| 引用本文: | 李晓露,王嘉信,柳劲松,等.考虑多重不确定性的虚拟电厂多主体协同交易优化策略[J].电力系统保护与控制,2025,53(21):133-145.[点击复制] |
| LI Xiaolu,WANG Jiaxin,LIU Jinsong,et al.Multi-stakeholder collaborative trading optimization strategy for virtual power plants considering multiple uncertainties[J].Power System Protection and Control,2025,53(21):133-145[点击复制] |
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| 摘要: |
| 随着新型电力系统建设的推进，虚拟电厂已成为分布式能源参与电力市场交易的重要手段。然而，新能源出力及电力市场价格的不确定性将导致虚拟电厂各利益主体决策空间的耦合性更为复杂，为虚拟电厂的优化运行带来极大挑战。为此，提出考虑多重不确定性的虚拟电厂多主体协同交易优化策略。首先，构造基于Wasserstein距离的虚拟电厂多主体协同交易分布鲁棒模型，并采用分布鲁棒机会约束表征新能源出力的不确定性，通过强对偶理论和最恶劣下界法对模型进行重构。其次，建立多主体协同交易的广义纳什均衡模型，通过驻点法定义博弈的均衡状态，结合线性化技术将其转化为混合整数线性规划问题。最后，算例结果表明所提协同交易优化策略在兼顾经济性与保守性的前提下，能够有效保障虚拟电厂各利益主体的合理收益。 |
| 关键词: 虚拟电厂 不确定性 分布鲁棒机会约束 协同交易 广义纳什均衡 |
| DOI：10.19783/j.cnki.pspc.241742 |
| 投稿时间：2024-12-27修订日期：2025-04-13 |
| 基金项目:国家自然科学基金项目资助(51977127) |
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| Multi-stakeholder collaborative trading optimization strategy for virtual power plants considering multiple uncertainties |
| LI Xiaolu1,WANG Jiaxin1,LIU Jinsong2,LIN Shunfu1 |
| (1. College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China;
2. State Grid Shanghai Electric Power Research Institute, Shanghai 200437, China) |
| Abstract: |
| With the rapid development of new power systems, virtual power plants (VPPs) have become a significant technical approach for integrating large-scale distributed energy resources into electricity market transactions. However, the uncertainties in renewable energy output and electricity market prices increase the coupling complexity of decision spaces among various stakeholders within a VPP, posing significant challenges to its optimal operation. To address this, a multi-stakeholder collaborative trading optimization strategy for VPPs considering multiple uncertainties is proposed. First, the distributionally robust optimization model for multi-stakeholder collaborative trading is constructed based on the Wasserstein distance. The uncertainties of renewable energy output are represented through distributionally robust chance constraints, and the model is restructured using strong duality theory and the worst-case lower-bound method. Then, a generalized Nash equilibrium model for multi-stakeholder collaborative trading is established. By defining the equilibrium state of the game through a stationary point method and applying linearization techniques, the problem is transformed into a mixed-integer linear programming formulation. Finally, numerical results demonstrate that the proposed collaborative trading optimization strategy effectively ensures reasonable profits for all stakeholders in the VPP while balancing economic efficiency and conservatism. |
| Key words: virtual power plant uncertainty distributionally robust chance constraint collaborative trading generalized Nash equilibrium |
