An Improved Methodology to Locate Faults in Onshore Wind Farm Collector Systems

Moisés Davi (), Alailton Júnior, Caio Grilo, Talita Cunha, Leonardo Lessa, Mário Oleskovicz and Denis Coury
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Moisés Davi: São Carlos School of Engineering, University of São Paulo, Av. Trab. São Carlense, 400, São Carlos 13566-590, Brazil
Alailton Júnior: São Carlos School of Engineering, University of São Paulo, Av. Trab. São Carlense, 400, São Carlos 13566-590, Brazil
Caio Grilo: São Carlos School of Engineering, University of São Paulo, Av. Trab. São Carlense, 400, São Carlos 13566-590, Brazil
Talita Cunha: São Carlos School of Engineering, University of São Paulo, Av. Trab. São Carlense, 400, São Carlos 13566-590, Brazil
Leonardo Lessa: São Carlos School of Engineering, University of São Paulo, Av. Trab. São Carlense, 400, São Carlos 13566-590, Brazil
Mário Oleskovicz: São Carlos School of Engineering, University of São Paulo, Av. Trab. São Carlense, 400, São Carlos 13566-590, Brazil
Denis Coury: São Carlos School of Engineering, University of São Paulo, Av. Trab. São Carlense, 400, São Carlos 13566-590, Brazil

Energies, 2025, vol. 18, issue 3, 1-16

Abstract: This paper explores the growing integration of Inverter-Based Resources (IBRs) into power systems and their effects on fault diagnosis strategies. Notably, the technical literature lacks assessments of the impacts and proposals for solutions for phasor-based fault location tasks, considering faults occurring within wind power plants, i.e., in their collector systems. In this context, this study evaluates the performance of six state-of-the-art phasor-based fault location methods, which are tested through simulations in a realistic wind farm modeled using PSCAD software. These simulations cover a wide range of fault scenarios, including variations in fault types, resistances, inception angles, locations, and wind farm generation levels. The proposed methodology, which combines the various fault location methods tailored to specific fault types, results in a substantial improvement, achieving an average fault location error of 1.89%, reflecting a 92% reduction in error compared to conventional methods. Additionally, the approach consistently maintains low fault location errors across collector busbars, regardless of circuit topology, highlighting its robustness, adaptability, and potential for widespread implementation in fault diagnosis systems within wind farms.

Keywords: fault location; inverter-based resources; wind farm collectors; wind power plant (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: 2025
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