Inverse Design of Single- and Multi-Rotor Horizontal Axis Wind Turbine Blades Using Computational Fluid Dynamics

Moghadassian, Behnam; Sharma, Anupam

doi:10.1115/1.4038811

Cited by 13 publications

(6 citation statements)

References 33 publications

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“…In aerodynamic evaluated processing, Selig and Tangler [3] use the blade element momentum (BEM) theory as for a method for aerodynamic analysis. Lee [4] used the vortex line method (VLM) and Moghadassian and Sharma [5] resolved Reynolds-averaged Navier-Stokes (RANS) equations using an actuator disk model (ADM) to emulate the rotor as a body force. These extensions permit analysis of unconventional rotor-and blade geometries, e.g., multi-rotor turbine configurations and rotor blades with dihedral and/or sweep.…”

Section: Introductionmentioning

confidence: 99%

A Combined Forecasting System Based on Modified Multi-Objective Optimization for Short-Term Wind Speed and Wind Power Forecasting

Zhou

Zhang

2021

Applied Sciences

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Wind speed and wind power are two important indexes for wind farms. Accurate wind speed and power forecasting can help to improve wind farm management and increase the contribution of wind power to the grid. However, nonlinear and non-stationary wind speed and wind power can influence the forecasting performance of different models. To improve forecasting accuracy and overcome the influence of the original time series on the model, a forecasting system that can effectively forecast wind speed and wind power based on a data pre-processing strategy, a modified multi-objective optimization algorithm, a multiple single forecasting model, and a combined model is developed in this study. A data pre-processing strategy was implemented to determine the wind speed and wind power time series trends and to reduce interference from noise. Multiple artificial neural network forecasting models were used to forecast wind speed and wind power and construct a combined model. To obtain accurate and stable forecasting results, the multi-objective optimization algorithm was employed to optimize the weight of the combined model. As a case study, the developed forecasting system was used to forecast the wind speed and wind power over 10 min from four different sites. The point forecasting and interval forecasting results revealed that the developed forecasting system exceeds all other models with respect to forecasting precision and stability. Thus, the developed system is extremely useful for enhancing forecasting precision and is a reasonable and valid tool for use in intelligent grid programming.

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Section: Introductionmentioning

confidence: 99%

A Combined Forecasting System Based on Modified Multi-Objective Optimization for Short-Term Wind Speed and Wind Power Forecasting

Zhou

Zhang

2021

Applied Sciences

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“…In order to account for the advantages of both the CFD and BEM methods, some researchers conducted wind turbine optimization by combining these two methods. In this way, the design accuracy and flexibility were improved while maintaining the low computational cost [31,32]. Another approach to reduce the computational cost of a CFD solution to a level as low as that of a BEM solution is to use a surrogate model such as the response surface method.…”

Section: Introductionmentioning

confidence: 99%

A CFD Based Application of Support Vector Regression to Determine the Optimum Smooth Twist for Wind Turbine Blades

Kaya

2019

Sustainability

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Computational fluid dynamics (CFD) is a powerful tool to estimate accurately the aerodynamic loads on wind turbine blades at the expense of high requirements like the duration of computation. Such requirements grow in the case of blade shape optimization in which several analyses are needed. A fast and reliable way to mimic the CFD solutions is to use surrogate models. In this study, a machine learning technique, the support vector regression (SVR) method based on a set of CFD solutions, is used as the surrogate model. CFD solutions are calculated by solving the Reynolds-averaged Navier–Stokes equation with the k-epsilon turbulence model using a commercial solver. The support vector regression model is then trained to give a functional relationship between the spanwise twist distribution and the generated torque. The smooth twist distribution is defined using a three-node cubic spline with four parameters in total. The optimum twist is determined for two baseline blade cases: the National Renewable Energy Laboratory (NREL) Phase II and Phase VI rotor blades. In the optimization process, extremum points that give the maximum torque are easily determined since the SVR gives an analytical model. Results show that it is possible to increase the torque generated by the NREL VI blade more than 10% just by redistributing the spanwise twist without carrying out a full geometry optimization of the blade shape with many shape-defining parameters. The increase in torque for the NREL II case is much higher.

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“…They declared that the method was rather robust and capable of recovering the blade shape corresponding to the prescribed target pressure distribution. Mileshin et al and Moghadassian and Sharma further applied their inverse design methods to improve the performance of multi‐stage compressors and wind turbine blades. Regarding the description of the blade shape, Lane, and Marshall developed an inverse design method by employing Class/Shape Transformation (CST) parameters to pursue better accuracy of the blade geometry .…”

Section: Introductionmentioning

confidence: 99%

An inverse design tool for two‐dimensional blade generation in aerospace engineering education

Zhu

Shi

et al. 2018

Comp Applic In Engineering

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An inverse design tool based on the theory of characteristic lines and coordinate system transformation, showing the capability of generating two‐dimensional blades with a given pressure distribution along the surface, has been coded with MATLAB and developed in the present work for undergraduate students in aerospace engineering. Validations of the inverse design tool have been evaluated for both single blade surface and plane cascade which show good agreements as comparing to the computational fluid dynamics (CFD) results. This tool provides an intuitive impression on blade generation and a clear picture for the underlying principles of blade design for undergraduate students in the major of aerospace engineering, which also serves sufficient freedom for students to derive their own blade geometry by merely prescribing a surface pressure distribution.

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Inverse Design of Single- and Multi-Rotor Horizontal Axis Wind Turbine Blades Using Computational Fluid Dynamics

Cited by 13 publications

References 33 publications

A Combined Forecasting System Based on Modified Multi-Objective Optimization for Short-Term Wind Speed and Wind Power Forecasting

A Combined Forecasting System Based on Modified Multi-Objective Optimization for Short-Term Wind Speed and Wind Power Forecasting

A CFD Based Application of Support Vector Regression to Determine the Optimum Smooth Twist for Wind Turbine Blades

An inverse design tool for two‐dimensional blade generation in aerospace engineering education

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