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Three Phase Grid-Tied Solar PV System: Modeling, Simulation, and MPPT Analysis using Artificial Neural Networks (ANN)

Author

Listed:
  • Ekhlas M. Thajeel

    (University of Technology, Iraq)

  • Hawraa Q. Hameed

    (University of Technology, Iraq)

  • Shaimaa A. Hussein

    (University of Technology, Iraq)

Abstract

Photovoltaic generators offer a low-environmental-impact, economic, and socially beneficial approach for producing electrical energy competitively. Recently much emphasis has been placed on the generation of clean energy, which has received increased attention. These natural and clean energy sources must contain all items required for their functioning. In this study, solar photovoltaic (PV) systems connected to a grid were simulated. The proposed model of the solar PV system, DC-DC converter, converter, and grid interface was formed. In solar PV systems, Maximum Power Point Tracking (MPPT) is essential because it boosts the output power of the system, allowing for efficient PV array use and voltage regulation. The interface receives power from the solar PV system by maintaining a constant voltage of the DC converter grid. The Pulse Width Modulation (PWM) sine wave technique is used to generate pulses for the converter. Artificial neural networks (ANNs) are effective machine learning tools based on the structure of the human brain. The actual and expected outputs are used by the ANN to enhance its performance. MATLAB/Simulink was used to construct and test the simulation system model, and the results were presented.

Suggested Citation

  • Ekhlas M. Thajeel & Hawraa Q. Hameed & Shaimaa A. Hussein, 2025. "Three Phase Grid-Tied Solar PV System: Modeling, Simulation, and MPPT Analysis using Artificial Neural Networks (ANN)," European Journal of Electrical Engineering and Computer Science, European Open Science, vol. 9(6), pages 55-64, November.
    • Handle: RePEc:epw:ejece0:v:9:y:2025:i:6:id:19760
    DOI: 10.24018/ejece.2025.9.6.760
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