Modeling-Based Energy Performance Assessment and Validation of Air-To-Water Heat Pump System Integrated with Multi-Span Greenhouse on Cooling Mode

Abstract

The purpose of this study was to conduct a modeling-based energy performance assessment and validation of an air-to-water heat pump (AWHP) system, in the cooling mode, integrated with a multi-span greenhouse using TRNSYS software. We used the building energy simulation (BES) model to investigate the performance characteristics of the AWHP system for greenhouse cooling. We modelled the components of the AWHP system, including the fan coil unit (FCU), water storage tank, and water circulation pump integrated with the greenhouse model. The proposed model included all the components of the experimental system. We validated the proposed model by comparing the simulation results with those obtained from field experiments. We investigated the cooling energy supply to the multi-span greenhouse, greenhouse internal air temperature, heat pump (HP) output temperature, and coefficient of performance (COP). We evaluated the performance of our model by calculating the Nash–Sutcliffe efficiency (NSE) coefficient of all the validated components. Furthermore, we performed linear regression analyses (R2) to determine the relationship between the different parameters. NSE values of 0.87, 0.81, and 0.93, for the greenhouse internal air temperature, the energy supply to the greenhouse, and the HP output water temperature, respectively, validated the prediction accuracy of the model. Moreover, R2 values of 0.83 and 0.39 indicated that cooling loads are more dependent on ambient solar radiation than ambient air temperature. Furthermore, an R2 value of 0.91 showed a linear relationship between the HP’s energy consumption and ambient air temperature. The average daily COP of the HP system was 2.9. Overall, the simulation results showed acceptable correlation with the experimental results. The high NSE values validated the high predictive power of the model. The proposed validation model can be used to improve the performance of systems by optimizing the control strategies and capacities of the equipment (e.g., the HP, the FCU, and the area of the greenhouse). We have provided detailed information to enable engineers, researchers, and consultants to implement the model for their specific needs.