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<p>This article presents the operation and control of various faults in the radial power system network, which includes the faults identification, measurement, categorization, and protection. The continuous presence of faults may damage the components of the network. It makes the power system engineers think to identify and trip the faults. The existing methods are able to identify faults with huge complex mathematics, more data occupation, poor accuracy, poor sensitivity, and inappropriate power quality problems like higher total harmonic distortion (THD). The existing methods also take more time to trip the fault. In order to overthrow the existing methods, an optimal hybrid bell algorithm (HBA) is proposed that is simple, consumes less data, and is easily applicable, which shows the novelty of the proposed research. The architecture of the HBA is a combined operation and control of the standard normal distribution and Poisson distribution methods for fault analysis. The performance parameters like accuracy, sensitivity, and THD are used for estimation of SLG (single line to ground), LL (line to line), LLG (line to line to ground), and LLL (line to line to line) faults in the network. The validity of the method is tested on the IEEE standard 9-bus and 39-bus systems. The performance realization for fault identification and termination in a radial network has been assessed with invasive weed optimization (IWO), fuzzy logic controller (FLC), artificial neural networks (ANN), and other existing methods. It is observed that performance parameters like improved accuracy (0.41%), improved sensitivity (0.49%), and least THD (9%) have been obtained with the proposed method in comparison with IWO, FLC, ANN, and other existing methods for fault identification and classification. The HBA also shows its dominance for protection against various faults, with the least time taken (0.55&#xa0;s) for fault termination and the least change in current (51%) with a simple mathematical approach. Such better results with the proposed method show its novelty. The critical situations like high impedance fault and voltage zero crossing have also been analyzed, in which the proposed approach shows its dominance over other methods. Further, the stability of the proposed method is validated with Routh-Hurwitz criteria.</p>

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An Accurate Fault Identification, Measurement and Protection in Radial Power System Network Using a New Hybrid Bell Algorithm

  • 期刊论文

  • 发表日期：

    2025年6月7日

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  • Abhinav Saxena,
  • Md. Abul Kalam,
  • Gyanesh Singh,
  • Yogendra Arya

摘要

This article presents the operation and control of various faults in the radial power system network, which includes the faults identification, measurement, categorization, and protection. The continuous presence of faults may damage the components of the network. It makes the power system engineers think to identify and trip the faults. The existing methods are able to identify faults with huge complex mathematics, more data occupation, poor accuracy, poor sensitivity, and inappropriate power quality problems like higher total harmonic distortion (THD). The existing methods also take more time to trip the fault. In order to overthrow the existing methods, an optimal hybrid bell algorithm (HBA) is proposed that is simple, consumes less data, and is easily applicable, which shows the novelty of the proposed research. The architecture of the HBA is a combined operation and control of the standard normal distribution and Poisson distribution methods for fault analysis. The performance parameters like accuracy, sensitivity, and THD are used for estimation of SLG (single line to ground), LL (line to line), LLG (line to line to ground), and LLL (line to line to line) faults in the network. The validity of the method is tested on the IEEE standard 9-bus and 39-bus systems. The performance realization for fault identification and termination in a radial network has been assessed with invasive weed optimization (IWO), fuzzy logic controller (FLC), artificial neural networks (ANN), and other existing methods. It is observed that performance parameters like improved accuracy (0.41%), improved sensitivity (0.49%), and least THD (9%) have been obtained with the proposed method in comparison with IWO, FLC, ANN, and other existing methods for fault identification and classification. The HBA also shows its dominance for protection against various faults, with the least time taken (0.55 s) for fault termination and the least change in current (51%) with a simple mathematical approach. Such better results with the proposed method show its novelty. The critical situations like high impedance fault and voltage zero crossing have also been analyzed, in which the proposed approach shows its dominance over other methods. Further, the stability of the proposed method is validated with Routh-Hurwitz criteria.