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The impact of heat pumps on day-ahead energy community load forecasting

Author

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  • Semmelmann, Leo
  • Hertel, Matthias
  • Kircher, Kevin J.
  • Mikut, Ralf
  • Hagenmeyer, Veit
  • Weinhardt, Christof

Abstract

The rapid ramp-up of heat pump installations in modern power systems constitutes an outstanding challenge for energy community and distribution grid operators. Accurate load forecasts can help community and grid operators to reduce electricity demand peaks by managing flexible devices. This paper shows that installed heat pumps change the load patterns, autocorrelation and peak loads of energy communities, as well as the most suitable forecasting methods. Based on a case study with real-world household and heat pump loads from Hamelin, Germany, we show significant improvements in forecasting quality by employing Transformer models. We publish our underlying data set, feature engineered data, forecasting results, best-performing methods, and benchmarking pipeline open-source, to contribute to the advancement of load forecasting in energy communities with heat pumps.

Suggested Citation

  • Semmelmann, Leo & Hertel, Matthias & Kircher, Kevin J. & Mikut, Ralf & Hagenmeyer, Veit & Weinhardt, Christof, 2024. "The impact of heat pumps on day-ahead energy community load forecasting," Applied Energy, Elsevier, vol. 368(C).
    • Handle: RePEc:eee:appene:v:368:y:2024:i:c:s0306261924007475
    DOI: 10.1016/j.apenergy.2024.123364
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    References listed on IDEAS

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    Cited by:

    1. Adam Maryniak & Marian Banaś & Piotr Michalak & Jakub Szymiczek, 2024. "Forecasting of Daily Heat Production in a District Heating Plant Using a Neural Network," Energies, MDPI, vol. 17(17), pages 1-19, September.

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