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Rooftop solar panels paired with home‐scale batteries are increasingly popular in the residential area and they bring a fantastic opportunity to households, considered as prosumers, to make benefits from trading electricity. Unlike research in the literature, we consider the trading with technical influences of utility requirements: Volt‐Watt and Volt‐Var functions. As possible active power curtailments may occur and lead to economic losses to households, our work reveals how a home energy management system (HEMS) maximizes profit from trading energy with an aggregator and an electricity retailer. Appropriate optimization problems are formulated with technical constraints, these functions, and home appliances. HEMS responses are optimized in two phases. The first phase is for planning an optimal day‐ahead energy commitment to the aggregator with a consideration of the predicted power curtailments. On the day of operation, the second phase tries to follow the commitment by reoptimizing the responses in the real condition. Simulation of a practical power system shows that addressing these functions can mitigate power curtailment, reduce economic loss, and improve home profits. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

The increasing penetration of renewable energy sources, featured by intermittent outputs, emphasizes the investigation of the potential effects on frequency deviation in the normal operation and solving the associated problems. This paper proposes a method for assessing the impacts of forecast errors in wind and solar generation outputs on a unit commitment problem. An iterative process is used across different spinning reserve requirements until the hourly average and intrahour variation forecast errors in demand and renewable energy generation are fully compensated at the lowest cost. The process, containing time series simulations, is applied to various confidence levels of the forecasted renewable energy generation so that violations of the frequency limit will not occur in the normal operation. The effectiveness and applicability of the proposed method are well illustrated through a case study on the 2030 power system of the island of Hokkaido in Japan. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

The increasing number of rooftop solar panels and home‐scale batteries in residential areas enables an emerging energy market for homeowners to take part in. By optimizing the energy usage at home, the surplus amount can be exported to the grid for selling to intermediaries like aggregators at a higher price than a feed‐in tariff set by the government. Though not trading with the power utility, the resulting reverse power flow may cause the service voltage to increase and violate the set upper limit. To avoid this problem, the utility asks all grid‐connected inverters to reduce the reverse power by installing volt–watt functions. Unfortunately, this kind of function may reduce the profits of the homeowners since the exported energy cannot match the amount committed to the aggregator. Our research addresses this issue by proposing a double‐layer optimization for each home energy management system. The first layer optimizes the one‐day home energy usage with consideration of uncertainty in the predicted data of load and solar irradiance to estimate the highest home profit as possible. Then, the second layer tries to reduce the high reverse power with minimal impact on the profit found in the first layer. A simulation of a distribution system shows that the proposed method is able to flatten the power profile flowing reversely to the grid and reduce the drawbacks of volt–watt functions. Homeowners are recommended to practice the proposed method when trading the surplus energy. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]