reduce CO₂ emission. So as to work toward this goal, the total number of distributed generators (DGs) using renewable energy connected into 6.6kV distribution system has been increasing rapidly. The DGs can reduce distribution loss by appropriate allocation. However, when a fault occurs such as distribution line fault and bank fault, DGs connecting outage sections are disconnected simultaneously. Since the simultaneous disconnection of DGs influences restoration configuration and normal configuration after the restoration, it is necessary to determine the system configuration in normal state considering simultaneous disconnection of DGs.<br>In this paper, the authors propose a computation method to determine the loss minimum configuration in normal state considering reconnection of DGs after simultaneous disconnection by fault occurrence. The feature of determined loss minimum configuration is satisfying with operational constraints even if all DGs are disconnected from the system. Numerical simulations are carried out for a real scale distribution system model with 252 sectionalizing switches (configuration candidates are 2²⁵²) and 120 DGs (total output is 38.46MW which is 23% of total load) in order to examine the validity of the proposed algorithm.

Distribution network has huge number of configuration candidates because the network configuration is determined by state of many sectionalizing switches (opened or closed) installing in terms of keeping power quality, reliability and so on. Since feeder current and voltage depends on the network configuration, distribution loss, voltage imbalance and bank efficiency can be controlled by changing state of these switches. In addition, feeder current and voltage change by out put of distributed generators (DGs) such as photovoltaic generation system, wind turbine generation system and so on, connected to the feeder. Recently, total number of DGs connected to distribution network increases drastically. Therefore, many configuration candidates of the distribution network must be evaluated multiply from various viewpoints such as distribution loss, voltage imbalance, bank efficiency and so on, considering power supply from connected DGs.<br>In this paper, the authors propose a multi-objective optimization method from three evaluation viewpoints ((1) distribution loss, (2) voltage imbalance and (3) bank efficiency) using pareto optimal solution. In the proposed method, after several high-ranking candidates with small distribution loss are extracted by combinatorial optimization method, each candidate are evaluated from the viewpoints of voltage imbalance and bank efficiency using pareto optimal solution, then loss minimum configuration is determined as the best configuration among these solutions. Numerical simulations are carried out for a real scale system model consists of 72 distribution feeders and 234 sectionalizing switches in order to examine the validity of the proposed method.

This paper presents a new computation method to determine simultaneously file optimal parameters of several voltage regulators such as load-ratio control transformer (LRT) and step voltage regulator (SVR) installed in a radial distribution network. The proposed method determines a combination of their control parameters by minimizing the weighted sum of deviations of line voltage from the upper and lower voltage limits and the amounts of voltage violations by referring to the stored data measured by IT switches. which are sectionalizing switches with sensors installed in the distribution feeder. The optimization algorithm is based on particle swarm optimization (PSO). which is one of the nonlinear optimization methods, by using the concept of swarm intelligence. In order to confirm the validity of the proposed method, numerical simulations are carried out oil a distribution network model. (c) 2008 Institute of Electrical Engineers of Japan. Published John by Wiley & Sons. Inc.

Distributed generators (DGs) such as fuel cells and solar cells are going to be installed in the demand side of distribution systems. The DGs can reduce distribution loss by appropriate allocation. However, there are several problems installing DGs such as service restoration of distribution system with DGs and so on. When one bank fault of distribution substation occurs in distribution system, since DGs are simultaneously disconnected from the system, it is not easy to restore isolated load by one bank switching in distribution substation. Therefore, a service restoration method to determine restoration configuration and restoration procedures (switching procedure from normal configuration to restoration configuration) taking into account simultaneous disconnection of DGs is needed. In this paper, the authors propose a computation method to determine the optimal restoration configuration and the restoration procedure considering simultaneous disconnection of DGs by one bank fault of distribution system. In the proposed algorithm, after all of the restoration configuration candidates are effectively enumerated under the operational constraints, the optimal configuration to restore the isolated load is selected among enumerated configuration candidates. After determining the optimal restoration configuration, the optimal restoration procedures are obtained by greedy algorithm. Numerical simulations are carried out for a real scale system model with 237 sectionalizing switches (configuration candidates are 2(237)) and 21 DGs (total Output is 5250 kW which is 3% of total load) in order to examine the validity of the proposed algorithm. (C) 2008 Wiley Periodicals, Inc. Electron Comm Jpn, 91(8): 44-55, 2008; Published online in Wiley InterScience (www.interscience. wiley.com). DOI 10.1002/ecj.10133

In order to devise countermeasures for harmonic disturbances and harmonic suppression in power systems effectively, it is necessary to develop a harmonic analysis approach with high accuracy. The major harmonic analysis approach is to re-create harmonic distribution in a power system model by using a simulation method. However, in order to carry out high-accuracy estimation of the harmonic distribution using the simulation method, after creating a load model which consists of several parameters associated with the measured harmonic impedance, the optimal load model parameters must be determined. So far, appropriate load model parameters have been determined by trial and error. Therefore, a systematic approach to determine the optimal load model parameters is needed to estimate the measured harmonic impedance with high accuracy.
In this paper, a determination method for the optimal load model parameters to estimate the measured harmonic impedance is proposed. The proposed method is based on Particle Swarm Optimization (PSO), which is one of the optimization methods using the concept of swarm intelligence. In order to check the validity of the proposed method, the load model parameters estimated by the proposed method are evaluated using test data and field data of Hokuriku Electric Power Co. (c) 2008 Wiley Periodicals, Inc.

Distributed generators (DGs) such as fuel cells and solar cells are going to be installed in the demand side of distribution systems. The DGs can reduce distribution loss by appropriate allocation. However, there are several problems installing DGs such as service restoration of distribution system with DGs and so on. When one bank fault of distribution substation occurs in distribution system, since DGs are simultaneously disconnected from the system, it is not easy to restore isolated load by one bank switching in distribution substation. Therefore, a service restoration method to determine restoration configuration and restoration procedures (switching procedure from normal configuration to restoration configuration) taking into account simultaneous disconnection of DGs is needed. In this paper, the authors propose a computation method to determine the optimal restoration configuration and the restoration procedure considering simultaneous disconnection of DGs by one bank fault of distribution system. In the proposed algorithm, after all of the restoration configuration candidates are effectively enumerated under the operational constraints, the optimal configuration to restore the isolated load is selected among enumerated configuration candidates. After determining the optimal restoration configuration, the optimal restoration procedures are obtained by greedy algorithm. Numerical simulations are carried out for a real scale system model with 237 sectionalizing switches (configuration candidates are 2237) and 21 DGs (total output is 5250 kW which is 3% of total load) in order to examine the validity of the proposed algorithm. © 2008 Wiley Periodicals, Inc.

Sending voltage profile of distribution feeder is controlled by changing a tap of distribution transformer. In a distribution network with distributed generators, for reasons of effect of reversed flows from them and existence of a great number of sending voltage profile candidates, it is not easy to control sending voltage profile within the acceptable voltage limit. In this paper, in order to determine the optical sending voltage profile of distribution transformer in a distribution network with distributed generators, the authors propose a new method to determine the optimal sending voltage profile so as to minimize the total number of tap position&apos;s change per day under constraints of acceptable voltage limit. In the proposed method, after calculating acceptable range of three-phase voltage of distribution feeder, the optimal profile of tap position within the calculated acceptable voltage range is determined among these candidates by using reduced ordered binary decision diagram (ROBDD) which is an efficient enumeration algorithm. In order to check the validity of the proposed method, numerical simulations are carried out for a distribution network model with a distributed generator. (c) 2007 Wiley Periodicals, Inc.

Global warming caused by carbon dioxide (CO₂₎ and other greenhouse gases is one of the serious environmental issues. Carbon dioxide is the biggest contributor to global warming. Many efforts to reduce emissions of CO₂ are carrying out in various fields. In electrical power system field, various approaches to reduce CO₂ emissions have been performed such as loss reduction, utilization of renewable energy, recycling of resources and so on. Especially, distribution loss minimization is effective to reduce CO₂ emissions because reduction of distribution loss leads to save the energy. For example, the largest distribution system in Japan consists of about 19,000 feeders. Much CO₂ emissions can be reduced by minimizing distribution loss of the largest distribution system. However, CO₂ emissions reduced by distribution loss minimization for the largest Japanese distribution system have not been estimated so far.<br>In this paper, the authors try to calculate annual CO₂ emissions reduced by distribution loss minimization for a distribution system model based on partial actual data, which is composed by 19,000 distribution feeders, 95,358 sectionalizing switches and 73,849 load sections. In the trial calculation, reduced CO₂ emissions are estimated by sequentially proceeding four procedures: (1) classification of distribution system model into several load areas, (2) determination of loss minimum configuration in each load area, (3) calculation of reduced annual distribution loss for each area, and (4) calculation of reduced annual CO₂ emissions. As the result of the trial calculation, reduced annual CO₂ emissions of 40 &times; 10⁶kg/year is estimated for the Japanese largest scaled 19,000 feeders distribution model.

This article has no abstract.

Since a distribution network has many sectionalizing switches, there are huge radial network configuration candidates by states (opened or closed) of sectionalizing switches. Recently, the total number of distributed generation such as photovoltaic generation system and wind turbine generation system connected to the distribution network is drastically increased. The distribution network with the distributed generators must be operated keeping reliability of power supply and power quality. Therefore, the many configurations of the distribution network with the distributed generators must be evaluated multiply from various viewpoints such as distribution loss, total harmonic distortion, voltage imbalance and so on. In this paper, the authors propose a multi evaluation method to evaluate the distribution network configuration candidates satisfied with constraints of voltage and line current limit from three viewpoints ((1) distribution loss, (2) total harmonic distortion and (3) voltage imbalance). After establishing a standard analytical model of three sectionalized and three connected distribution network configuration with distributed generators based on the practical data, the multi evaluation for the established model is carried out by using the proposed method based on EMTP (Electro-Magnetic Transients Programs).

Recently, the total number of distributed generation such as photovoltaic generation system and wind turbine generation system connected to distribution network is drastically increased. Distributed generation utilizing renewable energy can reduce the distribution loss and emission of CO2. However the distribution network with the distributed generators must be operated keeping reliability of power supply and power quality. In this paper, the authors propose a computation method to determine the maximum output of a distributed generator under the operational constrains ((1) voltage limit, (2) line current capacity, and (3) no reverse flow to bank) at arbitrary connection point and hourly period. In the proposed method, three-phase iterative load flow calculation is applied to evaluate the above operational constraints. Three-phase iterative load flow calculation has two simple procedures: (Procedure1) addition of load currents from terminal node of feeder to root one, and (Procedure2) subtraction of voltage drop from root node of feeder to terminal one. In order to check the validity of the proposed method, numerical simulations are accomplished for a distribution system model. Furthermore, characteristics of locational and hourly maximum output of distributed generator connected to distribution feeder are analyzed by several numerical examples.

In a distribution system, in order to enhance the reliability of power supply, the distribution feeder is divided into several sections by installing sectionalizing switches, and then each of sectionalized sections is connected to different feeder. For example, one feeder is divided into three sections by two sectionalizing switches, and then each of divided sections is connected to other feeder through sectionalizing switch. Since a distribution system with many feeders has many sectionalizing switches, the system configuration is determined by states (opened or closed) of sectionalizing switches. Usually, power utility tries to obtain distribution loss-minimum configuration among large numbers of configuration candidates. However, it is very difficult to determine the loss-minimum configuration that the mathematical optimality is guaranteed, because it is well known that determination of distribution system's configuration is to decide whether each sectionalizing switch is opened or closed by solving a combinatorial optimization problem.
In this paper, the authors propose a determination method of loss minimum configuration which the mathematical optimality is guaranteed for a three sectionalized and three connected distribution feeder network. A problem to determine the loss minimum configuration is formulated as a combinatorial optimization problems with four operational constraints ((1) feeder capacity, (2) voltage limit, (3) radial structure and (4) three sectionalization). In the proposed method, after picking up all partial configurations satisfied with radial structure constraint by using enumeration method, optimal combination of partial configurations is determined under the other operational constraints by using conventional optimization method. Numerical simulations are carried out for a distribution network model with 140 sectionalizing switches in order to examine the validity of the proposed algorithm in comparison with one of conventional meta-heuristics (Tabu search).

Open access to electric power transmission networks has been carried out in order to foster generation competition and customer choice worldwide. When several PPSs request to simultaneously supply power to customers based oil bilateral contracts, it is expected that the transmission network accepts amounts of wheeled power requested by the PPSs as much as possible. It is possible to maximize total requested wheeled power by controlling power flow through transmission lines. It is well known that FACTS device is available to control line flow flexibly. In this paper, in order to maximize total wheeled power simultaneously requested by several PPSs, the authors propose an algorithm to determine the optimal reactance of TCSC (a type of FACTS device). The proposed algorithm is based on Particle Swarm Optimization (PSO), which is an optimization method based on swarm intelligence. In the proposed algorithm, PSO is improved to enhance ability of searching global minimum by giving different characteristic to behavior of each agent. In order to check the validity of the proposed method, numerical results are shown for 6 and IEEE 30 bus system models. (c) 2006 Wiley Periodicals, Inc.

Distributed generators (DGs) such as fuel cells and solar cells etc. are going to be installed in demand side of distribution systems. The distributed generators can reduce distribution loss by appropriate allocation. However, there are several problems to install DGs such as service restoration of distribution system with DGs and so on. When one bank fault of distribution substation occurs in distribution system, since DGs are simultaneously disconnected from the system, it is not easy to restore isolated load by one bank switching in distribution substation. Therefore, a service restoration method to determine restoration configuration and restoration procedures (switching procedure from normal configuration to restoration configuration) taking into account simultaneous disconnection of DGs is needed. In this paper, the authors propose a computation method to determine the optimal restoration configuration and the restoration procedure considering simultaneous disconnection of DGs by one bank fault of distribution system. In the proposed algorithm, after all of restoration configuration candidates are effectively enumerated under the operational constraints, the optimal configuration to restore the isolated load is selected among enumerated configuration candidates. After determining the optimal restoration configuration, the optimal restoration procedures are obtained by greedy algorithm. Numerical simulations are carried out for a real scale system model with 237 sectionalizing switches (configuration candidates are 2237) and 21DGs (total output is 5250kW which is 3% of total load) in order to examine the validity of the proposed algorithm.

Japan set up the long-term R & D roadmap titled "PV2030" in 2004. This roadmap assumes the mass deployment of 100GW PV aggregation will supply 10% of national electricity up to year 2030. Under this condition, PV penetration will reach almost 100% in the majority of urban areas, which may allow less harmonization with the conventional power grid due to the frequent and huge reversal power flow from PVs. The authors have developed new concepts called "autonomy-enhanced PV cluster (AE-PVC)" to realize a less dependent PV aggregation on the existing power grids. This paper describes a configuration and functions of a battery storage station, which performs energy control in AE-PVC.

Harmonics bred from loads are mainly odd order because the current waveform has half-wave symmetry. Since the even harmonics are negligibly small, those are not generally measured in electric power systems. However, even harmonics were measured at a 500/275/154 kV substation in Hokuriku Electric Power Company after removal of a transmission line fault. The even harmonics caused malfunctions of protective digital relays because the relays used 4 th harmonics at the input filter as automatic supervisory signal. This paper describes the mechanism of generation of the even harmonics by comparing measured waveforms with ATP-EMTP simulation results. As a result of analysis, it is cleared that even harmonics are generated by three causes. The first cause is a magnetizing current of transformers due to flux deviation by DC component of a fault current. The second one is due to harmonic conversion of a synchronous machine which generates even harmonics when direct current component or even harmonic current flow into the machine. The third one is that increase of harmonic impedance due to an isolated power system produces harmonic voltages. The design of the input filter of protective digital relays should consider even harmonics generation in an isolated power system.

Sending voltage profile of distribution feeder is controlled by changing a tap of distribution transformer. In a distribution network with distributed generators, for reasons of effect of reversed flows from them and existence of a great number of sending voltage profile candidates, it is not easy to control sending voltage profile within the acceptable voltage limit. In this paper, in order to determine the optimal sending voltage profile of distribution transformer in a distribution network with distributed generators, the authors propose a new method to determine the optimal sending voltage profile so as to minimize total number of tap position's change per day under constraints of acceptable voltage limit. In the proposed method, after calculating acceptable range of three phase voltage of distribution feeder, the optimal profile of tap position within the calculated acceptable voltage range is determined among these candidates by using reduced ordered binary decision diagram (ROBDD) which is an efficient enumeration algorithm. In order to check the validity of the proposed method, numerical simulations are carried out for a distribution network model with a distributed generator.

in Japan, local power systems (77 kV) are served from the 275- or 154-kV substations. For enhancement of power supply reliability, the transmission lines are connected to several substations, and the operational configuration is radial. The local power system&apos;s configuration is determined by connecting and disconnecting transmission lines so as to keep the radial structure and satisfy the operation constraints. When a local power system has a number of transmission lines, many configuration candidates occur. Recently, an IEEJ committee made a practical scale local system model (IEEJ Local System Model). Since the IEEJ Local System Model has 76 transmission lines, the total number of configuration candidates is 2(76) (approximately 7.5 x 10(22)). In this paper, the authors try to strictly obtain the loss-minimum configuration under constraints such as substation capacity, line capacity, and radial structure in the IEEJ Local System Model. In order to obtain the optimal configuration, a new computation algorithm is proposed. In the proposed algorithm, the configuration determination problem is replaced as two combinatorial optimization problems based on the operational constraints [(1) substation capacity, (2) line capacity, and (3) radial structure]. One combinatorial optimization problem (subproblem 1) is to pick up all partial configurations so as to minimize total line loss under the substation capacity constraint. By using the enumeration method, subproblem 1 is solved. Subproblem 2 is solved by using the reduced ordered binary decision diagram (ROBDD). Since the proposed method is based on enumeration and Boolean function, the optimality of obtained solution is guaranteed. (C) 2004 Wiley Periodicals, Inc.

Open access to electric power transmission networks has been carried out in order to foster generation competition and customer choice in the worldwide. When several PPSs request to simultaneously supply power to customers based on bilateral contracts, it is expected that transmission network accepts amounts of wheeled power requested by the PPSs as much as possible. It is possible to maximize total requested wheeled power by controlling power flow through transmission lines. It is well known that FACTS device is available to control line flow flexibly. In this paper, in order to maximize total wheeled power simultaneously requested by several PPSs, the authors propose an algorithm to determine the optimal reactance of TCSC (one of FACTS devices). The proposed algorithm is based on Particle Swarm Optimization (PSO), which is one of optimization methods based on swarm intelligence. In the proposed algorithm, PSO is improved to enhance ability of searching global minimum by giving different characteristic to behavior of each agent. In order to check the validity of the proposed method, numerical results are shown for 6 and IEEE 30 bus system models.

Local power systems (66kV) are served from the 275kV or 154kV substations. In order to maintain power supply reliability, the transmission lines are connected to several substations, and the operational configuration is radial. Since practical local power system has a number of transmission lines, many configuration candidates occur. It is expected to effectively evaluate these configuration candidates from various viewpoints such as reliability of power supply, transmission loss and so on. In this paper, the authors propose a multi objective evaluation method by using deterministic and probabilistic approaches for local power system configuration. In the proposed multi objective evaluation method, after selecting system configuration candidates which satisfy N-1 security by using an optimization method based on Boolean function, these candidates are evaluated from viewpoints of expected outage time, transmission loss and facility operation rate. In order to check the validity of the proposed method, numerical results are shown for a practical local system model with about 39 × 1027 configuration.

In Japan, when a secondary radial power system (66 kV, 77 kV) has a number of connected feeders whose circuit breakers (CBs) can be opened or closed, the combinatorial number of possible system structures created by switching CBs becomes very large. In order to determine the optimal configuration of secondary radial power system in normal state and fault state, a new computation algorithm is proposed. The proposed algorithm is based on enumeration and Reduced Ordered Binary Decision Diagram (ROBDD). In order to verify the availability of the proposed approach, the authors obtain optimal configurations for normal and fault states on IEE of Japan secondary power system model (IEEJ model) by using the proposed method. IEEJ model has the distinctive characteristics of practical Japanese power systems, the total number of configuration candidates is the 76th power of 2 (= 75 000 000 000 000 billion approximately). The optimality of the system configuration obtained by the proposed method is mathematically guaranteed.

Dispersed generators (DGs) such as fuel cells and solar cells etc. are going to be installed in demand side of power systems. The dispersed facilities can reduce distribution system loss by the appropriate allocation. However, when a DG which has large capacity is disconnected from the distribution network by a fault, violation of the operational constraints such as the line capacity and voltage drop may occur. From a view point of system reliability, robust system configuration for suddenly disconnecting DG from the distribution network must be determined, since system operators can not control DG connection to the network in the on-line. In this paper, the authors propose an algorithm to determine the loss-minimum configuration for a distribution system with DGs maintaining system reliability. Namely, in the proposed algorithm, when the loss-minimum configuration is determined under the line current capacity and voltage drop constraints, n-1 contingencies for DGs are also considered. In order to determine the loss-minimum configuration, tabu search added strategic oscillation is employed. Numerical simulations are carried out for a real scale system model with 118 sectionalizing switches (configuration candidates is 2118) in order to examine the validity of the proposed algorithm. Furthermore, performance of the proposed method is compared with a conventional metaheuristic method, which is Simulated Annealing (SA), through numerical simulations for the system model.

Open access to electric power transmission networks has been carried out in order to foster generation competition and customer choice in the worldwide. Available transfer capability(ATC) is the largest additional amount of power above some base flow which can be transferred between two sets of buses under constraints such as voltage limit, overloads, stability and n-1 contingencies. Calculation of ATC is important to promote open access to electric power transmission networks. If there are several ATC between two sets of buses, simultaneous transfer capability(STC) of power transmission networks must be calculated. STC is defined as the ability of a transmission network to allow for the reliable movement of electric power from areas of supply to areas of demand. In this paper, a new algorithm to precisely calculate STC is proposed. The proposed method is based on linear programming(LP) based DC power flow and optimal power flow (OPF). Namely, LP base DC power flow is used to obtain the initial solution of STC, and then OPF using successive quadratic programming (SQP) is applied to obtain feasible solution of STC under the operational constraints such as balance of power supply and demand, voltage limit, overloads, generation limit, steady state stability and n-1 contingencies. Furthermore, if power wheeling transactions by several PPSs are simultaneously requested for the transmission network, it seems that the acceptable quantity for the requested wheeling power must be indicated to PPSs from a view point of the transmission network reliability. An algorithm to calculate the acceptable quantity for the requested wheeling power is also proposed by using STC computation. In order to check the validity of the proposed methods, numerical results are shown for 6 and IEEE 30 buses system models.

In Japan, local power systems (77kV) are served from the 275kV or 154kV substations. For enhancement of power supply reliability, the transmission lines are connected to several substations, and the operational configuration is radial. The local power system's configuration is determined by connecting and disconnecting transmission lines so as to keep the radial structure and satisfy the operational constraints. When a local power system has a number of transmission lines, many configuration candidates occurs. Recently, an IEEJ committee made a practical scale local system model (IEEJ Local System Model). Since IEEJ Local System Model has 76 transmission lines, the total number of configuration candidates is 276(=7.5×1022 approximately). In this paper, the authors try to strictly obtain the loss-minimum configuration under constraints such as substation capacity, line capacity and radial structure in IEEJ Local System Model. In order to obtain the optimal configuration, a new computation algorithm is proposed. In the proposed algorithm, the configuration determination problem is replaced as two combinatorial optimization problems based on the operational constraints (1)substation capacity, (2)line capacity and (3)radial structure). One combinatorial optimization problem (subprobleml) is to pick up all partial configurations satisfied with line capacity and radial structure constraints. The, other one (subproblem2) is to select the partial configurations so as to minimize total line loss under the substation capacity constraint. By using the enumeration method, subprobleml is solved. Subproblem2 is solved by using the reduced ordered binary decision diagram (ROBDD). Since the proposed method is based on enumeration and Boolean function, the optimality of obtained solution is guaranteed.

Dispersed generators (DGs) such as fuel cells and solar cells will be installed on the demand side of power systems. Such dispel scd facilities can reduce distribution system loss by appropriate allocation. Planning and operation of distribution systems with the dispersed facilities have already been discussed. In this paper, the authors discuss the extent to which distribution system loss can be reduced if DGs are optimally allocated on the demand side of the distribution system. In order to determine the optimal allocation and size of DGs so as to minimize the distribution system loss, an algorithm based on tabu search is employed. The proposed algorithm consists of iterated nested use of the tabu search algorithm. Namely, in the proposed algorithm, in one computational iteration, after the location of the DG is temporarily determined by tabu search, the size of the DG is also determined by tabu search so as to minimize the distribution system loss for the temporarily determined allocation. Numerical simulations are carried out fur two system models in order to examine the validity of the algorithm. (C) 2001 Scripta Technica, Electr Eng Jpn, 136(2): 1-8, 2001.

Secondary power systems (66kV) with radial system structures are served from the 275kV or 154kV substations. For enhancement of power supply reliability, the transmission line is connected to another substation. However, when the radial power system has a number of connected feeders, the combinatorial number of possible system structures by switching CBs becomes very large. In this paper, a new solution method to determine the optimal secondary power system configuration is proposed. In the proposed method, the determination problem of the optimal system structure is treated as a minimum spanning tree problem with constraints, and then it is solved by using reduced ordered binary decision diagram (ROBDD). Since the proposed method is based on Boolean function, the optimality of obtained solution is guaranteed. In order to check the validity of the proposed method, numerical simulations are carried out for system models, and the results obtained by branch and bound method are compared with these of proposed method.

Distributed generators (DGs) such as fuel cells, solar cells, wind mills and micro gas turbines, etc. are going to be installed in demand side of power systems. Such distributed generators can reduce distribution loss if they are placed appropriately in the distribution system. In this paper, tabu search application for finding the optimal allocation of DGs from a viewpoint of loss minimization is illustrated. In other words, the authors discuss about an implementation method of tabu search to find how much distribution loss can be reduced if DGs are optimally allocated at the demand side of a power system. Namely, locations and discrete capacities of DGs to minimize the distribution loss are determined by nested use of the tabu search algorithm. Numerical examples are shown to demonstrate the method.

Dispersed generators (DG) such as fuel cells and solar cells etc. are going to be installed in demand side of power systems. The dispersed facilities can reduce distribution system loss by the appropriate allocation. So far, planning and operation of distribution system with the dispersed facilities have been discussed. In this paper, the authors discuss about how much the distribution system loss minimization can be reduced if DGs are optimally allocated at the demand side of the distribution system. In order to determine the optimal allocation and size of DG for minimizing the distribution system loss, an algorithm based on tabu search is employed. The proposed algorithm consists of the repetition of nested use of the tabu search algorithm. Namely, in the proposed algorithm, in one computational iteration, after the location of DG is temporarily determined by tabu search, the size of DG is also determined by tabu search so as to minimize the distribution system loss for the temporarily determined allocation. Numerical simulations are carried out for two system models in order to examine the validity of the algorithm.

This paper proposes a new algorithm to obtain an approximate optimal solution for the load balancing of large-scale radial distribution system. Since the problem is formulated as a combinatorial optimization problem because of the discreteness of load section connection, it is difficult to solve a large-scale combinatorial optimization problem accurately within the reasonable computational time. So for, in order to find an approximate optimal solution quickly, the authors have published a solution method based on the network flow incremental algorithm. Although the incremental algorithm can find the optimal solution to the problem, the result is not always radial (feasible). So as to overcome this deficiency, in this paper, the authors propose a new algorithm that can find the load balanced radial distribution feeder configuration. The proposed algorithm picks up load by a unit of a section load. Therefore, the problem is elementarily a combinatorial optimization problem. However, to avoid the permutation, the algorithm employs a heuristic algorithm based on the mathematical concept of the optimality of the incremental algorithm. In picking up section load, the algorithm can take into account not only the current load balance but also the expected load which feeders should pick up afterward. To realize this algorithm, a combination of labels is introduced to each node. Through numerical examples, the validity of the proposed method is examined.

The authors have been proposing a new electrical power delivery system named FRIENDS Flexible, Reliable and Intelligent Electrical eNergy Delivery System). FRIENDS is a new concept of power distribution system which can realize unbundled power duality services after de-regulated conditions. In order to realize FRIENDS, we must develop a system network configuration of FRIENDS itself For unbundled power quality services, especially, for reliable power supply, the authors propose a new algorithm to create a network of FRIENDS. The proposed method is based on tabu search, and can find the, le: ast cost network configuration of FRIENDS under the constraint that no overloaded exists in multiple fault cases.

In planning a distribution system for urban area, when a feeder is newly installed, the route of the feeder must be determined among many candidates, considering investment cost and constraints. However, it is difficult for planners to find the optimal route of the newly installed feeder. Because too many candidates of route exist which can be constructed along the road on service area of the power company. It must be considered whether the end part of an existing feeder can be used as apart of newly installed feeder within specified loaded value. In this paper, in order to support planners' decision for selecting optimal route of newly installed feeders, the authors have formulated the problem mathematically, and propose a new solution algorithm to find the optimal route by referring Dijkstra Method. Through numerical examples, authors demonstrate the validity of the proposed method.

This paper describes a method of solving a large scale long term thermal unit maintenance scheduling problem. In the solution algorithm, the genetic algorithm(GA), the simulated annealing(SA) and the tabu search(TS) are cooperatively used. The solution algorithm keeps the advantages of individual algorithm and shows a reasonable combination of local search and global search. The method takes the maintenance class and several consecutive years scheduling into consideration. Several real scale numerical examples demonstrate the effectiveness of the proposed method.

Genetic Algorithm(GA) is well-known as a search algorithm based on the mechanics of natural selection and natural genetics. The ability of adaptiveness of GA is available for various problems in industrial fields. In this paper, GA is applied to scenario creation for the evaluating future plan in order to support planner's work. The proposed method is based on the planner's knowledge which is used to create scenarios by planner. The effectiveness of the proposed method is demonstrated by numerical results for an example of application to the power system planning.

Recently the task of planning in power systems is becoming a very complicated process for utility planners. This kind of planning has a lot of objectives to accomplish. In this paper we employ Negotiation Algorithm, which was proposed by the group of Chen-Ching Liu, for subtransmission power system planning to create a plan having many objectives. First, the Goal-Decision-Network(GDN) is constructed to model this planning problem, and Negotiation Algorithm is applied to utilize both subtrasmission system planning GDN, which attempts to capture its knowledge, and negotiation operators, which search for the most feasible and promising decisions in this planning GDN. Finally the negotiation expert system is demonstrated for the subtransmission system planning using a real system.

In general, electric power companies must prepare power supply capability for maximum electric load demand because it is very difficult at present to store electric power. It takes several years and requires a great amount of money to construct power generation and transmission facilities. Therefore, it is necessary to forecast long-ten load demand exactly in order to plan or operate power systems efficiently. Several methods have been investigated so far for the long-term load forecasting. However, because the electric loads consist of many complex factors, good forecasting has been very difficult.
This paper proposes a long-term load forecasting method using a recurrent neural network (RNN). This is a mutually connected network that has the ability of learning patterns and past records. In general, when interpolation is used for unlearned data sets, the neural network provides reasonably good outputs. However, when extrapolation is used, such as in long-term load forecasting, some kind of tunings have been necessary to obtain good results. Therefore, to solve the problem, a method is proposed in which growth rates are used as input and output data. Using the proposed method, successful results have been obtained and comparisons have been made with the conventional methods,

The voltage control calculation is the combinatorial optimization problem, and it has been difficult to solve this type of problem quickly with the conventional digital computer. However according to the modelling of excellent parallel processing ability of neurons, it has become possible to carry out the optimization with the Hopfield neural network model. In this paper, in order to solve the voltage control problem we propose an improved Hopfield model which has an individual input-output function for an individual neuron to achieve a drastic improvement in the calculation time.

In recent years, according to the modelling of excellent information processing ability of neurons, it has become possible to carry out pattern recognitions or optimizations with the neural network theory. In this paper, we show how to introduce the neural network theory to the load-flow calculation of rectangular coordinate. A problem which input-output functions have for neural network applications is pointed out, and effects of changes in load patterns and system size are discussed in terms of the optimal multiplier. Results of simulations are shown with the convergence characteristics.