Optimizing Power Line Undergrounding Decisions under Varying Wildfire Risk and Weather Scenarios

Conference · Fri Feb 07 04:00:00 EST 2025

OSTI ID:2583385

Taylor, S. ^[1]; Musselman, A. ^[2]; Roald, L. ^[1]; Watson, J. ^[2]

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1. Department of Electrical and Computer Engineering University of Wisconsin-Madison Madison, WI, USA
2. Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Abstract—The threat of wildfire ignitions from electric power equipment has led utilities to increasingly turn to preemptive power shutoffs, which, while effective in reducing grid-induced wildfire risk, can cause significant load loss. Undergrounding power lines is an alternative strategy for preventing grid-induced wildfires. However, undergrounding lines is costly, so an efficient undergrounding plan must balance reductions in wildfire risk and load loss with the cost of undergrounding lines. We propose a robust optimization model to identify which power lines to underground to maximize load served while limiting wildfire risk across a range of wildfire risk and weather scenarios. Since solving this problem may be computationally heavy for large power grids and many operating scenarios, we present a delayed constraint generation algorithm to iteratively add scenarios until an optimal solution is found. We evaluate the performance of this framework on the RTS-GMLC with scenarios representing a year of operating conditions and compare it with a stochastic programming formulation. Our results indicate that our undergrounding model is successful in reducing load shed and risk compared to baseline cases in which no mitigation action is taken and only power shutoffs are implemented (no undergrounding). The robust formulation also reduces more load shed than the stochastic formulation in the most extreme scenarios. Index Terms—grid resilience, optimization, transmission systems, underground power lines, wildfire risk.

• Research Organization: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA)
• DOE Contract Number: AC52-07NA27344
• OSTI ID: 2583385
• Report Number(s): LLNL-CONF-872362
• Country of Publication: United States
• Language: English