The science of making more torque from wind : diffuser experiments and theory revisited

History of the development of DAWT's stretches a period of more than 50 years. So far without any commercial success. In the initial years of development the conversion process was not understood very well. Experimentalists strived at maximising the pressure drop over the rotor disk, but lacked theoretical insight into optimising the performance. Increasing the diffuser area as well as the negative back pressure at the diffuser exit was found profitable in the experiments. Claims were made that performance augmentations with a factor of 4 or more were feasible, but these claims were not confirmed experimentally. With a simple momentum theory, developed along the lines of momentum theory for bare windturbines, it was shown that power augmentation is proportional to the mass flow increase generated at the nozzle of the DAWT. Such mass flow augmentation can be achieved through two basic principles: increase in the diffuser exit ratio and/or by decreasing the negative back pressure at the exit. The theory predicts an optimal pressure drop of 8/9 equal to the pressure drop for bare windturbines independent from the mass flow augmentation obtained. The maximum amount of energy that can be extracted per unit of volume with a DAWT is also the same as for a bare wind turbine. Performance predictions with this theory show good agreement with a CFD calculation. Comparison with a large amount of experimental data found in literature shows that in practice power augmentation factors above 3 have never been achieved. Referred to rotor power coefficients values of C P,rotort= 2.5 might be achievable according to theory, but to the cost of fairly large diffuser area ratio's, typically values of ß>4.5. © 2007 IOP Publishing Ltd

Fault Diagnosis approach based on a model-based reasoner and a functional designer for a wind turbine. An approach towards self-maintenance

The objective of this on-going research is to develop a design methodology to increase the availability for offshore wind farms, by means of an intelligent maintenance system capable of responding to faults by reconfiguring the system or subsystems, without increasing service visits, complexity, or costs. The idea is to make use of the existing functional redundancies within the system and sub-systems to keep the wind turbine operational, even at a reduced capacity if necessary. Re-configuration is intended to be a built-in capability to be used as a repair strategy, based on these existing functionalities provided by the components. The possible solutions can range from using information from adjacent wind turbines, such as wind speed and direction, to setting up different operational modes, for instance re-wiring, re-connecting, changing parameters or control strategy. The methodology described in this paper is based on qualitative physics and consists of a fault diagnosis system based on a model-based reasoner (MBR), and on a functional redundancy designer (FRD). Both design tools make use of a function-behaviour-state (FBS) model. A design methodology based on the re-configuration concept to achieve self-maintained wind turbines is an interesting and promising approach to reduce stoppage rate, failure events, maintenance visits, and to maintain energy output possibly at reduced rate until the next scheduled maintenance

Generating nested quadrature rules with positive weights based on arbitrary sample sets

For the purpose of uncertainty propagation a new quadrature rule technique is proposed that has positive weights, has high degree, and is constructed using onl

Bayesian model calibration with interpolating polynomials based on adaptively weighted Leja nodes

An efficient algorithm is proposed for Bayesian model calibration, which is commonly used to estimate the model parameters of non-linear, computationally expens

Bayesian model calibration with interpolating polynomials based on adaptively weighted Leja nodes

An efficient algorithm is proposed for Bayesian model calibration, which is commonly used to estimate the model parameters of non-linear, computationally expensive models using measurement data. The approach is based on Bayesian statistics: using a prior distribution and a likelihood, the posterior distribution is obtained through application of Bayes' law. Our novel algorithm to accurately determine this posterior requires significantly fewer discrete model evaluations than traditional Monte Carlo methods. The key idea is to replace the expensive model by an interpolating surrogate model and to construct the interpolating nodal set maximizing the accuracy of the posterior. To determine such a nodal set an extension to weighted Leja nodes is introduced, based on a new weighting function. We prove that the convergence of the posterior has the same rate as the convergence of the model. If the convergence of the posterior is measured in the Kullback-Leibler divergence, the rate doubles. The algorithm and its theoretical properties are verified in three different test cases: analytical cases that confirm the correctness of the theoretical findings, Burgers' equation to show its applicability in implicit problems, and finally the calibration of the closure parameters of a turbulence model to show the effectiveness for computationally expensive problems

Fatigue design load calculations of the offshore NREL 5MW benchmark turbine using quadrature rule techniques

A novel approach is proposed to reduce, compared to the conventional binning approach, the large number of aeroelastic code evaluations that are necessary to obtain equivalent loads acting on wind turbines. These loads describe the effect of long-term environmental variability on the fatigue loads of a horizontal-axis wind turbine. In particular Design Load Case 1.2, as standardized by IEC, is considered. The approach is based on numerical integration techniques and, more specifically, quadrature rules. The quadrature rule used in this work is a recently proposed "implicit" quadrature rule, which has the main advantage that it can be constructed directly using measurements of the environment. It is demonstrated that the proposed approach yields accurate estimations of the equivalent loads using a significantly reduced number of aeroelastic model evaluations (compared to binning). Moreover the error introduced by the seeds (introduced by averaging over random wind fields and sea states) is incorporated in the quadrature framework, yielding an even further reduction in the number of aeroelastic code evaluations. The reduction in computational time is demonstrated by assessing the fatigue loads on the NREL 5MW reference offshore wind turbine in conjunction with measurement data obtained at the North Sea, both for a simplified and a full load case

Windmills with increased power output due to tipvanes

Betz's formula, yielding the maximum power output of windmills is only valid under the assumption that the windmill causes a steady axial force acting on the air in a direction opposite to the undisturbed stream velocity. When radial as well as axial forces are applied to the air, this theorem is no longer valid and larger power output may be obtained. This paper deals with a type of windturbine where relatively small vanes, attached to the tips of the turbine blades, deflect the air radially outwards. It describes the lay-out of the system, its potential performance and the research concerning the feasibility of tipvanes