Research of the Transient Disturbance Detection of Power System Based on LMD Algorithm

• Published in: Sensors & transducers Vol. 161; no. 12; p. 344
• Main Authors: Wensi, Cao, Chuanjin, Huang, Guozhi, Zhang
• Format: Journal Article
• Language: English
• Published: Toronto IFSA Publishing, S.L 01.12.2013
• Subjects: Algorithms; Amplitudes; Computer simulation; Decomposition; Disturbances; Electric potential; Envelopes; Fault diagnosis; Frequency modulation; Mathematical models; Methods; Signal processing; Voltage
• ISSN: 2306-8515; 1726-5479; 1726-5479

To realize high-accuracy measurement parameter of transient disturbance signal, aiming at the transient disturbance signal is nonlinear, irregular and mutation characteristics. The local mean decomposition (LMD) algorithm is applied to the transient disturbance detection in power system for the first time. Transient disturbance signal is adaptively decomposed into a number of Product Function (PF) by the algorithm, and the PF is made of the envelope signal and pure Frequency Modulation signal. The amplitude and PF frequency respectively obtained by the envelope signal and pure Frequency Modulation signal. Further combination, the researchers can get the original signal of time frequency distribution curves. The amplitude and frequency curve, not only can accurately locate the disturbance moments, but also can detect the voltage fluctuation amplitude of typical transient disturbance signal, such as voltage swell, and voltage sag. The simulation waveform was influenced by "end effect" smaller. Simulation results show that LMD Algorithm is effective, and has better accuracy and computing speed than the HHT algorithm.