All modern wind turbines are endowed with a maximum power point control and tracking systems that ensure the optimal operation of the wind turbine. To achieve maximum conversion, the turbine must necessarily operate at an optimum tip speed ratio which to a very large extent depends on the variation of the power coefficient with respect to the tip speed ratio, a relationship that can only be determined experimentally. In the case of most of the current wind turbine designs, this can be achieved by appropriately controlling the rotational speed of the electric generator, as proposed first by Connor and Leithead (1993). When the primary variables can be measured, several maximum power point tracking (MPPT) algorithms have been developed and these are discussed by Datta and Ranganathan (2003). The concept of MPPT was first introduced in the design of solar panels carrying arrays of photovoltaic cells, for spacecraft in the 1970s with objective of maximizing the power transfer from the power source. Esram et al. (2006) have discussed some of the recent problems of tracking photovoltaic arrays. MPPT algorithms generally belong to three classes of algorithms: (1) based on maximizing the power generated at the grid side; (2) based on maximizing the power transfer from the wind to the generator at the rotor side; and (3) based on maximizing the total power transfer to the grid. What is required in the latter case is to be able to set the speed of the generator at a point where the power transfer from the wind to the generator is maximized; i. e., the source impedance of the generator is matched to the output impedance of the turbine in accordance with the maximum power-transfer theorem in electrical circuit theory. Examples of MPPT algorithms for wind turbines are presented in Qiaoet al. (2008), Taraft et al. (2008), Lee et al. (2009), Ors (2009), Jou et al. (2008).
Classical versions of MPPT algorithms employ a maximum power search algorithm (i. e., hill climbing method), and typical examples of these are presented in Van den Heever et al. (1989), Wang and Chang (2004), Tan and Islam (2004) for dynamically driving the operating point to the maximum power point. The hill climbing method seeks to optimize either the estimated power transferred from the turbine to the generator or the power transferred from the wind to the turbine. Most methods have relied on maximizing the latter, and this does not guarantee that the actual power transferred from the turbine to the generator is also optimized. Another drawback of these methods is the significant estimation errors in the real-time computation of the wind power captured by the turbine or the power
generated by the turbine which can often result in high-frequency power fluctuations that are highly undesirable to say the least. Several schemes have been proposed to alleviate the problems due to the errors in the estimation by using realtime estimates of the wind speed in addition to estimating the power coefficient, while other schemes use relatively robust control techniques based on fuzzy logic (see Abo-Khalil et al. (2004) for example). Another approach presented by Munteanu et al. (2009) has been to deliberately introduce a small probing signals or noise to determine the optimum point accurately.
Several strategies for achieving maximum power tracking and control have been proposed for a variety of power systems in Hohm (2003) and in Yu et al. (2003). In addition to the studies mentioned earlier, there have been a number of MPPT controllers proposed recently for wind turbines based on some form of optimal control by Bhowmik et al. (1999), Qiao et al. (2009), Koutroulis and Kalaitzakis (2006), Kawabe et al. (2007). In fact, a recent book by Munteanu et al. (2008), on the topic, has covered the optimal control-based strategies quite extensively. There have also been a few methods based on some form of optimal estimation of the wind speed (Qiao et al. 2008); Abo-Khalil and Lee 2008). A nonlinear controller-based MPPT method has also been proposed for wind turbines by Boukhezzar and Siguerdidjane (2005). Several of the optimal control strategies may be efficiently implemented for a wind turbine provided highly reliable nonlinear estimation algorithms that are used to estimate the states of the wind turbine in operation. One such approach is described and implemented by Vepa (2011).
Most of the wind turbine control systems differ in the manner in which they limit the energy converted to electricity when extreme winds are present and it is not safe to operate the MPPT controller. Thus, wind turbine control systems fall into two broad categories. Pitch-regulated wind turbines have an active control system that can vary the pitch angle of the turbine blade about its own axis to decrease the torque produced by the blades in a fixed-speed turbine and to decrease the rotational speed in variable-speed turbines. This type of control is usually employed in the presence of extreme wind speeds and when high rotational speeds and aerodynamic torques can damage the electricity generators and the power electronic converters. When wind speeds generate power above rated the power, the blades will pitch so that there is less lift and more drag due to increasing flow separation along the blade length. This will slow down the turbine’s rotational speed or the torque transferred to the shaft so that the rotational speed or the torque is kept constant below a set threshold. Pitch-regulated turbines see increasing power up until the rated wind speed, beyond which it sees constant power up until a cutout speed when the pitch control is no longer able to limit the rotational speed/ aerodynamic torque or where other forces like structural vibrations, turbulence, or gusts pose a threat to a rotating turbine.
The blade pitch angle is set at a desired value в = hd to protect the generator against excessive wind loads. The setting ensures that the maximum power transferred from the wind to the turbine is restricted. The blade angle set point is estimated from the maximum power coefficient set point at a certain operating wind speed range. This will ensure that when the wind turbine is tracking the
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maximum power point, the power transferred will be less than or equal to the maximum limit determined by the blade pitch angle. When the wind turbine is shut down, the blade pitch angle is set at a maximum permissible value, в = hd |max, and reduced depending on the operating wind speeds. To define the set point for the power coefficient in terms of a predefined power setting,
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To calculate the desired collective pitch setting angle for the blades, from the maximum rated power of the wind turbine and the estimated maximum expected wind speeds over time frame, the power coefficient set point is first estimated using the formula,
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Then if
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If Cp, se^pt < Cp, max|e=0, hd must satisfy,
Usually, this is implemented in MATLAB as a table lookup function, using a table of values of Cp max for a range of values of в. For the given value of Cp, set_pt, the table lookup function estimates the corresponding hd = h by appropriate interpolation.
Stall-regulated wind turbines, on the other hand, have their blades designed so that when wind speeds are high, the rotational speed or the aerodynamic torque, and thus the power production, decreases with increasing wind speed above a certain stall speed (when the blades are pitched into stall at a speed that is usually not the same as the rated wind speed). The decrease in power with increasing wind speeds is due to unsteady aerodynamic stall effects in the flow over the turbine blades (regions of the blade are stalled, propagating from the hub and outwards with increasing wind speeds). The blades are designed so that they will perform worse (in terms of energy extraction) in high wind speeds to protect the wind turbine without the need for active controls. The benefit of stall-regulation over
pitch-regulation is limited the capital cost of the turbine, as well as lower maintenance associated with more moving parts. Like the pitch-regulated wind turbines, stall-regulated wind turbines are also equipped with aerodynamic and mechanical brakes to bring the turbine to a halt and to reduce the lift and drag forces to a minimum in extreme wind speeds.
The difference then, between pitch-regulated and stall-regulated wind turbines, is mostly noticeable in high wind speeds. While the stall-regulated systems rely on the aerodynamic design of the blades to control the aerodynamic torque or the rotational speed of the turbine in high wind speeds, the pitch-regulated systems use an active pitch control for the blades. This allows the pitch-regulated systems to have a constant power output above the rated wind speed, while the stall-regulated systems are not able to keep a constant power output in high winds. On the other hand, stall-regulated wind turbines use very little of the generated power and are therefore more efficient in energy extraction than pitch-regulated wind turbines. The design of stall-regulated wind turbine generally requires the use of blade structural shape morphing or the use of active flow control techniques to induce stall at the most appropriate instances.
