search

TU-Delft-AI-Energy-Lab / MARL-iDR-Multi-Agent-Reinforcement-Learning-for-Incentive-based-Residential-Demand-Response

Code for the paper "MARL-iDR: Multi-Agent Reinforcement Learning for Incentive-based Residential Demand Response"
MIT License
18 stars 5 forks source link
demand-response demand-side-management energy-consumption energy-system human-computer-interaction incentive-program multi-agent-reinforcement-learning

readme

Case study for MARL-iDR-Multi-Agent-Reinforcement-Learning-for-Incentive-based-Residential-Demand-Response

This repository contains code for the paper:

Jasper van Tilburg, Luciano C. Siebert, Jochen L. Cremer, "MARL-iDR: Multi-Agent Reinforcement Learning for Incentive-based Residential Demand Response" IEEE PowerTech 2023, Belgrade, Serbia, https://arxiv.org/abs/2304.04086

Data

This repository includes only placeholder Excel files in /data which includes the first and last data samples. The full data that was used in the case studies in our paper can be downloaded from “Pecan Street Inc.” [Online]. Available: https://www.pecanstreet.org/

License

This work is licensed under a License: MIT