Co-optimization of power line shutoff and restoration under high wildfire ignition risk

被引：2

作者：

Rhodes, Noah ^{[1
]}

Roald, Line A. ^{[1
]}

机构：

[1] Univ Wisconsin Madison, Dept Elect & Comp Engn, Madison, WI USA

来源：

2023 IEEE BELGRADE POWERTECH | 2023年

基金：

美国国家科学基金会;

关键词：

Wildfire risk mitigation; preemptive power shutoffs; grid restoration; mixed-integer optimization;

D O I：

10.1109/POWERTECH55446.2023.10202865

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Electric power infrastructure has ignited several of the most destructive wildfires in recent history. Preemptive power shutoffs are an effective tool to mitigate the risk of ignitions from power lines, but at the same time can cause widespread power outages. This work proposes a mathematical optimization problem to help utilities decide where and when to implement these shutoffs, as well as how to most efficiently restore power once the wildfire risk is lower. Specifically, our model co-optimizes the power shutoff (considering both wildfire risk reduction and power outages) as well as the post-event restoration efforts given constraints related to inspection and energization of lines, and is implemented as a rolling horizon optimization problem that is resolved whenever new forecasts of load and wildfire risk become available. We demonstrate our method on the IEEE RTS-GMLC test case using real wildfire risk data and forecasts from US Geological Survey, and investigate the sensitivity of the results to the forecast quality, decision horizon and system restoration budget. The software implementation is available in the open source software package PowerModelsWildfire.jl.

引用

页数：7