CHAPTER 2 LITERATURE REVIEW

Transcription

1 40 CHAPTER 2 LITERATURE REVIEW The literature review presented in the thesis are classified into three major domains namely Wind turbine airfoil aerodynamics, Design and performance of wind turbine, Optimization of wind turbine and simulation techniques. 2.1 WIND TURBINE AIRFOIL AERODYNAMICS The aerodynamics of airfoils of wind turbine was studied by various researchers with a view to optimizing the wind turbine performance. Some of the literature related to airfoil aerodynamics are presented briefly in this section. The parking conditions of wind turbine rotor in upstream and downstream velocities were analyzed and reported by Apadopoulos et al. (1995). They have created power coefficient curve and assessed wake features due to variation of wind velocities and at stalled condition. They observed increased turbulent levels near the blade tips and around the hub height for various wind speeds. At the wake zone, they observed that there was no increase in turbulent energy and it was due to flat wake velocity profile and the absence of strong shear layers that produce turbulence. A limitation of this study is the terrain complexity in association with the fact that the prevailing wind velocity was particularly high, leading to a relatively weak wake.

2 41 The evolution of turbulence characteristics in wind turbine wakes were studied by Crespo and Hernandez (1996). They evaluated turbulent kinetic energy (k) and its dissipation rate ( ) by experimental methods and numerical methods using CFD. The characteristic values of turbulence velocity and length were calculated by algebraic combinations of k and. The spectrum of unperturbed basic flow was recovered for increasing turbulent kinetic energy by neglecting the effect of wake. The standard deviation of the axial velocity was used to measure the turbulence in wind turbine wakes. Since turbulence was isotropic neither in the atmospheric surface layer nor in the wake zones, in order to validate the results of the numerical model, it was necessary to make assumptions that relate k to the standard deviation in the wind direction. They considered two wake regions one at near the hub and the other away from hub for their analysis leaving the intermediate zone that had turbulence. The region next to the downstream of the rotor, where expansion occurs, was not considered in their analysis. A numerical multi-disciplinary optimization method for design of horizontal axis wind turbines was proposed by Fuglsang and Madsen (1999). The objective was to minimize the cost of generating energy. They considered design fatigue load, extreme wind loads and annual generation of energy. They developed an empirical approach to identify the sensitivities of the above parameters. The empirical approach saved substantial computing time. They considered 1.5 MW stall regulated rotor for optimization. They optimized the shape of the rotor to withstand the maximum strain and for economical use of material. The cost of energy was reduced compared to the traditional design with the same swept area. The optimum specific power was found to be 460 W/m 2, which is lower than that of modern Danish wind turbines. They suggested that airfoil sections should have a relatively high maximum lift at the entire span including the tip region for optimum characteristics. Further, they suggested that an increase in the swept area can

3 42 be achieved by increasing the length of the blade where as the tip section should not have minimum lift airfoils. The aerodynamic characteristics of wind turbines which are closely related to the geometry of the blade profiles were studied by Kamoun Badreddine et al. (2005). He developed an accurate lower order code for the analysis of airfoil in CFD software, based on the singularities method. In this method, source vortex distributions over the airfoil contour were used to compute the flow characteristics. In the analysis of the flow characteristics, the 2D incompressible potential flow model was used. The accuracy and the validity of the results had been tested using experimental data obtained from Wind Turbine Airfoil Catalogue of Risø National Laboratory, Roskilde, Denmark, in August 2001 and obtained good agreement. Zhou et al. (2011) presented the measurements of mean and fluctuating forces on an NACA0012 airfoil over a large range of angle ( ) of attack (0 90 ) and low to small chord Reynolds numbers (R e ) in the range of to They measured forces using a load cell, displayed good agreement with the results estimated from the LDA-measured cross-flow distributions of velocities in the wake based on the momentum conservation. The dependence of the forces on both and R e is determined. It has been found that the stall of an airfoil, characterized by a drop in the lift force and a jump in the drag force, occurs at R e and it is absent at R e = A theoretical analysis is developed to predict the dependence of mean lift and drag on. The airfoil with low Reynolds number was designed by Ronit K. Singh et al. (2012) for applications in small horizontal axis wind turbines to achieve better start up and low wind speed performances. They performed experiments on the improved airfoil (AF300) in an open circuit wind tunnel at Reynolds numbers of 38,000, 75,000, 128,000 and 205,000. A CFD analysis

4 43 was also performed to get additional information on the flow characteristics. Pressure distributions were obtained over the surface of the airfoil and the lift and drag forces were measured with a dynamometer at different angles of attack. 2.2 DESIGN AND PERFORMANCE OF WIND TURBINE The understanding and study of design and performance of wind turbines is important in the course of optimization of its performance. The research and finding of the researchers related to the design and performance of wind turbine is briefly presented in this section. The optimum design parameters for horizontal axis wind turbines was developed and tested by Collecutt and Flay (1996). They considered the design parameters such as the rotor diameter, rated power and tower height. The results of the study indicated that the cost of energy production reduces by the optimization of the relative combination of rotor diameter and rated power with respect to site mean annual wind speed. They optimized wind turbine for the mean annual wind speed range of 6-8 m/s. The cost of energy generation may be reduced up to 10% by properly choosing the wind turbines to suit the rated wind speed. A direct approach for the determination of aerodynamic performance characteristics of horizontal axis wind turbines was examined by Karam Y. Maalawi and Mahdy T.S. Badawy (2001). They developed analytical equations for optimizing chord and twist distribution for an ideal windmill along with an exact trigonometric function method. The variation of the angle of attack along blade span relative wind velocity was obtained directly from unique equation with specific rotor size and blade geometry. In their case study, the analysis of an existing turbine model was carried out and the results were compared with the findings of other investigators. They used

5 44 an ideal actuator disk model and obtained the optimum variations of the axial and rotational induction factors. They proposed a method to predict the performance of horizontal-axis wind turbines and applied to the existing machines of ERDA NASA MOD-0, with the capacity of 100 KW. The optimum aerodynamic blade geometry as well as the trimmed-rotor solutions were obtained and investigated in detail. Further, the authors concluded that the proposed method of analysis eliminated the complications of other numerical methods. Two families of NACA airfoils sections for horizontal-axis wind turbines were studied with the objective of increasing the power output and reported by Maalawi and Badr (2003). They considered the design parameters like number of blades, type of airfoil section and the blade root offset from hub center. They developed a computer program to automate the overall analysis procedures and predicted the variation of the power and thrust coefficients with the design tip speed ratio for various rotor configurations. In the program they varied the airfoil type along the blade and specific index number was assigned to each type. At any desired value of the angle of attack for a specified Reynold s number the lift and drag coefficients were determined. They refined the chord and twist distribution of the blade geometry by approximation of theoretical values. The effects of wind shear and the effect of tower shadow were also reported. The dimensionless chord and twist are calculated at equidistant stations along the blade for different values of blade number and TSR. The chord and rate of taper decreased with TSR for most of the selected airfoil types and number of blades. They predicted that substantial reduction in the power output occurs when the tower shadow or wind shear is taken into consideration. They determined maximum power output for specific airfoil type, number of blades, hub size and TSR.

6 45 Kamoun Badreddinne et al. (2005) optimized various parameters for horizontal axis wind turbines using lifting line theory. They compared their finds with the existing results using blade element momentum theory. They developed a simplified model capable of improving the performance of wind turbines using wind velocities more than 10 m/s. Kishinami et al. (2005) obtained the power coefficient values varying between 0.23 and 0.41 at 4.5 m/s speed rate using NACA profiles as the blade profile. Hirahara et al. (2005) also found that the highest power coefficient was 0.40 using NACA 2404 profiles as the blade profile at 3.7 m/s and 21.4 m/s speed stages. Ozdener (2005) used NACA 4415 profile as the wind turbine blade profile and reported rotation rates up to 2722 rpm and power coefficient up to at wind speed levels ranging between 5.4 m/s and 10.5 m/s. Maalawi and Badr (2003) had the highest power coefficient value of 0.49 on the NACA profile. A mathematical model was developed and implemented by Lanzafame and Messina (2007) for improving wind turbine design based on the blade element momentum theory and simulated for wide range of wind velocities in on design and off design conditions. It is difficult to predict the correct lift and drag coefficient values and correct evaluation of the axial and tangential flow factors using BEM theory. Hence, they considered tangential flow factor and developed a model for the representation of the lift and drag coefficients to optimize rotor performance at low wind velocities occurring at start-up phase of the turbine. Based on experimental results, they performed simulations to evaluate the best lift and drag coefficient representation. The turbine rotor performance was studied using the developed model and the results were compared with experimental findings. The investigation of rotation rates and power coefficients correspond to rotor models of miniature wind turbine manufactured using

7 46 NACA profiles by Ali Vardar and Ilknur Alibas (2007). They used 180 rotor models of 310mm diameter prepared from Balsa wood with various design parameters. The models were tested in a wind tunnel and rotation rates of each rotor were determined based on wind speed. They achieved a maximum power coefficient rate up to with 3077 rpm. They predicted and suggested the existence of following correlation. Rotation rate of rotor and blade angle Power coefficient and blade angle Power coefficient and rotor blade number Best rotor models with high rotation rates were moderately effective in terms of power coefficient. Development of small domestic wind turbine for built up areas were studied by Wang et al. (2008). In their study, a small wind turbine with scoop to grasp slow and turbulent wind flow in built up areas was designed, tested and optimized using the methodology with theoretical, physical and computational methods. The blades were modeled using BEM theory with FORTRAN code. From the model the chord and blade angle distribution along the radius were obtained. Using CFD a virtual wind tunnel was modeled to investigate the performance of the rotor with selected design options. In design, the various shapes of scoops were incorporated and tested. The power curves were drawn using CFD and annual power output was predicted using the new proposed method. Chalothorn Thumthae and Tawit Chitsomboon (2009) studied the numerical simulation of horizontal axis wind turbines (HAWTs) with untwisted blade to determine the optimal angle of attack that produces the highest power output. The CFD numerical solution was carried out by solving

8 47 conservation equations in a rotating reference frame wherein the blades and grids were fixed in relation to the rotating frame. A computational result obtained with 12 o pitch angle was compared favorably with the experimental data of the National Renewable Laboratory (USA), for both inviscid and turbulent conditions. Numerical experiments were conducted by varying the pitch angles and the wind speeds. The power output reached the maximum at pitch angles of 4.12 o, 5.28 o, 6.66 o and 8.76 o for the wind speeds 7.2, 8.0, 9.0 and 10.5 m/s respectively. The optimal angles of attack were also obtained. During analysis, 80% span length of the blade from hub, it was observed that the optimal angle of attack were nearer to the maximum lift point. As the Reynolds numbers are increased, the angle of attack increases as the speed increases. Ahmed et al. (2009) proposed a new method based on analytical approach for performance study of wind turbines. They divided a blade into 100 radial elements for designing rotor and predicting its peak performance. In each element, the chord length, twist angle and power coefficient were determined. They used the iterative process for the convergence of speed interference factor and maximization of power coefficient. Mathematical simulation based on analytical approach of performance evaluation was compared with the experimental results of 10KW HAWT rotors. Lanzafame and Messina (2010) studied the performance of a horizontal axis wind turbine, operating at its maximum power coefficient. It continuously was evaluated by a generated code based on Blade Element Momentum (BEM) theory. It was evaluated for performance and Annual Energy Production (AEP) at both constant and variable standard rotational velocities with maximum power coefficient. They demonstrated the methodology for determining the law of governing the rotational velocity of the rotor. They highlighted that the power coefficient was maximum for

9 48 specific range of wind velocities. They registered 13% increase of AEP for a turbine operating at variable velocity. 2.3 OPTIMIZATION OF WIND TURBINE AND SIMULATION TECHNIQUES The development of evolutionary algorithms like Genetic, neural network etc., attracted the researchers in the area of wind turbine design to optimize its parameters. These algorithms use random scattered search with local optimum and global optimum conditions. The various authors have attempted to optimize the parameters related to turbine and wind farms. Some of the literature related to the optimization of wind turbine parameters are discussed in this section. Fuglsang and Madsen (1999) used a global methodology involving many aspects of blade design including aerodynamics, blade structure, fatigue loads, noise generation and economical costs that are used to define an objective function as the ratio of the total cost of the turbine to the annual energy production. This objective function is optimized by using gradient based methods. Benini and Toffolo (2002) used evolutionary methods to optimize wind turbines. They fix the turbine power and include in the objective function economical costs. A very complete approach to blade optimization is realized by Hampsey (2002). His optimization procedure includes changes in the airfoil shape, but to avoid the computational cost involved in obtaining lift and drag tables, he used a 3D panel method to obtain the force distributions. The optimization of wind turbine blades was proposed by Jureczko et al. (2005). They used two methods for optimization. In the first method, the blade shape was modified to improve the stiffness and stability. In the second

10 49 method, the dynamic and mechanical properties of wind turbine were modified. They used their optimization tool for minimizing the vibrations of blades. They developed a modified genetic algorithm and implemented it for optimizing various objective functions with various constraints. The performance of horizontal axis wind turbines by accurately modeled using the vortex lattice method was studied by Lanzafame and Messina (2007). They used Genetic algorithm based optimization process for optimizing the aerofoil and geometry, the blade structure and the complete rotor system. They worked both in structural and aerodynamic optimization. Sargolzaei and Kianifar (2009) proposed artificial neural networks (ANNs) for estimating the power factor and torque of wind turbines, based on the experimental data gathered from seven prototype vertical Savonius rotors tested in wind tunnel. In their research, the rotors having diverse features that were situated in the wind tunnel had been tested repeatedly for 4 6 times in order to minimize the experimental errors. They suggested that the Reynolds number had a negligible effect on power ratio than the tip speed ratio (TSR). The main input parameter was predicted using neural network. Moreover, different tip speed ratios and different blade angles had been used for simulating the rotor s power factor and torque. The simulated results provided reasonable predictions and estimations of maximum power of rotors and increasing the effectiveness of Savonius turbines. The artificial neural networks simulations and the experimental results indicated that the increase in tip speed ratio enhanced power ratio and torque. Maximum and minimum amount of torque occurred for all the tested rotors at an angle of 60 o and 120 o respectively. Mohammad Monfared et al. (2009) proposed a novel fuzzy logic and artificial neural networks based approach for wind speed forecasting. They provided better precision for wind speed forecasting than conventional

11 50 methods. They used minimum neuron numbers associated with quicker learning process and exact wind speed prediction. They produced reasonably agreeable results by their proposed approach. Andrew Kusiak and Haiyang Zheng (2010) studied the power optimization by computing optimal control settings of wind turbines using data mining and evolutionary strategy algorithms. Data mining algorithms identified functional mapping between power output and controllable and non-controllable variables of a wind turbine. An evolutionary algorithm was applied to determine control settings for maximizing the power output of a turbine based on the identified model. Bharanikumar et al. (2010) presented a Maximum Power Point Tracking (MPPT) control algorithm for variable speed wind turbine driven using a permanent magnet generator. The wind-turbine, the permanent-magnet generator (PMG), the three-phase rectifier, the boost chopper and the inverter were considered in the system. The efficiency of Wind Energy Conversion System (WECS) was maximized by operating the wind turbine generator with variable rotor speed in proportion to the wind speed. In their algorithm, they used tracing of point at which maximum power occurs for every speed. The maximum wind power was determined by adjusting the rotating speed of the permanent-magnet generator in the real time. The simulation was made using MATLAB / SIMULINK and the results were compared with those of the laboratory set-up. 2.4 RESEARCH GAP The various airfoils are tested using experimental procedures and the results are presented by various researchers in the literature. There are no generalized correlations that could be applied to predict the coefficient of lift and drag for various NACA airfoils. The effect of Reynolds number on

12 51 coefficient of lift and drag has been attempted by some of the researchers using experimental set-up. It can be performed using the proposed modified correlation of the coefficient of lift and drag. From the literature, it is understood that the Blade Element Momentum (BEM) method used for maximising the power coefficient needs improvement. In the present work, BEM method is combined with Iterative method and Genetic Algorithm and it is used to optimize the wind turbine power coefficient. In the literature, it is stated that the most difficult issues for the BEM theory are mathematical representation of the correct lift and drag coefficient values and correct evaluation of the axial and tangential flow factors. These difficulties are rectified in this research work by developing the correlation for coefficient of lift and coefficient of drag and the evaluation of axial and tangential flow factors by Iterative method. In the present study, an iterative approach for computing the performance of the horizontal axis wind turbine is proposed and mathematical code is developed to compute the axial and tangential flow factors. In the literature survey on performance of wind turbine system, the convergence of axial and tangential flow factors are very limited and deals with optimizing the wind turbine parameters without considering convergence of flow factors. This study also considered the effect of drag and tip loss correction factor are considered for calculating the axial, tangential flow factors and power coefficient. The results of power coefficient is compared with the effect of drag and tip loss correction factor. A case study was made including the design of wind turbine, performance analysis with various assumptions and CFD analysis of airfoils. The airfoils NACA 4410 and NACA 2415 were taken into consideration for evaluating this proposed approach. The results are discussed and compared

13 52 with those obtained by other investigators. It is shown that the approach used in this study is efficient and saves much of the computational time compared with the commonly used iterative procedures. In the literature it is found that Genetic Algorithm is used for the optimization of chord and twist angle. It is not used for the optimization of power coefficient, angle of attack and tip speed ratio. In this research work, Genetic Algorithm is used to optimize the power coefficient, angle of attack and tip speed ratio of wind turbine blade at various wind velocities. The use of computational simulation can therefore be particularly useful for the optimization of wind turbine blade. Therefore, in the present research work, Genetic Algorithm code is developed for the computation of optimum power coefficient at various wind velocities. 2.5 OBJECTIVES OF THE RESEARCH WORK The objectives of the research are: To develop the correlations for predicting coefficient of lift and drag of NACA 4 series airfoils and validate with experimental results. To propose the modified correlation that can be applied for various NACA airfoils of different thickness. To analyze the effect of Reynolds number on the coefficient of lift and drag of various airfoils using the modified correlations for coefficient of lift and drag on NACA airfoils. To optimize the coefficient lift, drag and pressure using Computational Fluid Dynamics (CFD) method for various angles of attack of airfoil and validation with experimental results.

14 53 To optimize the power coefficient of horizontal axis wind turbine rotor using iterative approach and to develop an iterative method to identify the convergence of axial and tangential flow factors. To optimize the power coefficient, angles of attack and tip speed ratio of wind turbine with NACA airfoils at various wind velocities using Genetic Algorithm.