Development of intelligent MPPT (maximum power point tracking) control for a grid-connected hybrid power generation system

Chih-Ming Hong, Ting-Chia Ou and Kai-Hung Lu

Energy, 2013, vol. 50, issue C, 270-279

Abstract: A hybrid power control system is proposed in the paper, consisting of solar power, wind power, and a diesel-engine. To achieve a fast and stable response for the real power control, an intelligent controller was proposed, which consists of the Wilcoxon (radial basis function network) RBFN and the improved (Elman neural network) ENN for (maximum power point tracking) MPPT. The pitch angle control of wind power uses improved ENN controller, and the output is fed to the wind turbine to achieve the MPPT. The solar array is integrated with an RBFN control algorithm to track the maximum power. MATLAB (MATrix LABoratory)/Simulink was used to build the dynamic model and simulate the solar and diesel-wind hybrid power system.

Keywords: Hybrid power system; Wilcoxon (radial basis function network) RBFN; Improved (Elman neural network) ENN; (Maximum power point tracking) MPPT; Diesel-engine (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (61)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:50:y:2013:i:c:p:270-279

DOI: 10.1016/j.energy.2012.12.017

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