Parameter identification for solar cell models using harmony search-based algorithms |
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| Authors: | Alireza Askarzadeh Alireza Rezazadeh |
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| Affiliation: | 1. School of Mechatronic Engineering and Automation, Shanghai Key Laboratory of Power Station Automation Technology, Shanghai University, Shanghai 200072, China;2. Energy, Power and Intelligent Control, School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast BT9 5AH, UK;1. School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China;2. School of Electric and Information Engineering, Zhongyuan University of Technology, Zhengzhou 450007, China;3. School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, Jiangsu, China;1. Center of Operations Research, Miguel Hernández University of Elche (UMH), Avd. de la Universidad s/n, 03202, Elche, Alicante, Spain;2. Industrial Electronics Group, Miguel Hernández University of Elche (UMH), Avd. de la Universidad s/n, 03202, Elche, Alicante, Spain;1. School of Computer Engineering, Nanyang Technological University, Singapore;2. Faculty of Engineering & Industrial Sciences, Swinburne University of Technology, Australia |
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| Abstract: | Recently, accurate modeling of current vs. voltage (I–V) characteristics of solar cells has attracted the main focus of various researches. The main drawback in accurate modeling is the lack of information about the precise values of the models parameters, namely, photo-generated current, diode saturation current, series resistance, shunt resistance and diode ideality factor. In order to make a good agreement between experimental data and the models results, parameter identification with the help of an optimization technique is necessary. Because I–V curve of solar cells is extremely non-linear, an excellent optimization technique is required. In this paper, harmony search (HS)-based parameter identification methods are proposed to identify the unknown parameters of the solar cell single and double diode models. Simple concept, easy implementation and high performance are the main reasons of HS popularity to solve complex optimization problems. For this aim, three state-of-the-art HS variants are used to determine the unknown parameters of the models. The effectiveness of the HS variants is investigated with comparative study among different techniques. Simulation results manifest the superiority of the HS-based algorithms over the other studied algorithms in modeling solar cell systems. |
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