Cooperative game consistency optimal strategy of multi-microgrid system considering flexible load

ABSTRACT

In this paper, a cooperative game consistency optimal scheduling strategy for islanded multi-microgrid systems is proposed to solve the problem of energy mutualization and economic scheduling. Firstly, considering the power loss, flexible load demand, and other operating indicators, to maximize the user and supplier benefits, the real-time transaction electricity price model of the user side and the power supply side is constructed. On this basis, considering the energy sharing among microgrids and aiming at minimizing the operating cost of the multi-microgrid system, a multi-microgrid cooperative game optimization scheduling model is established. Then, the optimal solution of the cooperative game model is obtained by using the consensus algorithm of equal increment rate. The equivalence between the real-time transaction price of the user side and the power supply side and the transaction price on the microgrid is proven. The Shapley value method is used to complete the benefit distribution of each microgrid. Finally, the validity and reliability of the method are verified by an islanded multi-microgrid system. Simulation results show that when multiple microgrids are involved in a cooperative game, by optimizing the transaction electricity price among microgrids and the output of controllable distributed units, regulating and flexible load demand, energy sharing among microgrids can be achieved, and the overall operating costs of the alliance can be reduced. The total daily scheduling cost of cooperative game alliance is 1749 USD less than that of independent operation mode. Solving the cooperative game model by using an equal increment rate consensus algorithm allows the optimal global solutions to be obtained quickly, and the solution time is only 0.6 s, and effectively suppresses the negative effects of fluctuating or uncertain factors on the multi-microgrid system.

KEYWORDS:

• Islanded multi-microgrid system
• real-time transaction electricity price
• flexible load demand
• cooperative game
• consensus algorithm
• Shapley value method

Nomenclature

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Acknowledgments

This work was supported by the National Science Foundation of China (61364027) and the Natural Science Foundation of Guangxi (2019GXNSFAA185011).

Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Zhilin Lyu

Zhilin Lyu, Ph.D. degree, is a professor in College of Electrical Engineering at Guangxi University, Nanning, China. Her area of research is smart grid and complex system optimization and control.

Yongfa Lai

Yongfa Lai is currently pursuing the master’s degree in electrical engineering at Guangxi University, his research interests in smart grid and complex system optimization and control.

Xiao Yang

Xiao Yang is currently pursuing Ph.D. degree in electrical engineering at Huazhong University of Science and Technology, his research interests in artificial intelligence and power system.

Yuanzheng Li

Yuanzheng Li, Ph.D. degree, is a associate professor in School of Artificial Intelligence and Automation at Huazhong University of Science and Technology, Wuhan, China. His area of research is smart grid and microgrid optimization and operation.

Jiaqi Yi

Jiaqi Yi is currently pursuing the master’s degree in electrical engineering at Guangxi University, his research interests in smart grid and complex system optimization and control.