On the design and tuning of linear model predictive control for wind turbines. (August 2015)

• Record Type: Journal Article
• Authors: Jain, Achin; Schildbach, Georg; Fagiano, Lorenzo; Morari, Manfred
• Is Part Of: Renewable energy. Volume 80(2015)
• Page Start: 664
• Page End: 673
• Publication Date: 2015-08
• Subjects: Wind energy -- Wind turbines -- Model predictive control -- Sensitivity analysis -- Control system tuning; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2015.02.057
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: This paper presents a study on the design of linear model predictive control (MPC) for wind turbines, with a focus on the controller's tuning tradeoffs. A continuously linearized MPC approach is described and applied to control a 3-bladed, horizontal axis, variable speed wind turbine. The tuning involves a multiobjective cost function so that the performance can be optimized with respect to five defined measures: power variation, pitch usage, tower displacement, drivetrain twist and frequency of violating the nominal power limit. A tuning approach based on the computation of sensitivity tables is proposed and tested via numerical simulations using a nonlinear turbine model. The paper further compares the performance of the MPC controller with that of a conventional one. Highlights: We present a systematic approach to tune MPC for wind turbines. We consider multiobjective cost function in MPC involving 5 performance indices. The tuning methodology is based on computation of sensitivity tables. Even without wind preview, MPC can perform better than classical controllers. A higher flexibility in trading off different objectives is achieved with MPC.