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Energies 2017, 10(7), 865; doi:10.3390/en10070865

A Chaotic Improved Artificial Bee Colony for Parameter Estimation of Photovoltaic Cells

Departamento de Ciencias Computacionales, Universidad de Guadalajara, CUCEI. Av. Revolución 1500, Guadalajara, 44430 Jalisco, Mexico
Institute of Cybernetics, Tomsk Polytechnic University, 634050 Tomsk, Russia
Scientific Research Group in Egypt (SRGE), Cairo 12613, Egypt
Department of Computer, Damietta University, Damietta 34517, Egypt
School of Computer Science and Technology, Wuhan University of Technology, Wuhan 430070, China
Department of Mathematics, Faculty of Science, Zagazig University, Zagazig 44519, Egypt
Faculty of Computers Information, Cairo University, Cairo 12637, Egypt
Author to whom correspondence should be addressed.
Received: 9 May 2017 / Revised: 23 June 2017 / Accepted: 24 June 2017 / Published: 28 June 2017
View Full-Text   |   Download PDF [2777 KB, uploaded 29 June 2017]   |  


The search for new energy resources is a crucial task nowadays. Research on the use of solar energy is growing every year. The aim is the design of devices that can produce a considerable amount of energy using the Sun’s radiation. The modeling of solar cells (SCs) is based on the estimation of the intrinsic parameters of electrical circuits that simulate their behavior based on the current vs. voltage characteristics. The problem of SC design is defined by highly nonlinear and multimodal objective functions. Most of the algorithms proposed to find the best solutions become trapped into local solutions. This paper introduces the Chaotic Improved Artificial Bee Colony (CIABC) algorithm for the estimation of SC parameters. It combines the use of chaotic maps instead random variables with the search capabilities of the Artificial Bee Colony approach. CIABC has also been modified to avoid the generation of new random solutions, preserving the information of previous iterations. In comparison with similar optimization methods, CIABC is able to find the global solution of complex and multimodal objective functions. Experimental results and comparisons prove that the proposed technique can design SCs, even with the presence of noise. View Full-Text
Keywords: solar cells; photovoltaic modules; artificial bee colony; chaotic maps; parameter estimation solar cells; photovoltaic modules; artificial bee colony; chaotic maps; parameter estimation

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Oliva, D.; Ewees, A.A.; Aziz, M.A.E.; Hassanien, A.E.; Peréz-Cisneros, M. A Chaotic Improved Artificial Bee Colony for Parameter Estimation of Photovoltaic Cells. Energies 2017, 10, 865.

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