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Feature Selection of Non-intrusive Load Monitoring System Using STFT and Wavelet Transform

机译:基于STFT和小波变换的非侵入式负荷监测系统的特征选择

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This paper proposes a concept of non-intrusive load monitoring system for smart meter to monitor the situation of loads. In this study, the user can clearly know the power consumption of loads by observing the operation and time of use of loads, and then improve the habit of consumption to complete the goals of saving energy and reducing carbon. This paper employs a scheme of non-intrusive load monitoring system by extracting the significant and representative power signatures of voltage and current at utility service entry in identifying loads and analyzing the characteristics of loads, and then finds out the physical behavior of operation of loads to establish the model of loads. This paper uses short-time Fourier transform (STFT) and wavelet transform (WT) of time-frequency domain to analyze and compare different loads in the experiments. In the experiments, the results reveal wavelet transform is better than STFT on transient analysis of loads. Choice of power signatures affects the results of load recognition and computation time.
机译:提出了一种用于智能电表的非侵入式负荷监测系统的概念,用以监测负荷情况。在这项研究中,用户可以通过观察负载的运行和使用时间来清楚地了解负载的功耗,然后改善消费习惯,以实现节能降碳的目标。本文采用一种非侵入式负载监测系统方案,该方法通过提取公用事业服务入口处电压和电流的重要且有代表性的功率特征来识别负载并分析负载的特征,然后找出负载运行的物理行为。建立载荷模型。本文使用时频域的短时傅立叶变换(STFT)和小波变换(WT)来分析和比较实验中的不同负载。在实验中,结果表明在负载瞬态分析中,小波变换比STFT更好。电源签名的选择会影响负载识别和计算时间的结果。

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