A novel multiple impact factors based accuracy analysis approach for power quality disturbance detection

Nowadays, power quality problems are affecting people's daily life and production activities. With the aim to improve disturbance detection accuracy, a novel analysis approach based on multiple impact factors is proposed in this paper. First, a multiple impact factors analysis is implemented in which two perspectives, i.e., the wavelet analysis and disturbance features are considered simultaneously. Five key factors, including wavelet function, wavelet decomposition level, redundant algorithm, event type and disturbance intensity, start and end moment of disturbance, have been considered. Next, an impact factors based accuracy analysis algorithm is proposed, through which each factor's potential impact on disturbance location accuracy is investigated. Three transforms, i.e., the classic wavelet, lifting wavelet and redundant lifting wavelet are employed, and their superiority on disturbance location accuracy is investigated. Finally, simulations are conducted for verification. Through the proposed method, the wavelet based parameters can be validly selected in order to detect power quality disturbance accurately.