Proceedings of the International Renewable Energy Storage and Systems Conference (IRES 2023)

Potential of a Long-Term Predictive Controller for Managing Energy Storages to Reduce the Electric Grid-Load of an Air-Source Heat Pump

Authors
David Schmitt1, *, Tobias Reum1, Thorsten Summ1, Christoph Trinkl1, Tobias Schrag1
1Institute of New Energy Systems (InES), Technische Hochschule Ingolstadt, Esplanade 10, 85049, Ingolstadt, Germany
*Corresponding author. Email: david.schmitt@thi.de
Corresponding Author
David Schmitt
Available Online 11 July 2024.
DOI
10.2991/978-94-6463-455-6_21How to use a DOI?
Keywords
Storage Management; Peak Shaving; Predictive Control; Air-Source Heat Pump
Abstract

Electrifying the domestic heating sector is mandatory to decarbonize the buildings sector but leads to additional peak loads in the public grid. Air-source heat pumps the mostly used technology in this regard even though, they suffer from lower efficiency during times of high heat demands. The usage of energy storages and predictive controllers enables operation shifting and hence offers potential to decrease the peak loads in the electric grid. This potential can be increased by using a longer prediction horizon as extended operation shifting can be performed. In this contribution, a methodology to derive the theoretical potential on the grid peak load reduction of such a long-term predictive controller is introduced. The electric load profile of an air-source heat pump in a typical German single-family home was generated based on different weather data scenarios for the city of Ingolstadt. Based on the profile the dependency between peak load reduction and required storage capacity was identified. In the case study a reduction of the peak load from 21 – 31% for an unrenovated building was achieved using a 500 L buffer storage. Further investigation needs to be done to derive a more realistic potential for renovated or new buildings.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Renewable Energy Storage and Systems Conference (IRES 2023)
Series
Atlantis Highlights in Engineering
Publication Date
11 July 2024
ISBN
978-94-6463-455-6
ISSN
2589-4943
DOI
10.2991/978-94-6463-455-6_21How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - David Schmitt
AU  - Tobias Reum
AU  - Thorsten Summ
AU  - Christoph Trinkl
AU  - Tobias Schrag
PY  - 2024
DA  - 2024/07/11
TI  - Potential of a Long-Term Predictive Controller for Managing Energy Storages to Reduce the Electric Grid-Load of an Air-Source Heat Pump
BT  - Proceedings of the International Renewable Energy Storage and Systems Conference (IRES 2023)
PB  - Atlantis Press
SP  - 205
EP  - 211
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-455-6_21
DO  - 10.2991/978-94-6463-455-6_21
ID  - Schmitt2024
ER  -