可再生能源2025，Vol.43Issue(4)：542-551,10.
基于改进蝠鲼觅食优化算法的配电网储能选址定容研究
Research on site selection and capacity determination of energy storage in distribution network based on improved manta ray foraging optimization algorithm
摘要
Abstract
Energy storage has the characteristics of strong flexibility and fast response,which can effectively alleviate load fluctuations,voltage instability and other problems caused by new energy access.This paper proposes a double-layer power distribution based on an improved manta ray foraging optimization algorithm.The network energy storage site selection and capacity strategy aims to minimize energy storage investment costs,daily voltage fluctuations and daily load fluctuations,establish a two-layer site selection and capacity model,and introduce elite reverse learning strategies and adaptive tumbling factor improvements.The manta ray foraging optimization algorithm solution model was used,and the proposed method was simulated and verified using the connected new energy IEEE33 node distribution network as an example.The results showed that the proposed site selection and capacity optimization scheme can significantly reduce system voltage and load fluctuations,effectively reducing system investment costs.关键词
新能源/蝠鲼觅食优化算法/双层优化/精英反向学习策略Key words
new energy/manta ray foraging optimization algorithm/two-layer optimization/elite reverse learning strategy分类
能源科技引用本文复制引用
李亚飞,俞易涵,李展,邹启衡,黄颖,陈嘉栋,孟高军..基于改进蝠鲼觅食优化算法的配电网储能选址定容研究[J].可再生能源,2025,43(4):542-551,10.基金项目
国家自然科学基金项目(52377104). （52377104）
