A power-flow emulator approach for resilience assessment of repairable power grids subject to weather-induced failures and data deficiency

•Weather extreme conditions affect power grid failures/repairs and data is scarce.•A stochastic resilience framework is proposed for assess the weather-grid interaction.•A power-flow emulator is constructed to reduce the computational cost.•Imprecise probabilistic methodology is used to tackle lack...

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Vydané v:	Applied energy Ročník 210; s. 339 - 350
Hlavní autori:	Rocchetta, Roberto, Zio, Enrico, Patelli, Edoardo
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 15.01.2018 Elsevier
Predmet:	algorithms Artificial neural network case studies Credal sets Engineering Sciences Global sensitivity Load curtailing Power grids probabilistic models Resilience Severe weather stochastic processes uncertainty weather Severe weather Global sensitivity Load curtailing Power grids Artificial neural network Credal sets Resilience
ISSN:	0306-2619, 1872-9118
On-line prístup:	Získať plný text
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