Science – Future of Lithuania / Mokslas – Lietuvos Ateitis, Vol 6, No 2 (2014)

Artificial Neural Network In Maximum Power Point Tracking Algorithm Of Photovoltaic Systems

Modestas Pikutis (Vilniaus Gedimino technikos universitetas, Lithuania)


Scientists are looking for ways to improve the efficiency of solar cells all the time. The efficiency of solar cells which are available to the general public is up to 20%. Part of the solar energy is unused and a capacity of solar power plant is significantly reduced – if slow controller or controller which cannot stay at maximum power point of solar modules is used. Various algorithms of maximum power point tracking were created, but mostly algorithms are slow or make mistakes. In the literature more and more oftenartificial neural networks (ANN) in maximum power point tracking process are mentioned, in order to improve performance of the controller. Self-learner artificial neural network and IncCond algorithm were used for maximum power point tracking in created solar power plant model. The algorithm for control was created. Solar power plant model is implemented in Matlab/Simulink environment.

Article in: English

Article published: 2014-04-24

Keyword(s): artificial neural network, solar cells, maximum power point tracking.

DOI: 10.3846/mla.2014.26

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Science – Future of Lithuania / Mokslas – Lietuvos Ateitis ISSN 2029-2341, eISSN 2029-2252
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