Search Results for author: Hou Shengren

Found 2 papers, 2 papers with code

Optimal Energy System Scheduling Using A Constraint-Aware Reinforcement Learning Algorithm

1 code implementation • 9 May 2023 • Hou Shengren, Pedro P. Vergara, Edgar Mauricio Salazar Duque, Peter Palensky

To overcome this, in this paper, a DRL algorithm (namely MIP-DQN) is proposed, capable of \textit{strictly} enforcing all operational constraints in the action space, ensuring the feasibility of the defined schedule in real-time operation.

energy management reinforcement-learning +3

Paper
Code

Performance Comparison of Deep RL Algorithms for Energy Systems Optimal Scheduling

1 code implementation • 1 Aug 2022 • Hou Shengren, Edgar Mauricio Salazar, Pedro P. Vergara, Peter Palensky

This trade-off introduces extra hyperparameters that impact the DRL algorithms' performance and capability of providing feasible solutions.

energy management Reinforcement Learning (RL) +1

Paper
Code

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