An improved numerical model to predict the operating temperature and efficiency of solar photovoltaic systems

Solar photovoltaic (PV) technology has a huge potential for producing renewable energy and reducing greenhouse gas emissions. An increase in the PV cell temperature in real operating conditions reduces the actual output of a solar PV system. A 1D transient multi-layered model, based on the fundamentals of the finite difference method, has been developed to predict the operating cell temperature. Since a PV system operates in stochastic wind conditions and is not subjected to any predefined thermal boundary condition, several expressions of convection coefficient have been scientifically analyzed to determine the most suitable expression. The novel calculation approach assumes explicit radiation terms and implicit convection terms to linearize the equations and get rid of any iterative process. Comparison with experimental results shows that the convection coefficient derived from boundary layer theory corresponding to uniform heat flux predicts the cell temperature with the best accuracy showing a mean error of only $3.92\%$ and $0.{95}^{o}C$ . Splitting the heat source across different solar PV layers produces a maximum change of $0.{14}^{o}C$ only and can be avoided due to the involved complexity. The study proposes a new piece-wise function for PV efficiency in terms of cell temperature and irradiation. This novel function predicts PV efficiency on a sunny and a cloudy day with $1.62\%$ and $1.25\%$ mean errors, respectively, which are considerably lower than errors obtained using other popular functions in the literature. The model helps in predicting actual output from a PV system more accurately which should enable taking more informed decisions regarding the location of installation, PV technology, and the need for a cooling method.