Classification of Faults in Grid-Connected Photovoltaic System based on Wavelet Packet Transform and an Equilibrium Optimization Algorithm-Extreme Learning Machine
Abstract
A novel intelligent scheme using the wavelet packet transform (WPT) and extreme learning machine (ELM) is proposed for fault event classification in the grid-connected photovoltaic (PV) system. The WPT is applied for preprocessing the cycle of the post-fault voltage samples at the point of common coupling (PCC) measurement to get the normalized logarithmic energy entropy (NLEE). The ELM is applied to classify the different fault cases. To enhance the performance of ELM for faults classification, a hybrid optimization mechanism based on an equilibrium optimization algorithm (EOA) is proposed to optimize the selection of input feature subset and the number of ELM hidden nodes. Furthermore, to evaluate the proposed scheme's performance, a comprehensive evaluation was conducted on a 250 kW grid-connected photovoltaic system. From simulation, the classification accuracy is recorded to be 100% under the no-noise condition, while at the signal-to-noise ratios (SNR) of 30, 35, and 40 dB, the accuracies are 98.96, 99.04, and 99.36%, respectively. Moreover, the practical performance of the EOA-ELM classifier is validated using IEEE 34 bus system. The obtained results validate the effectiveness of the proposed scheme in terms of robustness against measurement noise, computation time, and detection accuracy.
Recommended Citation
M. Ahmadipour et al., "Classification of Faults in Grid-Connected Photovoltaic System based on Wavelet Packet Transform and an Equilibrium Optimization Algorithm-Extreme Learning Machine," Measurement: Journal of the International Measurement Confederation, vol. 197, article no. 111338, Elsevier, Jun 2022.
The definitive version is available at https://doi.org/10.1016/j.measurement.2022.111338
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
Equilibrium Optimizer Algorithm (EOA); Extreme Learning Machine (ELM); Fault Classification; Feature Selection; Grid-Connected Photovoltaic Systems; Wavelet Packet Transform (WPT)
International Standard Serial Number (ISSN)
0263-2241
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2022 Elsevier, All rights reserved.
Publication Date
30 Jun 2022
Comments
This work was supported by the Ministry of Higher Education, Malaysia, Grant LRGS/1/2018/UNITEN/01/1/3.