内蒙古电力技术2025，Vol.43Issue(4)：68-75,8.DOI:10.19929/j.cnki.nmgdljs.2025.0050
基于多种策略改进灰狼优化算法的分布式电源优化配置
Distributed Power Generation Optimization and Configuration Based on Improved Grey Wolf Optimization with Multiple Strategies
摘要
Abstract
The large-scale integration of distributed power sources at multiple points into the power grid is fundamentally changing the structure and operational characteristics of the grid.Improper site selection and capacity determination of distributed power sources can lead to a degradation in voltage quality and the occurrence of phenomena such as reverse power flow.To address the issue,a distributed power generation optimization configuration model is established with the goal of minimizing comprehensive costs,active power network losses,and the values of novel line voltage stability index.The traditional grey wolf optimization(GWO)algorithm is improved through best point set,nonlinear cosine convergence factor,and distribution estimation strategies.Case studies are conducted using the IEEE 33-node distribution network,revealing that the integration of distributed generation leads to reduce operation costs,significant reductions in line losses,and improvements in grid voltage stability.Thus,the case studies validate that the improved grey wolf optimization(IGWO)algorithm,compared to the traditional GWO algorithm and other optimization algorithms,demonstrates superior advantages in site selection and capacity determination for distributed generations.关键词
分布式电源/配电网/电压稳定/灰狼优化算法/选址定容Key words
distributed power generation/distribution network/voltage stability/grey wolf optimization algorithm/site selection and capacity determination分类
信息技术与安全科学引用本文复制引用
陈天宇,李升..基于多种策略改进灰狼优化算法的分布式电源优化配置[J].内蒙古电力技术,2025,43(4):68-75,8.基金项目
江苏省级产教融合型品牌专业建设项目"智能电网信息工程"(苏教办高函[2023]16号) （苏教办高函[2023]16号）
南京工程学院研究生创新训练计划项目"基于改进算法的配电网电压稳定分析控制"(TB202417048) （TB202417048）
