huabulengdeng's repositories
Combined-Heat-and-Power-System-Economic-Dispatch
Deep reinforcement learning approaches for CHP system economic dispatch
Data-for-Robust-planning-of-IEHS
Data for Robust planning of IEHS
Integrated-Energy-Systems-with-CAES
The optimal dispatch of CAES in the integrated energy systems
LoadPredicting
AARIMA,K-MEANS,DBN,FFNN,GBRT,LSTM,RFR,SEQ2SEQ,SVR,XGBOOST
Algorithms_MathModels
【国赛】【美赛】数学建模相关算法 MATLAB实现
autonomous-energy-controller-RL
Deep reinforcement learning for autonomous energy management
D3HRE
Data Driven Dynamic Hybrid Renewable Energy design and simulation framework
Data_IES_case
This is the data of an integrated energy system case.
DRL-for-microgrid-energy-management
We study the performance of various deep reinforcement learning algorithms for the problem of microgrid’s energy management system. We propose a novel microgrid model that consists of a wind turbine generator, an energy storage system, a population of thermostatically controlled loads, a population of price-responsive loads, and a connection to the main grid. The proposed energy management system is designed to coordinate between the different sources of flexibility by defining the priority resources, the direct demand control signals and the electricity prices. Seven deep reinforcement learning algorithms are implemented and empirically compared in this paper. The numerical results show a significant difference between the different deep reinforcement learning algorithms in their ability to converge to optimal policies. By adding an experience replay and a second semi-deterministic training phase to the well-known Asynchronous advantage actor critic algorithm, we achieved considerably better performance and converged to superior policies in terms of energy efficiency and economic value.
Economic-Load-dispatch-using-Genetic-Algorithm
An efficient optimization procedure based on genetic algorithm for the solution of economic load dispatch
EnergyPlus-co-simulation-toolbox
Simulate runtime binded EnergyPlus models from Matlab/Simulink.
Geosciences_Exploration
Practical skills in areas such as data analysis, regressions, optimization, spectral analysis, differential equations, image analysis, computational statistics, and Monte Carlo simulations. Emphasis is on scientific and engineering applications.
heat-power-plant-reinforcement-learning-experiment
RL in Energy Space
nempy
A flexible tool kit for modelling Australia's National Electricity Market dispatch procedure.
Online-Recurrent-Extreme-Learning-Machine
Online-Recurrent-Extreme-Learning-Machine (OR-ELM) for time-series prediction, implemented in python
opem
OPEM (Open Source PEM Fuel Cell Simulation Tool)
Ph.D-Thesis-On-CAES
All materials associated with my Ph.D. thesis, titled 'Research on Flexibility Modeling and Operation of Advanced Adiabatic Compressed Air Energy Storage at Source-Grid-Load Side'. 博士论文：源-网-荷先进绝热压缩空气储能灵活性建模及运行研究
RES_nuc
French electricity sector dispatch model for renewable electricity resources and nuclear energy
RLenergy
Optimal energy dispatch with reinforcement learning
scikit-opt
Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization Algorithm,Immune Algorithm, Artificial Fish Swarm Algorithm, Differential Evolution and TSP(Traveling salesman)
Smart-homes-and-weather_Evaluating-energy-use-efficiency-
Smart building technology allow buildings to be more efficient, comfortable and easier to manage by connecting IOT devices, collaborate, analyze and use real time intelligence with IOT applications and solutions as part of a Smart Building platform. A challenge for the implementation of such technologies is the evaluation of the energy use efficiency under variable climatic conditions during a year. GOALS Evaluate and predict energy efficiency performance from solar energy during a year and variable weather conditions. Tools to be used: Python Pandas, Scikit-Learn, Matplotlib Evaluate in what state of the USA solar energy is more or less efficient Tools to be used: Plotly or leaflet or D3 or Tableau (To be determined...)
Solar-Cells-Fuel-Cells-Batteries-and-Supercapacitors
Energy storage and conversion systems
TPA-LSTM
Temporal Pattern Attention for Multivariate Time Series Forecasting
TPWRS2019-PSP
Source code for Mou, Yuting, Anthony Papavasiliou, and Philippe Chevalier. "A Bi-Level Optimization Formulation of Priority Service Pricing." IEEE Transactions on Power Systems (2019).
TSE2018-SDDP
Model for paper on IEEE transactions on sustainable energy: Application of Stochastic Dual Dynamic Programming to the Real-Time Dispatch of Storage under Renewable Supply Uncertainty
Two_Layer_EMS
Code for IEEE Transactions: A Two-Layer Energy Management System for Microgrids With Hybrid Energy Storage Considering Degradation Costs.