In the last years, extreme weather events, including heat waves, have caused extensive and long-lasting interruptions in the electric power distribution systems of large urban areas. According to the current Performance-Based Regulation (PBR) approaches for incentives aimed at strengthening utility performance, these interruptions have to be quantitatively measured in network resilience metrics, rather than reliability metrics. In this distinction between resilience and reliability, a clear definition of the extreme events is required. This, however, is still lacking. To address the problem, in this work we propose a method to define heat waves, which relies on logistic regression with elastic-net penalization to quantitatively associate environmental and operating conditions of the network to significant increments of its failures. The methodology is validated by application to the medium voltage distribution network of the city of Milano, Italy.

A supervised classification method based on logistic regression with elastic-net penalization for heat waves identification to enhance resilience planning in electrical power distribution grids

Michele Compare;Luca Perfetto;Alessandro Bosisio;Enrico Zio
2020

Abstract

In the last years, extreme weather events, including heat waves, have caused extensive and long-lasting interruptions in the electric power distribution systems of large urban areas. According to the current Performance-Based Regulation (PBR) approaches for incentives aimed at strengthening utility performance, these interruptions have to be quantitatively measured in network resilience metrics, rather than reliability metrics. In this distinction between resilience and reliability, a clear definition of the extreme events is required. This, however, is still lacking. To address the problem, in this work we propose a method to define heat waves, which relies on logistic regression with elastic-net penalization to quantitatively associate environmental and operating conditions of the network to significant increments of its failures. The methodology is validated by application to the medium voltage distribution network of the city of Milano, Italy.
30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference
9789811485930
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1162771
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