Examinando por Autor "Ramadan, Abdelhady"
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Ítem Parameter Estimation of Modified Double-Diode and Triple-Diode Photovoltaic Models Based on Wild Horse Optimizer(MDPI, 2021-09) Ramadan, Abdelhady; Kamel, Salah; Taha, Ibrahim B. M.; Jurado-Melguizo, FranciscoThe increase in industrial and commercial applications of photovoltaic systems (PV) has a significant impact on the increase in interest in studying the improvement of the efficiency of these systems. Estimating the efficiency of PV is considered one of the most important problems facing those in charge of manufacturing these systems, which makes it interesting to many researchers. The difficulty in estimating the efficiency of PV is due to the high non-linear current–voltage characteristics and power–voltage characteristics. In addition, the absence of ample efficiency information in the manufacturers’ datasheets has led to the development of an effective electrical mathematical equivalent model necessary to simulate the PV module. In this paper, an application for an optimization algorithm named Wild Horse Optimizer (WHO) is proposed to extract the parameters of a double-diode PV model (DDM), modified double-diode PV model (MDDM), triple-diode PV model (TDM), and modified triple-diode PV model (MTDM). This study focuses on two main objectives. The first concerns comparing the original models (DDM and TDM) and their modification (MDDM and MTDM). The second concerns the algorithm behavior with the optimization problem and comparing this behavior with other recent algorithms. The evaluation process uses different methods, such as Root Mean Square Error (RMSE) for accuracy and statistical analysis for robustness. Based on the results obtained by the WHO, the estimated parameters using the WHO are more accurate than those obtained by the other studied optimization algorithms; furthermore, the MDDM and MTDM modifications enhanced the original DDM and TDM efficiencies.Ítem Parameter Estimation of Static/Dynamic Photovoltaic Models Using a Developed Version of Eagle Strategy Gradient-Based Optimizer(MDPI, 2021-11) Ramadan, Abdelhady; Kamel, Salah; Hassan, Mohamed H.; Tostado-Véliz, Marcos; Eltamaly, Ali M.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.