Performance analysis of concentrated photovoltaic system with compound parabolic concentrator using deep learning

Concentrated photovoltaic (CPV) technologies are well established technology for harnessing the solar power. CPV technologies employ low-cost optical components called concentrators to increase the incident solar energy on the photovoltaic (PV) module, thereby increasing the total energy output. The distribution of the concentrated heat flux and temperature on the PV module is crucial in deciding the thermal and electrical efficiency. Thus, the implementation of an effective cooling system is necessary for providing enhanced performance from the CPV system. In the present work, 116 parallel microchannels heat sink has been used to regulate the temperature of PV module present at the receiver of a 5x concentration ratio compound parabolic concentrator. A 3D CFD numerical model of CPV system is analyzed by coupling the concentrated heat flux obtained from optical investigation employing Monte Carlo Ray Tracing. Optical Analysis uses accurate Buie sunshape for representing the distribution of solar radiation in the solar disk and incorporation of surface errors for enhanced accuracy. The PV module is modelled in MATLAB Simulink for obtaining the electrical power. An artificial neural network is adopted to predict the essential parameters for electrical modeling involving concentrated heat flux, temperature, photocurrent, saturation current, series and shunt resistances. Correlation Coefficient (R2), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) error metrices were used to evaluate the model’s performance having direct normal irradiation (DNI), angle of incidence (AOI), ambient temperature (Tamb), wind speed (vw) and distance of PV cell from the centre of the module (D) as input variables. A high R2 value of 0.9993 for concentrated heat flux and 0.9915 for temperature were achieved with maximum cell temperature well below the critical temperature of 358 K. Maximum electrical power of 179 W was obtained at 840 W/m2 DNI with 7.6˚ angle of incidence.