Weight-scheduling for linear time-variant model predictive wind turbine control toward field testing

Abstract

Modern multi-megawatt wind turbines require powerful control algorithms which consider several control objectives at the same time and respect process constraints. Model predictive control (MPC) is a promising control method and has been a research topic for years. So far, very few studies evaluated MPC algorithms in field tests. This work aims to prepare a real-time MPC system for a full-scale field test in a 3 MW wind turbine. To this end, we introduce a weight-scheduling scheme for a linear time-variant MPC in order to ensure control operation over the entire operating range from the partial to the full load range. We use a rapid control prototyping process, in particular with comprehensive software-in-the-loop (SiL) tests, in order to design and validate the MPC system for the field test.In this contribution, we present the implementation of the linear time-variant MPC with weight-scheduling to be tested in the field test. With the weight-scheduling for the optimization problem inside the MPC, we achieved good performance over the entire operating range of the wind turbine. In the SiL tests, the proposed MPC algorithm achieved loads, comparable to the baseline controller of the wind turbine and improved the reference tracking of the power output and the rotational speed. The proposed linear time-variant MPC with weight-scheduling is fully validated in the presented software-in-the-loop tests and is ready for full-scale field test in the 3 MW wind turbine. We present the experimental field test results of the introduced MPC system in a separated contribution.

Robust control of wind turbines to reduce wind power fluctuation

“…Equation ( 21) is a constraint on the power to ensure the safety of the system, which is a prerequisite for the WPGS to operate by suppressing the damage caused by extreme loads. The constraints are given in Equations ( 22), ( 23), (24), and (25). The objective function is shown in Equation ( 26)…”

“…49 NREL 5 MW wind turbine is a numerical wind turbine model. 50 In the simulation experiment, the weighting values of the objective function (25)…”

“…24 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.…”

“…Li et al proposed an RMPC controller that takes into account the uncertainty and nonlinearity, which improves the stability of the control system 24 . 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 .…”

Control-oriented wind turbine load estimation based on local linear neuro-fuzzy models

“…Model-based controllers have the potential to combine these partially conflicting objectives. Literature considers load reduction within model-based controllers for WT either implicitly by damping the structural dynamics [2,3] or explicitly by modeling the loads [4] for more precise control actions. The state estimation required for the latter is often secondary or requires specific measurements [4,5].…”