| 引用本文: | 薛美佳,熊小伏,杨 堤,汪 松.基于两阶段博弈的“资源-机组-平台”型虚拟电厂能源管理策略[J].电力系统保护与控制,2025,53(23):101-112.[点击复制] |
| XUE Meijia, XIONG Xiaofu, YANG Di, WANG Song.Energy management strategy for “resource-unit-platform” virtual power plants based on a two-stage game framework[J].Power System Protection and Control,2025,53(23):101-112[点击复制] |
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| 摘要: |
| 为提升分布式能源资源管理效率，响应电网差异化调控需求，解决风光出力不确定性带来的风险问题，首先提出“资源机组平台”型虚拟电厂能源管理架构，通过能源管理平台与虚拟机组代理商交互增强调度灵活性。其次，设计两阶段博弈策略。第一阶段构建平台与多虚拟机组主从博弈模型，平台根据代理商上报的电功率购售需求，结合配电网电价动态调整与虚拟机组的交易电价。第二阶段引入广义纳什谈判合作博弈，将运营问题转化为成本最小化与利益分配问题，揭示“配电网价格波动→平台调价→机组交易策略调整”的联动效应。最后依托 KKT条件及强对偶理论将双层优化转化为单层混合整数线性规划，并纳入条件风险价值平抑不确定性风险。所提架构与策略形成“外部基准引导→内部自主调节→风险协同控制”的联动机制，在多元资源协同优化、风险管控及经济效益提升方面具有显著优势。 |
| 关键词: 虚拟电厂 能源管理 主从博弈 广义纳什谈判合作博弈 条件风险价值 |
| DOI：10.19783/j.cnki.pspc.250124 |
| 投稿时间：2025-02-07修订日期：2025-09-10 |
| 基金项目:重庆市技术创新与应用发展专项重点项目资助(CSTB2024TIAD-KPX0088) |
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| Energy management strategy for “resource-unit-platform” virtual power plants based on a two-stage game framework |
| XUE Meijia1,XIONG Xiaofu1,YANG Di2,WANG Song2 |
| (1. State Key Laboratory of Power Transmission Equipment Technology (Chongqing University), Chongqing 400044, China;
2. Chongqing Huizhi Energy Co., Ltd., Chongqing 400044, China) |
| Abstract: |
| To enhance the management efficiency of distributed energy resources, meet differentiated grid control requirements, and mitigate risks caused by wind-solar output uncertainties, a “resource-unit-platform” virtual power plant (VPP) energy management architecture is first proposed. The architecture enhances scheduling flexibility through interactions between the energy management platform and virtual unit aggregators. Second, a two-stage game strategy is designed. In the first stage, a master-slave (Stackelberg) game model is established between the platform and multiple virtual units. The platform adjusts the transaction prices offered to the units based on the power purchase and sale requirements reported by the aggregators and the dynamic electricity price of the distribution network. In the second stage, a generalized Nash bargaining cooperation game is introduced to transform the operational issues into one of cost minimization and benefit allocation. This reveals the interdependent effects of “distribution grid price fluctuations → platform price adjustment → unit transaction strategy adjustment”. Finally, by applying the (KKT) conditions and strong duality theory, the bi-layer optimization is reformulated as a single-layer mixed-integer linear programming problem, and conditional value-at-risk (CVaR) is incorporated to mitigate uncertainty-related risks. The proposed architecture and strategy form a coordinated mechanism of “external benchmark guidance → internal autonomous regulation → joint risk control”, offering significantly advantages in multi-resource co-optimization, risk management, and economic performance improvement. |
| Key words: virtual power plant energy management Stackelberg game generalized Nash bargaining cooperative game conditional value-at-risk (CVaR) |
