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The Effect of Magnetic Bearing on the Vibration and Friction of a Wind Turbine
Title
The Effect of Magnetic Bearing on the Vibration and Friction of a Wind Turbine.
Creator
Vorwaller, Mark, Lin, Kuo-Chi, Raghavan, Seetha, Gou, Jihua, University of Central Florida
Abstract / Description
Demands for sustainable energy have resulted in increased interest in wind turbines. Thus, despite widespread economic difficulties, global installed wind power increased by over 20% in 2011 alone. Recently, magnetic bearing technology has been proposed to improve wind turbine performance by mitigating vibration and reducing frictional losses. While magnetic bearing has been shown to reduce friction in other applications, little data has been presented to establish its effect on vibration and...
Show moreDemands for sustainable energy have resulted in increased interest in wind turbines. Thus, despite widespread economic difficulties, global installed wind power increased by over 20% in 2011 alone. Recently, magnetic bearing technology has been proposed to improve wind turbine performance by mitigating vibration and reducing frictional losses. While magnetic bearing has been shown to reduce friction in other applications, little data has been presented to establish its effect on vibration and friction in wind turbines. Accordingly, this study provides a functional method for experimentally evaluating the effect of a magnetic bearing on the vibration and efficiency characteristics of a wind turbine, along with associated results and conclusions.The magnetic bearing under examination is a passive, concentric ring design. Vibration levels, dominant frequency components, and efficiency results are reported for the bearing as tested in two systems: a precision test fixture, and a small commercially available wind turbine. Data is also presented for a geometrically equivalent ball bearing, providing a benchmark for the magnetic bearing's performance. The magnetic bearing is conclusively shown to reduce frictional losses as predicted by the original hypothesis. However, while reducing vibration in the precision test fixture, the magnetic bearing demonstrates increased vibration in the small wind turbine. This is explained in terms of the stiffness and damping of the passive test bearing. Thus, magnetic bearing technology promises to improve wind turbine performance, provided that application specific stiffness and damping characteristics are considered in the bearing design.
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Date Issued
2012
Identifier
CFE0004452, ucf:49326
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0004452
Coordinated Optimal Power Planning of Wind Turbines in an Offshore Wind Farm
Title
Coordinated Optimal Power Planning of Wind Turbines in an Offshore Wind Farm.
Creator
Vishwakarma, Puneet, Xu, Yunjun, Kapat, Jayanta, Kauffman, Jeffrey, Behal, Aman, University of Central Florida
Abstract / Description
Wind energy is on an upswing due to climate concerns and increasing energy demands on conventional sources. Wind energy is attractive and has the potential to dramatically reduce the dependency on non-renewable energy resources. With the increase in wind farms there is a need to improve the efficiency in power allocation and power generation among wind turbines. Wake interferences among wind turbines can lower the overall efficiency considerably, while offshore conditions pose increased...
Show moreWind energy is on an upswing due to climate concerns and increasing energy demands on conventional sources. Wind energy is attractive and has the potential to dramatically reduce the dependency on non-renewable energy resources. With the increase in wind farms there is a need to improve the efficiency in power allocation and power generation among wind turbines. Wake interferences among wind turbines can lower the overall efficiency considerably, while offshore conditions pose increased loading on wind turbines. In wind farms, wind turbines' wake affects each other depending on their positions and operation modes. Therefore it becomes essential to optimize the wind farm power production as a whole than to just focus on individual wind turbines. The work presented here develops a hierarchical power optimization algorithm for wind farms. The algorithm includes a cooperative level (or higher level) and an individual level (or lower level) for power coordination and planning in a wind farm. The higher level scheme formulates and solves a quadratic constrained programming problem to allocate power to wind turbines in the farm while considering the aerodynamic effect of the wake interaction among the turbines and the power generation capabilities of the wind turbines. In the lower level, optimization algorithm is based on a leader-follower structure driven by the local pursuit strategy. The local pursuit strategy connects the cooperative level power allocation and the individual level power generation in a leader-follower arrangement. The leader, could be a virtual entity and dictates the overall objective, while the followers are real wind turbines considering realistic constraints, such as tower deflection limits. A nonlinear wind turbine dynamics model is adopted for the low level study with loading and other constraints considered in the optimization. The stability of the algorithm in the low level is analyzed for the wind turbine angular velocity. Simulations are used to show the advantages of the method such as the ability to handle non-square input matrix, non-homogenous dynamics, and scalability in computational cost with rise in the number of wind turbines in the wind farm.
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Date Issued
2015
Identifier
CFE0005899, ucf:50896
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0005899
Analytical And Experimental Study Of Monitoring For Chain-Like Nonlinear Dynamic Systems
Title
Analytical And Experimental Study Of Monitoring For Chain-Like Nonlinear Dynamic Systems.
Creator
Paul, Bryan, Yun, Hae-Bum, Catbas, Fikret, Chopra, Manoj, University of Central Florida
Abstract / Description
Inverse analysis of nonlinear dynamic systems is an important area of research in the ?eld of structural health monitoring for civil engineering structures. Structural damage usually involves localized nonlinear behaviors of dynamic systems that evolve into different classes of nonlinearity as well as change system parameter values. Numerous parametric modal analysis techniques (e.g., eigensystem realization algorithm and subspace identification method) have been developed for system...
Show moreInverse analysis of nonlinear dynamic systems is an important area of research in the ?eld of structural health monitoring for civil engineering structures. Structural damage usually involves localized nonlinear behaviors of dynamic systems that evolve into different classes of nonlinearity as well as change system parameter values. Numerous parametric modal analysis techniques (e.g., eigensystem realization algorithm and subspace identification method) have been developed for system identification of multi-degree-of-freedom dynamic systems. However, those methods are usually limited to linear systems and known for poor sensitivity to localized damage. On the other hand, non-parametric identification methods (e.g., artificial neural networks) are advantageous to identify time-varying nonlinear systems due to unpredictable damage. However, physical interpretation of non-parametric identification results is not as straightforward as those of the parametric methods. In this study, the Multidegree-of-Freedom Restoring Force Method (MRFM) is employed as a semi-parametric nonlinear identification method to take the advantages of both the parametric and non-parametric identification methods.The MRFM is validated using two realistic experimental nonlinear dynamic tests: (i) large-scale shake table tests using building models with different foundation types, and (ii) impact test using wind blades. The large-scale shake table test was conducted at Tongji University using 1:10 scale 12-story reinforced concrete building models tested on three different foundations, including pile, box and fixed foundation. The nonlinear dynamic signatures of the building models collected from the shake table tests were processed using MRFM (i) to investigate the effects of foundation types on nonlinear behavior of the superstructure and (ii) to detect localized damage during the shake table tests. Secondly, the MRFM was applied to investigate the applicability of this method to wind turbine blades. Results are promising, showing a high level of nonlinearity of the system and how the MRFM can be applied to wind-turbine blades. Future studies were planned for the comparison of physical characteristic of this blade with blades created made of other material.
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Date Issued
2013
Identifier
CFE0004734, ucf:49818
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0004734
REALIZATION OF POWER FACTOR CORRECTION AND MAXIMUM POWER POINT TRACKING FOR LOW POWER WIND TURBINES
Title
REALIZATION OF POWER FACTOR CORRECTION AND MAXIMUM POWER POINT TRACKING FOR LOW POWER WIND TURBINES.
Creator
Gamboa, Gustavo, Batarseh, Issa, University of Central Florida
Abstract / Description
In recent years, wind energy technology has become one of the top areas of interest for energy harvesting in the power electronics world. This interest has especially peaked recently due to the increasing demand for a reliable source of renewable energy. In a recent study, the American Wind Energy Association (AWEA) ranked the U.S as the leading competitor in wind energy harvesting followed by Germany and Spain. Although the United States is the leading competitor in this area, no one has...
Show moreIn recent years, wind energy technology has become one of the top areas of interest for energy harvesting in the power electronics world. This interest has especially peaked recently due to the increasing demand for a reliable source of renewable energy. In a recent study, the American Wind Energy Association (AWEA) ranked the U.S as the leading competitor in wind energy harvesting followed by Germany and Spain. Although the United States is the leading competitor in this area, no one has been able successfully develop an efficient, low-cost AC/DC convertor for low power turbines to be used by the average American consumer. There has been very little research in low power AC/DC converters for low to medium power wind energy turbines for battery charging applications. Due to the low power coefficient of wind turbines, power converters are required to transfer the maximum available power at the highest efficiency. Power factor correction (PFC) and maximum power point tracking (MPPT) algorithms have been proposed for high power wind turbines. These turbines are out of the price range of what a common household can afford. They also occupy a large amount of space, which is not practical for use in one's home. A low cost AC/DC converter with efficient power transfer is needed in order to promote the use of cheaper low power wind turbines. Only MPPT is implemented in most of these low power wind turbine power converters. The concept of power factor correction with MPPT has not been completely adapted just yet. The research conducted involved analyzing the effect of power factor correction and maximum power point tracking algorithm in AC/DC converters for wind turbine applications. Although maximum power to the load is always desired, most converters only take electrical efficiency into consideration. However, not only the electrical efficiency must be considered, but the mechanical energy as well. If the converter is designed to look like a purely resistive load and not a switched load, a wind turbine is able to supply the maximum power with lower conduction loss at the input side due to high current spikes. Two power converters, VIENNA with buck converter and a Buck-boost converter, were designed and experimentally analyzed. A unique approach of controlling the MPPT algorithm through a conductance G for PFC is proposed and applied in the VIENNA topology. On the other hand, the Buck-boost only operates MPPT. With the same wind profile applied for both converters, an increase in power drawn from the input increased when PFC was used even when the power level was low. Both topologies present their own unique advantages. The main advantage for the VIENNA converter is that PFC allowed more power extraction from the turbine, increasing both electrical and mechanical efficiency. The buck-boost converter, on the other hand, presents a very low component count which decreases the overall cost and volume. Therefore, a small, cost-effective converter that maximizes the power transfer from a small power wind turbine to a DC load, can motivate consumers to utilize the power available from the wind.
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Date Issued
2009
Identifier
CFE0002730, ucf:48158
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0002730