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Training artificial neural networks by generalized likelihood ratio method:exploring brain-like learning to improve adversarial defensiveness
This repository contains source code necessary to reproduce the results presented in the following paper: Stability Constrained Reinforcement Learning for Real-Time Voltage Control (https://arxiv.o…
Supplementary spreadsheet for papaer "Review of Learning-Assisted Power System Optimization"
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Updated Sep 1, 2020
Model-based Reinforcement Learning for Optimal Power Flow
A toolbox for Distribution Optimal Power Flow (D-OPF) Algorithms
Benchmarks for the Optimal Power Flow Problem
The implementation of NeurIPS_2020_L2RPN_Track1(Robustness) and Track2 (Adaptability) Competition
Documents used for grad school application
Implementation of adversarial training under fast-gradient sign method (FGSM), projected gradient descent (PGD) and CW using Wide-ResNet-28-10 on cifar-10. Sample code is re-usable despite changing…
DQN, double DQN and Dueling DQN in electric power sistem control
This repository is a tool for visualizing an agent RL process from a grid2op format. It was made though a partnership between RTE and Artelys for the different challengers of the L2RPN RL Challenge.
An open-source platform for applying Reinforcement Learning for Grid Control (RLGC)
Grid2Op a testbed platform to model sequential decision making in power systems.
Reinforcement Learning Testbed for Power Consumption Optimization using EnergyPlus
It's a implementation about the paper Liang Huang, Suzhi Bi, and Ying-jun Angela Zhang, "Deep Reinforcement Learning for Online Computation Offloading in Wireless Powered Mobile-Edge Computing Netw…
We implemented a general, extensible Environment of a Smart Grid with the ability to simulate interactions between multiple Sources and Loads. Using the Environment, we implemented RL Battery Agent…
Thesis based on the development of a RL agent that manages a VPP through EVs charging stations. Main optimization objectives of the VPP are: Valley filling and peak shaving. Main action performed t…
Reinforcement Learning for Energy Imbalance Management using Voltage Control on TCLs
Implementations of DQN, DQN with PER, DDQN with PER, and DDDQN with PER agents to maximise reward in a 14 node power grid station
Warning: This project does not have any current developer. See bellow.