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Adaptation du régulateur du système de pompe à chaleur aux besoins du bâtiment : évaluation des courbes de chauffe adaptées à l’aide de méthodes basées sur les données.

Tailoring the heat pump system controller to the building: assessment of adapted heating curves using data-driven methods.

Numéro : 3148

Auteurs : WILL F., KLINGEBIEL J., VERING C., MÜLLER D.

Résumé

Space heating accounts for a large share of energy consumption in Germany due to fossil fuel combustion. To reduce combustion-related emissions, space heating electrification with heat pumps is promising. However, heat pumps increase the power demand related to the electrical grid. Therefore, minimizing the additional electrical power consumed by heat pumps is crucial, which can be achieved by either lowering the heating demand or enhancing the overall efficiency. While lowering the heating demand due to improvements to the building envelope is very cost-intensive, increasing the heat pump efficiency is substantially more cost-effective.
To achieve high efficiencies with heat pumps, low supply temperatures are required. Today, static heating curves (HCs) connect the heat pump with a specific building. Conventionally, the HC correlates the ambient temperature with the supply temperature. This method captures the fundamental principle that colder ambient conditions necessitate higher supply temperatures. While HCs are favored for their simplicity in implementation, inefficiencies arise as parameters and form of HC are usually chosen based on simplified heuristics which cannot capture building specifications and user behavior. Hence, a method to tailor the HC to the building and its usage is promising to increase efficiency while maintaining thermal comfort.
This paper introduces a method that optimizes the parameters and form of the HC by using data-driven models. Therefore, relevant data is collected in a system identification process using a conventional HC. The data is used to generate data-driven models that autonomously detect the underlying patterns between ambient conditions and supply temperature. From these models, a self-optimized HC (soHC) is derived using the DICE algorithm. We assess the performance of the soHC with different heating systems in annual building energy system performance simulations. The soHC outperforms the conventional HC in terms of efficiency with a decrease in energy usage of up to 7.3 % while maintaining thermal comfort. In future research, enhancements can be achieved by incorporating specific conditions like solar irradiation and presence detection into the approach.

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Pages : 10 p.

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Détails

  • Titre original : Tailoring the heat pump system controller to the building: assessment of adapted heating curves using data-driven methods.
  • Identifiant de la fiche : 30032968
  • Langues : Anglais
  • Source : 2024 Purdue Conferences. 8th International High Performance Buildings Conference at Purdue.
  • Date d'édition : 15/07/2024

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