Performance degradation of air source heat pumps under faulty conditions

Abstract

The ongoing European regulations towards the decarbonization of energy intensive sectors such as heating and cooling will lead to an increase of heat pump appliances. Apart from anomalies that can be detected in a preliminary phase after the start-up, soft faults such as refrigerant leakage and heat exchanger fouling may cause a performance degradation in such systems that evolves in time and that must be detected before it becomes too big. From this perspective, in a previous paper (Pelella et al. [1]) it has been demonstrated that, in cooling mode, a seasonal performance penalization up to 50% can be reached in case of a not-planned maintenance scenario, whereas wherever a timed or intelligent maintenance strategy is implemented based on data-monitoring, this impact can be significantly reduced. Therefore, in order to extend the analysis previously carried out to the heating cases, and to evaluate the consequent energetic degradation of the system in case of soft faults occurring, depending on different climate conditions and maintenance scenarios, this paper develops a physic-based model to simulate system components and to describe the fault phenomenology on a residential 2.6 kW air-to-air heat pump, operating in winter mode. The results show that in heating mode a 40% condenser fouling and a 30% refrigerant leakage cause a performance degradation of respectively 16% and 12%, whereas in case of evaporator fouling the performance penalization is only of 3.2%. Moreover, the performance degradation is enhanced by the overlapping effect of simultaneous faults. Finally, from seasonal simulations of the heat pump along an entire machine lifetime of 12 years, it is found that none of the maintenance strategies analysed is able to significantly reduce the number of scenarios penalized by faults, opening to the potential development of systems for the automatic fault detection, diagnosis, and evaluation (FDDE).

Keywords

• Heat pumps
• Physics-based model
• Soft faults
• Seasonal performance degradation
• Fault detection
• Diagnosis and evaluation