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Power Kites for Wind Energy Generation Fast Predictive Control of Tethered Airfoils

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Power Kites for Wind Energy Generation Fast Predictive Control of Tethered Airfoils FUTURE DIRECTIONS REFERENCES Tire modeling and tire parameter estimation are need- [1] L. Wingert, Not to Air Is human. Crane Communications, 2000. [2] N. Normann, Tyre Pressure Monitoring System for all Vehicle Categories. ed to reduce the cost of direct TPMSs and to overcome Crane Communications Inc.: ATZ Worldwide, 2000. the shortcomings of indirect TPMSs. A classical solu- [3] NHTSA, Federal Motor Vehicle Safety Standards [Online]. Available: tion is to model the dependence of tire/road friction on http://www.nhtsa.dot.gov/cars/rules [4] H. Shraim, A. Rabhi, M. Ouladsine, N.K. M’Sirid, and L. Fridman, “Esti- tire pressure, which can then be extracted from the fric- mation and analysis of the tire pressure effects on the comportment of the tion coefficient. Alternatively, one can consider addi- vehicle center of gravity},” in Proc. 9th Int. Workshop on Variable Structure Sys- tional factors that affect tire inflation pressure, such as tems, Italy), June 2006, pp. 268–273. [5] L. Li, F.-Y. Wang, Q. Zhou, and G. Shan, “Automatic tire pressure fault vertical force and vertical deflection [4]. A combination monitor using wavelet-based probability density estimation,” in Proc. IEEE of tire speed and tire height can estimate inflation more Intelligent Vehicle Symp., June 2003, pp. 80–84. precisely than current indirect TPMSs. This approach [6] N. Persson, F. Gustafsson, and M. Drevö, “Indirect tire pressure monitoring using sensor fusion,” in Proc. SAE 2002, Detroit, June 2002, no. 2002-01-1250. needs an additional height sensor or accelerometer, [7] C.R. Carlson and J.C. Gerdes, “Identifying tire pressure variation by non- which is available in vehicles with semi-active or active linear estimation of longitudinal stiffness and effective radius,” in Proc. suspensions. AVEC2002, Japan, 2002. Yet another approach relies on the fact that the reso- nance frequency of the tire changes with respect to pres- AUTHOR INFORMATION sure [5], [6], as modeled by V. Sankaranarayanan ([email protected]) received the Ph.D. degree in systems and control engineering from IIT- Bombay in 2006. He is currently a postdoctoral researcher in ∼ the Mechanical Engineering Department at Istanbul Techni- ωresonance = , m cal University. His research interests include nonlinear con- trol, underactuated systems, sliding mode control, and where k denotes tire stiffness, k denotes change in tire automotive control systems. stiffness, and m denotes mass acting on the tire. If the Levent Güvenç received the B.S. degree in mechanical tire pressure changes, then the spring constant changes, engineering from Bogaziçi University, Istanbul, in 1985, resulting in a change in the natural frequency. The the M.S. degree in mechanical engineering from Clemson wheel vibration can be measured either by the tire University in 1988, and the Ph.D. degree in mechanical speed or through an accelerometer. Alternatively, tire engineering from the Ohio State University in 1992. Since inflation can be identified through nonlinear identifica- 1996, he has been a faculty member in the Mechanical tion techniques, which rely on tire stiffness changes Engineering Department of Istanbul Technical University, with respect to pressure [7]. where he is currently a professor of mechanical engineer- Due to the U.S. law mandating direct TPMSs, sensor ing and director of the Mechatronics Research Lab and the industries are interested in producing cost-effective solu- EU-funded Automotive Controls and Mechatronics tions. While promising theoretical and practical results Research Center. His research interests include automotive [4]–[7] are available for indirect TPMSs, they have not yet control mechatronics, helicopter stability and control, and appeared in commercial products. applied robust control. Power Kites for Wind Energy Generation Fast Predictive Control of Tethered Airfoils BY MASSIMO CANALE, LORENZO FAGIANO, and MARIO MILANESE he problems posed by electric energy generation from contribution to total energy production within the next fossil sources include high costs due to large demand 15–20 years. Tand limited resources, pollution and CO2 production, Excluding hydropower plants, wind turbines are cur- and the geopolitics of producer countries. These problems rently the largest source of renewable energy [1]. Unfortu- can be overcome by alternative sources that are renewable, nately, wind turbines require heavy towers, foundations, cheap, easily available, and sustainable. However, current and huge blades, which impact the environment in terms renewable technologies have limitations. Indeed, even the of land usage and noise generated by blade rotation, and most optimistic forecast on the diffusion of wind, photo- require massive investments with long-term amortization. voltaic, and biomass sources estimates no more than a 20% Consequently, electric energy production costs are not yet competitive with thermal generators, despite recent Digital Object Identifier 10.1109/MCS.2007.909465 increases in oil and gas prices. 1066-033X/07/$25.00©2007IEEE DECEMBER 2007 « IEEE CONTROL SYSTEMS MAGAZINE 25 FIGURE 1 Kite surfing. Expert kite-surfers drive kites to obtain ener- FIGURE 2 KiteGen small-scale prototype of a yo-yo configuration. gy for propulsion. Control technology can be applied to exploit this The kite lines are linked to two electric drives. The flight of the kite is technique for electric energy generation. controlled by regulating the pulling force on each line, and energy is generated as the kite unrolls the lines. THE KITEGEN PROJECT generated energy [4]. This yo-yo configuration is under the To overcome the limitations of current wind power tech- control of the kite steering unit (KSU, see Figure 3), which nology, the KiteGen project was initiated at Politecnico di includes the electric drives (for a total power of 40 kW), the Torino to design and build a new class of wind energy drums, and all of the hardware needed to control a single generators in collaboration with Sequoia Automation, kite. The aims of the prototype are to demonstrate the abil- Modelway, and Centro Studi Industriali. The project focus ity to control the flight of a single kite, to produce a signifi- [2], [3] is to capture wind energy by means of controlled cant amount of energy, and to verify the energy tethered airfoils, that is, kites; see Figure 1. production levels predicted in simulation studies. The KiteGen project has designed and simulated a The potential of a similar yo-yo configuration is investi- small-scale prototype (see Figure 2). The two kite lines are gated, by means of simulation results, in [5] and [6] for one rolled around two drums and linked to two electric drives, or more kites linked to a single cable. In [5] and [6], it is which are fixed to the ground. The flight of the kite is con- assumed that the angle of incidence of the kites can be trolled by regulating the pulling force on each line. Energy controlled. Thus, the control inputs are not only the roll is collected when the wind force on the kite unrolls the angle ψ and the cable winding speed, as considered in [4] lines, and the electric drives act as generators due to the and in this article, but also the lift coefficient CL. rotation of the drums. When the maximal line length of For medium-to-large-scale energy generators, an alter- about 300 m is reached, the drives act as motors to recover native KiteGen configuration is being studied, namely, the the kite, spending a small percentage (about 12%, see the carousel configuration. In this configuration, introduced in “Simulation Results” section for details) of the previously [7] and shown in Figure 4, several airfoils are controlled by their KSUs placed on the arms of a verti- cal-axis rotor. The controller of each kite is 2 designed to maximize the torque exerted Onboard Sensors Kite Ground Sensors on the rotor, which transmits its motion to (Kite Position and Speed) W (Wind Speed and Direction, an electric generator. For a given wind 1 Line Strength) direction, each airfoil can produce energy ◦ 5 for about 300 of carousel rotation; only a 3 6 Lines 7 small fraction (about 1%, see the “Simula- 6 Control tion Results” section for details) of the Software generated energy is used to drag the kite ◦ against the wind for the remaining 60 . Actuation Unit 4 (Electric Drives and Winches) According to our simulation results, it is estimated that the required land usage FIGURE 3 Scheme of the kite steering unit. The kite steering unit, which provides auto- for a kite generator may be lower than a matic control for KiteGen, includes the electric drives, drums, and all of the hardware current wind farm of the same power by a needed to control a single kite. factor of up to 30–50, with electric energy 26 IEEE CONTROL SYSTEMS MAGAZINE » DECEMBER 2007 production costs lower by a factor up to 10–20. Such poten- tial improvement over current wind technology is due to several aerodynamic and mechanical reasons [8], [9]. For example, 90% of the power generated by a 2-MW three- blade turbine with a 90-m rotor diameter is contributed by only the outer 40% of the blade area, corresponding to about 120 m2. This dependence is due to the fact that the aerodynamic forces on each infinitesimal section of the blades are proportional to the square of its speed with respect to the air, and this speed increases toward the tip of the blades. In KiteGen, the tethered airfoils act as the outer portions of the blades, without the need for mechanical support of the tower and of the less-productive inner blade portions; see Figure 5. Indeed, a mean generated power of 620 kW is obtained in the simulation reported in Figure 16 FIGURE 4 KiteGen carousel configuration concept. Several airfoils for a single kite of 100-m2 area and 300-m line length.
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