Grasshopper optimization algorithm for parameter estimation of photovoltaic modules based on the single diode model

This paper presents an accurate application of the Grasshopper Optimization Algorithm (GOA) for estimating the optimal parameters of the single diode model (SDM) of a photovoltaic (PV) module from experimental data, which as is well known, and its non-linear current vs voltage (I–V) profile make its modeling challenging. The accuracy and execution time obtained with GOA were compared with metaheuristic techniques such as genetic algorithm (GA) and particle swarm optimization algorithm (PSO). The analysis and validation were effectuated on four different types of PV modules for each optimization algorithm, confirming a good relation between computational time and reliability of GOA in estimating the parameters of the PV module.