The effects of coolant mass flow rate and atmospheric indicators in a PV/T system with experimental and ANN's models

In this study, the effects of the mass flow rate of coolant and other atmospheric and positional variables on the performance and efficiency of a PV/T system have been experimentally researched and modeled with ANN's models. Mass flow rate, irradiance, ambient temperature, wind speed, wind direction, relative humidity and coolant water inlet temperature have been measured while solar azimuth angle and solar elevation angle have been calculated. These parameters have been selected as the input parameters (independent variables), mainly having the preliminary focus on the mass flow rate of the coolant. The performance parameters namely, electrical power production, thermal energy production, total energy production, temperature decrease on the PV module, electrical efficiency increase, surface temperature of the PV module and water outlet temperature for the PV modules have been experimentally measured. They were also computed by ANN models, as the output variables (dependent variables) with the most robust estimation of FBPANN based models depending on the real measurement data set from the experimental works. The relevance of the dependability of each targeted variables were revealed by statistical indicators in order to maintain the sensitivity of the ANN calculations. Among all the dependent parameters that were predicted by the ANN models, the strictest predictions were found for electrical power production by the FFANN1 model with the R value of 99.985% and the R2 value of 99.971%. Also, all of the performance parameters have robustly been predicted by the FFANN models. Besides, the order of importance of the predictors that effects dependent variables has been found. The mass flow rate has been determined to be highly effective on electrical efficiency increase, surface temperature of the PV module, electrical power production, thermal energy production and total energy production. The benefit of the present work is that the effects of daily working parameters such as mass flow rate of coolant with respect to the other atmospheric indicators on instantaneous electrical and thermal performance of a PV or PV/T system can be robustly predicted with their order of importance with the developed ANN models. It will make the investors to easily manage their systems.