Apr 4, 2023 · In this article, we model and solve the proactive control problem as a Markov decision process (MDP) and introduce an integrated testbed for spatiotemporal ...
Jul 12, 2021 · We model and solve the proactive control problem as a Markov decision process and introduce an integrated testbed for spatio-temporal wildfire propagation.
Abstract—Industrial electric power grid operation subject to an extreme event requires decision-making by human operators under stressful conditions.
Sep 12, 2024 · Power system operation during wildfires require resiliency-driven proactive control for load shedding, line switching and resource allocation ...
In this work, we model and solve the proactive control problem as a Markov decision process and introduce an integrated testbed for spatio-temporal wildfire ...
Dive into the research topics of 'Reinforcement-Learning-Based Proactive Control for Enabling Power Grid Resilience to Wildfire'. Together they form a unique ...
Jul 12, 2021 · Power system operation during wildfires require resiliency-driven proactive control for load shedding, line switching and resource allocation ...
Reinforcement Learning based Proactive Control for Enabling Power Grid Resilience to Wildfire. IEEE Transactions on Industrial Informatics. Impact Factor ...
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This paper [24] introduces an innovative approach to enhance power grid resilience against wildfires using reinforcement learning (RL). By developing a ...
This chapter focuses on the integration of ML into transmission system operation during wildfires for resiliency-driven proactive control.
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