电器与能效管理技术 ›› 2020, Vol. 0 ›› Issue (10): 55-63.doi: 10.16628/j.cnki.2095-8188.2020.10.009

• 储能控制技术 • 上一篇    下一篇

混合储能参与风电集群一次调频的容量配置优化

刘颖明, 陈亮, 王晓东, 王瑛玮   

  1. 沈阳工业大学 电气工程学院,辽宁 沈阳 110870
  • 收稿日期:2020-05-19 出版日期:2020-10-30 发布日期:2020-11-24
  • 作者简介:刘颖明(1973—),男,高级工程师,博士,研究方向为广域风电集群控制策略、风储联合系统多时空尺度协调优化控制策略等。|陈 亮(1994—),男,硕士研究生,研究方向为风电机组/集群控制策略优化。|王晓东(1978—),男,教授,博士生导师,博士,主要研究方向为风电机组控制、大规模储能系统及其应用技术。
  • 基金资助:
    * 国家自然科学基金资助项目(51677121);辽宁省“兴辽英才项目”(XLYC1802041)

Mixed Energy Storage Participating in Capacity Optimization Configuration of Wind Power Primary Frequency Regulation

LIU Yingming, CHEN Liang, WANG Xiaodong, WANG Yingwei   

  1. College of Electrical Engineering,Shenyang University of Technology,Shenyang 110870,China
  • Received:2020-05-19 Online:2020-10-30 Published:2020-11-24

摘要:

风电集群(WFC)合理配备混合储能系统可以降低风电出力波动对电网频率影响、在改善风电可调度性的基础上提升WFC收益。以风功率备用联合储能系统共同参与一次调频为基础,以风储系统收益最大化为目标,建立了WFC加入混合储能收益最高的优化模型,采用不易陷入局部最优的鲸鱼算法进行求解,得到WFC备用比例与混合储能最优配置方案。分析了风电备用比例对WFC最大收益以及蓄电池容量配置的影响以及混合储能对蓄电池寿命的影响,对比了WFC和单独风电场优化结果。最后,以东北某WFC作为算例,验证了所提出方法能有效提高WFC收益。

关键词: 风电集群(WFC), 储能容量优化, 鲸鱼算法, 一次调频, 混合储能

Abstract:

Wind power schedulability and frequency stability can be improved with wind power clusters equipped with hybrid energy storage systems.This paper is based on wind power standby and hybrid energy storage system participating in one frequency modulation.The maximization of the revenue of the wind energy cluster combined hybrid energy storage system is as the target.The whale algorithm that is not easy to fall into the local optimal solution is used to solve it,and the wind power cluster standby ratio and the optimal configuration scheme of hybrid energy storage are obtained.The impact of the wind power reserve ratio on the maximum revenue of the wind power cluster and the battery capacity configuration and the impact of hybrid energy storage on the battery life are analyzed,and the optimization results of the wind power cluster and the individual wind farm are compared.Finally,a wind power cluster in Northeast China is taken as an example to verify the effectiveness of the proposed method.

Key words: wind power cluster(WFC), energy storage capacity optimization, whale algorithm, primary frequency regulation, hybrid energy storage

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