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access icon openaccess Novel MPPT method based on large variance GA-RBF

This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Received 04/09/2018, Accepted 16/11/2018, Revised 16/11/2018, Published 16/11/2018

The photoelectric conversion efficiency of photovoltaic cells is mainly affected by temperature and irradiance. In order to promote the development of photovoltaic power generation, it is necessary to improve the photoelectric conversion efficiency of photovoltaic cells. This paper combines two major factors that affect photovoltaic cells, a maximum power point tracking scheme based on large variation GA-RBF network is proposed. The system used in this scheme is simulated through Matlab. The simulation results show that the new maximum power point tracking scheme has higher accuracy and rapidity, the photoelectric conversion efficiency of the photovoltaic cell is greatly improved.

Inspec keywords: radial basis function networks; circuit analysis computing; solar cells; genetic algorithms; maximum power point trackers; photovoltaic power systems

Other keywords: photovoltaic power generation; photoelectric conversion efficiency; large variance GA-RBF network; photovoltaic cell; Matlab; maximum power point tracking scheme; novel MPPT method

Subjects: Solar cells and arrays; Neural computing techniques; Optimisation techniques; Optimisation techniques; Power electronics, supply and supervisory circuits; Electronic engineering computing; Photoelectric conversion; solar cells and arrays

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http://iet.metastore.ingenta.com/content/journals/10.1049/joe.2018.8887
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