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Quadratic boost converter for wind energy conversion system using back propagation neural network maximum power point tracking

Author

Listed:
  • Ramji Tiwari
  • P. Pandiyan
  • S. Saravanan
  • T. Chinnadurai
  • N. Prabaharan
  • K. Kumar

Abstract

The article presents a DC-to-DC high step-up quadratic boost converter with maximum power point tracking (MPPT) technique using artificial neural network (ANN) for wind energy transfer systems. In order to get the maximum possible electrical energy from the wind speed, the proposed topology employs a back propagation network (BPN) based neural network control technique. A quadratic boost converter (QBC) is employed in this system to attain the higher voltage rating, and its performance is tested with a boost converter to determine its efficiency. The proposed system is developed in MATLAB/Simulink platform to demonstrate the operating principle under continuous conduction mode. The results obtained from this proposed system are more favourable as compared with classical perturb and observe (P%O).

Suggested Citation

  • Ramji Tiwari & P. Pandiyan & S. Saravanan & T. Chinnadurai & N. Prabaharan & K. Kumar, 2022. "Quadratic boost converter for wind energy conversion system using back propagation neural network maximum power point tracking," International Journal of Energy Technology and Policy, Inderscience Enterprises Ltd, vol. 18(1), pages 71-89.
    • Handle: RePEc:ids:ijetpo:v:18:y:2022:i:1:p:71-89
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