电工技术学报  2021, Vol. 36 Issue (11): 2288-2297    DOI: 10.19595/j.cnki.1000-6753.tces.200622
电力系统与综合能源 |
电力系统负荷非侵入式监测方法研究
雷怡琴, 孙兆龙, 叶志浩, 武晓康
海军工程大学电气工程学院 武汉 430033
Research on Non-Invasive Load Monitoring Method in Power System
Lei Yiqin, Sun Zhaolong, Ye Zhihao, Wu Xiaokang
College of Electrical EngineeringNaval University of Engineering Wuhan 430033 China
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摘要 为了实现对电力系统负荷的高效监测,提出了针对其暂态与稳态工作状况的非侵入式监测方法。对于准确获得任意稳态时刻的负荷工作状态的问题,提出了基于自筛选的优化遗传算法(AOGA)的稳态监测模型,将电力参数模型转换为有功分量模型及无功分量模型,以此建立双目标函数,解决了由于高谐波电流影响小、求解参数少引起监测误差的问题。优化遗传算法构造了自筛选程序,将适应度相同的结果先做筛选,再利用欧氏距离对功率进行判别,解决了传统遗传算法(GA)进行负荷监测时由于适应度相同引起误判的缺陷。当负荷进行投切时,为了准确获得投切类型,该文建立了基于功率-时间(P-T)的暂态监测Matlab-Simulink模型,首先利用离散傅里叶分解的方法提取暂态发生前后功率的变化量,通过对比功率匹配度对动作负荷进行识别;在功率监测的基础上,以负荷的谐波含有率为负荷特征进行谐波特征判别,进一步提高了暂态负荷监测的精度。
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关键词 非侵入式自筛选优化遗传算法双目标函数P-T 模型谐波特征    
Abstract:In order to monitor the power system load efficiently, this paper proposes a non-invasive monitoring method for its transient and steady-state working conditions. In order to accurately obtain the load working state at any steady-state time, an automatic screening optimized genetic algorithm (AOGA) is proposed, steady-state monitoring model, which transforms the power parameter model into active component model and reactive power component model, establishes double objective function, and solves the problem of monitoring error caused by small influence of high harmonic current and less solving parameters. The AOGA algorithm constructs a self screening program, which filters the results with the same fitness first, and then uses Euclidean distance to judge the power, which solves the defect of misjudgment caused by the same fitness in traditional genetic algorithm (GA). When the load is switched on and off, in order to obtain the switching type accurately, this paper establishes a power-time(P-T) based on power time, In the Matlab/Simulink model of transient monitoring, the discrete Fourier decomposition method is used to extract the power change before and after the transient occurrence, and the action load is identified by comparing the power matching degree; on the basis of power monitoring, the harmonic characteristics are identified by taking the harmonic content of the load as the load characteristics, which further improves the accuracy of the transient load monitoring.
Key wordsNon-invasive    automatic screening optimized genetic algorithm    double objective function    P-T mode    harmonic characteristics   
收稿日期: 2020-06-09     
PACS: TM762  
通讯作者: 叶志浩,男,1975年生,教授,博士生导师,研究方向为电力系统分析设计与保护。E-mail:yxyx928@126.com   
作者简介: 雷怡琴,女,1996年生,硕士研究生,研究方向为电力电子与电气传动,电磁环境及防护技术。E-mail:786790332@qq.com
引用本文:   
雷怡琴, 孙兆龙, 叶志浩, 武晓康. 电力系统负荷非侵入式监测方法研究[J]. 电工技术学报, 2021, 36(11): 2288-2297. Lei Yiqin, Sun Zhaolong, Ye Zhihao, Wu Xiaokang. Research on Non-Invasive Load Monitoring Method in Power System. Transactions of China Electrotechnical Society, 2021, 36(11): 2288-2297.
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https://dgjsxb.ces-transaction.com/CN/10.19595/j.cnki.1000-6753.tces.200622          https://dgjsxb.ces-transaction.com/CN/Y2021/V36/I11/2288