Optimisation of Energy and Exergy Analysis of 100 W Solar Photovoltaic Module Using ANN Method

Abstract

AbstractRenewable technologies are plentiful, long lasting, and eco-friendly. Solar energy, which generates both heat and light, is the most abundant source of energy. Solar photovoltaic modules use solar radiations to generate electricity and thermal energy, while the remaining solar radiation content is lost to the environment. The first law of thermodynamics was used to perform an energy analysis on a solar photovoltaic module, and the second law of thermodynamics was used to perform an exergy analysis to determine energy losses and exergy efficiency during the photovoltaic conversion process. The operating parameters of a solar photovoltaic module are as follows: ambient temperature, photovoltaic module surface temperature, overall heat transfer coefficient, short circuit current, open circuit voltage, fill factor and solar radiation. These were achieved on a sunny day in the month of February at R.L.J.I.T, Doddaballapur. The experimental data are utilised to calculate the solar photovoltaic module’s energy and exergy efficiencies. The efficiency of the solar panel performance decreases as the temperature of the module rises. As a result, by reducing heat from the surface of the solar photovoltaic module, the module’s efficiency can be increased. Surface heat can be eliminated by delivering water or air as a medium to the solar photovoltaic module. Finally, ANN model was developed to determine the performance prediction models using multilayer perceptron neural network, and it reveals that the developed model with six neurons gives better performance with a confidence interval of 95%.KeywordsSolar energyEnergyExergyPhotovoltaic moduleANNPerformance prediction model