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Maximum power point tracking algorithm based on fuzzy Neural Networks for photovoltaic generation system

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2 Author(s)
Su Haibin ; Electr. Power Sch., North China Univ. of Water Conservancy & Electr. Power, Zhengzhou, China ; Bian Jingjing

This paper proposes a algorithm of maximum power point tracking based on fuzzy Neural Networks for photovoltaic generation systems. The system is composed of a boost converter and DC pump motor load. The maximum power point tracking control is based on fuzzy Neural Networks to control a IGBT switch duty ratio of a boost converter. The fuzzy Neural Networks provide attractive features such as fast response, good performance. Therefore, the system is able to deliver energy with high power factor. Both traditional fuzzy logic controller and fuzzy Neural Networks controller are simulated and implemented to evaluate performance. Simulation and experimental results are provided for both controllers under the same atmospheric condition. From the simulation and experimental results, the fuzzy Neural Networks can deliver more power than the traditional fuzzy logic controller.

Published in:

Computer Application and System Modeling (ICCASM), 2010 International Conference on  (Volume:1 )

Date of Conference:

22-24 Oct. 2010