Wind energy is a fast-growing interdisciplinary field that encompasses multiple branches of engineering and science. Despite the growth in the installed capacity of wind turbines in recent years, larger wind turbines have energy capture and economic advantages, the typical size of utility scale wind turbines has grown by two orders of magnitude. Since modern wind turbines are large, flexible structures operating in uncertain environments, advanced control technology can improve their performance.The goal of this article is to describe the technical challenges in the wind industry relating to control engineering.

Control of Wind Turbines

Wind energy is currently the fastest-growing energy source in the world, with a concurrent growth in demand for the expertise of engineers and researchers in the wind energy field. There are still many unsolved challenges in expanding wind power, and there are numerous problems of interest to systems and control researchers. In this paper, we first review the basic structure of wind turbines and then describe wind turbine control systems and control loops. Of great interest are the generator torque and blade pitch control systems, where significant performance improvements are achievable with more advanced systems and control research. We describe recent developments in advanced controllers for wind turbines and wind farms, and we also outline many open problems in the areas of modeling and control of wind turbines.

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A tutorial on the dynamics and control of wind turbines and wind farms

Development of alternative energy sources has become a necessity as fossil energy resources are declining. At the same time, energy demand is rapidly increasing, putting the world on the verge of a global energy crisis. Moreover, the extensive use of conventional energy sources is polluting the environment and causing global warming. On the other hand, wind and other renewable energy sources are viable and clean alternatives to fossil fuels. Low operating cost and extensive availability make wind one of the most advantageous and effective renewable energy sources. This paper provides an exposure to the necessity for deployment of renewable energy sources and the worldwide installed capacity of wind power as well as a review of various wind technologies in conjunction with their applications and devices of operation. Furthermore, this paper discusses the cost of electric generation in wind power plants as well as the economic and environmental policies that advocate the installation of wind energy systems.

Wind energy: Trends and enabling technologies

LIDAR systems are able to provide preview information of wind disturbances at various distances in front of wind turbines. This technology paves the way for new control concepts in wind energy such as feedforward control and model predictive control. This paper compares a nonlinear model predictive controller with a baseline controller, showing the advantages of using the wind predictions in the optimization problem to reduce wind turbine extreme and fatigue loads on tower and blades as well as to limit the pitch rates. The wind information is obtained by a detailed simulation of a LIDAR system. The controller design is evaluated and tested in a simulation environment with coherent gusts and a set of turbulent wind fields using a detailed aeroelastic model of the wind turbine over the full operation region. Results show promising load reduction up to 50% for extreme gusts and 30% for lifetime fatigue loads without negative impact on overall energy production. This controller can be considered as an upper bound for other LIDAR assisted controllers that are more suited for real time applications. Copyright © 2012 John Wiley & Sons, Ltd.

Nonlinear model predictive control of wind turbines using LIDAR

The TurbSim stochastic inflow turbulence code was developed to provide a numerical simulation of a full-field flow that contains coherent turbulence structures that reflect the proper spatiotemporal turbulent velocity field relationships seen in instabilities associated with nocturnal boundary layer flows that are not represented well by the IEC Normal Turbulence Models (NTM). Its purpose is to provide the wind turbine designer with the ability to drive design code (FAST or MSC.ADAMS) simulations of advanced turbine designs with simulated inflow turbulence environments that incorporate many of the important fluid dynamic features known to adversely affect turbine aeroelastic response and loading.

TurbSim User's Guide

https://www.tpbin.com/Uploads/Subjects/f45646b1-fe82-4026-9021-364b880307b7.pdf

Adding feedforward blade pitch control to standard feedback controllers for load mitigation in wind turbines

https://www.tpbin.com/Uploads/Subjects/b6b73d9d-2734-41a3-b79e-c8cc8d590661.pdf

The use of preview wind measurements for blade pitch control

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Overview of the TurbSim Stochastic Inflow Turbulence Simulator

Light detection and ranging (LIDAR) systems are able to measure the speed of incoming wind before it reaches a wind turbine rotor. These preview wind measurements can be used in feedforward control systems designed to reduce turbine structural loads. However, the degree to which such preview-based control techniques can reduce loads by reacting to turbulence depends on how accurately the incoming wind field can be measured. This study examines the accuracy of different measurement scenarios that rely on coherent continuous-wave or pulsed Doppler LIDAR systems, in terms of root-mean-square measurement error, to determine their applicability to feedforward control. In particular, the impacts of measurement range, angular offset of the LIDAR beam from the wind direction, and measurement noise are studied for various wind conditions. A realistic simulation case involving a scanning LIDAR unit mounted in the spinner of a MW-scale wind turbine is studied in depth, with emphasis on preview distances that provide minimum measurement error for a specific scan radius. Measurement error is analyzed for LIDAR-based estimates of point wind speeds at the rotor as well as spanwise averaged blade effective wind speeds. The impact of turbulence structures with high coherent turbulent kinetic energy on measurement error is discussed as well. Copyright © 2013 John Wiley & Sons, Ltd.

Analysis of Light Detection and Ranging Wind Speed Measurements for Wind Turbine Control

Combined feedback/feedforward blade pitch control is compared to industry standard feedback control when simulated in realistic turbulent winds. The feedforward controllers are designed to reduce fatigue loads, increasing turbine lifetime and therefore reducing the cost of energy. Various collective pitch and individual pitch versions of two feedforward designs are studied: Gain-Scheduled Model-Inverse and Gain-Scheduled Shaped Compensator. The input to the feedforward controller is a measurement of incoming wind speed, which could potentially be provided by LIDAR. Three of the designs reduce structural loading compared to standard feedback control, without reducing power production.

Bonnie Jonkman

Papers

Adding feedforward blade pitch control to standard feedback controllers for load mitigation in wind turbines

The use of preview wind measurements for blade pitch control

Overview of the TurbSim Stochastic Inflow Turbulence Simulator

Analysis of Light Detection and Ranging Wind Speed Measurements for Wind Turbine Control

Combining Standard Feedback Controllers with Feedforward Blade Pitch Control for Load Mitigation in Wind Turbines