Comparisons of Two-Stage Models for Flood Mitigation of Electrical Substations

Brent Austgen (), Erhan Kutanoglu (), John J. Hasenbein () and Surya Santoso ()
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Brent Austgen: Operations Research and Industrial Engineering Program, The University of Texas at Austin, Austin, Texas 78712
Erhan Kutanoglu: Operations Research and Industrial Engineering Program, The University of Texas at Austin, Austin, Texas 78712
John J. Hasenbein: Operations Research and Industrial Engineering Program, The University of Texas at Austin, Austin, Texas 78712
Surya Santoso: Chandra Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas 78712

INFORMS Journal on Computing, 2025, vol. 37, issue 2, 270-292

Abstract: We compare stochastic programming and robust optimization decision models for informing the deployment of ad hoc flood mitigation measures to protect electrical substations prior to an imminent and uncertain hurricane. In our models, the first stage captures the deployment of a fixed quantity of flood mitigation resources, and the second stage captures the operation of a potentially degraded power grid with the primary goal of minimizing load shed. To model grid operation, we introduce adaptations of the direct current (DC) and linear programming alternating current (LPAC) power flow approximation models that feature relatively complete recourse by way of an indicator variable. We apply our models to a pair of geographically realistic flooding case studies, one based on Hurricane Harvey and the other on Tropical Storm Imelda. We investigate the effect of the mitigation budget, the choice of power flow model, and the uncertainty perspective on the optimal mitigation strategy. Our results indicate the mitigation budget and uncertainty perspective are impactful, whereas choosing between the DC and LPAC power flow models is of little to no consequence. To validate our models, we assess the performance of the mitigation solutions they prescribe in an alternating current (AC) power flow model.

Keywords: stochastic programming; robust optimization; power flow; flooding; hurricane; resilience; mitigation; risk management (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:inm:orijoc:v:37:y:2025:i:2:p:270-292

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