The Development of a Multiple Linear Regression Model To Predict the Performance of a Hybrid Solar Air Source Heat Pump Water Heater

AIUE Proceedings of the 2nd Energy and Human Habitat Conference 2021

7 Pages Posted: 7 Sep 2021

See all articles by Mandlenkosi Sikhonza

Mandlenkosi Sikhonza

Fort Hare University

S Tangwe

University of Fort Hare

C Manyi-Loh

University of Fort Hare

Date Written: July 26, 2021

Abstract

The hybrid solar air source heat pump (HSASHP) water heater comprised of a solar water heater (SWH) and an air source heat pump (ASHP) water heater. The study deal with the design and building of a multiple linear regression model to predict the energy factor of a residential HSASHP water heater installed in a residence in King Williams town with four adult occupants. A data acquisition system was built and employed to monitor the performance of the HSASHP water heater. The input parameters were the total volume of hot water consumed, the average ambient temperature and the global solar irradiance per day. The modelled was developed for the summer season and the correlation coefficient and the p-value between the model and the actual energy factor was 0.97 and 0.83, respectively. Furthermore, the prediction of the model output and the validated data gave excellent results of 0.98 for the correlation coefficient and 0.79 for the p-value. We can conclude that the mathematical model could predict the energy factor with more than 95% confidence level. The findings can assist homeowners and energy service companies to predict the energy and cost savings achieved by the HSASHP water heater when compared to the counterpart standalone electric geyser.

Keywords: Hybrid solar air source heat pump water heater, multiple linear regression model, energy factor, correlation coefficient, p-value

Suggested Citation

Sikhonza, Mandlenkosi and Tangwe, S and Manyi-Loh, C, The Development of a Multiple Linear Regression Model To Predict the Performance of a Hybrid Solar Air Source Heat Pump Water Heater (July 26, 2021). AIUE Proceedings of the 2nd Energy and Human Habitat Conference 2021, Available at SSRN: https://ssrn.com/abstract=3901087

Mandlenkosi Sikhonza (Contact Author)

Fort Hare University ( email )

South Africa

S Tangwe

University of Fort Hare

South Africa

C Manyi-Loh

University of Fort Hare

South Africa

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