A Potential Game Approach to Distributed Operational Optimization for Microgrid Energy Management With Renewable Energy and Demand Response

作者：Zeng, Jun; Wang, Qiaoqiao; Liu, Junfeng^*; Chen, Jianlong; Chen, Haoyong

来源：IEEE Transactions on Industrial Electronics, 2019, 66(6): 4479-4489.

DOI：10.1109/TIE.2018.2864714

• Distributed operational optimization
• demand response
• energy management
• microgrid
• potential game
• renewable energy

In view of Internet of Energy, advanced operational optimization in microgrid energy management system (MEMS) is expected to be scalable to accommodate various participants, support plug-and-play, and optimize energy utilization. Based on potential game, this paper presents a fully distributed operational optimization for MEMS with high penetration of renewable energy and demand response. After analyzing the microgrid and potential game, the establishment and proof of an exact potential game model is presented in detail. Then the beststrategy-response iterative algorithm is proposed to find the game Nash equilibrium in a distributed way. Finally, the proposed approach is simulated in an islanded microgrid to verify its efficiency and feasibility. The significances of this paper are as follows. First, the scheme and algorithm are fully distributed. All heterogeneous individuals are treated as independent decision-making entities without a central coordinator/processor. Second, the optimization process is open and dynamic. The convergence is achieved with no limits to type or number of players, even if the process of execution is corrupted with delay or losses in communication information. Third, the consistency between individual rationality and overall importance is guaranteed, and individual best-strategy-response behaviors necessarily improve overall optimality.

• 出版日期2019-6
• 单位华南理工大学