Power Quality Disturbances Feature Selection and Recognition Using Optimal Multi-Resolution Fast S-Transform and CART Algorithm

Power Quality Disturbances Feature Selection and Recognition Using Optimal Multi-Resolution Fast S-Transform and CART Algorithm

In order to improve the recognition accuracy and efficiency of power quality disturbances (PQD) in microgrids, a novel PQD feature selection and recognition method based on optimal multi-resolution fast S-transform (OMFST) and classification and regression tree (CART) algorithm is proposed. Firstly,...

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Bibliographic Details
Main Authors: Nantian Huang, Hua Peng, Guowei Cai, Jikai Chen
Format: Article
Language:English
Published: MDPI AG 2016-11-01
Series:Energies
Subjects:
power quality disturbances
optimal multi-resolution fast S-transform
classification and regression tree algorithm
feature selection
decision tree
Online Access:http://www.mdpi.com/1996-1073/9/11/927

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