电器与能效管理技术 ›› 2021, Vol. 0 ›› Issue (4): 85-93.doi: 10.16628/j.cnki.2095-8188.2021.04.016

• 储能技术 • 上一篇    下一篇

基于双层规划的电网侧储能配置算法研究

吴昌龙1, 罗华伟1, 秦正斌1, 禹海峰2, 徐志强2   

  1. 1.湖南经研电力设计有限公司, 湖南 长沙 410000
    2.规模化电池储能应用技术湖南省工程研究中心, 湖南 长沙 410000
  • 收稿日期:2020-12-24 出版日期:2021-04-30 发布日期:2021-05-14
  • 作者简介:吴昌龙(1988—),男,工程师,主要从事电网规划及电源接入系统研究。|罗华伟(1983—),男,高级工程师,主要从事电网规划及电源接入系统研究。|秦正斌(1987—),男,工程师,主要从事电网规划及电源接入系统研究。

Analysis of Grid-Side Energy Storage Configuration Strategy Based on Bi-Level Programming

WU Changlong1, LUO Huawei1, QIN Zhengbin1, YU Haifeng2, XU Zhiqiang2   

  1. 1. Hunan Jingyan Electric Power Design Co.,Ltd.,Changsha 410000,China
    2. Hunan Engineering Research Center of Large-Scale Battery Energy Storage Application Technoligy,Changsha 410000,China
  • Received:2020-12-24 Online:2021-04-30 Published:2021-05-14

摘要:

提出了考虑储能经济性,兼顾运行最佳策略的电网侧储能双层规划配置模型。上层经济性评估模型分析了电网侧储能系统替代发输配电及无功设备投资和参与调频辅助服务市场补偿等效益,以全寿命周期净效益最大为优化目标,对储能配置规模进行优化。下层运行模型以削峰填谷效果最佳为优化目标,对储能系统运行功率曲线进行优化。对基于自适应变异的粒子群优化算法进行双层迭代求解,对电网侧储能最佳配置结果进行寻优,算例分析结果表明优化粒子群算法有较好的寻优能力,双层策略可以实现削峰最佳,同时综合效益达到最大化。

关键词: 电网侧储能, 储能配置, 双层规划, 经济运行, 粒子群优化

Abstract:

A bi-level programming configuration model for grid-side energy storage considering the economics of energy storage and the best operation strategy was proposed.The upper-layer economic evaluation model calculates the full life cycle cost of the energy storage system and analyzes its benefits in replacing T&D,the investment in reactive power equipment and the compensation of participating in market for FM auxiliary services on the grid side,taking the maximum profit as the upper-layer goal to optimize the scale of energy storage allocation.The lower-layer operation model takes the best peak shaving and valley filling effect as the optimization objective through optimizing the operation power curve of the energy storage system.The particle swarm optimization algorithm based on adaptive mutation is used to solve the bi-level iterative solution and optimize the optimal energy storage configuration on the grid side.The analysis results of the calculation examples show that the optimized particle swarm optimization algorithm has better optimization ability,and the bi-level strategy can achieve the best peak clipping and the maximum comprehensive benefit.

Key words: grid side storage, energy storage configuration, bi-level programming, economic operation, particle swarm optimization

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