A repository of awesome Non-Intrusive Load Monitoring(NILM) with code.

A Python library for DLMS/COSEM

A Python library for IEC62056-21, Local Data Readout of Energy Meters. Former IEC1107

MESMO - Multi-Energy System Modeling and Optimization

Easy SimAuto (ESA): An easy-to-use Power System Analysis Automation Environment atop PowerWorld Simulator Automation Server (SimAuto)

EVLib is a library for the management and the simulation of Electric Vehicle (EV) activities, at a charging station level, within a Smart Grid environment.

This repo contains all the codes and data for 'Blending Data and Physics Against False Data Injection Attack: An Event-Triggered Moving Target Defence Approach'

PowerBiMIP is an open-source, efficient bilevel mixed-integer programming (BiMIP) solver, with a special focus on applications in power and energy systems.

GridAttackSim: Smart Grid Attack Simulation Framework

smart substation connection and configuration software based on IEC 61850 protocal and SCD file. Email: 570503271@qq.com

Готовая сборка webpack c сеткой smart-grid

Comwatt Integration for HomeAssistant

A diploma thesis investigating the options of controlling power demand of households to reduce peaks in total power consumption in smart grids.

Energy production of photovoltaic (PV) system is heavily influenced by solar irradiance. Accurate prediction of solar irradiance leads to optimal dispatching of available energy resources and anticipating end-user demand. However, it is difficult to do due to fluctuating nature of weather patterns.  In the study, neural network models were defined to predict solar irradiance values based on weather patterns. Models included in the study are artificial neural network, convolutional neural network, bidirectional long-short term memory (LSTM) and stacked LSTM.  Preprocessing methods such as data normalization and principal component analysis were applied before model training. Regression metrics such as mean squared error (MSE), maximum residual error (max error), mean absolute error (MAE), explained variance score (EVS), and regression score function (R2 score), were used to evaluate the performance of model prediction. Plots such as prediction curves, learning curves, and histogram of error distribution were also considered as well for further analysis of model performance. All models showed that it is capable of learning unforeseen values, however, stacked LSTM has the best results with the max error, R2, MAE, MSE, and EVS values of 651.536, 0.953, 41.738, 5124.686, and 0.946, respectively.

Smart Meter Data Analytics Tutorial @ 11th International Conference on Learning Representations (ICLR 2023)

Simulations code for MSc thesis.

pycity_scheduling - A Python framework for the development and assessment of optimization-based power scheduling algorithms for multi-energy systems in city districts. To cite this Original Software Publication: https://www.sciencedirect.com/science/article/pii/S2352711021001230

Scripts for a university project, a simple centralized smart grid energy cost minimization problem.

MATLAB code and data for the article 📋: I. Daminov, A. Prokhorov, R. Caire, M-C Alvarez-Herault, “Assessment of dynamic transformer rating, considering current and temperature limitations” in International Journal of Electrical Power & Energy Systems (IF: 3,588, Q1), 2021

Distribution System Simulator based on OpenDSS and OpenDSSDirect.py. Modern Syntax, DataFrames, Pint, Networkx, Algorithmic Agents.

HEAPO – An Open Dataset for Heat Pump Optimization with Smart Electricity Meter Data and On-Site Inspection Protocols

Implementation of bagging-based ensemble for solar irradiance prediction. Base learners used in ensemble learning is stacked-LSTM

A Comparative Study of Multi-Objective and Neuroevolutionary-based Reinforcement Learning Algorithms for Optimizing Electric Vehicle Charging and Load Management

A Graph Reinforcement Learning model that combines RL and Graph Neural Networks to solve Dynamic Economic Power Dispatch

Contains the code for the paper "Multi-Horizon Short-Term Load Forecasting Using Hybrid of LSTM and Modified Split Convolution"

A Deadline-Aware, Incentive-Compatible and Proportionally-Fair Mechanism for EV Charging in Distribution Grids

HTML layout for Richbee. The parallax effect has been implemented. System of modal windows with warnings. The development used GULP, BEM, BABEL, WEBPACK, SCSS, SMARTGRID

This project contains an extensible GAN Framework which can be used to generate power grid related data for simulations.

A Multi-Agent Reinforcement Learning (MARL) based pricing and incentive strategy for demand response in smart grids.

A simulator for blockchain-based local energy markets