Pricing strategy of shared energy storage and day-ahead optimization decision of park users based on Stackelberg game

张天雨; 王 罗; 孙 勇; 于 傲; 郑可迪; 郭鸿业; 陈启鑫

doi:10.3969/j.issn.1009-1831.2023.04.001

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Pricing strategy of shared energy storage and day-ahead optimization decision of park users based on Stackelberg game

更新时间：2026-03-05

- Pricing strategy of shared energy storage and day-ahead optimization decision of park users based on Stackelberg game
- Vol. 25, Issue 4, (2023)
- 作者机构：
  
  1. 清华大学电机工程与应用电子技术系,北京,100084
  2. 中国长江三峡集团有限公司,武汉,430010
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1009-1831.2023.04.001
  CLC：
- Published：2023
- 稿件说明：
移动端阅览
张天雨, 王罗, 孙勇, et al. Pricing strategy of shared energy storage and day-ahead optimization decision of park users based on Stackelberg game[J]. 2023, 25(4).
DOI：

张天雨, 王罗, 孙勇, et al. Pricing strategy of shared energy storage and day-ahead optimization decision of park users based on Stackelberg game[J]. 2023, 25(4). DOI： 10.3969/j.issn.1009-1831.2023.04.001.

摘要

针对目前用户自主投建储能成本过高和资源利用率不足的问题，可在园区引入共享储能，助力降低园区用户用电成本，并促进分布式可再生能源消纳。为实现共享储能服务商和园区用户的双赢，建立了共享储能服务商主导、园区用户跟随的主从博弈模型。共享储能服务商制定容量价格和功率价格，并利用条件风险价值（conditional value-at-risk，CVaR）评估光伏出力不确定性带来的收益风险；园区用户根据共享储能的价格及自身负荷和光伏出力预测，决策购买的储能容量和充放电功率策略。然后通解。最后，基于多用户多场景的算例，分析储能价格对博弈结果的影响，并对比购买共享储能与配置固定储能、不配置储能的经济性，论证了所提共享储能机制和优化决策模型的有效性。

Abstract

In view of the high cost and insufficient resource utilization of energy storage invested independently by users

the introduction of shared energy storage in the park is conducive to reducing the power cost of users in the park and promoting the consumption of distributed renewable energy. In order to achieve a win-win situation between shared energy storage service provider and park users

a Stackelberg game model in which shared energy storage service provider dominates and park users follow is established. The shared energy storage service provider sets the capacity price and power price and uses conditional value-at-risk to evaluate the income risk caused by the uncertainty of photovoltaic output. According to the price of shared energy storage and the forecast of their own load and photovoltaic output

park users decide the purchased energy storage capacity and charging and discharging power strategy. Through KKT optimality condition and the dual theorem of linear programming

the above Stackelberg game problems can be transformed into mixed integer linear programming problems. Finally

based on the example of multiuser and multi-scenario

the influence of energy storage price on the game result is analyzed

and the economy of shared energy storage is compared with that of fixed energy storage configuration and no energy storage confiodel.

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