Evaluation of lightning-related faults that lead to distribution network outages: An experimental case study
| Autor: | Marcelo Antonio Ravaglio, Kristie Kaminski Küster, Luciana Gonçalves de Mello, André Eugênio Lazzaretti, Alexandre Piantini, Signie Laureano França Santos, Luiz Felipe Ribeiro Barrozo Toledo, Cleverson L. S. Pinto |
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| Rok vydání: | 2019 |
| Předmět: |
Distribution networks
Computer science 020209 energy 020208 electrical & electronic engineering Energy Engineering and Power Technology Experimental data 02 engineering and technology Fault (power engineering) Lightning Power (physics) Reliability engineering Lead (geology) 0202 electrical engineering electronic engineering information engineering Transient (oscillation) Electrical and Electronic Engineering Voltage |
| Zdroj: | Electric Power Systems Research. 174:105848 |
| ISSN: | 0378-7796 |
| DOI: | 10.1016/j.epsr.2019.04.026 |
| Popis: | Lightning activity is often one of the major causes of voltage transient disturbances and interruptions in distribution networks. Although important researches have been performed on the correlation of lightning-related events and faults in distribution networks, there is still an open question about in which situations will a lightning-related fault self-extinguish or evolve to a sustained short-circuit that will lead to a power outage. This study aims to show, based on an analysis using data from a real monitored distribution system and high-voltage laboratory tests, that the conditions for sustained arc-formation from a lightning-induced fault depend on the utility infrastructure construction patterns and the characteristics of the distribution equipment available. The distribution feeder was modeled based on laboratory test results and the digital simulations are validated by comparing calculated and actual measured overvoltages. This paper presents an analysis of lightning-related faults in power distribution feeders, integrating experimental data and digital simulations. The proposed method is promising in predicting the effects of lightning on distribution networks, especially in identifying the feeder sections most prone to failures. |
| Databáze: | OpenAIRE |
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