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Optimally scheduling public safety power shutoffs

Antoine Lesage-Landry, Félix Pellerin, Duncan S. Callaway and Joshua A. Taylor

Article (2023)

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Abstract

In an effort to reduce power system-caused wildfires, utilities carry out public safety power shutoffs (PSPSs), in which portions of the grid are deenergized to mitigate the risk of ignition. The decision to call a PSPS must balance reducing ignition risks and the nega-tive impact of service interruptions. In this work, we consider three PSPS scheduling scenar-ios, which we model as dynamic programs. In the first two scenarios, we assume that N PSPSs are budgeted as part of the investment strategy. In the first scenario, a penalty is incurred for each PSPS declared past the Nth event. In the second, we assume that some costs can be recovered if the number of PSPSs is below N while still being subject to a penalty if above N. In the third, the system operator wants to minimize the number of PSPSs such that the total expected cost is below a threshold. We provide optimal or asymptotically optimal policies for each case, the first two of which have closed-form expressions. Lastly, we establish the applicability of the first PSPS model’s policy to critical peak pricing and obtain an optimal scheduling policy to reduce the peak demand based on weather observations.

Department: Department of Electrical Engineering
Research Center: GERAD - Research Group in Decision Analysis
Other
Funders: CRSNG/NSERC, Institute for Data Valorization, National Science Foundation, Advanced Research Projects Agency-Energy, University of California Office of the President Laboratory Fees Program
Grant number: 1351900, DE-AR0001061, LFR-20-652467
PolyPublie URL: https://publications.polymtl.ca/55995/
Journal Title: Stochastic systems
Publisher: Institute for Operations Research and the Management Sciences
DOI: 10.1287/stsy.2022.0004
Official URL: https://doi.org/10.1287/stsy.2022.0004
Date Deposited: 23 Jan 2024 16:08
Last Modified: 08 Apr 2025 11:23
Cite in APA 7: Lesage-Landry, A., Pellerin, F., Callaway, D. S., & Taylor, J. A. (2023). Optimally scheduling public safety power shutoffs. Stochastic systems, 19 pages. https://doi.org/10.1287/stsy.2022.0004

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