Logarithmic resilience risk metrics that address the huge variations in blackout cost

Fuente: arXiv
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Main Authors: Ahmad, Arslan, Dobson, Ian
Format: Preprint
Published: 2025
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author Ahmad, Arslan
Dobson, Ian
author_facet Ahmad, Arslan
Dobson, Ian
contents Resilience risk metrics must address the customer cost of the largest blackouts of greatest impact. However, there are huge variations in blackout cost in observed distribution utility data that make it impractical to properly estimate the mean large blackout cost and the corresponding risk. These problems are caused by the heavy tail observed in the distribution of customer costs. To solve these problems, we propose resilience metrics that describe large blackout risk using the mean of the logarithm of the cost of large-cost blackouts, the slope index of the heavy tail, and the frequency of large-cost blackouts.
format Preprint
id arxiv_https___arxiv_org_abs_2505_12016
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Logarithmic resilience risk metrics that address the huge variations in blackout cost
Ahmad, Arslan
Dobson, Ian
Risk Management
Applications
62P30 (Primary) 62G32 (secondary)
Resilience risk metrics must address the customer cost of the largest blackouts of greatest impact. However, there are huge variations in blackout cost in observed distribution utility data that make it impractical to properly estimate the mean large blackout cost and the corresponding risk. These problems are caused by the heavy tail observed in the distribution of customer costs. To solve these problems, we propose resilience metrics that describe large blackout risk using the mean of the logarithm of the cost of large-cost blackouts, the slope index of the heavy tail, and the frequency of large-cost blackouts.
title Logarithmic resilience risk metrics that address the huge variations in blackout cost
topic Risk Management
Applications
62P30 (Primary) 62G32 (secondary)
url https://arxiv.org/abs/2505.12016