Performance Evaluation of Discrete Wavelet Transform and Machine Learning Based Techniques for Classifying Power Quality Disturbances
This paper evaluates the performance of six different machine learning (ML) algorithms for
classifying power quality disturbances (PQDs), with statistical features extracted using …
classifying power quality disturbances (PQDs), with statistical features extracted using …
[PDF][PDF] Recognition of Hybrid PQ Disturbances Based on Multi-Resolution S-Transform and Decision Tree
F Zhao, D Liao, X Chen, Y Wang - Energy Engineering, 2023 - cdn.techscience.cn
Aiming at the problems of multiple types of power quality composite disturbances, strong
feature correlation and high recognition error rate, a method of power quality composite …
feature correlation and high recognition error rate, a method of power quality composite …
[PDF][PDF] Complex Power Quality Disturbances Classification Based on Multi-label Active Learning.
C Zhao, H Zhang, C Wei, Z Zeng - Journal of Engineering Science & …, 2022 - jestr.org
Power quality (PQ) disturbances generated during the power grid operation are complicated
and volatile in real life. If a large number of complex PQ disturbances (CPQDs) from power …
and volatile in real life. If a large number of complex PQ disturbances (CPQDs) from power …