A two-stage stochastic programming model for electric substation flood mitigation prior to an imminent hurricane

We present a stochastic programming model for informing the deployment of ad hoc flood mitigation measures to protect electric substations prior to an imminent and uncertain hurricane. The first stage captures the deployment of a fixed number of mitigation resources, and the second stage captures grid operation in response to a contingency. The primary objective is to minimize expected load shed. We develop methods for simulating flooding induced by extreme rainfall and construct two geographically realistic case studies, one based on Tropical Storm Imelda and the other on Hurricane Harvey. Applying our model to those case studies, we investigate the effect of the mitigation budget on the optimal objective value and solutions. Our results highlight the sensitivity of the optimal mitigation to the budget, a consequence of those decisions being discrete. We additionally assess the value of having better mitigation options and the spatial features of the optimal mitigation.

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Publication Details

Journal
IISE Transactions
Published
2024-08-20
DOI
https://doi.org/10.1080/24725854.2024.2393654
Citations
9
Primary Topic
Infrastructure Resilience and Vulnerability Analysis
Type
article
Field-Weighted Citation Impact
1.83
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article

A two-stage stochastic programming model for electric substation flood mitigation prior to an imminent hurricane

Erhan Kutanoğlu, John J. Hasenbein, Brent Austgen
9 citations
IISE Transactions
Infrastructure Resilience and Vulnerability Analysis
1.83
article

A two-stage stochastic programming model for electric substation flood mitigation prior to an imminent hurricane

Erhan Kutanoğlu, John J. Hasenbein, Brent Austgen
article en
9 citations

Abstract

We present a stochastic programming model for informing the deployment of ad hoc flood mitigation measures to protect electric substations prior to an imminent and uncertain hurricane. The first stage captures the deployment of a fixed number of mitigation resources, and the second stage captures grid operation in response to a contingency. The primary objective is to minimize expected load shed. We develop methods for simulating flooding induced by extreme rainfall and construct two geographically realistic case studies, one based on Tropical Storm Imelda and the other on Hurricane Harvey. Applying our model to those case studies, we investigate the effect of the mitigation budget on the optimal objective value and solutions. Our results highlight the sensitivity of the optimal mitigation to the budget, a consequence of those decisions being discrete. We additionally assess the value of having better mitigation options and the spatial features of the optimal mitigation.

IISE TransactionsVol. 57(8)
The University of Texas at Austin (US)
Climate action
Openalex Percentile: Top 16%
Infrastructure Resilience and Vulnerability Analysis
1.83
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