Parameter Estimation of PV Cells and Modules using Ant Lion Optimizer (ALO) Algorithm

Estimating parameters of the circuit model of photovoltaic (PV) cells and modules is one of the most important challenges in solar energy. Today, with the development and proliferation of the application of optimization algorithms, the problem of estimating the parameter of the photovoltaic module can be converted into an optimization problem. In this paper, using the Ant Lion Optimizer (ALO) algorithm, all parameters of the two-diode model of the photovoltaic system are determined. This algorithm is a population-based algorithm that has a fast convergence speed and obtains reliable results. Also, to verify the accuracy of the results, the results of the ALO algorithm were compared with the results of the Gravitational Search Algorithm (GSA), Harmony Search (HS), Pattern Search (PS) and experimental points for the RTC France photovoltaic cell and the photovoltaic module Photowatt-PWP 201. As per the simulation results, the root mean square error (RMSE) given by ALO algorithm is lower than that of other three algorithms, which signifies the more precision provided by ALO in estimating the PV cell / module parameters.