Evaluation of power quality disturbance in PV-connected IEEE-14 bus system using lifting-based wavelet transform and random forest

2022 ◽  
Author(s):  
S. Upadhyaya ◽  
C. N. Bhende ◽  
S. Mohanty ◽  
R. Pati
Keyword(s):  
Wavelet Transform ◽  
Random Forest ◽  
Power Quality ◽  
Power Quality Disturbance ◽  
Bus System

scholarly journals Feature Selection of Power Quality Disturbance Signals with an Entropy-Importance-Based Random Forest

Entropy ◽  
2016 ◽  
Vol 18 (2) ◽  
pp. 44 ◽  
Author(s):  
Nantian Huang ◽  
Guobo Lu ◽  
Guowei Cai ◽  
Dianguo Xu ◽  
Jiafeng Xu ◽  
...  
Keyword(s):  
Feature Selection ◽  
Random Forest ◽  
Power Quality ◽  
Power Quality Disturbance ◽  
Selection Of

scholarly journals Power Quality Disturbance Recognition Using Empirical Wavelet Transform and Feature Selection

Electronics ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 174
Author(s):  
Sihan Chen ◽  
Ziche Li ◽  
Guobing Pan ◽  
Fang Xu
Keyword(s):  
Feature Selection ◽  
Wavelet Transform ◽  
Power Quality ◽  
Electrical Equipment ◽  
Support Vector ◽  
Analysis Tool ◽  
Electrical Systems ◽  
Empirical Wavelet Transform ◽  
Power Quality Disturbance ◽  
System Calculation

With the growth of nonlinear electrical equipment, power quality disturbances (PQDs) often appear in electrical systems. To solve this, a practical heuristic methodology for PQD detection and classification based on empirical wavelet transform has been proposed. By using a multiresolution analysis tool, empirical wavelet transform, the voltage waveform signal is decomposed into several sub-signals, and some potential features are extracted in the statistical method. To reduce the feature vector dimensions, the ReliefF algorithm is used for feature selection and optimized for dimensionality reduction, which reduces the complexity of system calculation while ensuring accuracy. Finally, a classifier based on support vector machines (SVM) was built, and with the ranked feature vectors’ input, the PQD can be recognized. The experimental results verify that the classification results achieved high accuracy, which confirms the properties and robustness of the proposed approach in noisy environments.

SYMLET Wavelet Transform Applied to Inspect Power Quality Disturbance-Generated Signals

2015 ◽  
Vol 8 (4) ◽  
pp. 19-25
Author(s):  
Anand Deshmukh ◽  
◽  
Shekhappa G. Ankaliki ◽  
Keyword(s):  
Wavelet Transform ◽  
Power Quality ◽  
Power Quality Disturbance
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