energy management system for the microgrid

The Source code for paper "Optimal Energy System Scheduling Combining Mixed-Integer Programming and Deep Reinforcement Learning". Safe reinforcement learning, energy management

Energy Management Using Real-Time Non-Intrusive Load Monitoring

Artificial Load Profile Generator for DSM

Comwatt Integration for HomeAssistant

Harness the power of deep reinforcement learning to optimize your Home Energy Management System (HEMS). Our tailored agent, trained on the CoSES ProHMo Modelica framework, efficiently controls a building's heat pump and thermal storage valve.

DRL-based ESSs scheduling environments in distribution networks.

DEMKit Toolkit Core

This repository is used to generate data and evaluate Decision Transformers on the CityLearn (Challenge 2022) environment for urban energy management

Explore efficient energy management in renewable communities through the implementation of Model Predictive Control (MPC) and Reinforcement Learning (RL). This GitHub repository houses the codebase for optimizing renewable energy systems, promoting sustainable practices and smart energy utilization. MSc Mechanical Eng Thesis // Pier Luca Anania

Python-based utility for interfacing with the PZEM-017 DC Energy Monitoring Device. Easily read, modify settings, and monitor energy consumption of your solar or battery systems. Developed with assistance from ChatGPT by OpenAI.

"Game of Strom" is an interactive platform for energy management. Users optimize electricity costs in a virtual household manually or through AI-driven technologies. The application integrates real-life devices and services including PV systems, storage, electric cars, and dynamic pricing structures

In this repository, we explore the application of Transformer-based Reinforcement Learning approaches to solve complex real-world energy management problems using the CityLearn environment (Challenge 2022 and 2023).

A Python client library for interacting with the Comwatt API.

Shelly 3 EM Control is a Python program that enables interaction with Shelly 3 EM devices through cloud APIs. It allows for periodic data retrieval from sensors, which is then stored in a PostgreSQL database. The program also features a Tkinter-based graphical interface for convenient device management.

AI Crowd Competition implementing various Deep Reinforcement Learning methods for energy management control

Home assistant ČEZ HDO integration

A simulation for a virtual electric grid

Energy management for connecting your home to the electrical grid

DEMKit Scenario Example