Maximum Power Point Tracking Control for Non-Gaussian Wind Energy Conversion System by Using Survival Information...

Area of Science:

• Engineering
• Renewable Energy Systems
• Control Theory

Background:

• Wind energy conversion systems (WECS) face challenges in maximizing power output due to unpredictable wind conditions.
• Non-Gaussian wind velocity introduces significant uncertainty into WECS performance.
• Accurate tracking of turbine rotational speed is crucial for efficient power generation.

Purpose of the Study:

• To develop an advanced control strategy for WECS to improve conversion efficiency and maximize power output.
• To address the challenge of non-Gaussian wind disturbances in WECS control.
• To minimize stochastic tracking errors in wind turbine rotational speed.

Main Methods:

• A nonlinear state-space model was established for the WECS, incorporating shaft current, turbine rotational speed, and power output.
• Survival information potential was utilized to quantify uncertainty in stochastic tracking errors.
• A data-driven approach was employed to calculate survival information potential, avoiding complex probability formulations.
• A recursive optimization of a performance index function, considering survival information potential and control constraints, was used to determine the control input.

Main Results:

• The proposed maximum power point tracking (MPPT) control method demonstrated high efficiency in simulations.
• The actual wind turbine rotation speed accurately tracked the reference speed with reduced time and overshoot.
• The control method ensured consistent power output despite non-Gaussian wind noises.

Conclusions:

• The developed control strategy effectively enhances WECS performance under uncertain wind conditions.
• The method offers a robust solution for maximizing power output and improving tracking precision in WECS.
• The data-driven approach simplifies the implementation of advanced control techniques in WECS.