ROCOCO2HP SIGNED
Real-time optimal control of the CO2 heat pump system for residential use
Total Cost €
0EC-Contrib. €
0Partnership
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0ROCOCO2HP project word cloud
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Project "ROCOCO2HP" data sheet
The following table provides information about the project.
| Coordinator |
NORGES TEKNISK-NATURVITENSKAPELIGE UNIVERSITET NTNU
Organization address contact info |
| Coordinator Country | Norway [NO] |
| Total cost | 202˙158 € |
| EC max contribution | 202˙158 € (100%) |
| Programme |
1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility) |
| Code Call | H2020-MSCA-IF-2019 |
| Funding Scheme | MSCA-IF-EF-ST |
| Starting year | 2020 |
| Duration (year-month-day) | from 2020-03-01 to 2022-02-28 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | NORGES TEKNISK-NATURVITENSKAPELIGE UNIVERSITET NTNU | NO (TRONDHEIM) | coordinator | 202˙158.00 |
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Project 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.
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The information about "ROCOCO2HP" are provided by the European Opendata Portal: CORDIS opendata.