A new fault location method for distribution networks using sparse measurements |
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| Affiliation: | 1. School of Electrical Engineering, Wuhan University, Wuhan, Hubei 430072, China;2. School of Power and Mechanical Engineering, Wuhan University, Wuhan, Hubei 430072, China;1. Elec. Power and Machines Department, Faculty of Eng., Kafrelshiekh University, Egypt;2. Elec. Power and Machines Department, Faculty of Eng., Cairo University, Egypt;1. Department of Electrical Engineering, Southern Federal Institute of Education, Science and Technology, Pelotas, RS 96015-140, Brazil;2. Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611-6130, USA;3. Department of Electrical and Computer Engineering, University of São Paulo, São Carlos, SP 13560-480, Brazil;4. Department of Electrical Engineering, Technological University of Pereira, Pereira, Risaralda 660003, Colombia;5. Department of Engineering and Computer Science, Universidade Regional Integrada do Alto Uruguai e das Missões, Frederico Westphalen, RS 98400-000, Brazil |
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| Abstract: | In response to the growing demand to improve reliability and quality of power supply, distributed monitoring devices are gradually being implemented in distribution networks. On the other hand, utilities are demanding more accurate and reliable fault location systems to reduce the economic impact of power outages. This paper presents a novel method that takes full advantage of all available measurements to provide an accurate fault location. The developed method first uses an iterative state estimation based algorithm to find the nearest node to the fault location. It then examines all lines connected to the selected node and locates the fault. The performance of the proposed method is studied by simulation tests on a real 13.8 kV, 134-node distribution system under different fault scenarios. The results verify the accuracy of the algorithm and its robustness even under uncertain measured data. The method robustly handles measurement errors, and is applicable to any distribution network with laterals, load taps and heterogeneous lines. |
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| Keywords: | Distribution networks Fault location Measurement uncertainty Outage management State estimation |
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