基于粒子群寻优的家电负荷有序使用策略研究  

Strategy research on ordinal use of home appliance load based on particle swarm optimization

作　　者：孙毅[1] 裴俊亦 崔高颖 SUN Yi;PEI Jun-yi;CUI Gao-ying(School of Electrical Engineering,North China Electric Power University,Beijing 102206,China;State Grid Jiangsu Electric Power Research Institute,Nanjing 210003,China)

机构地区：[1]华北电力大学电气与电子工程学院,北京102206 [2]国网江苏省电力公司电力科学研究院,江苏南京210003

出　　处：《电力科学与技术学报》2018年第2期20-26,共7页Journal of Electric Power Science And Technology

基　　金：国家重点研发计划(2016YFB0901104);国家自然科学基金(51307051);中央高校基本科研业务费专项资金(2014ZP03;2015ZD01)

摘　　要：随着智能家居的推广,不断增长家庭电力需求,引起电网容量不足,对用户用电安全提出新的挑战。建立有效的家庭负荷有序使用策略以降低电网负荷峰值,已经成为电力需求侧管理的重要内容。针对这一问题,考虑用户用电的起始时间、结束时间、用电时长等用电习惯,提出一种基于粒子群寻优的家电负荷有序使用策略。首先,建立家电负荷优先级函数的模型,描述调控对于用户满意度的影响;其次,通过主客观赋权法对优先级函数的子目标进行权重分配,并根据优先级函数制定优化目标;而后,通过随机权重策略的粒子群算法寻优求解。最后,通过实验仿真,验证了该方法在有效降低用户用电负荷峰值的同时,还能够保证用户的用电满意度。With the development of smart homes,the growing power demand causes a shortage of power grid capacity.This paper establishes an effective ordering strategy of appliance loads to reduce the peak load of grid on the basis of the particle swarm optimization.Firstly,the starting time,end time,power consumption duration and other power usage habits of user＇s power consumption are considered to construct a model of household load priority function which describes the impact of regulation on user satisfaction.Next,the sub-goals of priority function are weighted by subjective and objective weighting methods,and the optimization objectives are formulated according to the priority function.Finally,the optimal solution is obtained by the particle swarm optimization algorithm of random weighting strategy.An example is included to verify this strategy.It is shown that the method not only effectively reduce the peak of the user＇s electricity load,but also guarantee the user＇s electricity satisfaction.

关 键 词：智能家电 有序优化控制 优先级 降低峰值 用户满意度 粒子群 

分 类 号：TM71[电气工程—电力系统及自动化]