Abstract: With development of power system capacity, analysis algorithms of power quality data faces higher requirement to ensure stable operation of electric equipment. While considering accuracy and noise resistance of algorithms, new challenges are also raised for detection of some weak or complex disturbances. In view of above requirements, in this paper, a general detection algorithm of power quality disturbances is proposed based on characteristics of abnormal disturbance waveform. The proposed algorithm combines sliding window and singular value decomposition, and a definite disturbance location can be given according to detection result. Meanwhile, an adaptive threshold based on waveform difference is also proposed for distinguishing abnormality from noise without need of adjusting parameters. Finally, effectiveness of the proposed algorithm is verified with simulation for a number of simulated and actual signals, showing that the algorithm has advantages of small computation amount and high real-time performance. Comparing with other algorithms, the proposed algorithm has higher sensitivity and noise resistance capability, applicable to various situations.
杨晓梅, 罗月婉, 肖先勇, 郭朝云. 基于自适应阈值和奇异值分解的电能质量扰动检测新方法[J]. 电网技术, 2018, 42(7): 2286-2294.
YANG Xiaomei, LUO Yuewan, XIAO Xianyong, GUO Chaoyun. A New Detection Approach of Power Quality Disturbances Based on Adaptive Threshold and Singular Value Decomposition. POWER SYSTEM TECHNOLOGY, 2018, 42(7): 2286-2294.
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