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AI-Optimized Control and Integration of Transcritical R744 Heat Pumps for Sustainable Heating Solutions

Project description

How AI could optimise heat pump systems

Heating homes and buildings efficiently is a major challenge in creating a low-carbon society, especially for systems that require substantial energy. R744 (CO2) heat pumps are gaining attention as a sustainable solution because they use an eco-friendly refrigerant and can integrate renewable energy sources (RESs) and hot thermal energy storage (HTES). However, they often do not perform their best, owing to poor control systems, especially when combined with RESs and HTES. Supported by the Marie Skłodowska-Curie Actions programme, the AI-Heat Pump project will develop an AI-driven real-time optimisation algorithm. This algorithm will ensure R744 heat pumps operate at peak efficiency, reducing costs by 15 % in multi-family homes.

Objective

The heating sector is a critical challenge in the global transition toward a low-carbon society, particularly for hard-to-abate applications requiring substantial energy (e.g. residential applications). Among various green technologies, transcritical R744 (CO2) heat pumps have emerged as a future-proof solution thanks to their eco-friendly and safe refrigerant (i.e. R744). On the one hand, R744-based heating systems can reduce dependence on fossil fuels, including Russian gas, especially by integrating renewable energy sources (RESs) and hot thermal energy storages (HTESs), enhancing resilience to energy price fluctuations. On the other hand, its energy and economic performance is hindered by suboptimal control between the heat pump and heat distribution/domestic hot water system, which becomes more complex when integrating RESs and HTES. Thus, the AI-Heat Pump project aims to develop and demonstrate the first ever artificial intelligence (AI)-driven real-time optimization algorithm to allow R744-based heating systems integrated with RESs and a HTES to always operate at the highest cost-effective conditions. The algorithm will be implemented with respect to RES availability, HTES status, heating demand, heat pump/heat distribution status and, electricity price and it will be tested on the transcritical R744 heat pump setup at SDU. Compared to the heat pumps using conventional refrigerants, i.e. synthetic refrigerants often classified as PFAS and/or slightly flammable, the algorithm will allow R744-based heating systems to be about 15 % more cost-effective in multi-family houses. The project will be carried out in close collaboration with the University of Edinburgh (HTES modelling) and Bitzer Electronics A/S (enhanced system control and integration). Therefore, as concrete value and impact, this project will lay robust foundations for sustainable future and thus pave the way for remarkable enhancements for business and society concerning the green heating sector.

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HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

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(opens in new window) HORIZON-MSCA-2025-PF

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Coordinator

SYDDANSK UNIVERSITET
Net EU contribution

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€ 263 393,28
Address
CAMPUSVEJ 55
5230 Odense M
Denmark

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Region
Danmark Syddanmark Fyn
Activity type
Higher or Secondary Education Establishments
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Total cost

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