综合智慧能源

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基于双层交易模型的独立新型储能参与现货-调频市场协同优化策略

郭秉霖, 张竞宇, 臧启勇   

  1. 山东电力工程咨询院有限公司, 山东 中国
    华北电力大学,
  • 收稿日期:2025-07-29 修回日期:2025-08-08
  • 基金资助:
    国家磁约束核聚变能发展研究专项(2019YFE03110000、2019YFE03110003); 国家电力投资集团2025年度科技项目(042500105290)

Collaborative optimization strategy of independent new energy storage participating in spot-frequency regulation market based on two-tier trading model

  1. , , China
    , ,
  • Received:2025-07-29 Revised:2025-08-08
  • Supported by:
    National Special Research Projects for the Development of Magnetic(2019YFE03110000、2019YFE03110003)

摘要: 储能作为具备灵活调节与快速响应特性的单一技术类新型经营主体,可同时参与电能量与调频等多市场交易。针对现有模型统筹性不足的问题,本文构建了储能协同参与电能量与调频市场的双层优化模型:上层以收益最大化为目标,优化其投标与出力策略;下层模拟市场出清,以最小化系统购电成本。通过引入互补松弛条件与强对偶理论,实现模型向混合整数线性规划的转化,兼顾可解性与扩展性。基于IEEE 30节点系统的仿真结果显示,该策略可使系统购电成本降低约5.8%,储能收益提升超20%,有效提升了资源配置效率与主体经济性。该模型可为储能等新型主体参与多市场交易提供决策支持与机制参考。

关键词: 储能系统, 多市场交易, 双层优化模型, 混合整数线性规划, 市场出清

Abstract: As a new type of business entity with flexible regulation and rapid response characteristics, energy storage can participate in multiple market transactions such as electric energy and frequency regulation at the same time. In view of the lack of coordination in existing models, this paper constructs a two-layer optimization model for energy storage to participate in the electric energy and frequency regulation market: the upper layer optimizes its bidding and output strategies with the goal of maximizing revenue; the lower layer simulates market clearing to minimize the system's electricity purchase cost. By introducing complementary relaxation conditions and strong duality theory, the model is transformed into mixed integer linear programming, taking into account both solvability and scalability. The simulation results based on the IEEE 30-node system show that this strategy can reduce the system's electricity purchase cost by about 5.8%, increase energy storage revenue by more than 20%, and effectively improve resource allocation efficiency and subject economy. This model can provide decision support and mechanism reference for new entities such as energy storage to participate in multi-market transactions.

Key words: Energy storage system, multi-market trading, two-level optimization model, mixed integer linear programming, market clearing