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Main Authors: Grandits, Thomas, Coss, Stefano, Haase, Gundolf
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2505.21679
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author Grandits, Thomas
Coss, Stefano
Haase, Gundolf
author_facet Grandits, Thomas
Coss, Stefano
Haase, Gundolf
contents District heating networks play a vital role in thermal energy supply in many countries. Thus, it comes to no surprise that these has been a central role in improving energy efficiency for private and public energy suppliers alike around the globe. Many studies have previously investigated the potential of energy saving by low temperature operation of the DHN and the integration of renewable energies. Many other studies consider this problem in terms of mixed integer lin-ear programming. Here, we instead investigate the utilization of well-established continuous optimization methods to improve DHN operation efficiency. We demonstrate that optimal control is able to model low temperature operation of a DHN for savings of around 8%, but can even further improve its operation when considering dynamic energy pricing, reducing the cost of operation by roughly 12%. We demonstrate the applicability of this method in a realistic, openly available network in Switzerland (OpenDHN), with a total runtime of less than 5 minutes on a standard desktop com-puter per experiment.
format Preprint
id arxiv_https___arxiv_org_abs_2505_21679
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Optimal dynamic thermal plant control: A study and benchmark
Grandits, Thomas
Coss, Stefano
Haase, Gundolf
Optimization and Control
District heating networks play a vital role in thermal energy supply in many countries. Thus, it comes to no surprise that these has been a central role in improving energy efficiency for private and public energy suppliers alike around the globe. Many studies have previously investigated the potential of energy saving by low temperature operation of the DHN and the integration of renewable energies. Many other studies consider this problem in terms of mixed integer lin-ear programming. Here, we instead investigate the utilization of well-established continuous optimization methods to improve DHN operation efficiency. We demonstrate that optimal control is able to model low temperature operation of a DHN for savings of around 8%, but can even further improve its operation when considering dynamic energy pricing, reducing the cost of operation by roughly 12%. We demonstrate the applicability of this method in a realistic, openly available network in Switzerland (OpenDHN), with a total runtime of less than 5 minutes on a standard desktop com-puter per experiment.
title Optimal dynamic thermal plant control: A study and benchmark
topic Optimization and Control
url https://arxiv.org/abs/2505.21679