Performance prediction and optimization of a photovoltaic thermal system integrated with phase change material using response surface method

In this study, a predictive model is developed based on the response surface method (RSM), to show the relationship between the operating factors (independent parameters) and some important response factors (dependent parameters) of a photovoltaic thermal system integrated with phase change material (PVT/PCM). The considered phase change material is the Rubitherm (RT) series of organic phase change materials. Moreover, both single and multi-objective optimization are conducted using RSM for different optimization objectives to recommend the optimal values of control factors for different operating conditions. The selected operating factors include PCM layer thickness, solar radiation, melting temperature of PCM and ambient temperature. Five response factors, including electrical power, thermal power, electrical exergy, thermal exergy and entropy generation are considered. To evaluate the model statistical adequacy, diagnostic analysis is performed for each response to indicate that the predictive model has a reasonable accuracy. The analysis of variance (ANOVA) test and perturbation analysis are also applied to evaluate the suitability and statistical importance of the recommended model and they show that the sensitivity of solar radiation on energy and exergy outputs is higher than that of other operating factors. According to the results, to maximize the electrical power, thermal power, electrical exergy, thermal exergy, and to minimize the entropy generation, simultaneously, it is recommended to select the PCM layer thickness of 1.5 cm, solar radiation of 901 W/m(2), melting temperature of 25 degrees C, and the ambient temperature of 40 degrees C, based on the proposed method in this study. (C) 2020 Elsevier Ltd. All rights reserved.