期刊
ENERGIES
卷 5, 期 11, 页码 4569-4589出版社
MDPI
DOI: 10.3390/en5114569
关键词
non-intrusive load monitoring; feature analysis; wavelet transform; short-time Fourier transform; energy management systems
资金
- National Science Council of the Republic of China, Taiwan [NSC 101-2221-E-228-001]
Energy management systems strive to use energy resources efficiently, save energy, and reduce carbon output. This study proposes transient feature analyses of the transient response time and transient energy on the power signatures of non-intrusive demand monitoring and load identification to detect the power demand and load operation. This study uses the wavelet transform (WT) of the time-frequency domain to analyze and detect the transient physical behavior of loads during the load identification. The experimental results show the transient response time and transient energy are better than the steady-state features to improve the recognition accuracy and reduces computation requirements in non-intrusive load monitoring (NILM) systems. The discrete wavelet transform (DWT) is more suitable than short-time Fourier transform (STFT) for transient load analyses.
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