基于NILM的污染源监测方法应用初探
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引用本文:刘春蕾1,庞鹏飞1,石纹赫1,胡伟俊2,戚 军2.基于NILM的污染源监测方法应用初探[J].计算技术与自动化,2022,(4):149-156
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刘春蕾1,庞鹏飞1,石纹赫1,胡伟俊2,戚 军2 (1. 国网河北省电力有限公司保定供电分公司河北 保定 071000
2. 浙江工业大学信息工程学院浙江 杭州 310023) 
中文摘要:鉴于现有污染源监测技术易于作弊的问题,提出了一种基于非侵入式负荷监测(NILM)的新型污染源监测方法,通过实时监测企业入户电力线路获取排污设备和治污设备启停信息。首先,对采集到的线路电压和电流信号进行小波去噪,然后,设计了基于最小二乘预测法的设备投切事件检测方法,最后,提出相位和频率矫正来提高设备负荷特征提取精度。BLUED数据库仿真以及实际工程应用结果表明:基于NILM技术的污染源监测方法能以较高的速度和精度检测出设备投切事件和负荷特征,同时具备较高的抗干扰能力和较低的实现难度,推广应用前景广阔。
中文关键词:NILM  污染源监测  小波滤波  最小二乘预测法  相位矫正  频率矫正
 
Exploration on Application of NILM Based on Pollution Source Monitoring Method
Abstract:In view of the easy cheating problem of existing pollution source monitoring technology, a new pollution source monitoring technology based on non-intrusive load monitoring(NILM) is proposed to obtain the information of sewage equipment and pollution control equipment by monitoring the power lines of corporates in real time. First, wavelet denoising is performed on the collected line voltage and current signals. Then, an equipment start-stop event detection method based on the least-square prediction method is designed. Finally, the phase correction and frequency correction are proposed to improve the extraction accuracy of load features. Results from BLUED database simulation and actual engineering application show that the proposed pollution source monitoring method based on NILM technology can detect equipment start-stop events and load characteristics with high speed and precision, meanwhile it has high anti-jamming ability and low difficulty of realization, so as broad prospects for popularization and application.
keywords:NILM  pollution source monitoring  wavelet denosing  least square prediction method  phase correction  frequency correction
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