Power Distribution Systems’ Vulnerability by Regions Caused by Electrical Discharges

Andréia S. Santos, Lucas Teles Faria, Mara Lúcia M. Lopes and Carlos R. Minussi ()
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Andréia S. Santos: Department of Electrical Engineering, São Paulo State University (UNESP), Ilha Solteira 15385-000, São Paulo, Brazil
Lucas Teles Faria: Department of Energy Engineering, São Paulo State University (UNESP), Rosana 19274-000, São Paulo, Brazil
Mara Lúcia M. Lopes: Department of Electrical Engineering, São Paulo State University (UNESP), Ilha Solteira 15385-000, São Paulo, Brazil
Carlos R. Minussi: Department of Electrical Engineering, São Paulo State University (UNESP), Ilha Solteira 15385-000, São Paulo, Brazil

Energies, 2023, vol. 16, issue 23, 1-19

Abstract: Energy supply interruptions or blackouts caused by faults in power distribution feeders entail several damages to power utilities and consumer units: financial losses, damage to power distribution reliability, power quality deterioration, etc. Most studies in the specialized literature concerning faults in power distribution systems present methodologies for detecting, classifying, and locating faults after their occurrence. In contrast, the main aim of this study is to prevent faults by estimating the city regions whose power grid is most vulnerable to them. In this sense, this work incorporates a geographical-space study via a spatial data analysis using the local variable electrical discharge density that can increase fault risks. A geographically weighted spatial analysis is applied to data aggregated by regions to produce thematic maps with the city regions whose feeders are more vulnerable to failures. The spatial data analysis is implemented in QGIS and R programming environments. It is applied to the real data of faults in distribution power grid transformers and electrical discharges in a medium-sized city with approximately 200,000 inhabitants. In this study, we highlight a moderate positive correlation between electrical discharge density and the percentage of faults in transformers by regions in the central and western areas of the city under study.

Keywords: power distribution systems (PDS); spatial data analysis (SDA); steady-state fault (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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