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Modified Neural Network for Dynamic Control and Operation of a Hybrid Generation Systems
ARTICLE

Journal of Applied Research and Technology Volume 12, Number 6, ISSN 1665-6423 Publisher: Elsevier Ltd

Abstract

This paper presents modified neural network for dynamic control and operation of a hybrid generation systems. PV and wind power are the primary power sources of the system to take full advantages of renewable energy, and the diesel-engine is used as a backup system. The simulation model of the hybrid system was developed using MATLAB Simulink. To achieve a fast and stable response for the real power control, the intelligent controller consists of a Radial Basis Function Network (RBFN) and an modified Elman Neural Network (ENN) for maximum power point tracking (MPPT). The pitch angle of wind turbine is controlled by ENN, and the PV system uses RBFN, where the output signal is used to control the DC

Citation

Huang, C.H. (2014). Modified Neural Network for Dynamic Control and Operation of a Hybrid Generation Systems. Journal of Applied Research and Technology, 12(6), 1154-1164. Elsevier Ltd. Retrieved April 13, 2021 from .

This record was imported from Journal of Applied Research and Technology on January 29, 2019. Journal of Applied Research and Technology is a publication of Elsevier.

Full text is availabe on Science Direct: http://dx.doi.org/10.1016/S1665-6423(14)71674-8

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