Optimal control of a heat pump-based energy system for space heating and hot water provision in buildings: Results from a field test

• Published in: Energy and buildings Vol. 310; p. 114116
• Main Authors: Mbuwir, Brida V., Geysen, Davy, Kosmadakis, George, Pilou, Marika, Meramveliotakis, George, Toersche, Hermen
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.05.2024
• Subjects: Buildings; Domestic hot water; Field test; Heat pump; Model predictive control; Optimisation; PVT collectors; Space heating; Model predictive control; PVT collectors; Field test; Heat pump; Buildings; Optimisation; Domestic hot water; Space heating
• ISSN: 0378-7788
• DOI: 10.1016/j.enbuild.2024.114116

This paper presents and discusses results from a field test that uses model predictive control (MPC) to optimise the operation of a multi-source heat pump-based energy system for space heating and hot water provision in a building. The objective of the optimisation is to minimise the electricity consumption of the heat pump using flexibility from the heat sources, the space heating and domestic hot water tanks while ensuring end-user comfort and system constraints. The field test was performed in the context of the RES4BUILD project. The integrated system consists of photovoltaic-thermal (PVT) collectors, an advanced vapour-compression multi-source heat pump and water buffer tanks for space heating and hot water needs. The heat pump utilises a solar buffer, a borehole thermal energy storage (BTES) and air as heat sources. The solar buffer is supplied with heat from the PVT collectors. The optimal operation of the system is obtained by monitoring and controlling the interactions between the different system components using MPC, taking into account the weather and heat load forecasts. Results have shown that MPC has a potential and added value for the optimal operation of multi-source heat pumps in real-life while considering system constraints and user behaviour to ensure thermal comfort. However, significant effort and expert knowledge are needed to develop the sufficiently accurate system models required by this control approach. The outcomes and conclusions of this work are therefore a basis for further development of such control approaches to improve their replicability and feasibility on a large scale, considering the diverse nature of energy system components in buildings.