电力系统保护与控制2025，Vol.53Issue(15)：59-70,12.DOI:10.19783/j.cnki.pspc.241419
基于CEEMDAN-SAOA的平抑风电波动混合储能系统定容优化配置
Capacity optimization of a hybrid energy storage system for wind power fluctuation suppression based on CEEMDAN-SAOA
摘要
Abstract
To address the problem of power fluctuations caused by direct grid connection of wind power,this paper proposes a capacity optimization algorithm based on improved Archimedes optimization algorithm with complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN).A weighted filtering algorithm,combining amplitude limiting and moving average,is used to smooth wind power output and reduce the lag in the smoothed signal,thus generating the reference power for grid-connected wind power and the hybrid energy storage system(HESS).To allocate HESS's internal power,the reference power is decomposed into high-and low-frequency components using CEEMDAN.Taking into account factors such as HESS power and capacity,state of charge(SOC),and load defect rate,a capacity optimization model aiming at the minimum annual comprehensive cost is constructed and solved by improved Archimedes optimization algorithm.Simulation analysis based on real case data shows that,compared with the original grid-connected wind power,the proposed HESS configuration scheme reduces power fluctuation by 13.538%and increases smoothness by 16.057%.Compared with the traditional single energy storage,the proposed method achieves better fluctuation mitigation and reduces the required capacity.Moreover,it lowers investment cost by 15.325%compared to the conventional Archimedes optimization algorithm.关键词
改进阿基米德算法/自适应噪声完全集合经验模态分解/风力发电/平抑功率波动/混合储能/容量配置Key words
improved Archimedes algorithm/complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)/wind power/power fluctuation suppression/hybrid energy storage/capacity allocation引用本文复制引用
黄冬梅,吴冰,时帅,李媛媛,宋巍,王晓亮..基于CEEMDAN-SAOA的平抑风电波动混合储能系统定容优化配置[J].电力系统保护与控制,2025,53(15):59-70,12.基金项目
This work is supported by the National Key Research and Development Program of China(No.2021YFC3101602). 国家重点研发计划项目资助(2021YFC3101602) （No.2021YFC3101602）
华能集团总部科技项目资助(HNKJ20-H66) （HNKJ20-H66）
