Optimally Scheduling Public Safety Power Shutoffs

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

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

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 negative impact of service interruptions. In this work, we consider three PSPS scheduling scenarios, 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.

Original languageEnglish (US)
Pages (from-to)438-456
Number of pages19
JournalStochastic Systems
Volume13
Issue number4
DOIs
StatePublished - 2023
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modeling and Simulation
  • Statistics, Probability and Uncertainty
  • Management Science and Operations Research

Keywords

  • dynamic programming
  • optimal policy
  • public safety power shutoffs
  • wildfires

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