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Day-ahead optimal peer-to-peer energy trading strategy for multi-microgrids based on Nash bargaining game with data-driven chance constraints by Boyu Chen; Yanbo Che; Yue Zhou; Shuaijun Zhao is a Engineering article available to read on EtoBox.

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This paper proposes an optimization model to obtain the day-ahead optimal peer-to-peer (P2P) trading strategy for multi-microgrids (MMG). Firstly, a joint economic energy and reserve scheduling model of a microgrid (MG) is established while considering specific network constraints. Then, to mitigate the impact of renewable energy and load forecasting errors, chance constraints are introduced for the reserve capacity and buses voltage limitations of an individual microgrid. Additionally, a versatile distribution method is adopted to capture the probability distribution of uncertain variables in a data-driven manner, avoiding any prior assumptions. Finally, Nash bargaining theory is employed to deal with the P2P energy trading problem among MMG. The problem is equivalently transformed into two sequential subproblems for solving. Moreover, the alternating direction method of multipliers algorithm is used to solve the subproblems in a distributed manner for privacy concerns. The proposed model not only enables effective P2P energy trading for MMG, but also ensures compliance with the internal network constraints of each MG. Furthermore, the scheduling strategy exhibits robustness in ha

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Author

Boyu Chen; Yanbo Che; Yue Zhou; Shuaijun Zhao

Publisher

Elsevier BV

Published

2023

Language

EN

Field

Engineering (Physical Sciences)