基于改进哈里斯鹰优化算法的微电网多目标优化调度  

Multi-Objective Optimal Scheduling of Microgrid Based on Improved Harris Hawks Optimization Algorithm

作　　者：王鑫 李升[1] WANG Xin;LI Sheng(School of Electric Power Engineering(School of Shenguorong),Nanjing Institute of Technology,Nanjing 211167,Jiangsu Province,China)

机构地区：[1]南京工程学院电力工程学院(沈国荣学院),江苏省南京市211167

出　　处：《分布式能源》2025年第1期91-100,共10页Distributed Energy

基　　金：江苏省级产教融合型品牌专业建设项目(苏教办高函[2023]16号)。

摘　　要：针对新能源发电接入以及考虑需求响应背景下的微电网优化调度问题,建立微电网模型;以考虑需求响应带来的用户用电不舒适度和系统的运行成本构建目标函数,调整用户可转移负荷。根据风光出力具有的随机性、波动性等特点,采用模糊K-means算法对风光出力数据进行聚类,得到典型的风光出力曲线。对哈里斯鹰优化(Harris hawks optimization,HHO)算法种群分布不均以及易陷入局部最优的问题进行改进:首先,在初始化种群阶段引入Tent映射,使得初始种群覆盖更全面,避免在早期陷入局部最优解;然后,在搜索阶段引入Levy飞行函数,增强算法的全局搜索能力,再将改进哈里斯鹰优化(improved HHO,IHHO)算法应用于寻优,并将其与经典算法进行对比。最终结果验证了所提策略的有效性以及IHHO算法的优越性。A microgrid model is established to address the optimization and scheduling of microgrid in the context of new energy generation access and demand response.The objective function is constructed to consider the user′s electricity discomfort caused by demand response and the operating cost of the system,and the user′s transferable load is adjusted.Based on the randomness and volatility of wind and solar power output,the fuzzy K-means algorithm is used to cluster the wind and solar power output data and obtain typical wind and solar power output curves.Next,this paper improves the Harris hawks optimization(HHO)algorithm to address the issues of uneven population distribution and susceptibility to local optima.Firstly,Tent mapping is introduced in the initialization stage of the population to make the initial population coverage more comprehensive and avoid falling into local optima in the early stage.Then,Levy flight function is introduced in the search stage to enhance the global search ability of the algorithm.Finally,improved HHO(IHHO)algorithm is applied to optimization and compared with classical algorithms.The final results validate the effectiveness of the proposed strategy and the superiority of the IHHO algorithm.

关 键 词：微电网 需求响应 改进哈里斯鹰优化(IHHO)算法 Levy飞行 优化调度 

分 类 号：TK01[动力工程及工程热物理] TM73[电气工程—电力系统及自动化]