Coyote optimization algorithm for parameters extraction of three-diode photovoltaic models of photovoltaic modules

Energy ◽  
2019 ◽  
Vol 187 ◽  
pp. 116001 ◽  
Author(s):  
Mohammed H. Qais ◽  
Hany M. Hasanien ◽  
Saad Alghuwainem ◽  
Adnan S. Nouh
2017 ◽  
Vol 2017 ◽  
pp. 1-8
Author(s):  
Wenjuan Jiang ◽  
Yunbo Shi ◽  
Wenjie Zhao

The accuracy of the magnetic core model is important to the analysis and design of the flux-gate sensor. The Jiles-Atherton model (J-A model) is the mostly used model to describe the hysteresis characteristics of the flux-gate core. But the parameters of J-A model are difficult to identify. In this paper, Fruit Fly Optimization Algorithm (FOA) is proposed to identify the parameters of the J-A model. In order to enhance the performance of the identification, a Modified Fruit Fly Optimization Algorithm (MFOA) is applied to extract the parameters of the flux-gate core. The effectiveness of MFOA is verified through five typical test functions. The influence of variation factor h on the performance of MFOA is discussed. The impact of variation factor h on parameters extraction of hysteresis loop is studied. It is shown that MFOA with appropriate selection of variation factor h will get better performance in the accuracy, stability, and simulation time compared to those of PSO and FOA.


Solar Energy ◽  
2017 ◽  
Vol 144 ◽  
pp. 594-603 ◽  
Author(s):  
Peijie Lin ◽  
Shuying Cheng ◽  
Weichang Yeh ◽  
Zhicong Chen ◽  
Lijun Wu

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Abdelhady Ramadan ◽  
Salah Kamel ◽  
Mahmoud M. Hussein ◽  
Mohamed H. Hassan

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