Extraction of solar cell parameters from a single current–voltage characteristic using teaching learning based optimization algorithm

Abstract

The determination of values of solar cell parameters is of great interest for the evaluation of solar cell performance. This paper proposes a simple, efficient and reliable method to extract all five parameters of a solar cell from a single illuminated current–voltage (I–V) characteristic using teaching learning based optimization (TLBO) algorithm. The TLBO is implemented by developing an interactive numerical simulation using LabVIEW as a programming tool. The effectiveness of the algorithm has been validated by applying it to the reported I–V characteristics of different types of solar cells such as silicon, plastic and dye-sensitized solar cells as well as silicon solar module. The obtained values of parameters by the TLBO algorithm are found to be in very good agreement with reported values of parameters. The algorithm is also applied to the experimentally measured I–V characteristics of a silicon solar cell and a silicon solar module for the extraction of parameters. It is observed that the TLBO algorithm repeatedly converges to give consistent values of solar cell parameters. It is demonstrated that our program based on TLBO algorithm can be successfully applied to a wide variety of solar cells and modules for the extraction of parameters from a single illuminated I–V curve with minimal control variables of the algorithm.