Gossen's First Law in the Modeling for Demand Side Management: A Thorough Heat Pump Case Study with Deep Learning based partial Time Series Data Generation
This repo contains the Matlab and Python implementation for the paper:
Chang Li, Gina Brecher, Jovana Kovačević, Hüseyin K. Çakmak, Kevin Förderer, Jörg Matthes, Veit Hagenmeyer. 2024. Gossen's First Law in the Modeling for Demand Side Management: A Thorough Heat Pump Case Study with Deep Learning based partial Time Series Data Generation. Energy Informatics. DOI: https://doi.org/10.1186/s42162-024-00353-z
- 'Matlab': This folder contains the codes used for the implementation of Random Forest (RF), the modified persistence model and the validation of the proposed hypothesis.
- 'Python': This folder contains the codes used for the implementation of LSTM and Transformer.
- 'Data': This file contains the data source.
This project is licensed under the terms of the MIT license. See the LICENSE file for details.