Research for the Mixed Disturbance Detection of Power System Using LMD Algorithm

• Published in: Sensors & transducers Vol. 161; no. 12; p. 352
• Main Authors: Wensi, Cao, Yan, Xu
• Format: Journal Article
• Language: English
• Published: Toronto IFSA Publishing, S.L 01.12.2013
• Subjects: Accuracy; Algorithms; Amplitudes; Decomposition; Disturbances; Electric potential; Fault diagnosis; Fourier transforms; Frequency distribution; Harmonics; Mathematical models; Methods; Substations; Voltage
• ISSN: 2306-8515; 1726-5479; 1726-5479

In order to realize the accurate identification of mixed disturbance signal in power system, the local mean decomposition (LMD) algorithm is applied to the mixed disturbance detection in power system for the first time. The typical power quality mixed disturbance signal include harmonics and voltage flicker signal, harmonics and voltage swell signal, harmonics and voltage sag signal, harmonics and voltage interruption signal, as well as the actual mixed disturbance signals occurred in smart substation, are selected and analyzed by LMD algorithm. Disturbance signal is adaptively decomposed into a number of Product Function (PF for short) by the algorithm, and the PF is made of the envelope signal and pure Frequency Modulation signal. We can get the original signal of frequency and amplitude distribution curves. Simulation results show that LMD algorithm is better than HHT algorithm in the parameter fluctuation of transient characteristic parameter detection, the detection accuracy, the end effect and running time. Detection results of Smart Substation shows that, the amplitude, frequency, start and end time of disturbance signal can be accurately detected by LMD algorithm, proving the correctness of the LMD algorithm. [PUBLICATION ABSTRACT]