Numerical Shape Optimization of a Wind Turbine Blades Using Artificial Bee Colony Algorithm

Derakhshan, Shahram; Tavaziani, Ali; Kasaeian, Nemat

doi:10.1115/1.4031043

Cited by 34 publications

(12 citation statements)

References 29 publications

(45 reference statements)

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“…It is also a coupled flow solver meaning that the momentum and continuity equations are solved simultaneously. This approach reduces the number of iterations required to obtain convergence criteria and no pressure correction term is required to retain mass conservation, leading to a more robust and accurate solver [30].…”

Section: Fig1 Laboratory Model Of Vertical Axis Tidal Turbinementioning

confidence: 99%

Experimental and numerical study of a vertical axis tidal turbine performance

2017

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In the present study, a vertical axis tidal turbine with movable blades was investigated using experimental and numerical methods. A laboratory model of this turbine type nominated as Hunter turbine was manufactured and tested in an established test rig. In the next step, 3D steady Reynolds-Averaged Navier-Stokes (RANS) equations were solved by CFD using k- turbulence model to predict turbine's performance. The numerical results were verified by the experimental data. In addition, effects of duct, neighbor turbines distance and layout on the power coefficient were investigated. The results showed that the power coefficient of a turbine in the present of ducts with area ratios of 0.1 to 0.26 increased from 0.14 to 0.29. It was also observed that in a four-turbine farm, the output power is maximum for a distance of 13D (diameter of turbine) between neighbor turbines and area ratio of 0.26. For this case, the farm's performance factor is 0.944.

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Section: Fig1 Laboratory Model Of Vertical Axis Tidal Turbinementioning

confidence: 99%

Experimental and numerical study of a vertical axis tidal turbine performance

2017

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“…This turbulence model is also used in Keerthana et al [11] to calculate the aerodynamic characteristics of a 3 kW HAWT. Derakhshan et al [12] compared the results obtained by Spalart-Allmaras, -, and SST turbulence models for estimating the aerodynamic performance of wind turbine blades. The results show that the three turbulence models predict nearly the same power at low wind speeds, but the results obtained by the -are more accurate at higher wind speeds.…”

Section: Introductionmentioning

confidence: 99%

Investigation of the Unsteady Flow Behaviour on a Wind Turbine Using a BEM and a RANSE Method

Alesbe

Abdel‐Maksoud

Aljabair

2016

Journal of Renewable Energy

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Analyses of the unsteady flow behaviour of a 5 MW horizontal-axis wind turbine (HAWT) rotor (Case I) and a rotor with tower (Case II) are carried out using a panel method and a RANSE method. The panel method calculations are obtained by applying the in-house boundary element method (BEM) panMARE code, which is based on the potential flow theory. The BEM is a three-dimensional first-order panel method which can be used for investigating various steady and unsteady flow problems. Viscous flow simulations are carried out by using the RANSE solver ANSYS CFX 14.5. The results of Case I allow for the calculation of the global integral values of the torque and the thrust and include detailed information on the local flow field, such as the pressure distribution on the blade sections and the streamlines. The calculated pressure distribution by the BEM is compared with the corresponding values obtained by the RANSE solver. The tower geometry is considered in the simulation in Case II, so the unsteady forces due to the interaction between the tower and the rotor blades can be calculated. The application of viscous and inviscid flow methods to predict the forces on the HAWT allows for the evaluation of the viscous effects on the calculated HAWT flows.

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“…The objective function of the problems has most commonly taken two forms that focus on the performance of : Aerodynamics [ 207 – 212 ] Maximise the lift Maximise the lift to drag ratio (L/D) Economics [ 205 , 206 , 213 ] Minimise the cost of energy (COE) Maximise the annual energy production (AEP) In 1999 Fuglsang and Madsen [ 205 ], aimed to minimise the COE, which is based on a number of factors: the cost of manufacture and erection, the structural fatigue and extreme loads imparted on the turbine, the AEP and finally the noise considerations. The optimisation algorithm consisted of a multi objective model using sequential linear programming; the results were tested using BEM theory with added tip loss corrections included.…”

Section: Turbine Mechanicsmentioning

confidence: 99%

Building a Digital Wind Farm

Hewitt

Margetts

Revell

2017

Arch Computat Methods Eng

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The purpose of this paper is to provide a high level, holistic overview of the work being undertaken in the wind energy industry. It summarises the main techniques used to simulate both aerodynamic and structural issues associated with wind turbines and farms. The motivation behind this paper is to provide new researchers with an outlook of the modelling and simulation landscape, whilst highlighting the trends and direction research is taking. Each section summarises an individual area of simulation and modelling, covering the important historical research findings and a comprehensive analysis of recent work. This segregated approach emphasises the key components of wind energy. Topics range in geometric scales and detail, ranging from atmospheric boundary layer modelling, to fatigue and fracture in the turbine blades. More recent studies have begun to combine a range of scales and physics to better approximate real systems and provide higher fidelity and accurate analyses to manufacturers and companies. This paper shows a clear trend towards coupling both scales and physics into singular models utilising high performance computing system.

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Numerical Shape Optimization of a Wind Turbine Blades Using Artificial Bee Colony Algorithm

Cited by 34 publications

References 29 publications

Experimental and numerical study of a vertical axis tidal turbine performance

Experimental and numerical study of a vertical axis tidal turbine performance

Investigation of the Unsteady Flow Behaviour on a Wind Turbine Using a BEM and a RANSE Method

Building a Digital Wind Farm

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