基于产消者随机博弈决策的共享储能协同优化

doi:10.19799/j.cnki.2095-4239.2025.0054

储能科学与技术 ›› 2025, Vol. 14 ›› Issue (8): 3216-3228.doi: 10.19799/j.cnki.2095-4239.2025.0054

• 储能技术经济性分析 • 上一篇

基于产消者随机博弈决策的共享储能协同优化

张帅¹^,²(), 张涛³, 裴玮¹^,²(), 马腾飞¹^,², 肖浩¹^,², 施婕⁴, 何传鑫⁴

^1.中国科学院电工研究所，北京 100190
^2.中国科学院大学，北京 100049
^3.中电投融和新能源科技有限公司，上海 201702
^4.上海融和元储能源有限公司，上海 201306

收稿日期:2025-01-13 修回日期:2025-02-14 出版日期:2025-08-28 发布日期:2025-08-18
通讯作者: 裴玮 E-mail:zhangshuaiyoung@mail.iee.ac.cn;peiwei@mail.iee.ac.cn
作者简介:张帅（1996—），男，博士研究生，研究方向为博弈论及其在电能市场交易中的应用，E-mail：zhangshuaiyoung@mail.iee.ac.cn；
基金资助:
国家电网有限公司总部科技项目资助(5108-202218280A-2-233-XG)

Collaborative optimization of shared energy storage based on prosumers’ decision-making in a stochastic game framework

Shuai ZHANG¹^,²(), Tao ZHANG³, Wei PEI¹^,²(), Tengfei MA¹^,², Hao XIAO¹^,², Jie SHI⁴, Chuanxin HE⁴

^1.Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, China
^2.University of Chinese Academy of Sciences, Beijing 100049, China
^3.China Power Investment Ronghe New Energy Technology Co. , Ltd. , Shanghai 201702, China
^4.Shanghai Robestec Energy Co. , Ltd. , Shanghai 201306, China

Received:2025-01-13 Revised:2025-02-14 Online:2025-08-28 Published:2025-08-18
Contact: Wei PEI E-mail:zhangshuaiyoung@mail.iee.ac.cn;peiwei@mail.iee.ac.cn

摘要/Abstract

摘要：

随着共享储能运营模式的不断发展，其已逐渐成为促进产消者点对点交易、提高经济效益的重要手段。但是产消者之间交易行为的不确定性，以及与共享储能之间复杂的交互关系，增加了点对点交易及共享储能优化运行的难度。基于此，本工作提出了一种基于产消者随机博弈决策的共享储能协同优化方法。为应对多产消者交易互动中的强不确定性问题，以产消者经济效益最大化为目标，构建了基于随机博弈的产消者点对点交易决策模型。通过利用随机博弈中的Markov决策过程对产消者进行多阶段交易行为建模，降低了不确定性对点对点交易的影响。并结合供需比价格机制计算最优交易价格，优化交易策略。将优化后的产消者群体视作一个联盟，与共享储能进行交易，考虑共享储能的运行特点，进一步通过最大化经济效益优化共享储能的充放电策略，解决了产消者与共享储能之间的协同优化问题，进而实现双方经济效益的最大化。最后通过仿真验证，证明了本工作提出方法的有效性。

关键词: 随机博弈, 点对点交易, 共享储能, 协同优化, 供需比价格机制

Abstract:

The development of shared-energy-storage operations has gradually become a key approach for prosumers to promote peer-to-peer (P2P) energy trading and enhance economic benefits. However, the uncertainty in prosumers' transaction behaviors and their complex interactions with shared-energy-storage systems complicate the optimization of P2P trading and shared-energy-storage operations. To address this challenge, this study proposes a collaborative optimization method for shared energy storage based on prosumers' decision-making within a stochastic game framework. To manage the notable uncertainty in multiprosumer trading interactions and maximize prosumers' economic benefits, a P2P trading decision-making model grounded in stochastic game theory is developed. The model employs a Markov decision process to represent the multistage trading behaviors of prosumers within the stochastic game, thereby reducing the influence of uncertainty on P2P trading. The optimal trading price is determined by incorporating a supply-demand ratio pricing mechanism, enabling the optimization of trading strategies. The optimized prosumer group is treated as a coalition that trades with shared energy storage. By considering the operational characteristics of shared energy storage, the model further optimizes its charging and discharging strategies to maximize economic benefits. This collaborative optimization between prosumers and shared energy storage resolves the coordination problem, ultimately maximizing economic benefits for both parties. Based on the proposed model, simulations are conducted and compared with traditional noncooperative game methods. The simulation results validate the advantages of the proposed method.

Key words: stochastic game, peer-to-peer trading, shared energy storage, collaborative optimization, supply-demand ratio pricing mechanism

中图分类号:

TM 73

张帅, 张涛, 裴玮, 马腾飞, 肖浩, 施婕, 何传鑫. 基于产消者随机博弈决策的共享储能协同优化[J]. 储能科学与技术, 2025, 14(8): 3216-3228.

Shuai ZHANG, Tao ZHANG, Wei PEI, Tengfei MA, Hao XIAO, Jie SHI, Chuanxin HE. Collaborative optimization of shared energy storage based on prosumers’ decision-making in a stochastic game framework[J]. Energy Storage Science and Technology, 2025, 14(8): 3216-3228.

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产消者	非合作博弈/元	随机博弈/元	增长率/%
产消者1	38162.83	39528.04	3.58
产消者2	39909.36	40471.46	1.41
产消者3	41851.06	43156.33	3.12
产消者4	41492.36	42609.72	2.69

基于产消者随机博弈决策的共享储能协同优化

Collaborative optimization of shared energy storage based on prosumers’ decision-making in a stochastic game framework

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