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Found 5 papers, 1 papers with code
An Optimization Method-Assisted Ensemble Deep Reinforcement Learning Algorithm to Solve Unit Commitment Problems
Unit commitment (UC) is a fundamental problem in the day-ahead electricity market, and it is critical to solve UC problems efficiently.
A Reinforcement Learning-based Volt-VAR Control Dataset and Testing Environment
To facilitate the development of reinforcement learning (RL) based power distribution system Volt-VAR control (VVC), this paper introduces a suite of open-source datasets for RL-based VVC algorithm research that is sample efficient, safe, and robust.
Learning to Operate an Electric Vehicle Charging Station Considering Vehicle-grid Integration
In this paper, we propose a novel centralized allocation and decentralized execution (CADE) reinforcement learning (RL) framework to maximize the charging station's profit.
Consensus Multi-Agent Reinforcement Learning for Volt-VAR Control in Power Distribution Networks
Volt-VAR control (VVC) is a critical application in active distribution network management system to reduce network losses and improve voltage profile.
Information Losses in Neural Classifiers from Sampling
It then bounds this expected total variation as a function of the size of randomly sampled datasets in a fairly general setting, and without bringing in any additional dependence on model complexity.
