Full-scale field test of a model predictive control system for a 3 MW wind turbine

Abstract

Model predictive control (MPC) is a strong candidate for modern wind turbine control. While the design of model predictive wind turbine controllers in simulations has been extensively investigated in academic studies, the application of these controllers to real wind turbines reveals open research challenges. In this work, we focus on the validation of a linear time-variant MPC system for a 3 MW wind turbine in a full-scale field test. First, the study proves the MPC’s capability to control the real wind turbine in the partial load region. Compared to the turbine’s baseline PID controller, the MPC system offers similar results for the electrical power output and for the occurring mechanical loads. Second, the study validates a previously proposed, simulation-based rapid control prototyping process for a systematic MPC development. The systematic development process allows to completely design and parameterize the MPC system in a simulative environment independent of the real wind turbine. Through the rapid control prototyping process, the MPC commissioning in the wind turbine’s programmable logic controller can be realized within a few hours without any modifications required in the field. Thus, this study establishes the proof of concept for a linear time-variant MPC system for a 3 MW wind turbine in a full-scale field test and bridges the gap between the control design and field testing of MPC systems for wind turbines in the multi-megawatt range.

Wind energy conversion technologies and engineering approaches to enhancing wind power generation: A review

“…This control design strategy can improve the dynamic efficiency of the WECSs by minimizing the systems’ complexities along with enhancing output power stability; and yet, this strategy was reported to require additional high-cost to develop control system for the wind farm application [ 158 ]. On the other hand, MBPC design strategy was reported to have a number of attractive features that make it more desirable for the advanced control of the PECs-based power generation systems; for instance [ 20 , 56 , 159 ]: it is able to handle well multivariable systems, constraints imposed on the systems are also dealt with satisfactorily, online optimization can be achieved, it is not too intricate to develop control systems, and cost optimizations can be better achieved during operation. Block diagram for MBPC design is illustrated in Figure 13 .…”

Robust control of wind turbines to reduce wind power fluctuation

“…25 A tube-based RMPC control strategy was proposed to WPGS, which is a nontrivial reference for the control of linear time-varying models. 26 The robustness of MPC is considered in research, mainly with respect to parameter uncertainty, static time-varying uncertainty in the system variables, and bounded disturbances. 27 MPC was developed for the wind turbine system.…”

“…Wintermeyer‐Kallen et al extended the design approach of RMPC to uncertain linear systems, which provides new ideas for the control of uncertain systems 25 . A tube‐based RMPC control strategy was proposed to WPGS, which is a nontrivial reference for the control of linear time‐varying models 26 . The robustness of MPC is considered in research, mainly with respect to parameter uncertainty, static time‐varying uncertainty in the system variables, and bounded disturbances 27 .…”

Comparative Study of Control Methods for a 2MW Doubly-Fed Induction Generator Wind Turbine

“…This approach is based on a linear parameter-varying model. Dickler et al, [16] have concentrated on verifying the effectiveness of a linear time-variant MPC system in a full-scale field test of a 3 MW wind turbine. Suboh et al, [16] develop a linear MPC controller to maximize the power production of DFIG wind turbines according to wind speed.…”