Modeling of Solar Power Plant Using a Neural Network Based on the Equivalent of a Single Diode

Various methods have been proposed for modeling solar panels, but modeling solar power plants using them is associated with challenges. In equivalent circuit-based methods, the modeling depends on factory data that changes over time. Modeling of voltage-current characteristic using intelligent methods such as neural network was less considered due to the low accuracy of modeling. In this article, a method independent of the manufacturer's data for modeling the solar power plant is presented, so that it is possible to accurately model the solar power plants that have been installed for several years. The proposed method consists of two steps, in the first step, open circuit voltage, maximum power point and short circuit current are modeled according to atmospheric conditions using neural network. In the second step, the unknown parameters of the equivalent circuit are determined by circuit analysis relations and using neural network outputs. Finally, to evaluate the proposed method, a 3-kW solar power plant was modeled, and the results show the appropriate accuracy of the proposed method for modeling the solar power plant.