lexian0326

lexian0326's Stars

• LabGong/psc4ddea

  Useful relevant papers and open source codes for Data-Driven Evolutionary Algorithms (DDEAs)

  Language:MATLAB131

• h-hg/DDEA

  Language:MATLAB3816

• thieu1995/mealpy

  A Collection Of The State-of-the-art Metaheuristic Algorithms In Python (Metaheuristic/Optimizer/Nature-inspired/Biology)

  Language:Python939193

• thomasmong/llm-power-scheduling

  Language:Python1310

• e2nIEE/pandapower

  Convenient Power System Modelling and Analysis based on PYPOWER and pandas

  Language:Python915492

• JiaxuanYou/pytorch_geometric

  Graph Neural Network Library for PyTorch

  Language:Python1

• snap-stanford/GraphGym

  Platform for designing and evaluating Graph Neural Networks (GNN)

  Language:Python1.7k187

• thu-ml/tianshou

  An elegant PyTorch deep reinforcement learning library.

  Language:Python8.1k1.1k

• MATPOWER/mpng

  MPNG

  Language:MATLAB106

• U-C4N/JECSO-MOPSO

  JECSO-MOPSO is a specialized multi-objective optimization algorithm for jet engine component sizing. It enhances the standard MOPSO algorithm to efficiently handle jet engine design constraints and improve Pareto-optimal solutions.

  Language:Python3

• RoydeZomer/IOC-SAMO-COBRA

  Efficient Multi-Objective Optimization for Problems with (In)expensive Objectives and Constraints

  Language:Python31

• bitzhangcy/Neural-PDE-Solver

  848122

• JonasBergHansen/Power-Flow-Balancing-with-Decentralized-Graph-Neural-Networks

  Repository code for Power Flow Balancing with Decentralized Graph Neural Networks

  Language:Python214

• StavrosOrf/DRL-for-Energy-Systems-Optimal-Scheduling

  The source code for Performance comparision of Deep RL algorithms for Energy Systems Optimal Scheduling

  Language:Python2

• Thinklab-SJTU/awesome-ml4co

  Awesome machine learning for combinatorial optimization papers.

  Language:Python1.8k203

• Mzhou-cityu/DeepOPF-Codes

  This repository stores the main codes for the DeepOPF projects.

  Language:Python222

• imezghani/StochasticACOPF

  Code of the paper: Stochastic AC Optimal Power Flow: A Data-Driven Approach

  Language:MATLAB176

• michaelfsb/hydrogen-energy-storage

  This project is in development. It is my attempt to MathWorks' Excellence in Innovation Project 204. This work will be part of my MSc in Automation and Systems Engineering at the Federal University of Santa Catarina.

  Language:MATLAB112

• Shuai-Lu/Supplement--Aggregate-Model-of-DHN-A-Physically-Informed-Data-Driven-Approach

  This repository provides the supplementary information for the paper "Aggregate Model of District Heating Network for Integrated Energy Dispatch: A Physically Informed Data-Driven Approach".

  4

• RahulNellikkath/Physics-Informed-Neural-Network-for-DC-OPF

  This repository contains the code for Physics-Informed Neural Network for DC Optimal Power Flow applications and the worst case guarantees

  Language:MATLAB246

• JarvisETHZ/Daline

  Daline: A Data-driven Power Flow Linearization Toolbox for Power Systems Research and Education

  Language:MATLAB17

• slow295185031/MOEA-dev

  Language:Matlab5380

• MLopez-Ibanez/irace

  Iterated Racing for Automatic Algorithm Configuration

  Language:R6215

• drgona/deeplearning-models

  A collection of various deep learning architectures, models, and tips

  4

• EMI-Group/evox

  Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.

  Language:Python24041

• Ntung029/LCOH-analysis

  Techno-economic analysis of hydrogen production cost in wholesale electricity markets

  Language:MATLAB167

• danielayamashita/Hierarchical-Building-Microgrid

  Implementation of a building hierarchical control for Microgrid using Model Predictive Control (MPC).

  1211

• jacopobr/optimal-residential-building-oslo

  The smart building concept aims to use smart technology to reduce energy consump- tion, as well as to improve comfort and users’ satisfaction. Forecasting of the indoor temperature is necessary for the regulation of energy devices to ensure occupant comfort, as well as for energy optimization.

  Language:Jupyter Notebook32

• WJ-Guo/MSCPSO

  the code of parper MSCPSO, (Multiple scale self-adaptive cooperation mutation strategy-based particle swarm optimization. Applied Soft Computing. 2020. )

  Language:MATLAB51

• BIMK/PlatEMO

  Evolutionary multi-objective optimization platform

  Language:MATLAB1.7k478