Integrated Fault Detection, Classification and Section Identification (I-FDCSI) Method for Real Distribution Networks Using μPMUs

Abdul Haleem Medattil Ibrahim (), Madhu Sharma () and Vetrivel Subramaniam Rajkumar
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Abdul Haleem Medattil Ibrahim: Department of Electrical and Electronics Engineering, University of Petroleum and Energy Studies, Dehradun 248007, India
Madhu Sharma: Department of Electrical and Electronics Engineering, University of Petroleum and Energy Studies, Dehradun 248007, India
Vetrivel Subramaniam Rajkumar: Department of Electrical Sustainable Energy, Delft University of Technology, 2628 CD Delft, The Netherlands

Energies, 2023, vol. 16, issue 11, 1-29

Abstract: This paper presents a rules-based integrated fault detection, classification and section identification (I-FDCSI) method for real distribution networks (DN) using micro-phasor measurement units ( μ PMUs). The proposed method utilizes the high-resolution synchronized realistic measurements from the strategically installed μ PMUs to detect and classify different types of faults and identify the faulty section of the distribution network. The I-FDCSI method is based on a set of rules developed using expert knowledge and statistical analysis of the generated realistic measurements. The algorithms mainly use line currents per phase reported by the different μ PMUs to calculate the minimum and maximum short circuit current ratios. The algorithms were then fine-tuned with all the possible types and classes of fault simulations at all possible sections of the network with different fault parameter values. The proposed I-FDCSI method addresses the inherent challenges of DN by leveraging the high-precision measurements provided by μ PMUs to accurately detect, classify, and sectionalise faults. To ensure the applicability of the developed IFDCSI method, it is further tested and validated with all the possible real-time events on a real distribution network and its performance has been compared with the conventional fault detection, classification and section identification methods. The results demonstrate that the I-FDCSI method has a higher accuracy and faster response time compared to the conventional methods and facilitates faster service restoration, thus improving the reliability and resiliency indices of DN.

Keywords: ?PMUs; fault detection; fault management; fault classification; section identification; distribution network; fault indicators; modelling; simulation; reliability indices (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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