Pinned Repositories
-SceneMover
Project of Siggraph Asia 2020 paper: Scene Mover: Automatic Move Planning for Scene Arrangement by Deep Reinforcement Learning
DRLforPowerSystemRecovery
Master Thesis Project for DRL in power system restoration using renewables
dyreson_etal_2021_earthsfuture
Regional Connections are Key to Planning for Future Power System Operations under Climate Extremes
Forecast-Electricity-Load-Demand-Using-Deep-Learning-Models
Forecast the Short Term Electricity Load Demand for Panama Power System using Deep Learning Models
Grid-ML
Power grid optimization problem solvers
Grid2Op
Grid2Op a testbed platform to model sequential decision making in power systems.
IntelliHealer
IntelliHealer: An imitation and reinforcement learning platform for self-healing distribution networks
load_forecasting_web_system
The project aims to use machine learning technology to achieve high-precision day-ahead load forecasting, to provide a reliable basis for market scheduling and market pricing, and to provide support for the formulation of urban power equipment maintenance plans.
MES_resilience
Model-to-predict-Energy-consumption-City-of-Seattle
Use Seattle's public energy data and build a model predicting energy consumption
ruoshuishui's Repositories
ruoshuishui/-SceneMover
Project of Siggraph Asia 2020 paper: Scene Mover: Automatic Move Planning for Scene Arrangement by Deep Reinforcement Learning
ruoshuishui/DRLforPowerSystemRecovery
Master Thesis Project for DRL in power system restoration using renewables
ruoshuishui/dyreson_etal_2021_earthsfuture
Regional Connections are Key to Planning for Future Power System Operations under Climate Extremes
ruoshuishui/Forecast-Electricity-Load-Demand-Using-Deep-Learning-Models
Forecast the Short Term Electricity Load Demand for Panama Power System using Deep Learning Models
ruoshuishui/Grid-ML
Power grid optimization problem solvers
ruoshuishui/Grid2Op
Grid2Op a testbed platform to model sequential decision making in power systems.
ruoshuishui/IntelliHealer
IntelliHealer: An imitation and reinforcement learning platform for self-healing distribution networks
ruoshuishui/load_forecasting_web_system
The project aims to use machine learning technology to achieve high-precision day-ahead load forecasting, to provide a reliable basis for market scheduling and market pricing, and to provide support for the formulation of urban power equipment maintenance plans.
ruoshuishui/MES_resilience
ruoshuishui/Model-to-predict-Energy-consumption-City-of-Seattle
Use Seattle's public energy data and build a model predicting energy consumption
ruoshuishui/Multi-feature-power-load-forecasting-based-on-deep-learning
基于深度学习的多特征电力负荷预测
ruoshuishui/passenger
ruoshuishui/PowerGridworld
PowerGridworld provides users with a lightweight, modular, and customizable framework for creating power-systems-focused, multi-agent Gym environments that readily integrate with existing training frameworks for reinforcement learning (RL). https://arxiv.org/abs/2111.05969
ruoshuishui/PowerSystems.jl
Data structures in Julia to enable power systems analysis. Part of the Scalable Integrated Infrastructure Planning Initiative at the National Renewable Energy Lab.
ruoshuishui/Reinforcement-Learning_for_Energy_Minimization_Using_CLoudsim
Implementation of RL in the cloud for energy minimization due to migration and excess power consumption.
ruoshuishui/robustACOPF
Codes and data supplemental files for the paper "Robust Optimization for Electricity Generation"
ruoshuishui/Short-Term-Wind-Speed-Prediction-based-on-Deep-Learning
LSTM neural network realizes the prediction of wind speed through the learning of various parameters. It can provide important support for the smooth operation of power system and the optimization of control strategy. The fuzzy rough set theory is used to reduce many factors that affect wind speed. It simplifies the input of the neural network prediction model and improves the accuracy and speed. Compared with the traditional neural network prediction method, MAE and MAPE in FRS-LSTM wind speed forecasting model have decreased and the accuracy has been improved greatly.
ruoshuishui/Smart-Grid-VPP-Creation-Simulation
Optimization of Virtual Power Plant formation process using Game Theory
ruoshuishui/SOE
This is the Matlab code for the Switch Opening and Exchange (SOE) method used in paper "Switch Opening and Exchange Method for Stochastic Distribution Network Reconfiguration" that has been accepted by and will be published in IEEE Transactions on Smart Grid.
ruoshuishui/Transactive-Energy-with-Reinforcment-Learning-Deep-Q-Network
Energy trading using DQN