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

CORDIS · observation · Publication date unknown

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 p

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recordType

award

status

SIGNED

region

EU

value

263393.28

unit

EUR