Parameter estimation of solar cell models is an important part of photovoltaic power generation system. However, it is still a challenging problem. In this study, an adaptive differential evolution with linear population reduction, called LRJADE, is developed to accurately estimate solar cell models parameters. In LRJADE, the linear population reduction strategy is employed to accelerate convergence speed. Additionally, the crossover rate repairing is also used. The performance of proposed LRJADE is verified by 13 benchmark functions and two solar cell model parameter estimation problems. Simulated results show that LRJADE not only obtains promising results in benchmark functions, but also achieves the very accurate solutions to solar cell model parameter estimation problems.
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St Peters Univ, St Peters Inst Higher Educ & Res, Madras, Tamil Nadu, IndiaSt Peters Univ, St Peters Inst Higher Educ & Res, Madras, Tamil Nadu, India
Chellaswamy, C.
Ramesh, R.
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Saveetha Engn Coll, Dept Elect & Commun Engn, Madras, Tamil Nadu, IndiaSt Peters Univ, St Peters Inst Higher Educ & Res, Madras, Tamil Nadu, India
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College of Automation & College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing,210023, ChinaCollege of Automation & College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing,210023, China
Yu, Yang
Wang, Kaiyu
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Faculty of Engineering, University of Toyama, Toyama-shi,930-8555, JapanCollege of Automation & College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing,210023, China
Wang, Kaiyu
Zhang, Tengfei
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College of Automation & College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing,210023, ChinaCollege of Automation & College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing,210023, China
Zhang, Tengfei
Wang, Yirui
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Faculty of Electrical Engineering and Computer Science, Ningbo University, Zhejiang,315211, ChinaCollege of Automation & College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing,210023, China
Wang, Yirui
Peng, Chen
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Department of Automation, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai,200444, ChinaCollege of Automation & College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing,210023, China
Peng, Chen
Gao, Shangce
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Faculty of Engineering, University of Toyama, Toyama-shi,930-8555, JapanCollege of Automation & College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing,210023, China
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Zarqa Univ, Fac Informat Technol, Dept Comp Sci, Zarqa 13110, JordanZarqa Univ, Fac Informat Technol, Dept Comp Sci, Zarqa 13110, Jordan
Aljaidi, Mohammad
Jangir, Pradeep
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Saveetha Inst Med & Tech Sci, Saveetha Sch Engn, Dept Biosci, Chennai 602105, India
Chandigarh Univ, Univ Ctr Res & Dev, Mohali 140413, India
Graph Era Hill Univ, Graph Era Deemed Univ, Dept CSE, Dehra Dun 248002, Uttarakhand, India
Appl Sci Private Univ, Appl Sci Res Ctr, Amman 11937, JordanZarqa Univ, Fac Informat Technol, Dept Comp Sci, Zarqa 13110, Jordan