计算机应用研究2023，Vol.40Issue(12)：3636-3642,3654,8.DOI:10.19734/j.issn.1001-3695.2023.04.0156
基于多策略协同进化差分算法的社区居民负荷优化调度
Optimal scheduling of community residents load based on multi-strategy co-evolutionary differential algorithm
摘要
Abstract
Aiming at the problem of load dispatching under demand response,it is necessary to provide a response scheme to meet the interests of residents and improve the stability of power grid operation.This paper considered electricity price,incen-tive demand response mechanism and residential electricity demand,and established a multi-user load scheduling high-dimen-sional objective optimization model with the goal of minimizing electricity cost and community load variance.Combining with the characteristics of the model,this paper proposed a cooperative co-evolutionary differential evolution algorithm based on multi-strategy.It designed a hybrid coding and population initialization strategy based on the characteristics of residential electricity consumption to improve the quality of the solution.It introduced the idea of cooperative co-evolution to decompose the problem variables,and divided the population according to the high-dimensional target grouping and aggregation to avoid falling into lo-cal optimum.In the evolution of each sub-population,it adopted a double differential mode coordination strategy,and construc-ted knowledge transfer individuals to realize information interaction between populations.Finally,it retained the complete excel-lent solution to the external file through the population merging strategy combining greedy and random selection to improve the convergence and distribution of the Pareto optimal set.Simulation results show that the proposed method can reduce the elec-tricity cost of community residents by about 18％and the variance of load fluctuation by more than 30％.As the number of re-sidents increases,the convergence and diversity of the algorithm are more obvious than other algorithms in the same field.关键词
需求响应/负荷调度/合作协同进化/差分进化/目标分组Key words
demand respond/load scheduling/cooperative co-evolution/differential evolution/target clustering分类
信息技术与安全科学引用本文复制引用
李冰,王雷震,张佳,王素欣,张瑞友..基于多策略协同进化差分算法的社区居民负荷优化调度[J].计算机应用研究,2023,40(12):3636-3642,3654,8.基金项目
国家自然科学基金重点资助项目(71831006) （71831006）
