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Simulation and control of intelligent photovoltaic system using new hybrid fuzzy-neural method

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Abstract

Nowadays, photovoltaic (PV) generation is growing fast as a renewable energy source. Nevertheless, the drawback of PV system is intermittent for depending on weather conditions. In this paper, a novel topology of intelligent PV system is presented. In order to capture the maximum power, hybrid fuzzy-neural maximum power point tracking method is applied in PV system. As a result, the effectiveness of the proposed method is represented and average tracking efficiency of the hybrid fuzzy-neural is incremented by approximately two percentage points in comparison with the conventional methods. It 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 proposed using MATLAB/Simulink.

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Authors and Affiliations

  1. Young Researchers and Elite Club, Saveh Branch, Islamic Azad University, Saveh, Iran

    Alireza Rezvani

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

    Majid Gandomkar

Authors
  1. Alireza Rezvani
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  2. Majid Gandomkar
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Corresponding author

Correspondence to Alireza Rezvani.

Appendix: Description of the detailed model

Appendix: Description of the detailed model

PV parameters Output power = 4.4 kW, carrier frequency in V MPPT PWM generator = 4.3 kHz and in grid-side controller = 5 kHz, boost converter parameters: L = 3.5 mH, C = 630 µF, PI coefficients in grid-side controller: K pVdc = 3.5, K iVdc = 7.3, K pId = 8.4, K iId = 343, K pIq = 8.4, K iIq = 343.

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Rezvani, A., Gandomkar, M. Simulation and control of intelligent photovoltaic system using new hybrid fuzzy-neural method. Neural Comput & Applic 28, 2501–2518 (2017). https://doi.org/10.1007/s00521-016-2210-2

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  • DOI: https://doi.org/10.1007/s00521-016-2210-2

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