5.3.3 TRANSECTA DE VERANO DE

For Region 3 of wind turbine operation, the expectation is to regulate the power output at the rated level while reducing the structural load [4]. As turbine size grows larger and larger, the wind turbine structure tends to be more flexible due to the adoption of lighter materials and increase in dimension. Load reduction is thus increasingly critical for the reliability and safety of turbine operation. Improvement in both blade design and control development can contribute to the alleviation of the fatigue loads for turbine, drive-train and tower structure. Advanced controller design is considered a relatively cost effective approach to load reduction, which can compensate for the system and environmental variations.

Load reduction control has been implemented and studied via generator torque control, blade pitch control and active flow control [36]. For pitch control based load reduction, both collective pitch control (CPC) and individual pitch control (IPC) have been studied. For CPC, the pitch angles of all turbine blades are adjusted simultaneously, and it is appropriate to control the variations slower than one rotor revolution. Due to its simplicity, CPC has been widely studied and implemented in wind industry [37]. A major drawback of CPC is the inability of dealing with asymmetric load for actual wind turbine. Asymmetric load distribution arises most often when the wind speed varies across the rotor disc due to factors such as vertical wind shear, change in wind direction, yaw error, and wake interaction [10]. Changes in blade characteristics such as surface icing and snow accumulation may also lead to asymmetric loading. Such drawback of CPC becomes a significant limitation nowadays as the turbine diameter becomes increasingly larger.

In comparison, IPC is achieved by controlling the pitching motion of each blade by the virtue of separate actuating mechanism [10], with a primary objective of controlling variations faster than the one rotor revolution. Therefore, IPC aims to deal with asymmetric loading. Typically the actuators for IPC are required to have higher bandwidth, for which high-stiffness electric motor actuators are more advantageous. Various sensing schemes have been investigated, such as strain gage at blade root [10], local blade inflow [12, 38] and LIDAR [39]. Bossanyi [10] designed LQG-based IPC controller to alleviate loads at blade roots by use of linear invariant models obtained through d-q axis. Larsen et al [12] designed gain scheduling PI-based IPC for load reduction by use of the local inflow angle and relative velocity on each of the blades.

Olsen et al. [38] designed IPC based on inflow angle measurements. In particular, Hand et al. [39] designed an IPC through directly measuring the upwind incoming flow field by use of LIDAR system, which appears promising for improving the system performance for feed-forward and model-based feedback control strategies.

Different control design methods have been applied to the IPC development. The IPC design is in principle a multi-input-multi-output control design problem. For industrial applications, Bossanyi [37] designed a multi-loop decentralized PI controller where two separate SISO loops are designed for rotor tilt and yaw moments, respectively. Kanev et al. [40] proposed an IPC algorithm for rotor balance within pitch and pitch rate constraints handled by an anti-windup scheme. Jelavic et al. [41] proposed a load estimation based IPC scheme. Van Engelen [42] proposed a high harmonics control for wind turbines by use of IPC to reduce loads in high frequency. Specially, a series of field tests had been conducted at the National Renewable Energy Laboratory (NREL) by Bossanyi et al. [43-45].

However, the loop coupling is a significant issue, especially among the generator torque, the first tower fore-aft mode and the first tower side-to-side mode control loops. It revealed that loop interaction tends to destabilize the closed-loop system when the size of the wind turbine rotor increases beyond a certain extent [46]. To solve this problem, centralized control design based on the state-space turbine model has appeared a better solution. The state-space model based IPC schemes by use of inflow angle measurements was initially investigated by NREL from 2002 to 2004 [38] and different sensor choices, such as hot wire, laser Doppler velocimetry system et al, are evaluated for inflow angle measurements. By far, the optimal and robust control methods have been widely applied

to the IPC design, such as the Linear Quadratic Gaussian (LQG) [10] and Η_∞ controls [47]. Besides, Selvam et al. [11] proposed a LQG-based IPC algorithm with feedforward disturbance rejection by use of the estimation of the wind speed. More recently, IPC was combined with flap control for load reduction [48].

It is noteworthy that a particular stream of work on wind turbine control has been developed following Balas’ Disturbance Accommodating Control (DAC) scheme [49]. Several control schemes have been studied following this framework, e.g. Stol [50], Hand [51], Wright [52], Wright and Fingersh [53], Wright and Stol [46]. Stol [50] applied Taylor theory to obtain linearized state-space model of wind turbines and applied DAC for periodic control of a wind turbine. Hand [51] built wind turbine models including vortex and applied DAC for wind disturbance cancellation along blades. Wright [52] applied DAC for IPC of a two-bladed turbine. Wright and Fingersh [53] implemented and tested DAC for IPC of the CART wind turbine in NREL. Wright and Stol [54] applied DAC for loads reduction at both blades and tower base of wind turbines by use of IPC. Besides, active yaw control of wind turbine was also achieved through periodic state- space IPC by Zhao et al. [55]. Recently, Hazim and Stol [56] applied LQR based periodic control to the IPC for floating offshore wind turbine.

To the author’s best knowledge so far, the reported work on IPC design has included only the model of vertical wind shear regarding wind asymmetry. For wind farm operation, the inter-turbine wake interaction is also significant [16]. It is potentially beneficial for further reduction of dynamic load by including wind turbine wake interaction.