Comparative Study of MPPT Controllers for a Wind Energy Conversion System

This paper aims to discuss the modeling and control of a wind turbine using the maximum power point tracking technique (MPPT) based on the Tip Speed Ratio (TSR) method to extract the maximum power. A comparative study has been carried out within a four-types control laws. Namely, conventional PI, nonlinear sliding mode, backstepping and finally, artificial neural network controller. To identify which is which to provide the best performances, the proposed control laws are tested under Matlab/Simulink under different operating conditions to check the controller's performances. The performed simulations show that MPPT artificial neural network ensure the best performance compared to other controller because of its ability to map between inputs and outputs and efficiently cope with wind energy conversion system (WECS) nonlinearities.

Automated summary

This paper discusses the modeling and control of a wind turbine using the MPPT technique based on the TSR method. A comparative study of four different control laws is conducted, and the performance of the proposed control laws is tested under various operating conditions. The simulations show that the MPPT artificial neural network controller outperforms other controllers due to its ability to map between inputs and outputs and effectively handle the nonlinearities of the wind energy conversion system.