CN109145506B - Optimal design method for outer side wing profile of wind turbine with high aerodynamic performance and low noise level - Google Patents
Optimal design method for outer side wing profile of wind turbine with high aerodynamic performance and low noise level Download PDFInfo
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Abstract
The invention discloses an optimal design method of an outer wing section of a wind turbine with high aerodynamic performance and low noise level, which comprises the steps of taking the maximum lift-drag ratio and the total aerodynamic noise sound pressure level of the wing section as optimization target parameters according to the performance requirements of the outer side part of a large wind turbine blade in a low wind speed area, and constraining the wing section design lift coefficient, the maximum lift coefficient, stall characteristic parameters, surface roughness stability and inflow turbulence stability to establish a wing section optimal design model; and then combining the inviscid-viscidity strong coupling iterative pneumatic prediction method, the semi-empirical noise prediction model and the optimization algorithm to form the high-performance and low-noise wing profile optimization method. Case optimization results show that the method provided by the invention can reduce the aerodynamic noise of the wing profile, improve the aerodynamic efficiency of the wing profile, ensure the improvement of the aerodynamic load characteristics and the stability of the aerodynamic performance under the non-design working condition, and finally realize the optimization design of the wing profile with high performance and low noise.
Description
Technical Field
The invention belongs to the technical field of wind turbine airfoil profile design, relates to an optimal design method of a wind turbine airfoil profile, and particularly relates to an optimal design method of a wind turbine outer side airfoil profile which is suitable for a low wind speed area and has high aerodynamic performance and low aerodynamic noise.
Background
The wind energy conversion efficiency and the load characteristic of the wind power blade are fundamentally influenced by the aerodynamic performance of the wind turbine airfoil. Therefore, the design optimization of the special airfoil profile of the wind turbine is a basic method for improving the wind energy capture efficiency and the operation reliability of the wind turbine blade.
The wind power industry in China develops rapidly, and the accumulated installed capacity is the first place in the world continuously for many years at present. With the massive development of inland areas such as north China, northeast China, northwest China and the like with rich wind resources, in recent years, the development of wind power in offshore areas and low wind speed areas has become a main trend of wind energy utilization in China. In order to reduce the power generation cost and improve the utilization rate of wind resources, offshore wind field wind turbines and low-wind-speed area wind field wind turbines both require longer blade sizes so as to increase the wind sweeping area of the impeller. The obvious increase of the size of the blade not only increases the flexibility of the blade and makes the contradiction between the aerodynamic efficiency and the load more prominent, but also greatly increases the tip speed ratio of the outer part of the blade and makes the aerodynamic noise of the blade more obvious. The literature shows that the aerodynamic noise source of the blade is mainly positioned at the outer side part of the blade, and the noise sound pressure level increases logarithmically along with the blade size. Wind energy is an environment-friendly energy utilization mode, and aerodynamic noise is almost the only negative influence factor. Particularly, for low wind speed areas such as south China, east China and China areas, which are vast in China, the population distribution is dense, a wind power plant is very close to residential areas of people, and the aerodynamic noise of the wind turbine can have a great influence on daily life and production of people. Therefore, the wind power blade noise reduction technology and the low-noise blade design technology are hot problems of the current blade design research.
The low-noise airfoil design optimization technology is one of basic effective means for reducing aerodynamic noise of the blade. At present, a large number of researchers develop the research on the design and control method of the low-noise wind turbine airfoil (especially the thin airfoil outside the blade). Research shows that the difficulty of low-noise airfoil design optimization is that the maximum lift-drag ratio for representing the aerodynamic efficiency of an airfoil and the total sound pressure level of aerodynamic noise of the airfoil generally have a positive correlation. That is, simply reducing the airfoil aerodynamic noise total sound pressure level tends to cause the airfoil maximum lift-to-drag ratio to also decrease; simply increasing the airfoil maximum lift-to-drag ratio also tends to increase the overall sound pressure level. The intrinsic mechanism is that the most significant parameter influencing the maximum lift-drag ratio of the airfoil is the relative camber of the airfoil. Higher airfoil camber leads to greater lift-to-drag ratio, but flow separation at the trailing edge is also more severe, and the separated flow pressure fluctuates more severely, resulting in greater aerodynamic noise. Therefore, there are few scholars who have to allow for a slight increase in airfoil aerodynamic noise in order to improve airfoil aerodynamic efficiency. The weak positive correlation between the airfoil noise pressure level and the lift-drag ratio determines that the traditional inverse design method cannot effectively meet the contradictory requirements, and a multi-objective optimization design method is required to be used for fully exploring in an airfoil design space, particularly finely adjusting geometric characteristic parameters (such as trailing edge thickness, leading edge radius and the like) which have nonlinear influence on the airfoil noise pressure level to obtain an ideal result. At present, the maximum lift-drag ratio and the noise sound pressure level are used as dual targets by a numerical optimization method to realize the improvement of the aerodynamic efficiency of the airfoil profile and the reduction of the aerodynamic noise, but other important performances such as stall characteristics, leading edge roughness sensitivity and the like are sacrificed. In addition, the students propose a comprehensive optimization design method considering the multi-disciplinary performance characteristic parameters of the wing profiles to realize the improvement of the overall performances of the outer wing profiles, such as aerodynamic performance, structure and noise performance. However, since the optimization process is a multi-parameter balancing process, the optimization model cannot guarantee the reduction of the pneumatic sound pressure level of the final result; the designed maximum lift-to-drag ratio and sound pressure level of the airfoil are often improved simultaneously. There is therefore a need for a more efficient design optimization method to achieve a low noise airfoil with high aerodynamic performance.
Disclosure of Invention
In view of the above problems, the invention establishes an outside airfoil optimization design model according to the unique performance requirements of the wind turbine blades in the wind field of the low wind speed area, and aims to adopt a dual-target optimization method to realize low noise and high aerodynamic efficiency of the airfoil, and simultaneously restrain the design lift coefficient, the maximum lift coefficient, stall characteristic parameters, surface roughness stability and inflow turbulence stability of the airfoil to ensure other important aerodynamic characteristics of the airfoil, so as to form the wind turbine outside airfoil optimization design method with high aerodynamic performance and low aerodynamic noise level.
The technical purpose of the invention is realized by the following technical scheme:
an optimal design method for an outer side airfoil of a wind turbine with high aerodynamic performance and low noise level is characterized in that the maximum lift-drag ratio and the total aerodynamic noise sound pressure level of the outer side airfoil are taken as optimization targets according to the aerodynamic performance requirements and the noise level requirements of blades of the wind turbine, and the method comprises the following steps:
SS1, determining the maximum relative thickness of a target outer side wing profile and design working condition conditions thereof, wherein the design working condition conditions at least comprise an operation attack angle range and an operation Reynolds number condition between cut-in and cut-out wind speeds;
selecting an airfoil with the maximum relative thickness basically the same as that of the target outer airfoil as an initial airfoil according to the maximum relative thickness of the target outer airfoil;
SS2. Determining an optimized objective function F for the target outside airfoil:
the optimization objective function F at least comprises a maximum lift-drag ratio l/d for representing the aerodynamic efficiency of the wing profile max And a total acoustic pressure level S of aerodynamic noise of the airfoil characterizing the self-noise level of the airfoil pl,total Two optimization objectivesThe parameters are set to be in a predetermined range,
total sound pressure level S of aerodynamic noise of said airfoil pl,total At least comprises the sound pressure level of airfoil turbulent boundary layer trailing edge noise, the sound pressure level of separated flow noise, the sound pressure level of laminar boundary layer vortex shedding noise, the sound pressure level of blunt trailing edge noise and the sound pressure level of turbulent inflow noise,
respectively determining the weight coefficient of each optimization target parameter according to the design requirement emphasis of the target outer side wing profile, respectively determining the normalized scale factor of each optimization target parameter according to the magnitude, respectively determining the expected coefficient of each optimization target parameter according to the increase and decrease expectation in the optimization process,
the expression of the optimized objective function F is F =sigmae i w i s i f i ，
Wherein, f i Optimizing the target parameters for each item, e i Optimizing the desired coefficient, w, of the objective parameter for each item i Optimizing the weight coefficient, s, of the target parameter for each item i Optimizing the normalized scale factor of the target parameter for each item;
SS3, determining a constraint parameter system of the target outer side airfoil, wherein the constraint parameter system at least comprises a pneumatic load characteristic parameter representing the airfoil under the design working condition and a stability parameter representing the change of the airfoil aerodynamic characteristics along with the non-design working condition;
SS4, taking the geometrical characteristic parameters of the airfoil profile as the design variables of the target outer side airfoil profile, and determining the geometrical design space of the target outer side airfoil profile at least according to the geometrical characteristic and structure compatibility requirements of the initial airfoil profile;
and SS5, performing iterative optimization on the optimization objective function F by adopting a multi-objective optimization algorithm, calculating the aerodynamic performance and the aerodynamic noise characteristic of the wing profile in each iterative optimization process, and judging whether the optimization objective function F reaches an optimal solution or not by analyzing the aerodynamic performance and the aerodynamic noise characteristic of the wing profile to finally obtain the target outer side wing profile.
In the optimal design method of the outer side wing profile of the wind turbine with high aerodynamic performance and low noise level, the outstanding contradiction between the aerodynamic efficiency and the aerodynamic performance is caused by the flexible long blade in the low wind speed areaDynamic noise relationship, wherein the aerodynamic efficiency of the blade is related to the maximum lift-drag ratio l/d of the airfoil max Closely related, the aerodynamic noise of the blade is represented by the total sound pressure level S of the aerodynamic noise pl,total And (5) characterizing. Therefore, from the level of the airfoil profile, with the maximum lift-drag ratio l/d max And aerodynamic noise total sound pressure level S pl,total As a constituent parameter for the pneumatic optimization objective. The two sub-target parameters are combined by an expectation coefficient, a weight coefficient, a magnitude and a normalized scale factor to form an overall optimization objective function F.
Preferably, in step SS2, the optimization objective function F is a maximum objective function F MAX Optimizing the maximum lift-drag ratio l/d of the expected airfoil shape in the target parameter max Is increased in the optimization process, the expected coefficient is set to plus 1, and the total sound pressure level S of the airfoil aerodynamic noise is expected pl,total Reducing in the optimization process, setting the expected coefficient to be-1, and setting the maximum objective function F MAX Is F MAX ＝w 1 s 1 (l/d) max -w 2 s 2 S pl,total Wherein w is 1 、w 2 Respectively, the maximum lift-to-drag ratio l/d max Airfoil aerodynamic noise total sound pressure level S pl,total And w is a weight coefficient of 1 +w 2 ＝100、w 1 >w 2 ；s 1 、s 2 Respectively, is the maximum lift-drag ratio l/d max Airfoil aerodynamic noise total sound pressure level S pl,total Is normalized to a scale factor, s 1 、s 2 According to the maximum lift-to-drag ratio l/d max Airfoil aerodynamic noise total sound pressure level S pl,total Is determined.
Further, in step SS2, the total sound pressure level S of the aerodynamic noise of the airfoil pl,total The sound pressure level at discrete frequency within the frequency range of 10Hz to 20000Hz under the design working condition is logarithmically superposed to obtain the sound pressure level, and the sound pressure level at each frequency comprises five pneumatic noise sources, namely turbulent flow boundary layer trailing edge noise, separation flow noise, laminar flow boundary layer vortex shedding noise, blunt trailing edge noise and turbulent flow inflow noise.
Preferably, in step SS3, the characterizing the aerodynamic load characteristic parameters under the design condition of the airfoil profile at least includes settingCoefficient of lift of meter C l,design And coefficient of maximum lift C l,max So as to improve the blade torque in the low wind speed area and reduce the possible limit load.
Further, in step SS3, the stability parameter characterizing the airfoil aerodynamic characteristics as a function of the off-design condition at least includes: stall characteristic parameter M for representing fluctuation of aerodynamic characteristics of airfoil after stall along with attack angle stallx Maximum lift coefficient C representing stability of aerodynamic load and efficiency of airfoil profile along with changes of rough conditions of blade surface l,max To the maximum lift-to-drag ratio l/d max Surface roughness sensitivity parameter S cl ,S ld Maximum lift coefficient C representing stability of aerodynamic loading and efficiency of airfoil profile with changes of free incoming flow turbulence l,max To the maximum lift-to-drag ratio l/d max Free incoming flow turbulence sensitivity parameter T cl ,T ld 。
Further, in step SS3, the stall characteristic parameter M stallx The product of the variation of the lift coefficient at a certain attack angle relative to the maximum lift coefficient at the stall attack angle and the average variation rate of the lift coefficient is adopted for definition; surface roughness stability parameter S cl ,S ld Free incoming flow turbulence stability parameter T cl ,T ld The method is characterized in that the method is defined by adopting the form of relative change rate of characteristic parameters under design conditions and corresponding parameters under non-design conditions, and expressions of the four parameters are respectively as follows:
wherein C is l,max,ft ,(l/d) max,ft Maximum lift coefficient and maximum lift-drag ratio under a condition of fixed transition corresponding to a rough surface, C l,max,TI ,(l/d) max,TI The maximum lift coefficient and the maximum lift-drag ratio under certain high-turbulence free incoming flow are obtained. That is, the main constraint parameters in the airfoil optimization method provided by the invention are as follows: c l,design ,C l,max ,M stallx ,S cl ,S ld ,T cl ,T ld And seven parameters are equal.
Preferably, in step SS4, the geometric design space of the target outer airfoil is constituted by the variation range of each design variable.
Further, in step SS4, the design variable form of the airfoil is determined by an airfoil geometric analysis mode, the airfoil analysis mode adopts a spline curve method, and the corresponding airfoil design variable is a parameter representing the geometric characteristics thereof and at least comprises the maximum relative thickness and the maximum thickness position X of the airfoil t Relative camber C am Maximum camber position X cam Leading edge radius R le And the thickness T of the trailing edge tr And the like. Three factors are considered in the range of the wing profile design variable, and firstly, the change range is ensured to be large enough, so that the design space has sufficiency, and the optimal solution is ensured to be obtained; secondly, the non-physical result of the excessively singular geometric shape is avoided; finally, the geometrical compatibility of the new airfoil with other airfoils is ensured. The geometrical compatibility of the airfoil is generally obtained by constraining the maximum thickness position, the maximum camber position and the like of the airfoil.
Preferably, in the step SS5, the adopted optimization algorithm is a multi-objective micro-genetic algorithm, the aerodynamic performance and noise characteristic analysis of the airfoil profile is required in each step of the optimization iteration process, and the reynolds number of the aerodynamic performance analysis and the noise characteristic analysis of the airfoil profile is determined according to the range of the operating reynolds number at the outer position of the blade where the target outer airfoil is located.
Further, in step SS5, the airfoil aerodynamic performance analysis in each optimization iteration process includes three working conditions, which are a design working condition, a rough surface working condition and a high turbulence free inflow working condition, wherein the design working condition is a natural transition and uniform inflow condition, the rough surface working condition is simulated by setting a fixed transition point on the upper and lower surfaces of an airfoil, and the high turbulence inflow working condition takes an inflow turbulence level of an outer blade of the blade when the blade normally operates at a wind condition above a rated wind speed as an inflow turbulence condition.
Further, in the step SS5, under each working condition, the aerodynamic coefficient within the range from-5 ° to 25 ° of the angle of attack needs to be calculated, so that the maximum lift-drag ratio, the design lift coefficient, the maximum lift coefficient, the stall parameter and the like under each working condition are obtained through analysis, and each target and the constraint parameter are further obtained through calculation.
Further, in the step SS5, the airfoil aerodynamic performance is calculated by adopting a non-viscous boundary layer coupling iteration method, and the transition prediction method is based on the small perturbation theory e N The method, wherein N is a perturbation amplification factor; different in-flow turbulence levels can be simulated by setting the value of N.
Further, in step SS5, the airfoil aerodynamic noise analysis needs to calculate the total sound pressure level of airfoil self-noise under five noise sources, where the five aerodynamic noise sources are airfoil turbulent boundary layer trailing edge noise, separation flow noise, laminar boundary layer vortex shedding noise, blunt trailing edge noise, and turbulent inflow noise, the aerodynamic noise of the first four sound sources is analyzed by using a BPM semi-empirical model, and the aerodynamic noise of the last sound source is analyzed by using a modified Amiet semi-empirical model.
Further, in the step SS5, the noise sound pressure levels of the five sound sources at each discrete frequency point of the 34 discrete frequency points selected in the frequency range of 10Hz to 20000Hz are sequentially calculated, so as to obtain the total sound pressure level of the airfoil aerodynamic noise in the calculated frequency domain.
The working principle of the airfoil optimization design method of the invention is further described as follows:
the invention provides a high-performance low-noise wing-shaped optimal design method, belonging to a typical double-target multi-working-condition wing-shaped aerodynamic optimal design method. Compared with the existing wing profile noise optimization method, the method is improved mainly in two aspects. The first is to simplify the optimization objective function to ensure the optimal implementation of the main objective parameters. The main contradiction of the low-noise wind power blade wing profile in the low wind speed area is the contradiction between aerodynamic efficiency and aerodynamic noise, so that the maximum lift-drag ratio and the total sound pressure level of the aerodynamic noise of the wing profile are only taken as target parameters, and a multi-target global optimization algorithm is adopted to fully and optimally design the wing profile space so as to ensure the improvement of the maximum lift-drag ratio of the wing profile and the reduction of the total sound pressure level of the noise. Secondly, complex constraint parameters are adopted to ensure the realization of other important aerodynamic performance characteristics of the wing profile. The design of the wind turbine airfoil in the low wind speed area needs to consider the contradiction between the aerodynamic efficiency and the load caused by the increase of the size of the blade and the influence of the complex operation condition on the performance stability of the blade besides the special consideration of the noise requirement. The blade airfoil profile in the low wind speed area needs to have a high design lift coefficient to improve the wind wheel torque of the blade airfoil profile, but the increase of the design lift coefficient usually causes the maximum lift coefficient to increase, so that the limit load also increases. The invention therefore ensures good load characteristics by limiting the lower bound of the design lift coefficient and the upper bound of the maximum lift coefficient. On the other hand, the wind power blade in the low wind speed area has complex operation conditions, and besides the rough condition of the blade surface is easy to change, the typical wind condition of the low wind speed area is characterized by high turbulence characteristic. The large scale turbulence makes the blade operating attack angle changeable (gust turbulence), and the small scale turbulence makes the free incoming flow turbulence higher (up to more than 20%). In order to improve the aerodynamic efficiency and the load stability of the blade under the complex operation condition, the aerodynamic performance stability of the airfoil under the non-design working condition must be effectively restrained. The method uses the stall characteristic parameters to represent the characteristics of aerodynamic force changing along with the attack angle after an airfoil stall point and uses the characteristics as one of main constraint parameters, and the target airfoil is expected to have smaller stall characteristic parameters so as to reduce the fatigue load of the blade; the stability of the aerodynamic performance of the airfoil is represented by sensitivity parameters of the maximum lift coefficient and the maximum lift-drag ratio changing along with surface roughness, free incoming flow turbulence and the like and is used as a part of constraint parameters; the target airfoil is expected to have a lower surface roughness sensitivity parameter and a lower incoming flow turbulence sensitivity parameter to ensure the performance stability of the blade under variable operating conditions.
According to the airfoil optimization mathematical model, an effective high-performance low-noise wind turbine airfoil optimization design method is finally formed by combining an airfoil geometric design and a multi-objective optimization method through a fast and steady aerodynamic prediction method and a noise semi-empirical prediction model.
Compared with the prior art, the invention has the beneficial results that: the optimized design method of the wind turbine airfoil section can ensure that the airfoil section has good aerodynamic load characteristic and stall characteristic and aerodynamic performance stability under variable working conditions such as rough surface, high turbulence free incoming flow and the like while realizing high aerodynamic efficiency and low aerodynamic noise under the working condition of airfoil section design, thereby obtaining the special airfoil section for the wind turbine with high performance and low noise, and providing basic support for reducing the aerodynamic noise of the wind turbine blade and improving the wind energy conversion efficiency and the performance stability.
Drawings
FIG. 1 is a flow chart of a high performance, low noise airfoil optimization method proposed by the present invention;
FIG. 2 is a geometrical profile of a low-noise high-performance wind turbine airfoil newly designed according to the present invention;
FIG. 3 is a plot of airfoil sound pressure level for the new airfoil proposed by the present invention under design conditions;
FIG. 4 is a comparison of lift-drag ratio curves for a new airfoil profile and an initial airfoil profile under the influence of surface roughness;
FIG. 5 is a comparison of lift-to-drag ratio curves for a new airfoil profile versus an initial airfoil profile under the influence of high turbulence inflow;
FIG. 6 is a comparison of lift curves for a new airfoil and an initial airfoil under the influence of surface roughness;
FIG. 7 is a comparison of lift curves for a new airfoil and an initial airfoil under the influence of high turbulence inflow.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the following detailed description of the technical solutions and advantages of the present invention is provided with the best mode and the accompanying drawings.
According to the mainstream model of a horizontal axis wind turbine in a wind field in China at present, a certain 2 MW-level blade is selected as a reference blade. The target airfoil profile is a wind turbine airfoil profile at the spanwise position of the outer side of the blade, and the relative thickness of the wind turbine airfoil profile is 21%. When the blade normally works (between cut-in and cut-out wind speeds), the actual running Reynolds number of the airfoil at the position is about 4.5E +06, and the Reynolds number range related up and down is about 3.0E + 06-6.0E +06.
The outer side of the blade is the main area of the wind turbine for capturing wind energy and is also the main part for generating aerodynamic noise. Thus, the blade outboard airfoil optimization objective focuses on the maximum lift-to-drag ratio, which characterizes the airfoil aerodynamic efficiency, and the total acoustic noise level, which characterizes the airfoil self-noise level. That is to say, the airfoil profile optimization objective function provided by the invention consists of the maximum lift-drag ratio (l/d) max ) And the total sound pressure level S of the aerodynamic noise pl,total Two sub-target parameters. Because the two parameters are different in required weight and magnitude, a unified maximum objective function F is formed by further combining the weight coefficient and the normalized scale factor MAX . For both sub-objective functions, it is expected that the maximum lift-to-drag ratio increases and the total noise sound pressure level decreases during the optimization process. The assignment of the normalization scale factors and the weighting factors is shown in table 1, wherein the normalization factors are determined from the magnitude of the parameter values of the existing wind turbine airfoil with the same relative thickness (21%).
TABLE 1 model coefficients for high Performance, low noise airfoils
The total weight of the maximum lift-drag ratio and the total aerodynamic sound pressure level is 100, and the aerodynamic efficiency has a decisive influence on the power generation cost of the wind turbine, so that the weight of the maximum lift-drag ratio is 75% and is far greater than the weight of the total aerodynamic sound pressure level (accounting for 25%).
Thus, the optimized objective function of the large-thickness airfoil of the blade root is obtained as follows:
F＝w i s i p i f i
＝w 1 s 1 (l/d) max -w 2 s 2 S spl,total
＝0.75s 1 (l/d) max -0.25s 2 S spl,total
note that the setting of the above-described specific weight coefficient may be autonomously assigned according to design requirements at the time of application.
The high-performance and low-noise wind turbine airfoil optimization model takes the maximum lift-drag ratio representing the aerodynamic efficiency as a design target, simultaneously considers the aerodynamic load characteristic of the airfoil and the aerodynamic performance stability of the airfoil performance under the non-design operating condition, and takes the parameters as the constraint conditions of the optimization model to ensure the design realization of the high-performance airfoil. Specifically, the constraint parameters provided by the invention comprise a design lift coefficient C l,design Maximum coefficient of lift C l,max Stall characteristic parameter M of stall-followed airfoil aerodynamic characteristics fluctuating along with angle of attack stallx Surface roughness sensitivity parameter S of maximum lift coefficient and maximum lift-drag ratio cl ,S ld Sensitivity parameter T of free incoming flow turbulence of maximum lift-drag ratio and maximum lift coefficient cl ,T ld . The settings of the specific constraint parameters are shown in table 2 below. Wherein the setting of each constraint parameter is based on a comparison of the parameters for an existing 21% relative thickness airfoil.
TABLE 2 model parameters for high Performance, low noise Airfoil optimization design
It should be noted that in the optimization algorithm, the constraint parameters of the airfoil are essentially coupled to the target parameters in a manner of penalty function, so that the airfoil with better performance can be ensured to be a feasible solution through strict constraint conditions. It can be seen from the table that the constraint conditions of the target airfoil are very strict with reference to the existing reference airfoil and the initial airfoil. For example, the design lift coefficient of the target airfoil must be higher than 1.01, and the maximum lift coefficient must be less than 1.5; meanwhile, for all four sensitivity parameters which are used for representing the aerodynamic performance stability of the airfoil, the sensitivity parameters are required to be smaller than those of the reference airfoil, namely, the aerodynamic performance stability of the target airfoil is ensured to be better than that of the initial airfoil and the reference airfoil.
The initial airfoil selected in the optimization case of the present invention is a NACA63421 airfoil widely used in multi-megawatt blade design. The airfoil has a large amount of reliable experimental data, the stall is gentle, but the design lift coefficient is low, the maximum lift-drag ratio is low, the aerodynamic noise is high, and further optimization is needed. The invention adopts a spline method to carry out parametric analysis on the initial airfoil profile, and the design variables of the airfoil profile are geometric characteristic parameters, such as the maximum thickness position X t Relative camber C am Maximum camber position X cam Leading edge radius R le Tail edge thickness T tr And the like. The range of the airfoil design variable considers the following three factors, firstly, the change range is ensured to be large enough, so that the design space has sufficiency; further, the non-physical result that the geometric shape is too singular is avoided; finally, the geometrical compatibility of the new airfoil with other airfoils is ensured. For the NACA63421 airfoil, the range of variation settings for the design variables are as shown in table 3:
TABLE 3 Airfoil design variable space
The target airfoil is designed by adopting a blunt trailing edge, and the relative thickness of the trailing edge is about 0.5 percent.
The airfoil optimization model is formed, a high-performance and low-noise airfoil optimization design method is formed by further combining an airfoil geometric design module, a pneumatic performance calculation module, a pneumatic noise analysis module and an optimization algorithm module under three working conditions, and the frame flow of the method is shown in figure 1. The optimization case provided by the invention is to obtain an optimal solution by adopting a multi-objective genetic algorithm to obtain a target airfoil profile. In the optimization method, the geometric design module realizes the parametric analysis and the shape modification design of the initial airfoil profile. The airfoil aerodynamic performance analysis under three working conditions all adopts a non-viscous boundary layer coupling iteration method, and the adopted transition prediction method is based on small disturbanceTheory of motion e N The method, wherein N is a perturbation amplification factor. In the three working conditions, the specific calculation condition of the design working condition is natural transition, N =9, and the corresponding free incoming flow turbulence degree is about 0.07%; the surface roughness working condition is simulated by adopting a fixed transition mode, a fixed transition point on the upper surface is at a position with 1% chord length, and a transition point on the lower surface is at a position with 10% chord length; the high turbulence free-run calculation condition was N =2.6, corresponding to a free-run turbulence of 1%. Reynolds numbers corresponding to the three working conditions are Re =4.5E +06, and the attack angle ranges are (-5-25 degrees). The noise analysis was calculated under conditions Re =4.5e +06, inflow turbulence intensity 0.05%, turbulence length scale 0.06m, inflow angle of attack 3 °. Among the five considered pneumatic noise sources, the trailing edge noise of an airfoil turbulent boundary layer, the noise of separated flow, the vortex shedding noise of a laminar boundary layer and the blunt trailing edge noise are analyzed by adopting a BPM semi-empirical model, and the pneumatic noise of turbulent inflow is analyzed by adopting a modified Amiet semi-empirical model. Finally, the total sound pressure level of the airfoil pneumatic noise in the frequency range of 10Hz to 20000Hz is obtained. Further, according to the wing profile performance analysis and evaluation results, the optimization algorithm module compares a wing profile target function, constraint and the like, judges whether an optimal solution is achieved and carries out the next iteration.
The geometry of the target airfoil CAS-LN-210 airfoil resulting from the present example is shown in FIG. 2. The comparison of the sound pressure levels of the target airfoil and the initial airfoil in the frequency domain under the design conditions is shown in fig. 3. The comparison curve of lift-drag ratio under the design working condition and the non-design working condition is shown in fig. 4-5, and the comparison curve of lift coefficient under the design working condition and the non-design working condition is shown in fig. 6-7. The design target parameter and constraint parameter pairs for the detailed target airfoil versus the initial airfoil are shown in table 4.
TABLE 4 Performance characteristics and constraint parameters Table for target airfoils
As can be seen from the graph, in terms of the target parameters, first, the maximum lift-drag ratio of the target airfoil is improved5.9 percent. The sound pressure level pair of the target airfoil profile and the initial airfoil profile in the frequency domain is shown in fig. 2. It can be seen that the aerodynamic noise energy is mainly concentrated in the low frequency region, and although the noise sound pressure level of the target airfoil is lower than that of the original airfoil in the high frequency region, the maximum sound pressure level of the target airfoil is reduced in the low frequency region; so that the total sound pressure level of the airfoil aerodynamic noise is reduced from 79.3842 to 78.7232. Namely, the method provided by the invention reduces the aerodynamic noise of the wing profile while improving the aerodynamic efficiency of the wing profile, so that the overall objective function F is realized obj Is greatly optimized. In the aspect of constraint parameters, the design lift coefficient of the airfoil is effectively improved, and the increase of the maximum lift coefficient meets the constraint condition (<1.5). In terms of stall characteristics, the target airfoil maintains good stall characteristics of the original airfoil, again with stall characteristic parameters less than 10. In the aspect of aerodynamic performance stability, the four sensitivity parameters are smaller than those of the initial airfoil profile; particularly, the sensitivity parameter of the maximum lift coefficient along with the surface roughness is reduced from 7.41 percent of the initial airfoil profile to 4.09 percent of the target airfoil profile, the sensitivity parameters of the maximum lift coefficient and the maximum lift-drag ratio along with the free incoming flow turbulence are reduced by about 50 percent, namely the stability of the aerodynamic performance of the target airfoil profile along with the change of the complex operation working condition is obviously enhanced. The more intuitive results are shown in fig. 4-7. The comprehensive chart results show that the optimization design method provided by the invention can reduce the aerodynamic noise of the wing profile and improve the aerodynamic efficiency of the wing profile, and simultaneously ensure that the aerodynamic load characteristics of the wing profile and the stability of the aerodynamic performance under the non-design working condition are improved, and finally realize the optimization design of the wing profile with high performance and low noise.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, but rather as the subject matter of any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention.
Claims (10)
1. An optimal design method for an outer side airfoil of a wind turbine with high aerodynamic performance and low noise level is characterized in that the maximum lift-drag ratio and the total aerodynamic noise sound pressure level of the outer side airfoil are taken as optimization targets according to the aerodynamic performance requirements and the noise level requirements of blades of the wind turbine, and the method comprises the following steps:
SS1, determining the maximum relative thickness of a target outer side wing profile and design working condition conditions thereof, wherein the design working condition conditions at least comprise an operation attack angle range and an operation Reynolds number condition between cut-in and cut-out wind speeds;
selecting an airfoil with the maximum relative thickness basically the same as that of the target outer airfoil as an initial airfoil according to the maximum relative thickness of the target outer airfoil;
SS2. Determining an optimized objective function F for the target outside airfoil:
the optimization objective function F at least comprises a maximum lift-drag ratio l/d for representing the aerodynamic efficiency of the wing profile max And a total acoustic pressure level S of aerodynamic noise of the airfoil characterizing the self-noise level of the airfoil pl,total Two items of optimization target parameters are set according to the formula,
total sound pressure level S of aerodynamic noise of said airfoil pl,total The sound pressure level of discrete frequency in the frequency range of 10Hz to 20000Hz under the design working condition is logarithmically superposed to obtain the sound pressure level at least comprising the sound pressure level of wing-shaped turbulent flow boundary layer trailing edge noise, the sound pressure level of separation flow noise, the sound pressure level of laminar flow boundary layer vortex shedding noise, the sound pressure level of blunt trailing edge noise and the sound pressure level of turbulent inflow noise,
respectively determining the weight coefficient of each optimization target parameter according to the design requirement emphasis of the target outer side wing profile, respectively determining the normalized scale factor of each optimization target parameter according to the magnitude, respectively determining the expected coefficient of each optimization target parameter according to the increase and decrease expectation in the optimization process,
the expression of the optimized objective function F is F =sigmae i w i s i f i ，
Wherein f is i Optimizing the target parameters for each item, e i Optimizing the desired coefficient, w, of the objective parameter for each item i Optimizing the weight coefficient, s, of the target parameter for each item i Optimizing the normalized scale factors of the target parameters for each item;
and wherein the optimization objective function F is the maximumLarge objective function F MAX Optimizing the maximum lift-drag ratio l/d of the desired wing shape in the target parameter max Is increased in the optimization process, the expected coefficient is set to plus 1, and the total sound pressure level S of the airfoil aerodynamic noise is expected pl,total Reducing in the optimization process, setting the expected coefficient to be-1, and setting the maximum objective function F MAX Is F MAX ＝w 1 s 1 l/d max -w 2 s 2 S pl,total Wherein w is 1 、w 2 Respectively, the maximum lift-to-drag ratio l/d max Airfoil aerodynamic noise total sound pressure level S pl,total And w is a weight coefficient of 1 +w 2 ＝100、w 1 >w 2 ；s 1 、s 2 Respectively, the maximum lift-to-drag ratio l/d max Airfoil aerodynamic noise total sound pressure level S pl,total Is normalized to a scale factor, s 1 、s 2 According to the maximum lift-to-drag ratio l/d max Airfoil aerodynamic noise total sound pressure level S pl,total Determining the magnitude of the signal;
SS3, determining a constraint parameter system of the target outer side airfoil, wherein the constraint parameter system at least comprises a pneumatic load characteristic parameter representing the airfoil under the design working condition and a stability parameter representing the change of the airfoil aerodynamic characteristics along with the non-design working condition; the stability parameters for representing the airfoil aerodynamic characteristics along with the variation of the non-design working conditions at least comprise: stall characteristic parameter M for representing fluctuation of aerodynamic characteristics of airfoil after stall along with attack angle stallx Maximum lift coefficient c representing stability of aerodynamic load and efficiency of airfoil profile along with changes of rough conditions of blade surface l,max To the maximum lift-to-drag ratio l/d max Surface roughness sensitivity parameter S cl ,S ld Maximum lift coefficient c representing stability of aerodynamic loading and efficiency of airfoil profile with changes in free-incoming flow turbulence l,max To the maximum lift-to-drag ratio l/d max Free incoming flow turbulence sensitivity parameter T cl ,T ld Wherein, in the step (A),
the stall characteristic parameter M stallx The product of the variation of the lift coefficient at a certain attack angle relative to the maximum lift coefficient at the stall attack angle and the average variation rate of the lift coefficient is adopted for definition; watch (A)Surface roughness stability parameter S cl ,S ld Free incoming flow turbulence stability parameter T cl ,T ld The method is defined by adopting the form of relative change rate of characteristic parameters under the design condition and corresponding parameters under the non-design condition, and expressions of the four parameters are respectively as follows:
wherein c is l,max,ft ,l/d max,ft Maximum lift coefficient and maximum lift-drag ratio under a condition of fixed transition corresponding to a rough surface, c l,max,TI ,l/d max,TI The maximum lift coefficient and the maximum lift-drag ratio under certain high-turbulence free incoming flow are obtained;
SS4, taking the geometrical characteristic parameters of the airfoil profile as the design variables of the target outer side airfoil profile, and determining the geometrical design space of the target outer side airfoil profile at least according to the geometrical characteristic and structure compatibility requirements of the initial airfoil profile;
and SS5, performing iterative optimization on the optimization objective function F by adopting a multi-objective optimization algorithm, calculating the aerodynamic performance and the aerodynamic noise characteristic of the wing profile in each iterative optimization process, and judging whether the optimization objective function F reaches an optimal solution or not by analyzing the aerodynamic performance and the aerodynamic noise characteristic of the wing profile to finally obtain the target outer side wing profile.
2. According to the claimsThe optimal design method of 1 is characterized in that in the step SS3, the aerodynamic load characteristic parameters under the characteristic airfoil design working condition at least comprise a design lift coefficient c l,design And coefficient of maximum lift c l,max To increase the blade torque in the low wind speed region while reducing the possible limit load.
3. The optimal design method according to claim 1, wherein in step SS4, the geometric design space of the target outer airfoil is constituted by the variation range of each design variable.
4. The optimal design method according to claim 3, wherein in step SS4, the design variable form of the airfoil is determined by an airfoil geometric analysis mode, the airfoil analysis mode adopts a spline curve method, and the corresponding airfoil design variables are parameters representing the geometric characteristics of the airfoil and at least comprise the maximum relative thickness and the maximum thickness position X of the airfoil t Relative camber C am Maximum camber position X cam Leading edge radius R le And the thickness T of the trailing edge tr 。
5. The optimal design method according to claim 1, wherein in the step SS5, the adopted optimization algorithm is a multi-objective micro-genetic algorithm, the aerodynamic performance and noise characteristic analysis of the airfoil profile is required in each step of optimization iteration process, and the Reynolds number of the aerodynamic performance analysis and the noise characteristic analysis of the airfoil profile is determined according to the running Reynolds number range of the blade outer side position of the target outer side airfoil.
6. The optimal design method according to claim 5, wherein in step SS5, the analysis of the aerodynamic performance of the airfoil profile in each step of the optimization iteration process includes three operating conditions, which are a design operating condition, a surface roughness operating condition and a high-turbulence free inflow operating condition, respectively, wherein the design operating condition is a natural transition and uniform inflow operating condition, the surface roughness operating condition is simulated by setting a fixed transition point on the upper and lower surfaces of the airfoil profile, and the high-turbulence inflow operating condition is an inflow turbulence level when the blade on the outer side of the blade normally operates at a wind condition above a rated wind speed.
7. The optimal design method according to claim 6, wherein in step SS5, aerodynamic coefficients within an attack angle range from-5 ° to 25 ° are calculated under each working condition, so that the maximum lift-drag ratio, the design lift coefficient, the maximum lift coefficient and the stall parameter under each working condition are obtained through analysis, and each target and constraint parameter are further obtained through calculation.
8. The optimal design method according to claim 7, wherein in the step SS5, the airfoil aerodynamic performance is calculated by a non-viscous boundary layer coupling iteration method, and the transition prediction method is e based on a small perturbation theory N The method, wherein N is a perturbation amplification factor; different inflow turbulities can be simulated by setting the value of N.
9. The optimal design method according to claim 8, wherein in step SS5, the airfoil aerodynamic noise analysis is to calculate the total sound pressure level of airfoil self-noise under five noise sources, wherein the five aerodynamic noise sources are airfoil turbulent boundary layer trailing edge noise, separation flow noise, laminar boundary layer vortex shedding noise, blunt trailing edge noise and turbulent inflow noise, the aerodynamic noise of the first four sound sources is analyzed by using BPM semi-empirical model, and the aerodynamic noise of the last sound source is analyzed by using modified Amiet semi-empirical model.
10. The optimal design method according to claim 9, wherein in step SS5, the noise sound pressure levels of the five sound sources at each discrete frequency point in the 34 discrete frequency points selected from the frequency range of 10Hz to 20000Hz are sequentially calculated to obtain the total sound pressure level of the airfoil aerodynamic noise at each discrete frequency point.
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