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This paper focused on the performance monitoring and modeling of a 6.0 kW, 2000 L hybrid direct expansion solar assisted heat pump (DX-SAHP) water heater used for the production of hot water in a university students’ accommodation with 123 females. The data of total electrical energy consumed, volume of hot water consumed, ambient temperature, relative humidity, and solar irradiance were obtained from the data acquisition systems and analyzed in conjunction with the energy factor (EF) of the system. A multiple linear regression model was developed to predict the EF. The EF of the hybrid DX-SAHP water heater was determined from the summation of the coefficient of performance (COP) of the heat pump unit and the solar fraction (SF) of the solar collectors. The operations of the hybrid energy system were analyzed based on three phases (first phase from 00:00–08:00, second phase from 08:30–18:30, and third phase from 19:00–23:30) over 24 h for the entire monitoring period. The average EF of the hybrid energy system per day during the second phase of operation was 4.38, while the SF and COP were 0.697 and 3.683, respectively. The developed multiple linear regression model for the hybrid DX-SAHP water heater accurately predicted the determined EF.

This study quantifies the potential of a 4.0 kW air source heat pump (ASHP) unit retrofitted to a 12.0 kW, 1000 L electric boiler coupled to a 1000 L storage tank. A data acquisition system was built to monitor the performance of the electric boiler and the ASHP water heater. The annual electrical energy saving and the load factor reduction from the electric boiler because of the ASHP unit retrofit was 34,805.94 kWh and 0.124. The net present value payback period of the ASHP system was 1.60 years. A Wilcoxon rank sum test was employed to compare both the volumes of hot water and electrical energy consumed by the two systems. Linear regression models of the daily volumes of hot water and electrical energy consumed by both systems were established. The results should be of great value to the management of universities that are considering energy-efficient interventions with a significant return on investment.