Optimized economic nonlinear model predictive control for wind turbine: A superior approach for enhanced power and structural load reduction.

This article focuses on optimizing economic nonlinear model predictive control (ENMPC) for wind turbine operation to enhance power output while reducing mechanical loads. Using a validated nonlinear wind turbine model based on the NREL 5 MW reference turbine, the study tunes ENMPC weighting coefficients to balance energy generation and structural fatigue reduction, comparing its performance against traditional proportional–integral (PI) control. Simulation results under standard and extreme wind gust conditions, following IEC 61400 standards, demonstrate that the optimized ENMPC achieves higher average power output, smoother generator speed and torque regulation, and reduced mechanical stress compared to PI control. The study highlights ENMPC’s potential for real-time industrial application without requiring additional sensors and suggests future work involving hardware-in-the-loop testing and field validation to confirm effectiveness in operational environments.