考虑新能源消纳与储能参与调频的共享储能主从博弈鲁棒定价方法

doi:10.11930/j.issn.1004-9649.202301004

摘要/Abstract

摘要： 针对大规模储能应用交易机制不明确、投资成本难回收等问题，提出了一种共享储能的定价方法，建立了一种以共享储能运营商为领导者、风电场为跟从者的考虑储能参与调频的共享储能主从博弈分布鲁棒定价模型。上层以共享储能运营商盈利最大为目标，提出储能不仅可从风电场获利，还可参与系统调频获取收益。下层以风电场收益最大为目标，建立考虑风电不确定性的两阶段风电场分布鲁棒优化模型，第一阶段最大化基础场景的售电收益，第二阶段最小化不确定场景下风电场上网偏差惩罚成本期望。基于西北地区实际风电场运行数据设计算例并进行仿真分析。结果表明：共享储能运营商合理的定价策略，不仅有利于改善新能源场站调节能力，减少弃风，还可提高储能利用率，实现博弈双方的互利共赢。

关键词: 共享储能, 主从博弈, 分布鲁棒优化, 储能调频, 定价机制

Abstract: For the unclear trading mechanism of large-scale energy storage application and the difficulty in recovering investment costs, this paper proposes a pricing method for shared energy storage. A distributionally robust pricing model based on master-slave game for shared energy storage with shared energy storage operators as leaders and wind farms as followers considering energy storage participating in frequency modulation is built. The upper layer aims at maximizing the profit of shared energy storage operators. It is proposed that energy storage can not only benefit from wind farms but also obtain revenue by participating in system frequency modulation. The lower layer aims at maximizing the revenue of wind farms and builds a two-stage distributionally robust optimization model of wind farm considering the uncertainty of wind power. The first stage maximizes the revenue of electricity sales in the basic scenario, and the second stage minimizes the penalty cost expectation of wind farm grid deviation under uncertain scenarios. An example is designed and simulated based on the actual wind farm operation data in Northwest China. The results show that the reasonable pricing strategy of shared energy storage operators is not only conducive to improving the regulation capacity of new energy stations and reducing wind abandonment, but also increasing the utilization rate of energy storage and achieving mutual benefit and win-win results for both parties in the game.

Key words: shared energy storage, master-slave game, distributionally robust optimization, energy storage frequency modulation, pricing mechanism

齐彩娟, 车彬, 杨燕, 陈宝生. 考虑新能源消纳与储能参与调频的共享储能主从博弈鲁棒定价方法[J]. 中国电力, 2023, 56(8): 26-39.

QI Caijuan, CHE Bin, YANG Yan, CHEN Baosheng. Master-Slave Game-Based Robust Pricing Method of Shared Energy Storage Considering Renewable Energy Accommodation and Energy Storage Participating in Frequency Modulation[J]. Electric Power, 2023, 56(8): 26-39.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202301004

https://www.electricpower.com.cn/CN/Y2023/V56/I8/26

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