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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

Repository Structure

  • '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.

License

This project is licensed under the terms of the MIT license. See the LICENSE file for details.

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