The use of reversibly operated high-temperature fuel cell CHP-modules (rSOC-CHP) enables in the fuel cell mode (i) a highly efficient production of electricity and heat directly at the location of consumption and (ii) also offers the possibility to locally produce and store green hydrogen if the system is operating in electrolysis mode. Operating the rSOC-CHP module in the fuel cell mode enables the conversion of the chemical energy of a gasiform fuel (e.g. natural gas) and an oxidizer directly into electrical energy by only producing very low emissions. Heat and water are gained as by-products. The resulting heat can be used for hot water preparation and for room heating. The fed-in of surplus heat into the district heating grid is also an option. In electrolysis mode, steam is converted into green hydrogen with the help of electricity generated from renewable energy sources and stored for later use. This operation is particularly favored by the low tariff periods resulting from the fluctuating generation of wind and photovoltaic systems. The stored green hydrogen can be used in fuel cell mode as a completely emission-free alternative to natural gas. The project also aims to investigate the addition of hydrogen to natural gas (feed into the natural gas grid) or the partial substitution of fossil fuels with hydrogen and their influence on the behavior of the entire infrastructure. Due to the simple scalability of the rSOC-CHP technology, not only the sustainable supply of single-family and multi-party houses, but also of larger office complexes up to entire city districts could be realized. In the project CELL4LIFE, this technology is to be examined primarily in the context of increasing the autarky rate and the resilience of plus-energy districts. Both reliability and durability must be increased in order to accelerate the commercialization of solid oxide fuel cells. A time-efficient and accurate prediction of system performance as a function of the operating environment could reduce the time required to find the operating optimum within a wide range of parameters. In order to predict the performance of the rSOC-CHP technology, a forecasting method based on a neural network is being developed in CELL4LIFE.
|Effective start/end date||1/09/21 → 31/08/25|
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