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Hard Disk Drive Servo Systems
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Both low- and high-power, rigid- and flexible-drive-train, induction- or permanent-magnet-synchronous-generator-based WECS have been chosen as illustrative examples.
Appendix C groups together some photos, diagrams and real-time captures that accompany the implementation of the reported case studies. This page intentionally blank 2 Wind Energy Conversion Systems 2. The first step in every wind energy project is the identification of suitable sites and prediction of the economic viability of the wind project.
The energy available in the wind varies as the cube of wind speed. Wind is highly variable, both in space and in time. The importance of this variability becomes critical since it is amplified by the cubic relation of the available energy. The variability in time of the wind can be divided into three distinct time scales Burton et al. First, the large time scale variability describes the variations of the amount of wind from one year to another, or even over periods of decades or more.
The second is the medium time scale, covering periods up to a year. These seasonal variations of the wind are much more predictable.
Therefore, the suitability of a given site, in terms of wind variability, is usually assessed in terms of monthly variations, covering one year. The assessment is done by statistical analysis of long time several years measurements of wind speed. Finally, the short term time scale variability, covering time scales of minutes to seconds, called turbulence, is also well known and it presents interest in the wind turbine design process. The medium time scale wind variability, further called monthly variation, is typically characterized in terms of probability distribution over one year.haumiliruckmind.tk
Control Theory & Optimization
The Weibull distribution is commonly used to fit the wind speed frequency distribution Burton et al. A special case is when k 2 , the Weibull distribution becoming a Rayleigh distribution. The influence of the k parameter on the probability density function is presented in Figure 2. Simply speaking, the variation of the hourly mean speed around the annual mean is small as k is higher, as depicted in Figure 2. Probability density 0. The influence of the scale factor on the probability density function is presented in Figure 2.
The estimation of the Weibull distribution parameters — c and k — is usually done with two methods. One method for calculating parameters c and k is starting from Equation 2. Since Equation 2. Knowing the annual variation of the wind on a given site is important, but it is not sufficient for assessing the economic viability of the wind turbine installation.
This value incorporates the combined effects of the wind speed frequency distribution and the dependence on the air density and the cube of the wind speed. The power of the wind over an area A is given by 1 UAv3 , 2 Pt 2. Thus, the mean wind power density, over an area A, can be calculated with Ptmean 1 U v3 , 2 A 2. After integrating Equation 2. Using Equations 2. The evolution of the mean wind power density as a function of the Weibull distribution function parameters, c and k, is presented in Figure 2. Mean wind power density When the power conversion efficiency power coefficient; see Section 2.
In conclusion, the Weibull distribution gives information about the annual variation of the wind speed as well as on the mean power density of a given site. A good case scenario is having a site which can be characterized by a Weibull distribution with a high scale factor c and a reduced shape factor k. This conversion takes place in two steps, as follows. The rotor drives a rotating electrical machine, the generator, which outputs electrical power. Several wind turbine concepts have been proposed over the years. A historical survey of wind turbine technology is beyond the scope here, but someone interested can find that in Ackermann Today, the vast majority of manufactured wind turbines are horizontal axis, with either two or three blades.
HAWT is comprised of the tower and the nacelle, mounted on the top of the tower Figure 2. Except for the energy conversion chain elements, the nacelle contains some control subsystems and some auxiliary elements e. Figure 2.
This mechanism could be a tail vane small wind turbines or an electric yaw device medium and large wind turbines. Concerning the power conversion chain, it involves naturally some loss of power. Because of the nonzero wind velocity behind the wind turbine rotor one can easily understand that its efficiency is less than unity.
Also, depending on the operating regime, both the motion transmission and the electrical power generation involve losses by friction and by Joule effect respectively. Being directly coupled one with the other, the energy conversion chain elements dynamically interact, mutually influencing their operation.
Consider an actuator disc Figure 2. Energy extracting actuator disc The conditions velocity and pressure in front of the actuator disc are denoted with subscript u, the ones at the disc are denoted with 0 and, finally, the conditions behind the disc are denoted with w. The power coefficient, denoting the power extraction efficiency, is defined as Cp P Pt 0.
Thus, the performance of a wind turbine is primarily characterized by the manner in which the main indicator — power — varies with wind speed. Besides that, other indicators like torque and 2. The generally accepted way to characterize the performances of a wind turbine is by expressing them by means of non-dimensional characteristic performance curves Burton et al.
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The tip speed ratio of a wind turbine is a variable expressing the ratio between the peripheral blade speed and the wind speed. The tip speed ratio is a key variable in wind turbine control and will be extensively used in the rest of the book. It characterizes the power conversion efficiency and it is also used to define the acoustic noise levels.