湖南电力 ›› 2026, Vol. 46 ›› Issue (1): 142-149.doi: 10.3969/j.issn.1008-0198.2026.01.019

• 电力规划与市场 • 上一篇    下一篇

考虑机会成本的储能多场景竞价投标策略

郎益涛1, 黄美珑1, 吴沂林1, 刘心刚1, 徐铮2, 沈非凡2, 张冀2   

  1. 1.中电建新能源集团股份有限公司山东分公司,山东 济南 250000;
    2.湖南大学电气与信息工程学院,湖南 长沙 410082
  • 收稿日期:2025-10-17 修回日期:2025-11-24 出版日期:2026-02-25 发布日期:2026-03-10
  • 通信作者: 徐铮(2002),男,研究生在读,研究方向为储能优化调度和电力市场运行。
  • 作者简介:郎益涛(1976),男,本科,高级工程师,研究方向为市场趋势与需求、项目开发与投资、成本控制与效益提升。黄美珑(2001),女,本科,研究方向为新能源发电技术、储能技术、智能运维技术。吴沂林(2001),男,大专,研究方向为新能源发电技术、储能技术、数字化管理平台建设。刘心刚(1980),男,硕士,高级工程师,研究方向为市场趋势与需求分析、新能源行业标准、商业模式创新。沈非凡(1992),男,工学博士,副教授,研究方向为风电场优化运行与控制、主动配电网优化运行与控制等。张冀(1988),男,副教授,研究方向为高效热管理系统、先进热储技术及新能源发电系统优化。
  • 基金资助:
    中电建新能源集团股份有限公司重点项目(2024-011)

Research on Bidding Strategy for Energy Storage in Multiple Scenarios Considering Opportunity Cost

LANG Yitao1, HUANG Meilong1, WU Yilin1, LIU Xingang1, XU Zheng2, SHEN Feifan2, ZHANG Ji2   

  1. 1. Shandong Branch of Power China New Energy Group Co., Ltd., Jinan 250000, China;
    2. College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
  • Received:2025-10-17 Revised:2025-11-24 Online:2026-02-25 Published:2026-03-10

摘要: 针对储能参与多市场竞价时对机会成本考虑不足、限制资源分配效率的问题,提出一种考虑机会成本的储能联合竞价策略。首先,基于山东省电力现货市场机制,分析储能参与电能量和调频辅助服务市场的交易模式及机会成本的量化方法。在此基础上,构建以独立储能为上层领导者、交易中心为下层跟随者的主从博弈双层优化模型。上层模型以储能综合收益最大化为目标,下层模型以电力市场出清成本最小化为目标。将混合整数非线性双层模型通过KKT条件和大M法转化为可求解的混合整数线性规划模型,并利用专业求解器进行求解。算例分析结果表明,所提策略能够有效量化机会成本对竞价决策的影响,优化储能在多市场中的资源分配,显著提升储能的经济效益。该策略为高比例可再生能源电力系统中储能的市场化运营提供了理论和技术支持。

关键词: 储能系统, 电力市场, 机会成本, 主从博弈, 双层优化

Abstract: To adress the issues of insufficient consideration of opportunity costs and limited resource allocation efficiency when energy storage participates in multi-market bidding, a joint bidding strategy for energy storage considering opportunity costs is proposed. Firstly, based on the spot market mechanism of Shandong Province's power system, the transaction mode for energy storage participating in the electricity energy and frequency regulation auxiliary service markets and quantification method of opportunity costs are analyzed. On this basis, a leader-follower game bilevel optimization model with independent energy storage as the upper-level leader and the trading center as the lower-level follower is constructed. The upper model aims to maximize the comprehensive revenue of energy storage, while the lower model aims to minimize the clearing cost of the power market. By combining the KKT conditions and the big M method, the mixed-integer nonlinear bilevel model is transformed into a solvable mixed-integer linear programming model, and a professional solver is used for solution. The case study results show that the proposed strategy can effectively quantify the impact of opportunity costs on bidding decisions, optimize the resource allocation of energy storage in multiple markets, and significantly improve the economic benefits of energy storage. This strategy provides theoretical and technical support for the market-oriented operation of energy storage in power systems with high proportions of renewable energy.

Key words: energy storage system, power market, opportunity cost, leader-follower game, bilevel optimization

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