High-Accuracy Power Quality Disturbance Classification Using the Adaptive ABC-PSO as Optimal Feature Selection Algorithm

High-Accuracy Power Quality Disturbance Classification Using the Adaptive ABC-PSO as Optimal Feature Selection Algorithm

Power quality disturbance (PQD) is an important issue in electrical distribution systems that needs to be detected promptly and identified to prevent the degradation of system reliability. This work proposes a PQD classification using a novel algorithm, comprised of the artificial bee colony (ABC) a...

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Bibliographic Details
Main Authors: Supanat Chamchuen, Apirat Siritaratiwat, Pradit Fuangfoo, Puripong Suthisopapan, Pirat Khunkitti
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Energies
Subjects:
power quality disturbance classification
optimal feature selection
probabilistic neural network
particle swarm optimization
artificial bee colony
Online Access:https://www.mdpi.com/1996-1073/14/5/1238

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https://www.mdpi.com/1996-1073/14/5/1238

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