1 citations · 2 across the 3 of their papers we have counts for
3 papers
eess.SY2024
Data-driven Under Frequency Load Shedding Using Reinforcement Learning
Glory Justin, Santiago Paternain
Underfrequency load shedding (UFLS) is a critical control strategy in power systems aimed at maintaining system stability and preventing blackouts during severe frequency drops. Tr…
cs.LG2024★ 1 cited
Adaptive Primal-Dual Method for Safe Reinforcement Learning
Weiqin Chen, James Onyejizu, Long Vu +5
Primal-dual methods have a natural application in Safe Reinforcement Learning (SRL), posed as a constrained policy optimization problem. In practice however, applying primal-dual m…
eess.SP2024★ 1 cited
Learning Non-myopic Power Allocation in Constrained Scenarios
Arindam Chowdhury, Santiago Paternain, Gunjan Verma +2
We propose a learning-based framework for efficient power allocation in ad hoc interference networks under episodic constraints. The problem of optimal power allocation -- for maxi…