Enhanced chaotic JAYA algorithm for parameter estimation of photovoltaic cell/modules.

Autor: Premkumar M; Department of Electrical and Electronics Engineering, GMR Institute of Technology, Rajam, Andhra Pradesh 532127, India. Electronic address: premkumar.m@gmrit.edu.in., Jangir P; Rajasthan Rajya Vidyut Prasaran Nigam Ltd., Sikar, Rajasthan 332025, India. Electronic address: pkjmtech@gmail.com., Sowmya R; Department of Electrical and Electronics Engineering, National Institute of Technology, Tiruchirappalli, Tamil Nadu 620015, India. Electronic address: sowmyanitt@gmail.com., Elavarasan RM; Clean and Resilient Energy Systems (CARES) Laboratory, Texas A&M University, Galveston, TX 77553, USA. Electronic address: rajvikram787@gmail.com., Kumar BS; Department of Computer Science and Engineering, GMR Institute of Technology, Rajam, Andhra Pradesh 532127, India. Electronic address: santhosh.b@gmrit.edu.in.
Jazyk: angličtina
Zdroj: ISA transactions [ISA Trans] 2021 Oct; Vol. 116, pp. 139-166. Date of Electronic Publication: 2021 Jan 25.
DOI: 10.1016/j.isatra.2021.01.045
Abstrakt: Parameters for defining photovoltaic models using measured voltage-current​ characteristics are essential for simulation, control, and evaluation of photovoltaic-based systems. This paper proposes an enhanced chaotic JAYA algorithm to classify the parameters of various photovoltaic models, such as the single-diode and double-diode models, accurately and reliably. The proposed algorithm introduces a self-adaptive weight to regulate the trend to reach the optimal solution and avoid the worst solution in various phases of the search space. The self-adaptive weight capability also allows the proposed technique to reach the best solution at the earliest phase, and later, the local search process starts, which also increase the ability to explore. A three different chaotic process, including sine, logistics and tent map, is proposed to optimize the consistency of each generation's best solution. The proposed algorithm and its variants proposed are used to solve the parameter estimation problem of various PV models. To show the proficiency of the suggested algorithm and its variants, an extensive simulation is carried out using MATLAB/Simulink software. Two statistical tests are conducted and compared with the latest techniques for validating the performance of the suggested algorithm and its variants. Comprehensive analysis and experimental results display that the suggested algorithm can achieve highly competitive efficiency in terms of accuracy and reliability compared to other algorithms in the literature. This research will be backed up with extra online service and guidance for the paper's source code at https://premkumarmanoharan.wixsite.com/mysite.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2021 ISA. Published by Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
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