考虑主从博弈定价模式的共享储能分布鲁棒优化配置方法研究

doi:10.11930/j.issn.1004-9649.202307016

摘要/Abstract

摘要：

“碳达峰、碳中和”目标和新型电力系统构建促进新能源不断发展，对于储能设施提出更高需求。在此背景下，在对风电场进行储能配置时，考虑定价机制下利用共享经济模式对储能进行配置优化，并探讨计及风电出力不确定性对储能配置方案的影响。首先，基于主从博弈制定价格，提出一种以共享储能运营商为领导者，以各风电场为跟随者，并最大化各主体利润的共享储能优化配置模型；然后，针对风电出力波动，引入基于矩信息的分布鲁棒优化方法构建机会约束以描述不确定性，采用矩信息完善模糊集以降低模型保守性，通过切比雪夫不等式将各风电场模型重构为混合整数二阶锥规划模型以便求解；最后，通过中国西北地区某实际风电场数据进行算例分析，结果表明，所提优化配置模型能够减少冗余投资，促进储能参与配置并应对实际风电波动。

关键词: 共享储能, 储能配置, 主从博弈, 分布鲁棒优化, 储能服务定价

Abstract:

The goals of carbon peaking and carbon neutrality and the construction of new power system have promoted the continuous development of new energy resources, while bringing along higher demands for energy storage. When configuring energy storage for wind farms in the power system, the shared economic model is used to optimize the configuration of energy storage with consideration of the pricing mechanism, and the impact of wind generation uncertainty on the energy storage configuration scheme is discussed. Firstly, based on the Stackelberg game for determining the price, a shared energy storage optimal configuration model is proposed, in which the shared energy storage operator is the leader, wind farms are the followers, and the profit of each participant is maximized. Then, to address the fluctuations of wind power output, a moment information-based distributionally robust optimization method is introduced to construct chance constraints to describe uncertainties, where the moment information is used to complete the ambiguity set to reduce the conservatism. The wind farm model is reconstructed into a mixed integer second-order cone programming model through Chebyshev inequality for solution. Finally, case studies are conducted based on the actual wind farm data in Ningxia, and the results show that the proposed optimal configuration model can reduce redundant investment, promote energy storage to participate in configuration and address the actual wind power generation fluctuations.

Key words: shared energy storage, energy storage configuration, Stackelberg game, distributionally robust optimization, energy storage service pricing

齐彩娟, 陈宝生, 韦冬妮, 杨钊. 考虑主从博弈定价模式的共享储能分布鲁棒优化配置方法研究[J]. 中国电力, 2024, 57(7): 40-53.

Caijuan QI, Baosheng CHEN, Dongni WEI, Zhao YANG. Distributionally Robust Optimal Configuration for Shared Energy Storage Based on Stackelberg Game Pricing Model[J]. Electric Power, 2024, 57(7): 40-53.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202307016

https://www.electricpower.com.cn/CN/Y2024/V57/I7/40

图/表 16

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参数		数值
最小、最大容量/(MW·h)		0、20
最小、最大充放电功率/MW		0、15.56
充放电效率		0.85
单位容量投建成本/(元·(kW·h)^–1)		336.332
单位日运维成本/(元·MW^–1)		26

参数		数值
最小、最大容量/(MW·h)		0、20
最小、最大充放电功率/MW		0、15.56
充放电效率		0.85
单位容量投建成本/(元·(kW·h)^–1)		336.332
单位日运维成本/(元·MW^–1)		26

算例	利润
算例	风电场1	风电场2	风电场3	风电场总体	共享储能运营商
1	12.1552	21.3678	11.7902	45.3132
2	12.5197	21.7712	12.4249	46.7158	2.3236
3	12.4191	21.7425	12.1984	46.3600	2.5698

算例	利润
算例	风电场1	风电场2	风电场3	风电场总体	共享储能运营商
1	12.1552	21.3678	11.7902	45.3132
2	12.5197	21.7712	12.4249	46.7158	2.3236
3	12.4191	21.7425	12.1984	46.3600	2.5698

风电场	储能投建成本	储能运维成本	向电网		惩罚成本	总利润
风电场	储能投建成本	储能运维成本	购电成本	售电收入	惩罚成本	总利润
1	0.4717	0.0843	0.7117	13.4229	0	12.1552
2	0.4717	0.0633	0.5469	22.4497	0	21.3678
3	0.8554	0.1238	0.9507	13.7201	0	11.7902
总体	1.7988	0.2714	2.2093	49.5927	0	45.3132