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Intelligent hybrid power generation system using new hybrid fuzzy-neural for photovoltaic system and RBFNSM for wind turbine in the grid connected mode

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Abstract

Photovoltaic (PV) generation is growing increasingly fast as a renewable energy source. Nevertheless, the drawback of the PV system is intermittent because of depending on weather conditions. Therefore, the wind power can be considered to assist for a stable and reliable output from the PV generation system for loads and improve the dynamic performance of the whole generation system in the grid connected mode. In this paper, a novel topology of an intelligent hybrid generation system with PV and wind turbine is presented. In order to capture the maximum power, a hybrid fuzzy-neural maximum power point tracking (MPPT) method is applied in the PV system. The average tracking efficiency of the hybrid fuzzy-neural is incremented by approximately two percentage points in comparison with the conventional methods. The pitch angle of the wind turbine is controlled by radial basis function network-sliding mode (RBFNSM). Different conditions are represented in simulation results that compare the real power values with those of the presented methods. The obtained results verify the effectiveness and superiority of the proposed method which has the advantages of robustness, fast response and good performance. Detailed mathematical model and a control approach of a three-phase grid-connected intelligent hybrid system have been proposed using Matlab/Simulink.

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Authors and Affiliations

  1. Department of Electrical Engineering, Saveh Branch, Islamic Azad University, Saveh, 3919715179, Iran

    Alireza Rezvani

  2. Department of Electrical Engineering, Karaj Branch, Islamic Azad University, Karaj, 3148635731, Iran

    Ali Esmaeily

  3. Iran Water and Power Resources Development Company (IWPCO), Tehran, Iran

    Alireza Rezvani & Hasan Etaati

  4. Department of Electrical Engineering, Science and Research Branch, Islamic Azad University, Tehran, 1477893855, Iran

    Mohammad Mohammadinodoushan

Authors
  1. Alireza Rezvani
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  2. Ali Esmaeily
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  3. Hasan Etaati
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  4. Mohammad Mohammadinodoushan
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Correspondence to Alireza Rezvani.

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Rezvani, A., Esmaeily, A., Etaati, H. et al. Intelligent hybrid power generation system using new hybrid fuzzy-neural for photovoltaic system and RBFNSM for wind turbine in the grid connected mode. Front. Energy 13, 131–148 (2019). https://doi.org/10.1007/s11708-017-0446-x

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  • DOI: https://doi.org/10.1007/s11708-017-0446-x

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