Browsing by Author "Erfort, Gareth"
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- ItemNumerical Investigation of a novel blade for use in vertical axis wind turbines.(Stellenbosch : Stellenbosch University, 2019-12) Erfort, Gareth; Von Backstrom, T. W.; Venter, GerhardENGLISH ABSTRACT: Renewable energy prospects in South Africa have been growing thanks to the government’s commitment to alternative energy sources. The country has committed to 36 projects ranging in size from 52 MW to 140 MW. South Africa’s sole energy distributor has been implementing rolling black-outs due to unscheduled maintenance on their plants. This has resulted in average two hour periods of no power for citizens and companies alike. These entities have turned to storage and small scale renewable generation to tide them over during a black out. Within the country wind power is therefore being utilized on both a commercial and private scale. Vertical axis wind turbines have been identified for their applicability in large scale off shore wind farms and ability to operate in urban environments, as a future power generation technology. At this time the vertical axis wind turbine is however not a common sight for power generation. Studies have indicated that a few inherent traits of this turbine design have hindered deployment due to increased manufacturing cost associated with their mitigation. The variation in torque generated during the course of rotation is an example. It can result in drive train stresses, and negatively affect the fatigue life of drive components. This dissertation is aimed at reducing the variation in torque experienced by a straight bladed Darrieus turbine during operation. The study proposed a novel blade that would allow for adjustments to the forces experienced by the turbine during rotation. A virtual laboratory was used to analyse the effect of the blade. An analytical model for a two-bladed H-rotor was implemented in Python and validated against published data. The model was based on the double multiple streamtube (DMST) method as it provided fast accurate solutions. The blade is designed to have an adaptive distortion on the upper surface. The distortion is able to change height and thereby control the tripping of the boundary layer from laminar to turbulent flow. Lift and drag coefficients for the blade were obtained through computational fluid dynamic (CFD) simulations in the open source software OpenFOAM. A transitional turbulence model based on momentum thickness and intermittency was implemented and adjusted to increase efficiency. A random forest surrogate model was used in optimization to determine the exact nature of the proposed distortion. The blade design proved effective in reducing the torque ripple. Placement of the distortion was predominantly on the leading edge (LE) of the blade, where a small change in shape had the largest effect on the boundary layer. The optimized solution reduced the maximum possible torque that the turbine could achieve by synchronously increasing the drag experienced by the blade with the torque fluctuations. The reduction in ripple resulted in an increased life span of the drive train shaft by an estimated 36%. An equation relating the reduction in torque ripple to the reduction in coefficient of performance was identified.
- ItemNumerical optimisation of a small-scale wind turbine through the use of surrogate modelling(University of Cape Town, Energy Research Centre, 2017) Erfort, Gareth; Von Backstrom, Theodor Willem; Venter, GerhardENGLISH ABSTRACT: Wind conditions in South Africa are suitable for small-scale wind turbines, with wind speeds below 7 m.s−1. This investigation is about a methodology to optimise a full wind turbine using a surrogate model. A previously optimised turbine was further optimised over a range of wind speeds in terms of a new parameterisation methodology for the aerodynamic profile of the turbine blades, using non-uniform rational B-splines to encompass a wide range of possible shapes. The optimisation process used a genetic algorithm to evaluate an input vector of 61 variables, which fully described the geometry, wind conditions and rotational speed of the turbine. The optimal performance was assessed according to a weighted coefficient of power, which rated the turbine blade’s ability to extract power from the available wind stream. This methodology was validated using XFOIL to assess the final solution. The results showed that the surrogate model was successful in providing an optimised solution and, with further refinement, could increase the coefficient of power obtained.