Application of model predictive control for optimal operation of wind turbines

Yuan Yuan; Pei Cao; J. Tang

doi:10.1117/12.2260351

19 April 2017 Application of model predictive control for optimal operation of wind turbines

Yuan Yuan, Pei Cao, J. Tang

Proceedings Volume 10171, Smart Materials and Nondestructive Evaluation for Energy Systems 2017; 101710G (2017) https://doi.org/10.1117/12.2260351
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2017, Portland, Oregon, United States

Abstract

For large-scale wind turbines, reducing maintenance cost is a major challenge. Model predictive control (MPC) is a promising approach to deal with multiple conflicting objectives using the weighed sum approach. In this research, model predictive control method is applied to wind turbine to find an optimal balance between multiple objectives, such as the energy capture, loads on turbine components, and the pitch actuator usage. The actuator constraints are integrated into the objective function at the control design stage. The analysis is carried out in both the partial load region and full load region, and the performances are compared with those of a baseline gain scheduling PID controller. The application of this strategy achieves enhanced balance of component loads, the average power and actuator usages in partial load region.

Citation Download Citation

Yuan Yuan, Pei Cao, and J. Tang "Application of model predictive control for optimal operation of wind turbines", Proc. SPIE 10171, Smart Materials and Nondestructive Evaluation for Energy Systems 2017, 101710G (19 April 2017); https://doi.org/10.1117/12.2260351

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