6 papers
Machine Learning Guided Optimal Transmission Switching to Mitigate Wildfire Ignition Risk
Weimin Huang, Ryan Piansky, Bistra Dilkina +1
To mitigate acute wildfire ignition risks, utilities de-energize power lines in high-risk areas. The Optimal Power Shutoff (OPS) problem optimizes line energization statuses to man…
Robust Capacity Expansion under Wildfire Ignition Risk and High Renewable Penetration
Tomás Tapia, Ryan Piansky, Yury Dvorkin +1
In power systems, the risk of wildfire ignition has increased significantly in recent years. The impact and severity of these events on energy dispatch, as well as their societal r…
Optimizing Battery and Line Undergrounding Investments for Transmission Systems under Wildfire Risk Scenarios: A Benders Decomposition Approach
Ryan Piansky, Rahul K. Gupta, Daniel K. Molzahn
With electric power infrastructure posing an increasing risk of igniting wildfires under continuing climate change, utilities are frequently de-energizing power lines to mitigate w…
Evaluating Undergrounding Decisions for Wildfire Ignition Risk Mitigation across Multiple Hazards
Ryan Piansky, Daniel K. Molzahn, Nicole D. Jackson +1
With electric power infrastructure increasingly susceptible to impacts from climate-driven natural disasters, there is an increasing need for optimization algorithms that determine…
Equitably allocating wildfire resilience investments for power grids: The curse of aggregation and vulnerability indices
Madeleine Pollack, Ryan Piansky, Swati Gupta +1
Social vulnerability indices have increased traction for guiding infrastructure investment decisions to prioritize communities that need these investments most. One such plan is th…
Quantifying Metrics for Wildfire Ignition Risk from Geographic Data in Power Shutoff Decision-Making
Ryan Piansky, Sofia Taylor, Noah Rhodes +3
Faults on power lines and other electric equipment are known to cause wildfire ignitions. To mitigate the threat of wildfire ignitions from electric power infrastructure, many util…