activity
20212024
most citedOptimizing Transmission Infrastructure Investments to Support Line De-energization for Mitigating Wildfire Ignition Risk

13 citations · 23 across the 6 of their papers we have counts for

collaborators

6 papers

eess.SY2024

Long Duration Battery Sizing, Siting, and Operation Under Wildfire Risk Using Progressive Hedging

Ryan Piansky, Georgia Stinchfield, Alyssa Kody +2

Battery sizing and siting problems are computationally challenging due to the need to make long-term planning decisions that are cognizant of short-term operational decisions. This…

math.OC2024★ 8 cited

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…

eess.SY2022★ 2 cited

Sharing the Load: Considering Fairness in De-energization Scheduling to Mitigate Wildfire Ignition Risk using Rolling Optimization

Alyssa Kody, Amanda West, Daniel K. Molzahn

Wildfires are a threat to public safety and have increased in both frequency and severity due to climate change. To mitigate wildfire ignition risks, electric power system operator…

eess.SY2022★ 13 cited

Optimizing Transmission Infrastructure Investments to Support Line De-energization for Mitigating Wildfire Ignition Risk

Alyssa Kody, Ryan Piansky, Daniel K. Molzahn

Wildfires pose a growing risk to public safety in regions like the western United States, and, historically, electric power systems have ignited some of the most destructive wildfi…

cs.LG2021

Modeling the AC Power Flow Equations with Optimally Compact Neural Networks: Application to Unit Commitment

Alyssa Kody, Samuel Chevalier, Spyros Chatzivasileiadis +1

Nonlinear power flow constraints render a variety of power system optimization problems computationally intractable. Emerging research shows, however, that the nonlinear AC power f…

eess.SY2021

A Reinforcement Learning Approach to Parameter Selection for Distributed Optimal Power Flow

Sihan Zeng, Alyssa Kody, Youngdae Kim +2

With the increasing penetration of distributed energy resources, distributed optimization algorithms have attracted significant attention for power systems applications due to thei…