基于二次分解平抑风电波动的混合储能系统容量配置  

Capacity Allocation of Hybrid Energy Storage System for Stabilizing Wind Power Fluctuations Through Twice Decomposition

作　　者：刘扬波 张熙 康龙云[1] 刘林 朱春生 黄晟 LIU Yangbo;ZHANG Xi;KANG Longyun;LIU Lin;ZHU Chunsheng;HUANG Sheng(School of Electric Power Engineering,South China University of Technology,Guangzhou 510640,China;Southern Offshore Wind Power Joint Development Co.,Ltd,Zhuhai 519080,China)

机构地区：[1]华南理工大学电力学院,广州510640 [2]南方海上风电联合开发有限公司,珠海519080

出　　处：《电力系统及其自动化学报》2024年第9期61-69,共9页Proceedings of the CSU-EPSA

基　　金：广东省重点领域研发计划资助项目(2021B0101230003)。

摘　　要：针对风电并网功率波动问题,提出基于二次分解的混合储能系统容量优化配置方案。首先,根据风电并网功率波动限值,对风电功率进行经验模态分解,并重构为并网参考功率和混合储能系统参考功率,以实现风功率整体平抑;其次,考虑到经验模态分解算法出现的模态混叠、端点效应加剧等问题,提出基于北方苍鹰优化-变分模态分解算法的混合储能系统内部功率分配策略;最后,建立平抑风电出力波动的混合储能容量优化配置模型,并基于K-均值聚类得到的典型日数据对建立的模型进行求解。算例分析表明,所提策略的优化配置方案能够有效平抑风电功率波动,满足风电并网功率波动的要求,减少混合储能系统成本。To address the issue of grid-connected wind power fluctuations,an optimized capacity allocation scheme for a hybrid energy storage system(HESS)based on twice decomposition is proposed in this paper.First,based on the fluc-tuation limits of grid-connected wind power,the wind power is decomposed and reconstructed into grid-connected refer-ence power and HESS reference power through empirical mode decomposition(EMD),thus achieving the overall stabi-lization of wind power.Second,considering the problems such as mode mixing and exacerbated endpoint effects associ-ated with the EMD algorithm,an internal power allocation strategy for HESS based on the northern goshawk optimiza-tion-variational mode decomposition(NGO-VMD)algorithm is put forward.Finally,an optimized capacity allocation model of HESS for stabilizing the fluctuations in wind power output is established,and it is solved by using the typical daily data obtained by K-means clustering.The analysis result of a case study demonstrates that under the proposed strategy,the optimized allocation scheme can effectively stabilize the wind power fluctuations,satisfy the requirements for grid-connected wind power fluctuations and reduce the costs of HESS.

关 键 词：风电功率波动 二次分解 北方苍鹰优化算法 K-均值 

分 类 号：TM614[电气工程—电力系统及自动化]