黄南天, 包佳瑞琦, 蔡国伟, 赵树野, 刘德宝, 王俊生, 王盼盼. 多主体联合投资微电网源–储多策略有限理性决策演化博弈容量规划[J]. 中国电机工程学报, 2020, 40(4): 1212-1225,1412. DOI: 10.13334/j.0258-8013.pcsee.190908
引用本文: 黄南天, 包佳瑞琦, 蔡国伟, 赵树野, 刘德宝, 王俊生, 王盼盼. 多主体联合投资微电网源–储多策略有限理性决策演化博弈容量规划[J]. 中国电机工程学报, 2020, 40(4): 1212-1225,1412. DOI: 10.13334/j.0258-8013.pcsee.190908
HUANG Nan-tian, BAO Jia-rui-qi, CAI Guo-wei, ZHAO Shu-ye, LIU De-bao, WANG Jun-sheng, WANG Pan-pan. Multi-agent Joint Investment Microgrid Source-storage Multi-strategy Bounded Rational Decision Evolution Game Capacity Planning[J]. Proceedings of the CSEE, 2020, 40(4): 1212-1225,1412. DOI: 10.13334/j.0258-8013.pcsee.190908
Citation: HUANG Nan-tian, BAO Jia-rui-qi, CAI Guo-wei, ZHAO Shu-ye, LIU De-bao, WANG Jun-sheng, WANG Pan-pan. Multi-agent Joint Investment Microgrid Source-storage Multi-strategy Bounded Rational Decision Evolution Game Capacity Planning[J]. Proceedings of the CSEE, 2020, 40(4): 1212-1225,1412. DOI: 10.13334/j.0258-8013.pcsee.190908

多主体联合投资微电网源–储多策略有限理性决策演化博弈容量规划

Multi-agent Joint Investment Microgrid Source-storage Multi-strategy Bounded Rational Decision Evolution Game Capacity Planning

  • 摘要: 针对多主体联合投资单一微电网源–储规划场景中难以平衡多投资主体利益冲突,以及传统博弈方法假设参与人完全理性的局限性,提出一种配电网运营商与微电网运营商联合投资的基于演化博弈微电网源–储容量规划新方法。首先,建立微电网系统及内部源、储模型,并结合峰谷电价确定含储能微电网运行策略。其次,以微电网运营商运行成本及内部经济收益,以及配电网运营商投资微电网成本、配电网网损、延缓配电网升级成本及售购电收益的总经济支付最小为目标,建立参与人支付函数模型。再次,从参与者、策略集、支付函数及复制者动态方程出发,建立计及参与人有限理性的多策略集演化博弈模型,并提出求解多策略集演化稳定策略的方法。最后,通过实际系统算例证明所提出的多策略集演化博弈微电网源–储规划策略的有效性。采用非博弈、传统博弈与演化博弈等不同场景开展对比实验,实验证明演化博弈方法在平衡微电网运营商与配电网运营商的收益方面具有更好的效果。

     

    Abstract: Aiming at the multi-agent joint investment in a single microgrid source-storage planning scenario, it is difficult to balance the conflicts of multiple investment subjects, and the traditional game theory assumes the limitations of participants’ complete rationality, and proposed a new method based on evolutionary game to plan the microgrid source-storage capacity with distribution network operators and microgrid operators jointly invested. Firstly, established a microgrid system and internal source and storage models, and combined the peak and valley electricity prices to determine the operation strategy of the microgrid containing energy storage. Secondly, with the operating costs and internal economic benefits of microgrid operators, as well as the total economic benefits of distribution grid operators investing in microgrid costs, distribution network losses, delaying distribution network upgrade costs and selling electricity revenues, established a multi-participant payment function model. Thirdly, based on the participants, the strategy set, payment function and the dynamic equation of the replicator, a multi-strategy evolutionary game model considering the bounded rationality of the participants was established, and a method for solving the multi-strategy evolutionary stability strategy was proposed. Finally, the effectiveness of the proposed multi-strategy evolutionary game microgrid source-storage planning strategy was illustrated by the actual system. Comparative experiments were carried out in different scenarios such as non-gaming, traditional game and evolutionary game. Experiments show that the evolutionary game method has better effects in balancing the benefits of microgrid operators and distribution network operators.

     

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