ADV preview based nonlinear predictive control for maximizing power generation of a tidal turbine with hydrostatic transmission

As the development of tidal turbines attracts more and more attention in recent years, reliable design and efficient control of tidal turbines are becoming increasingly important. However, the majority of existing tidal turbines still utilize traditional fixed ratio geared transmissions and the associated control designs focus on simple feedback controllers that use measurements or possibly estimates of the turbine itself or current local tidal profile. Therefore, the measurement and control are inevitably affected by the inherent delay with respect to the current tidal speeds. This paper proposes a novel tidal turbine with continuously variable speed hydrostatic transmissions and a nonlinear predictive controller that uses short-term predictions of the approaching tidal speed field to enhance the maximum tidal power generations when the tidal speed is below the rated value. The controller is designed based on an offline finite-horizon continuous time minimization of a cost function, and an integral action is incorporated into the control loop to increase the robustness against parameter variations and uncertainties. A smooth second order sliding mode observer is also designed for parameter estimations in the control loop. A 150 kW tidal turbine with hydrostatic transmission is designed and implemented. The results demonstrate that the averaged generator power increases by 6.76% with this preview based nonlinear predictive controller compared with a classical non-predictive controller

Feedforward control for wave disturbance rejection on floating offshore wind turbines

Floating offshore wind turbines allow wind energy to be harvested in deep waters. However, additional dynamics and structural loads may result when the floating platform is being excited by wind and waves. In this work, the conventional wind turbine controller is complemented with a novel linear feedforward controller based on wave measurements. The objective of the feedforward controller is to attenuate rotor speed variations caused by wave forcing. To design this controller, a linear model is developed that describes the system response to incident waves. The performance of the feedback-feedforward controller is assessed by a high-fidelity numerical tool using the DTU 10MW turbine and the INNWIND.EU TripleSpar platform as references. Simulations in the presence of irregular waves and turbulent wind show that the feedforward controller effectively compensates the wave-induced rotor oscillations. The novel controller is able to reduce the rotor speed variance by 26%. As a result, the remaining rotor speed variance is only 4% higher compared to operation in still water.Comment: Initial submission to the Science of Making Torque from Wind (TORQUE) 2020 conference, 10 pages, 7 figure

Nonlinear predictive generalized minimum variance LPV control of wind turbines

More advanced control strategies are needed for use with wind turbines, due to increases in size and performance requirements. This applies to both individual wind turbine controls and for the total coordinated controls for wind farms. The most successful advanced control method used in other industries is predictive control, which has the unique ability to handle hard constraints that limit system performance. However, wind turbine control systems are particularly difficult in being very nonlinear and dependent upon the external parameter variations which determine behaviour. Nonlinear controllers are often complicated to implement. The approach proposed here is to use one of the latest predictive control methods which can be used with linear parameter varying (LPV) models. These can approximate the behaviour of nonlinear wind turbines and provide a simpler control structure to implement. The work has demonstrated the feasibility and benefits that may be obtained

Fault-tolerant load reduction control for large offshore wind turbines

Offshore wind turbines suffer from asymmetrical loading (blades, tower etc.), leading to enhanced structural fatigue. As well as asymmetrical loading different types of faults (pitch system faults etc.) can occur simultaneously, causing degradation of load mitigation performance and enhanced fatigue. Individual pitch control (IPC) provides an important method to achieve mitigation of rotor asymmetric loads, but this may be accompanied by a resulting enhancement of pitch movement leading to increased possibility of pitch system faults, which negative effects on IPC performance.This thesis focuses on combining the fault tolerant control (FTC) techniques with load reduction strategies by a more intelligent pitch control system (i.e. collective pitch control and IPC) for offshore wind turbines in a system level to reduce the operation & maintenance costs and improve the system reliability. The scenario of load mitigation is analogous to the FTC problem because the action of rotor/tower bending can be considered as a fault effect. The essential concept is to attempt to account for all the "fault effects" in the rotor and tower systems which can weaken the effect of bending moment reduction through the use of IPC.Motivated by the above, this thesis focuses on four aspects to fill the gap of the combination between FTC and IPC schemes. Firstly, a preview control system using model predictive control with future wind speed is proposed, which could be a possible alternative to using LiDAR technology when using preview control for load reduction. Secondly, a multivariable IPC controller for both blade and tower load mitigation considering the inherent couplings is investigated. Thirdly, appropriate control-based fault monitoring strategies including fault detection and fault estimation FE-based FTC scheme are proposed for several different pitch actuator/sensor faults. Furthermore, the combined analysis of an FE-based FTC strategy with the IPC system at a system level is provided and the robustness of the proposed strategy is verified

A Doppler Lidar system with preview control for wind turbine load mitigation

This dissertation focuses on the development of a system for wind turbine in order to mitigate the load from unstable wind speed. The work is divided into 2 main parts: a cost efficient Doppler wind Lidar system is developed based on a short coherence length laser system in combine with multiple length delayline concept; a preview pitch control is developed based on the design of a combination of 2 degree of freedom (2-DOF) feedback / feedforward control with a model predictive control

Lidars and wind turbine control. Pt. 1

In recent years lidar technology found its way into wind energy. The main application is still the site assessment, but the possibility to optimize the energy production and reduce the loads by nacelle or spinner based lidar systems is becoming an important issue. In terms of control the inflowing wind field is the main disturbance to the wind turbine and most of the wind turbine control is designed to deal with variations in this disturbance. From control theory, the control performance can be improved with the knowledge of the disturbance. Due to the measurement principle and the complexity of the wind lidar assisted control is a wide field of research. The main idea is to divide the problem in a measurement and a control problem. The presented work describes first how wind characteristics, such as wind speed, direction and shears, can be reconstructed from the limited provided information (see Section 9.2). Based on the models of the wind turbines (see Section 9.3) it is investigated in Section 9.4, how well the lidar information can be correlated to the turbines reaction. In the next sections, several controllers are presented, see Table 15. All controllers are designed first for the case of perfect measurement and then adjusted for realistic measurements. The most promising approach is the collective pitch feedforward controller using the knowledge of the incoming wind speed providing an additional control update to assist common collective pitch control. Additional load reduction compared to the sophisticated feedback controllers could be archived (Schlipf et al., 2010a). The concept has been successfully tested on two research wind turbines (Schlipf et al., 2012a; Scholbrock et al., 2013). Then a feedforward control strategy to increase the energy production by tracking optimal inflow conditions is presented. The comparison to existing indirect speed control strategies shows a marginal increase in energy output at the expense of raised fluctuations of the generator torque (Schlipf et al., 2011). A Nonlinear Model Predictive Control (NMPC) is also presented, which predicts and optimizes the future behavior of a wind turbine using the wind speed preview adjusting simultaneously the pitch angle and the generator torque. The NMPC achieves further load reductions especially for wind conditions near rated wind speed (Schlipf et al., 2012b). Furthermore, a cyclic pitch feedforward controller using the measured horizontal and vertical shear is introduced to assist common cyclic pitch control for further reduction of blade loads. Simulations results from Dunne et al. (2012) are promising, but they have to be further investigated under more realistic conditions. Finally, the benefit of lidar assisted yaw control is explored. A promising way to obtain a accurate measurement of the wind direction is to measure it over the full rotor plane ahead of the turbine by lidar. The expected increase of the energy output is about one percent of the annual energy production, when using the wind direction signal from the lidar system instead of the sonic anemometer (Schlipf et al., 2011)