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...
| Autores: | , , , , |
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| 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 |
| 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. |
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