Resilience-oriented planning for microgrid clusters considering P2P energy trading and extreme events

Zheng Xu, Yue Chen, Linwei Sang, Haifeng Qiu, Zhi Wu and Hengqing Ye

Applied Energy, 2025, vol. 388, issue C, No S0306261925002909

Abstract: Multiple microgrids (MGs) can work more collaboratively and economically thanks to peer-to-peer (P2P) energy transactions. Nevertheless, the more frequent contingencies pose threats to the energy trading of multi-MGs, underscoring the need to strike a balance between economic efficiency and resilience. To safeguard the co-operational security of MG clusters, this paper proposes a resilience-oriented planning method considering extreme events and their destructive impacts on multi-agent energy trading. Firstly, a multi-agent resilient planning model is established, aiming at reducing the planning cost through collaborative energy sharing while ensuring the existence of alternative solutions under contingencies. Both the internal uncertainties of renewable energy sources and load variations and the external stochastic transaction disruptions are considered. To ensure the convexity and continuity of the model, it is proven that the complementary constraints of energy storage in both the normal and contingency conditions can be relaxed without introducing binary variables. Then, an incentive-driven P2P pricing strategy is devised by working on the dual of the social cost minimization problem. The equality and inequality coupling constraints among multi-stakeholders are decoupled in a distributed manner with limited information exchange. The convergence and optimality of the proposed distributed algorithm are supported with theoretical guarantees, and then it is solved efficiently by incorporating the scenario-decoupled column and constraint generation approach. Numerical experiments on island MG systems validate the efficacy and superiority of the proposed planning method, which is of great significance in improving multi-agent grid profitability and resilience.

Keywords: Resilient planning; Multi-agent microgrids; P2P trading; Extreme events; Distributed pricing strategy (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.apenergy.2025.125560

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