946 resultados para FEM, wind turbine blade, Ansys, static and modal analysis, experimental test
Resumo:
POWERENG 2011
Resumo:
This work is aimed at optimizing the wind turbine rotor speed setpoint algorithm. Several intelligent adjustment strategies have been investigated in order to improve a reward function that takes into account the power captured from the wind and the turbine speed error. After different approaches including Reinforcement Learning, the best results were obtained using a Particle Swarm Optimization (PSO)-based wind turbine speed setpoint algorithm. A reward improvement of up to 10.67% has been achieved using PSO compared to a constant approach and 0.48% compared to a conventional approach. We conclude that the pitch angle is the most adequate input variable for the turbine speed setpoint algorithm compared to others such as rotor speed, or rotor angular acceleration.
The unsteady development of a turbulent wake through a downstream low-pressure turbine blade passage
The unsteady development of a turbulent wake through a downstream low-pressure turbine blade passage
Resumo:
This paper presents two-dimensional LDA measurements of the convection of a wake through a low-pressure (LP) turbine cascade. Previous studies have shown the wake convection to be kinematic but have not provided details of the turbulent field. The spatial resolution of these measurements has facilitated the calculation of the production of turbulent kinetic energy and this has revealed a mechanism for turbulence production as the wake converts through the bladerow. The measured ensemble-averaged velocity field confirmed the previously reported kinematics of wake convection while the measurements of the turbulence quantities showed the wake fluid to be characterised by elevated levels of turbulent kinetic energy (TKE) and to have an anisotropic structure. Based on the measured mean and turbulence quantities, the production of turbulent kinetic energy was calculated. This highlighted a TKE production mechanism that resulted in increased levels of turbulence over the rear suction surface where boundary layer transition occurs. The turbulence production mechanism within the bladerow was also observed to produce more nearly isotropic turbulence. Production occurs when the principal stresses within the wake are aligned with the mean strains. This coincides with the maximum distortion of the wake within the blade passage and provides a mechanism for the production of turbulence outside of the boundary layer.
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The advantages of timber in wind turbine blade construction are discussed, and its properties emphasized. The use of timber/epoxy construction enables a high technical specification to be achieved. Tables are given for specific compressive strengths, fatigue strengths and flexural modulus for wind epoxy and glass reinforced polyester composites. Cost ratios are also discussed for the two materials and the cost advantage for wood is emphasized. (A.J.)
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The Brushless Doubly-Fed Machine (BDFM) is a brushless electrical generator which allows variable speed operation with a power converter rated at only a fraction of the machine rating. This paper details an example implementation of the BDFM in a medium-scale wind turbine. Details of a simplified design procedure based on electrical and magnetic loadings are given along with the results of tests on the manufactured machine. These show that a BDFM of the scale works as expected but that the 4/8 BDFM chosen was slower and thus larger than the turbine's original induction machine. The implementation of the turbine system is discussed, including the vector-based control scheme that ensures the BDFM operates at a demanded speed and the Maximum Power Point Tracking (MPPT) scheme that selects the rotor speed that extracts the most power from the incident wind conditions.
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This paper aims to solve the fault tolerant control problem of a wind turbine benchmark. A hierarchical controller with model predictive pre-compensators, a global model predictive controller and a supervisory controller is proposed. In the model predictive pre-compensator, an extended Kalman Filter is designed to estimate the system states and various fault parameters. Based on the estimation, a group of model predictive controllers are designed to compensate the fault effects for each component of the wind turbine. The global MPC is used to schedule the operation of the components and exploit potential system-level redundancies. Extensive simulations of various fault conditions show that the proposed controller has small transients when faults occur and uses smoother and smaller generator torque and pitch angle inputs than the default controller. This paper shows that MPC can be a good candidate for fault tolerant controllers, especially the one with an adaptive internal model combined with a parameter estimation and update mechanism, such as an extended Kalman Filter. © 2012 IFAC.
Resumo:
In a wind-turbine gearbox, planet bearings exhibit a high failure rate and are considered as one of the most critical components. Development of efficient vibration based fault detection methods for these bearings requires a thorough understanding of their vibration signature. Much work has been done to study the vibration properties of healthy planetary gear sets and to identify fault frequencies in fixed-axis bearings. However, vibration characteristics of planetary gear sets containing localized planet bearing defects (spalls or pits) have not been studied so far. In this paper, we propose a novel analytical model of a planetary gear set with ring gear flexibility and localized bearing defects as two key features. The model is used to simulate the vibration response of a planetary system in the presence of a defective planet bearing with faults on inner or outer raceway. The characteristic fault signature of a planetary bearing defect is determined and sources of modulation sidebands are identified. The findings from this work will be useful to improve existing sensor placement strategies and to develop more sophisticated fault detection algorithms. Copyright © 2011 by ASME.