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Project of Siggraph Asia 2020 paper: Scene Mover: Automatic Move Planning for Scene Arrangement by Deep Reinforcement Learning
Master Thesis Project for DRL in power system restoration using renewables
Regional Connections are Key to Planning for Future Power System Operations under Climate Extremes
Forecast the Short Term Electricity Load Demand for Panama Power System using Deep Learning Models
Power grid optimization problem solvers
Grid2Op a testbed platform to model sequential decision making in power systems.
IntelliHealer: An imitation and reinforcement learning platform for self-healing distribution networks
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.
Use Seattle's public energy data and build a model predicting energy consumption
基于深度学习的多特征电力负荷预测
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
Data structures in Julia to enable power systems analysis. Part of the Scalable Integrated Infrastructure Planning Initiative at the National Renewable Energy Lab.
Implementation of RL in the cloud for energy minimization due to migration and excess power consumption.
Codes and data supplemental files for the paper "Robust Optimization for Electricity Generation"
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.
Optimization of Virtual Power Plant formation process using Game Theory
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.
Energy trading using DQN
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.