文章摘要
考虑能量-功率双重价值的园区微电网多主体主从博弈
Optimal Scheduling of Multi-Agent Master-Slave Game in Park-Level Power Grids Considering Deep Exploration of Resource Energy-Power Value
投稿时间:2026-01-13  修订日期:2026-07-08
DOI:
中文关键词: 园区微电网  主从博弈  能量-功率协同  动态定价  二分法
英文关键词: park-level microgrid  master–slave game  energy–power coordination  dynamic pricing  bisection method
基金项目:国家重点研发计划(2024YFE0199400)
作者单位邮编
随权 郑州大学电气与信息工程学院 450001
曹文学* 三峡大学电气与新能源学院 443002
廖  伟 国网湖北省电力有限公司 
王秋杰 三峡大学电气与新能源学院 
刘  畅 长江勘测规划设计研究有限责任公司 
王仲源 三峡大学电气与新能源学院 
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中文摘要:
      针对园区微电网中多利益主体协同不足、可调负荷功率支撑价值挖掘不充分以及传统需求响应模型难以兼顾经济性、灵活性和用户满意度的问题,提出一种考虑能量-功率双重价值的园区微电网多主体主从博弈优化调度方法。首先,构建包含电能交易收益、功率支撑收益和外电网波动惩罚成本的能源运营商(Energy Producer, EP)运行模型;其次,面向热泵、水泵和电动汽车等可调负荷,建立兼顾电能量转移、正反向功率支撑和用户满意度的负荷聚合商(Load Aggregator, LA)运行模型。在此基础上,通过电能交易价格和正反向功率支撑价格引导柔性负荷响应,实现多主体利益协调与社会福利优化。针对模型中存在的非线性问题,采用线性化处理与二分迭代算法求解 Stackelberg 均衡。仿真结果表明,所提方法能够有效平抑功率波动、增强功率支撑能力,并在保障用户满意度的同时实现多主体收益的公平分配。与传统方案相比,该策略能够使得EP的收益提升1.14%,降低LA的成本降低7.59%,社会福利提升35.82%。所提策略可充分挖掘多主体资源潜力,在保障系统安全运行的同时提升了经济性与灵活性。
英文摘要:
      To address the issues of insufficient coordination among multiple stakeholders in park-level microgrids, inadequate exploitation of the power support value of flexible loads, and the difficulty of traditional demand response models in balancing economy, flexibility, and user satisfaction, a multi-agent Stackelberg game-based optimal scheduling method considering both energy and power values is proposed. First, an operation model for the Energy Producer (EP) is established, incorporating electricity trading revenue, power support revenue, and fluctuation penalty costs associated with the external grid. Then, for flexible loads including heat pumps, water pumps, and electric vehicles, a Load Aggregator (LA) operation model is developed, considering energy shifting, bidirec-tional power support, and user satisfaction simultaneously. On this basis, flexible load responses are guided through electricity trading prices and bidirectional power support prices, thereby achieving multi-agent benefit coordination and social welfare op-timization. To solve the nonlinear problem, linearization techniques and a bisection iterative algorithm are employed to obtain the Stackelberg equilibrium. Simulation results demonstrate that the proposed method can effectively smooth power fluctuations, enhance power support capability, and realize fair profit allocation among multiple agents while maintaining user satisfaction. Compared with conventional schemes, the proposed strategy increases the EP’s profit by 1.14%, reduces the LA’s cost by 7.59%, and improves social welfare by 35.82%. The proposed strategy fully exploits the resource potential of multiple agents, thereby enhancing both economic performance and operational flexibility while ensuring secure system operation.
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