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Energies 2018, 11(10), 2615; https://doi.org/10.3390/en11102615

Designing Localized MPPT for PV Systems Using Fuzzy-Weighted Extreme Learning Machine

1
Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou 215123, China
2
College of Information Engineering, China Jiliang University, Hangzhou 310018, China
3
School of Electrical and Information Engineering, The University of Sydney, Western Avenue, Sydney, NSW 2006, Australia
*
Author to whom correspondence should be addressed.
Received: 12 September 2018 / Revised: 27 September 2018 / Accepted: 29 September 2018 / Published: 1 October 2018
(This article belongs to the Section Sustainable Energy)
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PDF [1837 KB, uploaded 1 October 2018]
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Abstract

A maximum power point tracker (MPPT) should be designed to deal with various weather conditions, which are different from region to region. Customization is an important step for achieving the highest solar energy harvest. The latest development of modern machine learning provides the possibility to classify the weather types automatically and, consequently, assist localized MPPT design. In this study, a localized MPPT algorithm is developed, which is supported by a supervised weather-type classification system. Two classical machine learning technologies are employed and compared, namely, the support vector machine (SVM) and extreme learning machine (ELM). The simulation results show the outperformance of the proposed method in comparison with the traditional MPPT design. View Full-Text
Keywords: maximum power point tracker; solar irradiance classification system; extreme learning machine; support vector machine maximum power point tracker; solar irradiance classification system; extreme learning machine; support vector machine
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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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Du, Y.; Yan, K.; Ren, Z.; Xiao, W. Designing Localized MPPT for PV Systems Using Fuzzy-Weighted Extreme Learning Machine. Energies 2018, 11, 2615.

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