Session: 08-12-01: Optimization, Uncertainty and Probability

Paper Number: 166165

Adaptive Control Design for Wind Turbine Blade Failure Mitigation Validated Through Control-Embedded CFD Simulation 

 

This study presents the speed control of a vertical axis wind turbine (VAWT) to maintain operational efficiency under varying aerodynamic conditions. A conventional state-space model was developed, where the drag parameters were obtained through Computational Fluid Dynamics (CFD) simulations using the Large Eddy Simulation (LES) approach. Based on this model, two controllers were designed: a conventional Proportional-Integral-Derivative (PID) controller and an adaptive PID controller. The performance of both controllers was evaluated through step response tests and disturbance rejection scenarios, with metrics based on the Integral of Squared Error (ISE) and Integral of Absolute Error (IAE).To enhance the realism of the validation process, a time-dependent CFD simulation was performed, incorporating the control system in real-time as the simulation progressed. This co-simulation approach allowed the controllers to interact dynamically with a more accurate aerodynamic model of the turbine. Furthermore, a final test was conducted where the turbine underwent a gradual change in its geometry, affecting its aerodynamic parameters and posing a significant challenge to the controllers. The results showed that while the conventional PID controller provided adequate performance in step response tests, it exhibited degraded performance in disturbance rejection scenarios and ultimately failed in the final CFD-integrated simulation due to its inability to adapt to the evolving aerodynamic conditions. Conversely, the adaptive PID controller demonstrated consistent performance across all tests, maintaining similar overshoot and settling time characteristics while achieving superior ISE and IAE indices compared to the conventional PID.These findings highlight the importance of adaptive control strategies in maintaining turbine efficiency under dynamic aerodynamic conditions. The integration of CFD-based modeling with real-time control provides a more realistic testing framework, offering valuable insights into the behavior of control systems in wind energy applications. This study underscores the limitations of fixed-gain PID controllers in handling time-varying aerodynamic properties and demonstrates the advantages of adaptive control in ensuring robust turbine operation under uncertain and evolving conditions. Furthermore, the results suggest that integrating real-time adaptive control with CFD-based simulations can bridge the gap between theoretical modeling and practical implementation, offering a pathway toward more efficient wind energy systems. Future research could explore alternative adaptive control strategies and machine learning-based approaches to further improve turbine performance and resilience in highly variable environmental conditions. Additionally, experimental validation of these findings using physical prototypes would further strengthen the conclusions and provide insights into real-world implementation challenges. Investigating control strategies that incorporate predictive models or reinforcement learning could further enhance adaptability and efficiency in fluctuating wind conditions

Presenting Author: Helio S. Esteban Universidad Industrial de Santander

Presenting Author Biography: Helio Esteban is a doctoral student in Mechanical Engineering at the Universidad Industrial de Santander (UIS). He obtained his Master’s degree in Mechanical Engineering in 2022 from the same institution and graduated cum laude in 2019 as a Mechatronics Engineer from the Universidad Autónoma de Bucaramanga (UNAB).

His research focuses on the modeling and control of dynamic systems, with a particular emphasis on the analysis of delays in closed-loop systems and their application in vibration damping. He has worked on the development of robust and adaptive control strategies to enhance the stability and performance of complex systems, with applications in remotely operated vehicles (ROVs), the control of unstable systems, and the use of finite element methods in the automotive sector and vibration analysis.

Additionally, he has participated in industrial research projects and national funding calls within the oil sector, contributing to the development of innovative solutions for engineering challenges in this field.

Authors:

Helio S. Esteban Universidad Industrial de Santander
Nicolas Becerra Universidad Industrial de Santander
Carlos Borras Pinilla Universidad Industrial De Santander- UIS