1. Design and monitoring of a hybrid energy system: performance analysis and modelling
- Author
-
Stephen Tangwe and Mandlenkosi Sikhonza
- Subjects
General Computer Science ,business.industry ,General Chemical Engineering ,Electric potential energy ,solar fraction ,General Engineering ,Hybrid energy ,Coefficient of performance ,Energy factor ,Engineering (General). Civil engineering (General) ,data acquisition system ,Solar water ,multiple linear regression model ,Reduction (complexity) ,Data acquisition ,hybrid solar water heater and air source heat pump water heater ,Air source heat pumps ,energy factor ,Environmental science ,TA1-2040 ,Process engineering ,business ,coefficient of performance - Abstract
The utilization of a hybrid energy system (combined solar water heater (SWH) and an air source heat pump (ASHP) water heater) can result in over 80% reduction in the electrical energy consumed as the system is capable to operate with an energy factor of above 4.0. A major challenge is to develop credible methodology or mathematical model to predict energy savings. The research focused on the design and installation of a hybrid energy system and a data acquisition system to monitor its performance. The average weekday volume of hot water consumed, thermal energy gained by water in the tank of the air source heat pump (ASHP) water heater, electrical energy consumed, and the COP were 225.03 L, 5.25 kWh, 1.52 kWh, and 3.50. The average weekday global solar radiation, ambient temperature, solar fraction of the solar water heater (SWH) and the energy factor of the hybrid energy system were 579.67 W/m2, 23.58°C, 0.52, and 4.02, respectively. A multiple linear regression model was developed to predict the energy factor of the hybrid energy system. Both the modelled and validated results showed very good determination coefficients of 0.952 and 0.935, with the trained and validated dataset. Hence, by employing both multiple linear regression model and a multiple 2D contour plot simulation, the energy factor and the variation of the input parameters can be accurately determined. The developed model can help homeowners, energy service companies, and policy makers to appreciate and confidently support the rollout of the technology for sanitary water heating.
- Published
- 2021