A Bi-level optimization-based community energy management system for optimal energy sharing and trading among peers

The economic and environmental benefits of renewable energy have increased in significance over the past decade. Local energy markets can play a vital role in energy transition by facilitating the rapid proliferation of renewable-based energy resources, thereby increasing the renewable energy hosting capacity of the power grid. This paper proposes an energy management system for a smart locality that facilitates local energy trading involving consumers with renewable energy units, a central storage facility, and a power grid. Two optimization frameworks for sharing surplus onsite produced energy are developed here. The first framework maximizes the combined revenue of sellers and buyers, while the second, a game theoretical model, maximizes consumer utilization at the lower level and the revenue of the common storage facility at the higher level. An intensive study is carried out to investigate the benefits of energy sharing that maximizes overall revenue. The results indicate that the grid pricing scheme is a major factor that determines the revenue sharing between the central storage facility entity and the consumers. The first framework results in optimal resource allocation, while the second framework concentrates only on revenue generation. Results indicate that the energy seller profits are higher if the real-time grid prices are used and if the consumers are not charged according to their willingness to pay. (c) 2020 Elsevier Ltd. All rights reserved.

Automated summary

This paper proposes an energy management system for a smart locality that facilitates local energy trading, and develops two optimization frameworks for optimal resource allocation and revenue maximization. The study finds that energy sharing can maximize overall revenue, and grid pricing scheme is a major factor in determining revenue sharing between entities.