Maximum Power Point Tracking Based on SVR and GA

Zhi Guang Tian; Lin Tian; Jian He; Zhen Hua Huang; Da Hai Zhang; De Da Sun

doi:10.4028/www.scientific.net/AMM.687-691.3231

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 687-691Maximum Power Point Tracking Based on SVR and GA

Maximum Power Point Tracking Based on SVR and GA

Abstract:

With the increasing application of Photovoltaic (PV) power system, it is important to make PV system always achieve its maximum power output, so maximum power point tracking (MPPT) technique develops. Based on Support Vector Regression (SVR) and Genetic Algorithm (GA), a novel MPPT method is proposed in this paper. The SVR model uses the solar radiation and temperature as two inputs, and uses the voltage at maximum power point (MPP) as output. Furthermore, GA is introduced to search the best parameters for SVR. Results validate the effectiveness of the proposed MPPT method.

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Periodical:

Applied Mechanics and Materials (Volumes 687-691)

Pages:

3231-3234

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.687-691.3231

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Online since:

November 2014

Authors:

Zhi Guang Tian, Lin Tian, Jian He, Zhen Hua Huang, Da Hai Zhang, De Da Sun

Keywords:

Genetic Algorithm (GA), Maximum Power Point Tracking (MPPT), Photovoltaic System, Renewable Energy, Support Vector Regression (SVR)

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