尾部风险驱动的储能运营商与多微网协同博弈调度

付文龙; 陈静波; 文子豪; 张鑫; 胡文涛; 孙晓娇

doi:10.19799/j.cnki.2095-4239.2026.0463

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尾部风险驱动的储能运营商与多微网协同博弈调度

储能技术经济性分析 | 更新时间：2026-10-22

- 尾部风险驱动的储能运营商与多微网协同博弈调度
- Tail-risk-driven coordinated stackelberg game scheduling between energy storage operator and multi-microgrids
- 储能科学与技术 2026年15卷第10期页码：4204-4215
- 作者机构：
  
  1.三峡大学电气工程学院，湖北宜昌 443002
  2.梯级水电站运行与控制湖北省重点实验室（三峡大学），湖北宜昌 443002
- 作者简介：
  
  付文龙（1988—），男，博士，副教授，研究方向为新能源发电系统综合建模与新能源发电预测，E-mail：ctgu_fuwenlong@126.com。
- 基金信息：
  
  梯级水电站运行与控制湖北省重点实验室开放基金(2025KJX05)
- DOI：10.19799/j.cnki.2095-4239.2026.0463
  中图分类号： TM 73
- 收稿：2026-05-27，
  
  修回：2026-08-12，
  
  纸质出版：2026-10-28
- 稿件说明：
移动端阅览
付文龙, 陈静波, 文子豪, 等. 尾部风险驱动的储能运营商与多微网协同博弈调度[J]. 储能科学与技术, 2026, 15(10): 4204-4215.

FU Wenlong, CHEN Jingbo, WEN Zihao, et al. Tail-risk-driven coordinated stackelberg game scheduling between energy storage operator and multi-microgrids[J]. Energy Storage Science and Technology, 2026, 15(10): 4204-4215.
付文龙, 陈静波, 文子豪, 等. 尾部风险驱动的储能运营商与多微网协同博弈调度[J]. 储能科学与技术, 2026, 15(10): 4204-4215. DOI： 10.19799/j.cnki.2095-4239.2026.0463.

FU Wenlong, CHEN Jingbo, WEN Zihao, et al. Tail-risk-driven coordinated stackelberg game scheduling between energy storage operator and multi-microgrids[J]. Energy Storage Science and Technology, 2026, 15(10): 4204-4215. DOI： 10.19799/j.cnki.2095-4239.2026.0463.

摘要

随着分布式新能源规模化接入，新型电力系统运行正由传统确定性调度向高不确定性调度转变。为增强系统在极端新能源波动场景下的韧性，并提高储能资源配置效率，本研究提出一种尾部风险驱动的储能运营商与多微网协同博弈调度策略。首先，基于多微网净出力构建多维综合风险代理指标，并引入条件风险价值一致性校准机制生成尾部风险保持型典型场景集。其次，建立共享储能运营商与多微电网主从博弈模型，上层在条件风险约束下，以最大化共享储能运营商效益为目标制定调度策略；下层多微网通过内部功率互济、储能容量租赁及充放电策略响应上层价格信号；最终，采用粒子群优化算法与CPLEX求解器相结合求解模型。本研究的算例仿真结果表明，所提方法能够有效表征新能源出力不确定性的尾部风险特征，在有限经济代价下抑制联络线功率波动；同时与各微电网独立配置储能模式相比，协同调度模式下多微电网的储能容量与功率配置需求分别降低约10%和8%，多微网侧综合成本降低5439元，实现储能资源配置规模与利用效率的协同优化。

Abstract

With the large-scale integration of distributed renewable energy

the operation of new power systems is shifting from traditional deterministic scheduling to scheduling under high uncertainty. To enhance system resilience under extreme renewable energy fluctuation scenarios and improve the allocation efficiency of energy storage resources

this paper proposes a tail-risk-driven coordinated Stackelberg game scheduling strategy between an energy storage operator and multiple microgrids (MMG). First

a multidimensional comprehensive risk proxy index is constructed based on the net output of the multi-microgrids

and a conditional value-at-risk (CVaR) consistency calibration mechanism is introduced to generate typical scenarios with tail-risk preservation. Second

a Stackelberg game model between the shared energy storage operator and the multi-microgrids is established. At the upper level

CVaR constraints are considered

and the scheduling strategy is formulated with the objective of maximizing the benefit of the shared energy storage operator. At the lower level

the multi-microgrids respond to upper-level price signals through internal power mutual support

energy storage capacity leasing

and charging/discharging strategies. Finally

the model is solved by combining particle swarm optimization with the CPLEX solver. The simulation results of the examples in this paper show that the proposed method can effectively characterize the tail-risk features of renewable energy output uncertainty and suppress tie-line power fluctuations at a limited economic cost. Compared with the independent energy storage configuration mode of each microgrid

the coordinated scheduling mode reduces the energy storage capacity and power configuration requirements of the multi-microgrids by approximately 10% and 8%

respectively

and reduces the MMG-side comprehensive cost by 5439 yuan

thereby achieving coordinated optimization of energy storage configuration scale and utilization efficiency.

关键词

Keywords

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