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To evaluate the performance of a photovoltaic panel, several parameters must be extracted from the photovoltaic. These parameters are very important for the evaluation, monitoring and optimization of photovoltaic. Among the methods developed to extract photovoltaic parameters from current-voltage (I-V) characteristic curve, metaheuristic algorithms are the most used nowadays. A new metaheuristic algorithm namely enhanced vibrating particles system algorithm is presented here to extract the best values of parameters of a photovoltaic cell. Five recent algorithms (grey wolf optimization (GWO), moth-flame optimization algorithm (MFOA), multi-verse optimizer (MVO), whale optimization algorithm (WAO), salp swarm-inspired algorithm (SSA)) are also implemented on the same computer. Enhanced vibrating particles system is inspired by the free vibration of the single degree of freedom systems with viscous damping. To extract the photovoltaic parameters using enhanced vibrating particles system algorithm, the problem can be set as an optimization problem with the objective to minimize the difference between measured and estimated current. Four case studies have been implemented here. The results and comparison with other methods exhibit high accuracy and validity of the proposed enhanced vibrating particles system algorithm to extract parameters of a photovoltaic cell and module.weather conditions change, analytical methods become ineffective [18].Numerical extraction techniques based on some algorithm fit the points on the PV characteristic curve. Compared to the analytical method, an accurate result can be attained since the algorithm tries to consider all points on the characteristic curve [19]. In the literature, the Newton-Raphson method is the most used [19] [20] [21]; In [22], a numerical method is proposed for modeling and the simulation of PV. The method finds the five parameters from the current-voltage characteristic by using three points of the curve (maximum power, open circuit and short circuit). In [23], the Levenberg Marquardt algorithm is

Parameters extraction is instrumental to standard PV cells design. Reports indicates that heuristic algorithms are the most effective methods for accurately determinining the values of parameters. However, local concentration is against recent heuristic methods, and they are inhibited producing optimal results. This paper seeks to show that combining the heuristics algorithms with the Newton Raphson method can considerably increased the accuracy of results. An inspired artifact technique from the drone squadron simulation from control center is proposed for the extraction of the best constitutive parameters. This study equally provides clarifications on the approaches recently reported and proposed to build objective function. Furthermore, comparative evaluation of the current ten best heuristics algorithms that are published in the PV estimation domain is also undertaken. Moreover, this study investigates the convergence of algorithms when points of the number of current-voltage characteristics are varied. The results from this study highlight the differences between the two formulation, and it shows the best formulation accuracy. The results obtained from seven study cases that are considered in this present study, with the combined Newton Raphson performance method and Drone Squadron optimisation, were employed to extract precise PV module parameters.The study of the numbers of points reveals that the algorithm converges and is more precise when the numbers of points of the I-V characteristic are reduced. However, if these points are minimal, the algorithm will be hindered from returning optimal results.

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