电力系统及其自动化学报2019，Vol.31Issue(10)：140-144,5.DOI:10.19635/j.cnki.csu-epsa.000165
改进鸟群算法在家电负荷分解中的应用
Application of Improved Bird Swarm Algorithm in Home Appliance Load Decomposition
摘要
Abstract
Load monitoring is an important part of intelligent electricity,and playing a vital role in energy conservation and emission reduction. Aiming at the problem of non-intrusive load monitoring in household electricity networks,a load decomposition method is proposed based on improved bird swarm algorithm(IBSA). Using this method,the low-frequency steady-state current obtained by a smart meter is selected as the load feature,and a mathematical optimiza-tion model for the relation between the total monitored current and the calculated value obtained by accumulating the current of each appliance is established. In addition,the bird swarm algorithm(BSA)is improved to calculate the time factor of each appliance. The analysis results of examples show that the proposed method can effectively identify the op-erating state of appliances and estimate the current of each appliance without adding the cost of measurement hardware, and can achieve the identification and simultaneous switching of multiple appliances with similar power range.关键词
非侵入式负荷监测/鸟群算法/负荷分解/低频稳态电流/时间系数Key words
non-intrusive load monitoring/bird swarm algorithm(BSA)/load decomposition/low-frequency steady-state current/time factor分类
信息技术与安全科学引用本文复制引用
王慧娟,杨文荣,杨庆新..改进鸟群算法在家电负荷分解中的应用[J].电力系统及其自动化学报,2019,31(10):140-144,5.基金项目
省部共建电工装备可靠性与智能化国家重点实验室(河北工业大学)自主课题基金资助项目(EERIZZ2018002) （河北工业大学）
