Gas engine heat pump system: Experimental facility and thermal evaluation for 5 different units

Gas Engine Heat Pump requires simplified characterization models that allow evaluating its economic and energy impacts. These simplified solutions can be implemented in complex simulation algorithms for different commercial solutions with a low computational cost. The study aims to develop a simplif...

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Detalles Bibliográficos
Autores: Sánchez Ramos, José, Guerrero Delgado, M. Carmen, Álvarez Domínguez, Servando, Molina Féliz, José Luis, Cabeza, Luisa F.
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2019
País:España
Institución:Universitat de Lleida (UdL)
Repositorio:Repositori Obert UdL
OAI Identifier:oai:repositori.udl.cat:10459.1/66708
Acceso en línea:https://doi.org/10.1016/j.enconman.2019.112060
http://hdl.handle.net/10459.1/66708
Access Level:acceso abierto
Palabra clave:Gas engine-driven heat pump
Experimental model
Waste heat recovery
Thermal characterization
Inverse modelling
Descripción
Sumario:Gas Engine Heat Pump requires simplified characterization models that allow evaluating its economic and energy impacts. These simplified solutions can be implemented in complex simulation algorithms for different commercial solutions with a low computational cost. The study aims to develop a simplified characterization model highly accurate, easy to reproduce and apply. The methodology carried out uses an experimental installation to analyze different units tested under different operating conditions. With the results of the carried out experimentation, it will be possible to know the real thermal response of these HVAC systems and to develop the simplified characterization model based on operating curves. The thermal behaviour of the systems could be evaluated using the defined curves under any operating condition of the GEHP system. Moreover, they are based on parameters available in the manufacturer datasheets. The results of the validation show that this model is highly accurate. It has a maximum error of 25% and an average error of less than 7%. Also, the formulation shows that it is easy to reproduce and to apply. Last, uncertainty analysis shows reasonable confidence in the identified performance curves.