Project description DEENESFRITPL Making building energy systems easier to operate The EU is moving away from fossil fuels and paving the way for a greener future with plans for near-zero energy homes. CO2 heat pumps will play a key role in a decarbonised future of building heating systems. The EU-funded ROCOCO2HP project will work to increase the efficiency of such systems. It is developing efficient real-time optimal control (RTOC) for the CO2 heat pump as part of a building energy supply system. The project will combine scientific expertise on RTOCs with advanced experimental conditions with the CO2 heat pump for residential heating use at the host laboratory. Machine learning methods will be used to develop the non-linear system model. The findings of this project will bring new knowledge and theories to develop new RTOCs, which currently have large computational load that in turn makes them difficult to operate with real building energy systems. Show the project objective Hide the project objective Objective The aim of this project is to develop efficient real-time optimal control (RTOC) for the carbon dioxide (CO2) heat pump as a part of a building energy supply system and validate its reliability experimentally. This is necessary to increase the system efficiency. For a high system efficiency with CO2 heat pumps for heating purpose, a low water return temperature from building heating systems is crucially important. However, this is still difficult to achieve due to well-established heating solutions and control strategies that are not suitable for CO2 heat pumps. CO2 is considered as one natural refrigerant, which has the merit of nonflammability, non-toxicity, and low price when compared with traditional refrigerants. Current well-functioning control methods are developed for heat pumps based on HFCs. Current RTOCs have the disadvantage of large computational load, which makes them difficult to operate with real building energy systems. Furthermore, experimental validations for the developed RTOC cannot be conducted due to lack of advanced experimental conditions. A reliable and experimental-validated RTOC for CO2 heat pump systems is urgently needed. This project will be developed by combining my scientific expertise on RTOCs with advanced experimental conditions with the CO2 heat pump for residential heating use at the host laboratory. Model-based predictive control (MPC) will be used to develop the RTOC. Machine learning methods will be used to develop the non-linear system model. Further, the RTOC with multiplexed optimization strategy (MOS) will be implemented in simulation environment. After the reliability of the developed RTOC in simulation environment is validated, the RTOC will be tested in experimental conditions. Finally, the reliability of the developed RTOC will be validated in experimental conditions. This project will bring new knowledge and theories to develop the RTOC for CO2 heat pump systems and will help me become an independent researcher. Fields of science engineering and technologymechanical engineeringthermodynamic engineeringnatural sciencescomputer and information sciencesartificial intelligencemachine learningnatural sciencescomputer and information sciencessoftwaresoftware applicationssimulation software Programme(s) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Topic(s) MSCA-IF-2019 - Individual Fellowships Call for proposal H2020-MSCA-IF-2019 See other projects for this call Funding Scheme MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF) Coordinator NORGES TEKNISK-NATURVITENSKAPELIGE UNIVERSITET NTNU Net EU contribution € 202 158,72 Address Hogskoleringen 1 7491 Trondheim Norway See on map Region Norge Trøndelag Trøndelag Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00
