Operation Mechanism of Shared Energy Storage for Renewable Energy Station Clusters Under Asymmetric Information

LIU Shuangshuo; LI Xiaozhu; LI Jianlin; YIN Chunya; WANG Hailong

doi:10.7500/AEPS20250804007

English Version Journal Login

您当前的位置：

首页 >

文章列表页 >

Operation Mechanism of Shared Energy Storage for Renewable Energy Station Clusters Under Asymmetric Information

Engineering Application | 更新时间：2026-10-12

- Operation Mechanism of Shared Energy Storage for Renewable Energy Station Clusters Under Asymmetric Information
- Automation of Electric Power Systems Vol. 50, Pages: 201-212(2026)
- 作者机构：
  
  1.可再生能源发电与并网技术教育部工程研究中心（新疆大学），新疆维吾尔自治区乌鲁木齐市 830047
  2.国家能源用户侧储能创新研发中心（北方工业大学），北京市 100144
  3.北京海博思创科技股份有限公司，北京市 100094
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China(52307108);Beijing Natural Science Foundation(L242008)
- DOI：10.7500/AEPS20250804007
  CLC：
- Received：04 August 2025，
  
  Revised：2026-01-30，
  
  Online First：20 May 2026，
  
  Published：25 November 2026
- 稿件说明：
移动端阅览
刘双硕,李笑竹,李建林等.不对称信息下的新能源场站群共享储能运营机制[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20250804007.

LIU Shuangshuo,LI Xiaozhu,LI Jianlin,et al.Operation Mechanism of Shared Energy Storage for Renewable Energy Station Clusters Under Asymmetric Information[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20250804007.
刘双硕,李笑竹,李建林等.不对称信息下的新能源场站群共享储能运营机制[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20250804007. DOI：

LIU Shuangshuo,LI Xiaozhu,LI Jianlin,et al.Operation Mechanism of Shared Energy Storage for Renewable Energy Station Clusters Under Asymmetric Information[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20250804007. DOI：

摘要

随着新能源场站强制配储政策的取消，集中式共享储能成为降低投资成本、提升消纳效率的重要手段。然而，新能源场站与共享储能之间存在信息不对称，导致利益分配冲突，传统博弈方法难以有效协调私有信息。为此，提出一种不对称信息下新能源场站群与共享储能的运营机制，构建“声明-决策-优化-学习”四阶段动态博弈框架。在该框架中，新能源场站基于自身类型选择策略，储能运营商通过观测场站行为，利用贝叶斯更新动态推断其真实类型，并调整定价与实施惩罚，以实现类型识别与激励相容。针对高、低波动二值离散类型场景的仿真结果表明，所提方法能有效缓解信息不对称导致的利益偏差；高波动场站租赁价格较低波动场站高7%，体现了风险溢价；贝叶斯更新对场站真实类型的识别准确率稳定在95%以上；与完全信息博弈相比，运营商收益提升7%，动态投资回收期缩短1.6年。该研究为多主体协同的共享储能系统优化提供了新理论与方法支撑。

Abstract

With the abolition of the mandatory energy storage allocation policy for renewable energy stations

centralized shared energy storage has become a vital measure to reduce investment costs and improve accommodation efficiency. Nevertheless

information asymmetry exists between renewable energy stations and shared energy storage

which leads to conflicts in benefit distribution. Traditional game methods struggle to effectively coordinate private information. To this end

an operation mechanism of renewable energy station clusters and shared energy storage under asymmetric information is proposed

and a four-stage dynamic game framework of “declaration-decision-optimization-learning” is constructed. Within this framework

renewable energy stations select strategies based on their own types. By observing the behaviors of the stations

the energy storage operator dynamically infers their true types via Bayesian updating

and adjusts pricing and imposes penalties to realize type identification and incentive compatibility. Simulation results under the binary discrete-type scenario of high and low volatility show that the proposed method can effectively mitigate benefit deviations caused by information asymmetry. The leasing price for high-volatility stations is 7% higher than that for low-volatility stations

reflecting the risk premium. The identification accuracy of the true station types through Bayesian updating remains stably above 95%. Compared with the complete-information game

the operator’s revenue increases by 7%

and the dynamic payback period is shortened by 1.6 years. This study provides new theoretical and methodological support for the optimization of multi-agent collaborative shared energy storage systems.

关键词

Keywords

references

李江林 . 新能源基地多能互补协调控制关键技术探讨［J］. 电气时代， 2025 （ 1 ）： 38 - 41 .

Li Jianglin . Discussion on key technologies of multi-energy complementary coordinated control in new energy base ［J］. Electric Age ， 2025 （ 1 ）： 38 - 41 .

叶青 . 我国共享储能从试点示范走向产业化［N］. 科技日报， 2024-04-12 （6）.

Ye Qing . Shared energy storage in China： from pilot demonstration to industrialization ［N］. Science and Technology Daily ， 2024-04-12 （6）.

徐辉，谭振龙 . 以自调度模式破解新能源配储“建而不用”难题［J］. 中国电力企业管理， 2024 （ 34 ）： 55 - 59 .

Xu Hui ， Tan Zhenlong . Solving the problem of “building but not using” new energy distribution and storage by self-dispatching mode ［J］. China Power Enterprise Management ， 2024 （ 34 ）： 55 - 59 .

孙英聪，陈来军，李笑竹，等 . 考虑资源相关性的新能源场站群集中式共享储能优化配置［J］. 太阳能学报， 2024 ， 45 （ 7 ）： 2 - 9 .

Sun Yingcong ， Chen Laijun ， Li Xiaozhu ， et al . Optimal allocation of centralized shared energy storage for renewable energy station clusters with consideration of resource correlation ［J］. Acta Energiae Solaris Sinica ， 2024 ， 45 （ 7 ）： 2 - 9 .

陈昌铭，章天晗，沈子康，等 . 新型电力系统的发用电侧共享储能商业模式研究综述［J］. 电力系统自动化， 2025 ， 49 （ 15 ）： 20 - 42 .

Chen Changming ， Zhang Tianhan ， Shen Zikang ， et al . Review of shared energy storage business modes on generation and user sides in new power systems ［J］. Automation of Electric Power Systems ， 2025 ， 49 （ 15 ）： 20 - 42 .

杨昶兴，李笑竹，陈来军，等 . 计及联盟合作成本的新能源场站共享储能优化配置策略［J］. 电网技术， 2025 ， 49 （ 4 ）： 1403 - 1412 .

Yang Changxing ， Li Xiaozhu ， Chen Laijun ， et al . Energy storage allocation strategy for renewable energy generation station clusters co-build and share considering the cost of alliance cooperation ［J］. Power System Technology ， 2025 ， 49 （ 4 ）： 1403 - 1412 .

高芊芊，山雨琦，朱晓荣 . 基于合作博弈的共享混合储能电站规划［J］. 太阳能学报， 2024 ， 45 （ 12 ）： 509 - 519 .

Gao Qianqian ， Shan Yuqi ， Zhu Xiaorong . Planning of shared hybrid energy storage power station based on cooperative game ［J］. Acta Energiae Solaris Sinica ， 2024 ， 45 （ 12 ）： 509 - 519 .

郝艺博，杜锡力，李笑竹，等 . 考虑储能性能差异的新能源场站群共享储能交易模式［J］. 发电技术， 2022 ， 43 （ 5 ）： 687 - 697 .

Hao Yibo ， Du Xili ， Li Xiaozhu ， et al . Shared energy storage trading mode of new energy station group considering energy storage performance difference ［J］. Power Generation Technology ， 2022 ， 43 （ 5 ）： 687 - 697 .

荀汉龙，刘杨，金旭冉，等 . 考虑新能源场站闲置储能的储能电站两阶段配置优化研究［J］. 浙江电力， 2024 ， 43 （ 9 ）： 49 - 57 .

Xun Hanlong ， Liu Yang ， Jin Xuran ， et al . Research on two-stage configuration optimization of energy storage power station considering idle energy storage in new energy stations ［J］. Zhejiang Electric Power ， 2024 ， 43 （ 9 ）： 49 - 57 .

Lan Z ， Hu J H ， Fang X ， et al . Risk-based optimization for facilitating the leasing services of shared energy storage among renewable energy stations ［J］. Frontiers in Energy Research ， 2023 ， 11 ： 1286045 .

He Y ， Xiao J W ， Wang Y W ， et al . Subjective-uncertainty-oriented dynamic renting framework for energy storage sharing ［J］. Applied Energy ， 2025 ， 378 ： 124765 .

Han J P ， Fang Y C ， Li Y W ， et al . Optimal planning of multi-microgrid system with shared energy storage based on capacity leasing and energy sharing ［J］. IEEE Transactions on Smart Grid ， 2025 ， 16 （ 1 ）： 16 - 31 .

Liu J C ， Song Y N . Multi-objective configuration optimization model of shared energy storage on the power side ［J］. Journal of Energy Storage ， 2025 ， 114 ： 115706 .

樊建军，吴春潮，左东明，等 . 基于主从博弈模型的新能源消纳均衡控制技术研究［J］. 电子设计工程， 2025 ， 33 （ 4 ）： 82 - 85 .

Fan Jianjun ， Wu Chunchao ， Zuo Dongming ， et al . Research on the balanced control technology of new energy consumption based on the master-slave game model ［J］. Electronic Design Engineering ， 2025 ， 33 （ 4 ）： 82 - 85 .

Li C P ， Liu Y ， Li J H ， et al . Research on the optimal configuration method of shared energy storage basing on cooperative game in wind farms ［J］. Energy Reports ， 2024 ， 12 ： 3700 - 3710 .

喻颖倩，何川，刘天琪，等 . 计及储能调频与寿命损耗的多套餐共享储能主从博弈分布鲁棒定价方法研究［J］. 中国电机工程学报， 2025 ， 45 （ 4 ）： 1450 - 1464 .

Yu Yingqian ， He Chuan ， Liu Tianqi ， et al . Research on robust pricing method of shared energy storage multi-package master-slave game distributed robust considering energy storage frequency modulation and life loss ［J］. Proceedings of the CSEE ， 2025 ， 45 （ 4 ）： 1450 - 1464 .

Li J H ， Zhao Z Z ， Wang X L ， et al . Optimized configuration of shared energy storage in renewable energy power plants considering multiple master-slave game pricing modes ［J］. Journal of Energy Storage ， 2025 ， 115 ： 116012 .

袁国淳，车彬，何川，等 . 考虑主从博弈多套餐定价与分布鲁棒机会约束的新能源共享储能优化配置［J］. 电网技术， 2026 ， 50 （ 3 ）： 1102 - 1114 .

Yuan Guochun ， Che Bin ， He Chuan ， et al . Research on optimal allocation of renewable energy sharing storage considering multi-package pricing of master-slave game and opportunity constraint of distributed robust ［J］. Power System Technology ， 2026 ， 50 （ 3 ）： 1102 - 1114 .

马楠，刘国伟，吴杰康，等 . 租赁市场中储能容量配置双层鲁棒优化模型［J］. 电网技术， 2025 ， 49 （ 2 ）： 653 - 665 .

Ma Nan ， Liu Guowei ， Wu Jiekang ， et al . A double-layer robust optimization model for energy storage capacity allocation in the leasing market ［J］. Power System Technology ， 2025 ， 49 （ 2 ）： 653 - 665 .

王国英，王成福，牛远方，等 . 含产消者租赁共享储能的主动配电网协同优化决策［J］. 电力系统自动化， 2025 ， 49 （ 1 ）： 105 - 116 .

Wang Guoying ， Wang Chengfu ， Niu Yuanfang ， et al . Cooperative optimal decision-making for active distribution network with shared energy storage leased by prosumers ［J］. Automation of Electric Power Systems ， 2025 ， 49 （ 1 ）： 105 - 116 .

Akerlof G A . The market for “lemons”： quality uncertainty and the market mechanism ［J］. The Quarterly Journal of Economics ， 1970 ， 84 （ 3 ）： 488 .

Harsanyi J C . Games with incomplete information played by “Bayesian” players： part Ⅰ the basic model ［J］. Management Science ， 1967 ， 14 （ 3 ）： 159 - 182 .

Spence M . Job market signaling ［J］. The Quarterly Journal of Economics ， 1973 ， 87 （ 3 ）： 355 .

Li J ， Wu X T ， Li T . Demand response management of smart grid based on Bayesian Stackelberg game approach ［J］. Journal of Systems Science and Complexity ， 2026 ， 39 （ 4 ）： 1477 - 1496 .

Huang B X . Rolling optimization method of virtual power plant demand response based on Bayesian Stackelberg game ［J］. Energy Informatics ， 2025 ， 8 ： 46 .

白雪，武昭原，韩晓男，等 . 考虑多元盈利模式的新能源基地共享储能优化配置［J］. 现代电力， 2025 ， 42 （ 3 ）： 601 - 613 .

Bai Xue ， Wu Zhaoyuan ， Han Xiaonan ， et al . Optimal configuration of sharing energy storage in new energy bases considering diversified business models ［J］. Modern Electric Power ， 2025 ， 42 （ 3 ）： 601 - 613 .

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Shared Energy Storage Service Mechanism Based on Time-slot Capacity Leasing and Energy Trading

Optimal Allocation Method for Centralized Backup Energy Storage of Data Center Clusters Under Shared Framework

Optimal Capacity Allocation of Electricity-Hydrogen Shared Energy Storage for Regional Integrated Energy Systems

Data-driven Distributionally Robust Optimization and Operation Method for Active Distribution Networks Based on Kolmogorov-Arnold Networks

International Experiences and Insights from Market-based Balancing Mechanisms for Power Systems

Related Author

TIAN Xin

CHEN Laijun

SUN Yingcong

WANG Chuan

MEI Shengwei

LI Bingle

YE Chengjin

DING Yi

Related Institution

College of Energy and Electrical Engineering, Qinghai University

Department of Electrical Engineering, Tsinghua University

Guizhou Power Grid Co., Ltd.

College of Electrical Engineering, Zhejiang University

School of Electrical Engineering, Southwest Jiaotong University

AI问答

⁰