A Novel Theoretical and Practical Methodology for Extracting the Parameters of the Single and Double Diode Photovoltaic Models

Abstract

Solar Photovoltaic (PV) system is one of the most significant forms of renewable energy resources, and it requires accuracy to assess, design, and extraction of its parameters. In the literature, several methods have been extensively applied to mimic the nonlinearity and multi-model behavior of the PV system in order to maximize its accuracy, reliability, and overall system cost. However, there is no method to date that can guarantee the extracted parameter of the PV model is the most accurate one. Therefore, this paper presents a unique approach known as Hybridized Arithmetic Operation Algorithm (HAOA) based on Efficient Newton Raphson (ENR) to experimentally extract the parameters of the single-diode (SD) and double-diode (DD) PV models at the variability of the climatic changes. Firstly, the formulation of the objective function is efficiently built to roughly predict the initial root values of the PV equation. Secondly, the Lévy flight and Brownian strategies are integrated with four AOA to thoroughly analyze the feature space of this problem. The chaotic map and robust mutation techniques are systematically employed in the beginning and halves of generations to ensure the algorithm can reach globally at few numbers iterations. The experimental findings revealed that the proposed HAOA-ENR outperformed all other methods found in the literature, with average RMSE values of 4.96E-35 and 9.43E-36 for the SD and DD PV models, respectively. The experimental comparison and statistical criteria prove the ability of the proposed HAOA-ENR to estimate the parameter of any PV model at any weather conditions with zero or tiny error values.

Keywords: PV model; Parameters extraction; AOA; Newton Raphson method; Lambert W function