Volume 8 Number 10 (Oct. 2013)
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JSW 2013 Vol.8(10): 2569-2574 ISSN: 1796-217X
doi: 10.4304/jsw.8.10.2569-2574

Maximum Power Point Tracking of Photovoltaic Generation Based on Forecasting Model

Weiliang Liu1, Changliang Liu2, Liangyu Ma1, Yongjun Lin1, Jin Ma1

1Department of Automation, North China Electric Power University, Baoding, China
2State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, Beijing, China

Abstract—In order to make full utilization of photovoltaic (PV) array output power, which depends on solar irradiation and ambient temperature, maximum power point tracking (MPPT) techniques are employed. Among all the MPPT strategies, the Perturb and Observe (P&O) algorithm is more attractive due to its simple control structure. Nevertheless, steady-state oscillations always appear due to the perturbation. In this paper, forecasting model of maximum power point (MPP) based on Support Vector Machine (SVM) is established, and a new MPPT algorithm composed of the forecasting model and small step P&O is presented. Experimental results show that SVM model could predict the MPP exactly, and the effectiveness of the proposed MPPT algorithm is validated using hardware platform based on single-chip microcomputer.

Index Terms—Maximum power point tracking, Perturb and Observe, support vector machine, forecasting model.

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Cite: Weiliang Liu, Changliang Liu, Liangyu Ma, Yongjun Lin, Jin Ma, "Maximum Power Point Tracking of Photovoltaic Generation Based on Forecasting Model," Journal of Software vol. 8, no. 10, pp. 2569-2574, 2013.

General Information

ISSN: 1796-217X (Online)
Frequency:  Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKIGoogle Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsweditorialoffice@gmail.com
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