Parameter Estimation of Static/Dynamic Photovoltaic Models Using a Developed Version of Eagle Strategy Gradient-Based Optimizer

Abdelhady Ramadan,Ali M Eltamaly,Mohamed H Hassan,Salah Kamel,Marcos Tostado-Véliz

doi:10.3390/su132313053

Abdelhady Ramadan, Ali M Eltamaly + Show 3 more

Open Access

https://doi.org/10.3390/su132313053

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Abstract

The global trend towards renewable energy sources, especially solar energy, has had a significant impact on the development of scientific research to manufacture high-performance solar cells. The issue of creating a model that simulates a solar module and extracting its parameter is essential in designing an improved and high performance photovoltaic system. However, the nonlinear nature of the photovoltaic cell increases the challenge in creating this model. The application of optimization algorithms to solve this issue is increased and developed rapidly. In this paper, a developed version of eagle strategy GBO with chaotic (ESCGBO) is proposed to enhance the original GBO performance and its search efficiency in solving difficult optimization problems such as this. In the literature, different PV models are presented, including static and dynamic PV models. Firstly, in order to evaluate the effectiveness of the proposed ESCGBO algorithm, it is executed on the 23 benchmark functions and the obtained results using the proposed algorithm are compared with that obtained using three well-known algorithms, including the original GBO algorithm, the equilibrium optimizer (EO) algorithm, and wild horse optimizer (WHO) algorithm. Furthermore, both of original GBO and developed ESCGBO are applied to estimate the parameters of single and double diode as static models, and integral and fractional models as examples for dynamic models. The results in all applications are evaluated and compared with different recent algorithms. The results analysis confirmed the efficiency, accuracy, and robustness of the proposed algorithm compared with the original one or the recent optimization algorithms.

Highlights

Since the surge in fossil fuel prices, the world’s attention has turned to renewable energy sources, such as wind and solar energy
The integer dynamic model is considered the more popular dynamic model and the fractional model has been developed to increase the accuracy of the integer model [18]
The gradient-based optimizer (GBO) algorithm is a proposed metaheuristic optimization algorithm, which is presented in reference [30]

Summary

Introduction

Since the surge in fossil fuel prices, the world’s attention has turned to renewable energy sources, such as wind and solar energy. Solar energy has several advantages beyond resources. These advantages are simple in installation, low maintenance activities, and suitable for different sizes. The mentioned advantages of solar energy are still weak regarding high efficiency [1], increased interest in renewable energy sources has led to an increase in researchers’ interest in developing these systems and increasing their efficiency. Developing an optimal mathematical model that simulates the natural photovoltaic system is one of the biggest challenges for researchers. The difficulty of developing these models is due to the nonlinear properties of solar cells [2]

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Conclusion