A new Fuzzy&Wavelet-based adaptive thresholding method for detecting PQDs in a hydrogen and solar-energy powered EV charging station
Küçük Resim Yok
Tarih
2023
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Pergamon-Elsevier Science Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This study presents a hybrid fuzzy decision-maker (FDM) and un-decimated wavelet transform (UWT)-based method for detecting power quality disturbances (PQDs) in a developed hydrogen and solar energy-powered electric vehicle (EV) charge station. The proposed adaptive FDM&UWT-based hybrid method eliminated the lack of performance of threshold-based signal analysis methods in noise-containing signals and it is implemented for a reliable PQD detection and integration in a developed microgrid. Also, the proposed method has eliminated the need for a processing-intensive filtering process to reduce noise from the signal. With this adaptive approach, detection errors in boundary condi-tions in threshold value methods are avoided and at the same time, cost and computa-tional burden are minimized by using only the peak values in the detail coefficients of the voltage signal. The mean test accuracy is 96.13% for the FDM method using pyramidal UWT in noise-free conditions. Besides, the pyramidal UWT-FDM has a mean classification accuracy of 94.96% under 20-40 dB high-level noise conditions. The effectiveness of the UWT-FDM method is also tested using an experimental setup. The mean test accuracy for experimental data is 96.66%.(c) 2022 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
Açıklama
Anahtar Kelimeler
Power quality, Distributed generation, Fuzzy logic decision making, Automated fault detection, EV charge Stations
Kaynak
International Journal of Hydrogen Energy
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
48
Sayı
18
