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We propose a method to estimate transmission‐line overloads due to forecast errors of power output of renewable energy sources. The proposed method involves particle swarm optimization and optimal power flow calculations. The effectiveness of the method is confirmed via numerical simulations using a modified IEEE RTS 24‐bus system model. The results indicate that the proposed method can determine the forecast errors of the renewable power output that causes thermal overload, and further predict the occurrences of transmission‐line overload under generator activation in supply and demand planning. Furthermore, we explain the occurrence mechanism of transmission‐line overload due to forecast errors, which may contribute to improve the daily supply and demand planning. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The photovoltaic (PV) power output might be frequently curtailed to maintain electricity supply‐demand balance in future power systems. In our previous study, we proposed a new method for updating the battery energy storage system (BESS) charge/discharge and the generator unit commitment (UC) schedules based on the forecasted and actual PV power outputs. The forecast dataset was updated every 3 h (eight times a day). Although the simulation results showed that the proposed method could reduce the supply‐demand imbalances, it was not clear whether the forecasted or actual values made contributions. Therefore, in this study, we propose and evaluate a real‐time scheduling and operation method using the forecasted and actual PV power outputs assuming that the forecasted dataset is updated only once a day. Numerical simulations of supply‐demand operations are conducted on the power system model of the Kanto area of Japan for one year. The results show that the previous study method has a slight advantage over proposed method in terms of curtailed PV energy and operational cost of thermal generators reduction, but the difference is very small, indicating that the contribution of the actual PV power outputs is greater than that of the forecasted PV power outputs. [ABSTRACT FROM AUTHOR]

In recent years, the aggregation business has gained a lot of attention in Japan. Aggregators will make contracts with customers with photovoltaic (PV) power systems and battery energy storage systems (BESSs) including electric vehicles (EVs) to participate in electricity markets. Aggregators might have to pay electricity supply‐demand imbalance charges when generated and consumed energies contracted at the day‐ahead supply‐demand market are different from those at the current day operation due to distribution network constraints such as voltage and power flow limitations. Therefore, the information on network constraints is very important for aggregators to determine their day‐ahead schedules. In this paper, we evaluated the relationship between aggregator supply‐demand schedules and the distribution system operation. It was assumed that the reverse power flow limitations due to network constraints are notified to the aggregators by distribution system operator (DSO). Two cases of the aggregators' schedules of PV systems and stationary BESSs were compared in the simulations. In addition, aggregator strategies for making adequate schedules were evaluated. [ABSTRACT FROM AUTHOR]

In future power systems with extremely large integration of photovoltaic (PV) generation, it is necessary to not only properly maintain supply–demand balance without power shortfall but also utilize as much PV energy as possible. The application of PV power forecast and energy storage devices to power system operation is necessary. In this study, we propose a method for determining and modifying the charging and discharging schedule of a battery energy storage system (BESS) and the unit commitment of thermal generators based on the PV power forecast. The proposed method is evaluated by numerical simulations for one year. The results show that both the energy shortfall and PV curtailment can be reduced by the proposed method. [ABSTRACT FROM AUTHOR]

SUMMARY The 2011 Tohoku earthquake had a great impact on Japanese energy policy. It is expected that nuclear power plants will be phased out and a large amount of generation from renewable energy sources will be installed. Attention is particularly focused on photovoltaic (PV) generation, technology in which Japan is superior, and a high price is set in the feed-in tariff policy, which started in 2012. However, large integration of PV into power grids may cause imbalances between power supply and demand. It will be indispensable to use PV power generation forecasts in economic-load dispatching control (EDC), so that the economics and reliability of power systems networks can be maintained. Thus, in the previous study, we proposed an EDC method with unit commitment (UC) based on the results provided by a day-ahead PV forecast. In this study, we evaluate the frequency and trend of shortfalls and surpluses of power due to error in forecasting PV power generation by numerical simulations using the power system model of the Kanto area in Japan. The results showed that shortfalls or surplus power occur not only due to overestimations or underestimations of PV power, but also due to the operating conditions of the power systems. [ABSTRACT FROM AUTHOR]