Optimal Scheduling with Potential Game of Community Microgrids Considering Multiple Uncertainties

Qiang Luo, Chong Gao, Junxiao Zhang, Qingbin Zeng, Yingqi Yi () and Chaohui Huang
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Qiang Luo: Power Grid Planning Research Center, Guangdong Power Grid Co., Ltd., Guangzhou 510080, China
Chong Gao: Power Grid Planning Research Center, Guangdong Power Grid Co., Ltd., Guangzhou 510080, China
Junxiao Zhang: Power Grid Planning Research Center, Guangdong Power Grid Co., Ltd., Guangzhou 510080, China
Qingbin Zeng: Guangzhou Power Electrical Technology Co., Ltd., Guangzhou 510635, China
Yingqi Yi: School of Electric Power, South China University of Technology, Guangzhou 510641, China
Chaohui Huang: Guangzhou Power Electrical Technology Co., Ltd., Guangzhou 510635, China

Energies, 2025, vol. 18, issue 16, 1-17

Abstract: As the global carbon neutrality process accelerates, the proportion of distributed power sources such as wind power and photovoltaic power continues to increase. This transformation, while promoting the development of clean energy, also brings about the issue of new energy consumption. As wind and solar distributed generation rapidly expands into modern power grids, consumption issues become increasingly prominent. In this paper, a robust optimal scheduling method considering multiple uncertainties is proposed for community microgrids containing multiple renewable energy sources based on potential games. Firstly, the flexible loads of community microgrids are quantitatively classified into four categories, namely critical base loads, shiftable loads, power-adjustable loads, and dispersible loads, and a stochastic model is established for the wind power and load power; secondly, the user’s comprehensive electricity consumption satisfaction is included in the operator’s scheduling considerations, and the user’s demand is quantified by constructing a comprehensive satisfaction function that includes comfort indicators and economic indicators. Further, the flexible load-response expectation uncertainty and renewable generation uncertainty model are used to establish a robust optimization uncertainty set. This set portrays the worst-case scenario. Based on this, a two-stage robust optimization framework is designed: with the dual objectives of minimizing operator cost and maximizing user satisfaction, a potential game model is introduced to achieve a Nash equilibrium between the interests of the operator and the users, and solved by a column and constraint generation algorithm. Finally, the rationality and effectiveness of the proposed method are verified through examples, and the results show that after optimization, the cost dropped from CNY 2843.5 to CNY 1730.8, a reduction of 39.1%, but the user satisfaction with electricity usage increased to over 98%.

Keywords: community microgrids; multiple uncertainties; robust optimization; potential game; load comfort level (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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