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<p>In remote areas where clean resources are abundant but regulatory resources are scarce, constructing hybrid pumped storage power plants and forming virtual power plants (VPPs) by aggregating wind and water can enhance the profitability of clean energy. Based on this, we propose a two-layer optimization model for cooperative day-ahead bidding among multiple VPPs, considering hydraulic coupling. In the outer layer, the market clearing results are optimized using participant bidding information, with the goal of maximizing social welfare. The inner layer, which comprises the multi-watershed VPP alliance, optimizes the alliance’s bidding strategy based on market clearing results to enhance market revenue by addressing the uncertainty of wind and photovoltaic power output, the hydraulic coupling characteristics of the watersheds, cooperatively optimizing the regulatory resources within individual VPPs and among multi-watershed VPPs, and realizing the spatiotemporal transfer of water resources. Furthermore, to ensure fairness in revenue distribution among the VPPs, we propose an improved Shapley value allocation that takes hydraulic coupling and water resource contribution degree into account. The Karush–Kuhn–Tucker (KKT) method is adopted to solve the transformation of the two-layer model. The case study results indicate that the VPP alliance significantly increased the cleared energy during peak load periods under the cooperative bidding mode, with growth of 30.92&#xa0;MW&#xa0;h in summer and 31.41&#xa0;MW&#xa0;h in winter. The total revenue improved by up to 78.07%, verifying the effectiveness and economic efficiency of the proposed model and promoting the efficient participation of clean energy in the energy market in remote areas.</p>

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Cooperative game bidding model for multiple virtual power plants considering hydraulic coupling

  • 期刊论文

  • 发表日期：

    2026年7月19日

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  • Xiaodong Yu,
  • Xu Ling,
  • Qiuting Guo,
  • Jianghui Xi,
  • Xiongguang Zhao

摘要

In remote areas where clean resources are abundant but regulatory resources are scarce, constructing hybrid pumped storage power plants and forming virtual power plants (VPPs) by aggregating wind and water can enhance the profitability of clean energy. Based on this, we propose a two-layer optimization model for cooperative day-ahead bidding among multiple VPPs, considering hydraulic coupling. In the outer layer, the market clearing results are optimized using participant bidding information, with the goal of maximizing social welfare. The inner layer, which comprises the multi-watershed VPP alliance, optimizes the alliance’s bidding strategy based on market clearing results to enhance market revenue by addressing the uncertainty of wind and photovoltaic power output, the hydraulic coupling characteristics of the watersheds, cooperatively optimizing the regulatory resources within individual VPPs and among multi-watershed VPPs, and realizing the spatiotemporal transfer of water resources. Furthermore, to ensure fairness in revenue distribution among the VPPs, we propose an improved Shapley value allocation that takes hydraulic coupling and water resource contribution degree into account. The Karush–Kuhn–Tucker (KKT) method is adopted to solve the transformation of the two-layer model. The case study results indicate that the VPP alliance significantly increased the cleared energy during peak load periods under the cooperative bidding mode, with growth of 30.92 MW h in summer and 31.41 MW h in winter. The total revenue improved by up to 78.07%, verifying the effectiveness and economic efficiency of the proposed model and promoting the efficient participation of clean energy in the energy market in remote areas.