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

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

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.

Suggested Citation

  • Hong, Chih-Ming & Ou, Ting-Chia & Lu, Kai-Hung, 2013. "Development of intelligent MPPT (maximum power point tracking) control for a grid-connected hybrid power generation system," Energy, Elsevier, vol. 50(C), pages 270-279.
    • Handle: RePEc:eee:energy:v:50:y:2013:i:c:p:270-279
    DOI: 10.1016/j.energy.2012.12.017
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    References listed on IDEAS

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    1. Howlader, Abdul Motin & Izumi, Yuya & Uehara, Akie & Urasaki, Naomitsu & Senjyu, Tomonobu & Yona, Atsushi & Saber, Ahmed Yousuf, 2012. "A minimal order observer based frequency control strategy for an integrated wind-battery-diesel power system," Energy, Elsevier, vol. 46(1), pages 168-178.
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    3. Perera, A.T.D. & Wickremasinghe, D.M.I.J. & Mahindarathna, D.V.S. & Attalage, R.A. & Perera, K.K.C.K. & Bartholameuz, E.M., 2012. "Sensitivity of internal combustion generator capacity in standalone hybrid energy systems," Energy, Elsevier, vol. 39(1), pages 403-411.
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