Peer-to-Peer transactive energy trading of multiple microgrids considering renewable energy uncertainty

• Published in: International journal of electrical power & energy systems 2023-10, Vol.152, p.109235, Article 109235
• Main Authors: Yan, Xingyu, Song, Meng, Cao, Jiacheng, Gao, Ciwei, Jing, Xinyi, Xia, Shiwei, Ban, Mingfei
• Format: Article
• Language: English
• Subjects: Distributed energy resources; Distributionally robust optimization; Microgrid; Peer-to-peer transactive energy trading; Renewable energy uncertainty
• ISSN: 0142-0615; 1879-3517
• DOI: 10.1016/j.ijepes.2023.109235

•the distributionally robust optimization method is adopted for renewable uncertainty.•an alternating direction method of multipliers algorithm is used for privacy protection.•peer-to-peer transactive energy trading improves the profit of microgrids.•the network transmission cost will encourage the electricity transactions nearby. Distributed renewable energy requires market-based measures to remain competitive as subsidies are phased out. However, the intermittence and volatility of renewable energy power generation lead to great challenges in decision-making. To address the uncertainty issues induced by inaccurate RE forecast, this paper proposed a peer-to-peer transactive energy trading strategy for multiple microgrids based on distributionally robust optimization. First, an uncertainty fuzzy set based on Wasserstein distance is created for the renewable energy prediction errors in each microgrid. Second, a day-ahead microgrids peer-to-peer transactive energy trading model is proposed based on the distributionally robust optimization theory to address the power fluctuation problems of renewable energy. Third, using the dual theory, the proposed nonlinear model is addressed by transforming it into a linear and convex programming problem. Considering the independence of microgrids, a distributed strategy based on the alternating direction method of multipliers is then developed to preserve their privacy. Finally, the case study proves that the method proposed can increase the income of microgrids containing renewable energy through peer-to-peer transactions, protect the privacy of microgrids, and then promote the development of renewable energy. The distributionally robust optimization approach also guarantees the economy and reliability of the transaction results for real-time deployment.