CN109611268B - Design optimization method for double-impeller horizontal shaft wind turbine - Google Patents
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
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Abstract
The invention provides a design optimization method for a double-impeller horizontal shaft wind turbine, which comprises the following steps of: establishing a DRWT design optimization model; solving the DRWT design optimization model; and predicting the pneumatic performance of the DRWT in the DRWT design optimization model solving process by coupling an AL theory and CFD. Aiming at the model design of DRWT, the invention provides a method for solving a detailed flow field between two stages of impellers by using a numerical simulation method of coupling AL theory and CFD (computational fluid dynamics) as well as taking the maximum output power of DRWT as an optimized design target and taking the load borne by a tower frame as a constraint by taking the pitch angle combination, the distance between the two stages of impellers, the size of the two stages of impellers and the rotating speed of the two stages of impellers as design variables, so that the optimization of the design variables is facilitated, the pneumatic performance of a double-impeller wind turbine is predicted and evaluated, the accuracy and the speed of predicting the pneumatic performance of the DRWT are greatly improved, the design efficiency of the DRWT is improved, and a foundation is laid for the engineering design of the DRWT and the engineering application.
Description
Technical Field
The invention relates to a design optimization method, in particular to a design optimization method for a double-impeller horizontal shaft wind turbine, and belongs to the technical field of wind turbines.
Background
Horizontal Axis Wind Turbines (HAWT) can be classified into a lift type Wind Turbine and a drag type Wind Turbine, wherein the lift type Wind Turbine rotates at a high speed, and the drag type Wind Turbine rotates at a low speed. For wind power generation, a lift force type horizontal axis wind turbine is mostly adopted. Most horizontal axis wind turbines have a wind aligning device (also called a yaw system) which can rotate along with the change of wind direction, and when the direction of a wind speed vector changes, the wind direction can be quickly and smoothly aligned, so that the wind wheel can obtain the maximum wind energy; for a large wind turbine, a transmission device consisting of a wind direction sensing element and a servo motor is utilized, and meanwhile, the transmission device also forms a component of a cabin of the wind driven generator.
The traditional horizontal axis wind turbine is of a Single-impeller structure, and a Single-impeller wind turbine (SRWT) can absorb 59.3% of the incoming wind energy at most, namely the Betz limit. In order to improve the aerodynamic efficiency of the Wind Turbine, the concept of the multi-stage impeller is introduced into the horizontal axis Wind Turbine, but the Dual-Rotor Wind Turbine (DRWT) has the most application potential in terms of cost. DRWT has the following features: (1) the pneumatic efficiency of the double-impeller wind turbine can exceed the Betz limit; the maximum power coefficient of the two-stage wind turbine impeller with the same size is obtained by Newman based on theoretical analysis of the multi-stage actuating disc of the wind turbine, and is 64%. (2) The double-impeller wind turbine can reduce the length and the weight of a single blade while ensuring the power output; the relatively short blades can greatly reduce the ultimate load and elastic deformation on a single impeller; in other words, a dual-impeller wind turbine may avoid the risk of increasing the power generated by increasing the length of the blades of a single-impeller wind turbine. (3) The double-impeller wind turbine can output more energy than the single-impeller wind turbine, so that the double-impeller wind turbine has the potential of reducing the production cost of unit electric energy. (4) The double-impeller wind turbine has higher power density, so that the arrangement of a wind power plant adopting the double-impeller wind turbine is more compact.
With the development of offshore wind power and the development and utilization of low-wind-speed wind resources, wind turbines gradually develop in a large-scale direction. However, the ever increasing size of wind turbines creates a number of real-world problems to limit further increases in blade length. The DRWT can improve the whole wind energy absorption efficiency of the wind turbine, and can overcome the risk of the whole wind turbine caused by continuously increasing the length of the blades of the wind turbine while ensuring the power output. The DRWT concept is proposed mainly to improve the wind energy absorption efficiency per unit area, thereby improving the overall aerodynamic efficiency of the unit. At present, DRWT research is only carried out in a model test research stage, a test model is mainly designed by taking the existing mature wind turbine impeller as a model main impeller in a scaled-down mode, and the model main impeller of the other stage is obtained by scaling the model main impeller according to needs. Assume a first stage impeller radius of R1The radius of the second-stage impeller is R2(ii) a DRWT can be divided into three categories according to the difference in radius of the two-stage impeller: r1＝R2、R1>R2、R1<R2. The first and second categories are primarily intended to improve overall aerodynamic efficiency by further harnessing the energy in the first stage impeller wake, and the third category is intended to improve overall aerodynamic efficiency by reducing the second categoryThe loss of the blade root of the stage impeller improves the pneumatic efficiency of the unit. Since the wake behind the first stage impeller has a larger velocity opposite to the rotation direction of the first stage impeller, the rotation direction of the second stage impeller opposite to the first stage impeller can absorb more wind energy, so the research of DRWT mainly focuses on the counter-rotating DRWT. Model test research mainly researches the influence of the distance between two stages of impellers, the rotating speed matching of the two stages of impellers and the size of the two stages of impellers on the overall output power of the wind turbine, but the Reynolds number corresponding to the characteristic size of a wind tunnel test model is greatly different from that of an actual wind turbine, the rule reflected by the test is not necessarily suitable for the prototype DRWT, and can only be used as the reference for designing the prototype DRWT, and a design method aiming at the prototype DRWT is not available at present. The pneumatic performance prediction is the key of wind turbine design, the engineering application mainly adopts a BEMT method (Blade Element Momentum Theory), the calculation speed is high, but the actual second-stage impeller of the DRWT cannot work in the wake flow of the full development of the first-stage impeller, and the BEMT cannot realize the pneumatic performance prediction of the second-stage impeller; the traditional CFD method (Computational Fluid Dynamics) has large calculation amount and low efficiency. In addition, since the DRWT is an integral body in which two stages of impellers are coupled to each other, the conventional engineering method cannot realize an engineering optimization design function for the integral coupling design.
Disclosure of Invention
Aiming at the defects or improvement requirements of the prior art, the invention provides a design optimization method of a double-impeller horizontal-shaft wind turbine, which can realize the rapid design optimization of the coordinated efficient operation of two stages of impellers of a prototype DRWT and has the technical effects of high efficiency and high precision.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention provides a design optimization method for a double-impeller horizontal shaft wind turbine, which comprises the following steps of:
s1, establishing a DRWT design optimization model;
s2, solving the DRWT design optimization model;
and S3, predicting the pneumatic performance of the DRWT in the DRWT design optimization model solving process by a method of coupling AL (Actuator Line) and CFD (computational fluid dynamics).
Further, the building of the DRWT design optimization model in step S1 includes the following steps:
s11, taking a mature SRWT impeller with excellent pneumatic performance as a reference impeller and a main impeller, keeping the size of the main impeller unchanged, and converting the main impeller in proportion according to design requirements to obtain another stage of impeller, wherein the main impeller and the another stage of impeller rotate in opposite directions;
s12, with R1、ω1、θ1、R2、ω2、θ2And D, taking the bending moment borne by the tower root and the torque borne by the tower root as constraint conditions, and carrying out DRWT design optimization model establishment by taking the maximum average output power in a certain wind speed range as an optimization target.
Further, if R1＝R2The first-stage impeller is a main impeller, and the second-stage impellers are the same as the main impeller in shape and are in one-to-one correspondence in size; if R is1>R2The first-stage impeller is a main impeller, and the second-stage impeller is obtained by reducing the main impeller in proportion; if R is1<R2The second-stage impeller is a main impeller, and the first-stage impeller is obtained by reducing the main impeller in proportion.
Further, the solving process in step S2 includes the following steps:
s21, initializing a DRWT design optimization model, wherein R1＝R2、θ1＝θ2、ω1＝ω2、D＝1/3R1；
S22, solving the initialization model of the step S21 by matching with a genetic algorithm or other optimization algorithms, and changing the design variables of the DRWT within the range of constraint conditions;
s23, calculating the load borne by the DRWT two-stage impeller and the output power of the DRWT after the design variables are changed in the step S22, and judging whether constraint conditions are met; if yes, continuing optimization; otherwise, return to step S22;
s24, if the calculation parameters in the step S23 meet the constraint conditions, judging whether the optimization algorithm is converged, if so, outputting the design variable parameters of the optimized DRWT; otherwise, return to step S22 to cycle back and forth.
Further, the prediction process in step S3 includes the steps of:
s31, giving a DRWT initial flow field and a DRWT blade initial position, solving the volume force of the blade according to the initial flow field and airfoil data, and substituting the volume force of the blade into an N-S equation;
s32, solving an N-S (Navier-Stokes) equation of given volume force to obtain a velocity field converged at the moment N;
s33, determining the relative speed and the power angle of the two-stage impeller according to the convergence speed field obtained in the step S32;
s34, determining the lift resistance coefficients of the wing profiles at different radial positions of the two-stage impeller according to the power angles of the two-stage impeller obtained in the step S33;
s35, calculating lift force and resistance force borne by the two-stage impeller blade according to the relative speed obtained in the step S33 and the lift resistance coefficient obtained in the step S34, calculating DRWT output power and bending moment, torque and other loads borne by the root of the tower according to the calculated lift force and resistance force, and monitoring the output power and the loads;
s36, rotating the impeller to a new position, determining the volume force of the new position of the impeller, substituting the volume force into an N-S equation, updating the solution of the time N to the time N +1, and circulating the steps S32 to S36;
and S37, ensuring that the solving time is long enough until the load monitored in the step S35 is changed in a stable and periodic manner, and considering that the calculation is converged.
Compared with the prior art, the invention has the following beneficial effects:
aiming at the model design of DRWT, the invention provides a method for solving a detailed flow field between two stages of impellers by using a numerical simulation method of coupling AL theory and CFD (computational fluid dynamics) as well as taking the maximum output power of DRWT as an optimized design target and taking the load borne by a tower frame as a constraint by taking the pitch angle combination, the distance between the two stages of impellers, the size of the two stages of impellers and the rotating speed of the two stages of impellers as design variables, so that the optimization of the design variables is facilitated, the pneumatic performance of a double-impeller wind turbine is predicted and evaluated, the accuracy and the speed of the prediction of the pneumatic performance of the DRWT are greatly improved, the design efficiency of the DRWT is improved, and a foundation is laid for the engineering design of the DRWT and the.
Drawings
FIG. 1 is a schematic diagram of the DRWT structure of the present invention.
FIG. 2 is a flow chart of design optimization according to the present invention.
FIG. 3 is a flow chart of the aerodynamic performance prediction in the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments. Examples of the embodiments are illustrated in the accompanying drawings, and specific embodiments described in the following embodiments of the invention are provided as illustrative of the embodiments of the invention only and are not intended to be limiting of the invention.
A double-impeller horizontal shaft wind turbine is shown in figure 1, wherein the radius of a first-stage impeller is R1Angular velocity of rotation omega1Angle of pitch theta1(ii) a The radius of the second-stage impeller is R2Angular velocity of rotation omega2Angle of pitch theta2(ii) a The center distance between the two stages of impellers is D. The invention provides a design optimization method for a double-impeller horizontal shaft wind turbine, which is used for guiding the design of a large DRWT (dry weight wind turbine) with two-stage impellers coupled with each other and comprises the following steps of:
step S1, establishing DRWT design optimization model. Further, the establishment of the DRWT design optimization model specifically includes the following steps:
s11, the conventional mature SRWT impeller with excellent aerodynamic performance is used as a reference impeller and is used as a main impeller. The main impeller can be a first-stage impeller or a second-stage impeller, and the size of the main impeller is kept unchanged in the design optimization process. According to design requirements, the other stage of impeller is obtained by scaling the main impeller. If R is1＝R2The first-stage impeller is a main impeller, and the size and the shape of the second-stage impeller are the same as those of the first-stage impeller; if R is1>R2The first-stage impeller is a main impeller, and the second-stage impeller is obtained by reducing the first-stage impeller in proportion; if R is1<R2The second-stage impeller is a main impeller, and the first-stage impeller is obtained by reducing the main impeller in proportion. The two-stage impeller rotating directions in the three cases are opposite.
S12, with R1、ω1、θ1、R2、ω2、θ2D is a design variable; taking the bending moment M borne by the root of the tower and the torque T borne by the root of the tower as constraint conditions, and simultaneously applying other constraints to design variables according to design requirements; average output power P within a certain wind speed rangeiThe maximum is an optimization target, and a DRWT design optimization model is established. Wherein, P in the formula (1)iIs the output power of the DRWT at different wind speeds.
And step S2, solving the DRWT design optimization model. Further, the solving process specifically includes the following steps:
s21, initializing a DRWT design optimization model, wherein R1＝R2、θ1＝θ2、ω1＝ω2、D＝1/3R1。
And S22, solving the DRWT design optimization model by matching with a genetic algorithm or other optimization algorithms, changing the design variables of the DRWT, and controlling the DRWT design variables in a constraint range.
S23, calculating the load borne by the DRWT two-stage impeller, the output power of the DRWT, the bending moment and the torque borne by the root of the tower and the like after the design variables are changed, judging whether the calculated load and output power meet the constraint of the design optimization model, continuing the optimization process if the calculated load and output power meet the constraint, and returning to the step S22 if the calculated load and output power do not meet the constraint.
S24, if the calculation parameters in the step S23 meet the constraint conditions, judging whether the optimization algorithm is converged, if so, outputting the design variable parameters of the optimized DRWT; otherwise, returning to step S22, repeating steps S22 to S24, and repeating the steps.
And step S3, predicting the pneumatic performance of the DRWT in the DRWT design optimization model solving process by adopting an AL theory and CFD coupling method. The specific prediction process comprises the following steps:
and S31, setting the initial flow field of the DRWT and the initial position of the DRWT blade, solving the volume force of the blade according to the initial flow field and the airfoil data, and substituting the volume force of the blade into an N-S equation.
And S32, solving an N-S equation of the given volume force to obtain a velocity field converged at the moment N.
Wherein: f is the volume force of the impeller blade, rho is the air density, C is the chord length of the leaf element, ClIs the coefficient of airfoil lift, CdIs the airfoil drag coefficient.
And S33, determining the relative speed and the power angle of the two-stage impeller according to the convergence speed field obtained in the step S32.
And S34, determining the lift resistance coefficients of the airfoils at different radial positions of the two-stage impeller according to the power angles of the two-stage impeller obtained in the step S33.
And S35, calculating the lift force and the resistance force borne by the two-stage impeller blade according to the relative speed obtained in the step S33 and the lift resistance coefficient obtained in the step S34, calculating the DRWT output power and the bending moment, the torque and other loads borne by the tower root according to the calculated lift force and resistance force, and monitoring the output power and the loads.
And S36, rotating the impeller to a new position, determining the volume force of the impeller at the new position, substituting the volume force into the N-S equation, updating the solution of the time N to the time N +1, and circulating the steps S32 to S36.
And S37, ensuring that the solving time is long enough until the load monitored in the step S35 is changed in a stable and periodic manner, and considering that the calculation is converged.
The aerodynamic performance prediction method mainly adopts an AL theory to calculate the volume force in an N-S control equation, so that the rapid calculation of the stress of the two-stage impeller is realized, and the problem that the traditional CFD method consumes a large amount of calculation resources when the boundary layer flow is solved is avoided; a CFD method is adopted to calculate a detailed flow field between two stages of DRWT impellers, and an accurate incoming flow field is provided for the second stage impeller; and finally, accurate and efficient prediction of DRWT pneumatic performance and efficient design of DRWT are realized.
Aiming at the model design of DRWT, the invention provides a method for solving a detailed flow field between two stages of impellers by using a numerical simulation method of coupling AL theory and CFD (computational fluid dynamics) as well as taking the maximum output power of DRWT as an optimized design target and taking the load borne by a tower frame as a constraint by taking the pitch angle combination, the distance between the two stages of impellers, the size of the two stages of impellers and the rotating speed of the two stages of impellers as design variables, so that the optimization of the design variables is facilitated, the pneumatic performance of a double-impeller wind turbine is predicted and evaluated, the accuracy and the speed of the prediction of the pneumatic performance of the DRWT are greatly improved, the design efficiency of the DRWT is improved, and a foundation is laid for the engineering design of the DRWT and the.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, the word "comprising" does not exclude the presence of data or steps not listed in a claim.
Claims (4)
1. A design optimization method for a double-impeller horizontal-shaft wind turbine is characterized by comprising the following steps:
s1, establishing a DRWT design optimization model;
s2, solving the DRWT design optimization model;
s3, predicting the pneumatic performance of the DRWT in the DRWT design optimization model solving process by an AL and CFD coupled numerical simulation method, wherein the predicting process comprises the following steps:
s31, giving a DRWT initial flow field and a DRWT blade initial position, solving the volume force of the blade according to the initial flow field and airfoil data, and substituting the volume force of the blade into an N-S equation;
s32, solving the N-S equation of the given volume force to obtain the timenA converged velocity field;
s33, determining the relative speed and the power angle of the two-stage impeller according to the convergence speed field obtained in the step S32;
s34, determining the lift resistance coefficients of the wing profiles at different radial positions of the two-stage impeller according to the power angles of the two-stage impeller obtained in the step S33;
s35, calculating lift force and resistance force borne by the two stages of impeller blades according to the relative speed obtained in the step S33 and the lift resistance coefficient obtained in the step S34, calculating DRWT output power and bending moment load and torque load borne by the root of the tower according to the calculated lift force and resistance force, and monitoring the DRWT output power, the bending moment load and the torque load;
s36, rotating the impeller to a new position, determining the volume force of the impeller at the new position, substituting the volume force into the N-S equation, and calculating the timenIs updated tonAt time +1, loop through steps S32 to S36;
and S37, ensuring that the solving time is long enough until the load monitored in the step S35 is changed in a stable and periodic manner, and considering that the calculation is converged.
2. The method for optimizing the design of a dual-impeller horizontal-axis wind turbine as claimed in claim 1, wherein the establishing of the DRWT design optimization model in step S1 comprises the following steps:
s11, taking a mature SRWT impeller with excellent pneumatic performance as a reference impeller and a main impeller, keeping the size of the main impeller unchanged, and converting the main impeller in proportion according to design requirements to obtain another stage of impeller, wherein the main impeller and the another stage of impeller rotate in opposite directions;
s12, radius of the first-stage impellerR 1Angular velocity of rotationω 1Pitch angleθ 1And the radius of the second stage impellerR 2Angular velocity of rotationω 2Pitch angleθ 2And center-to-center spacing of two-stage impellersDAnd (3) establishing a DRWT design optimization model by taking the bending moment borne by the tower root and the torque borne by the tower root as constraint conditions and taking the maximum average output power in a certain wind speed range as an optimization target for design variables.
3. The method for optimizing the design of the double-impeller horizontal-axis wind turbine as claimed in claim 2, wherein: if it isR 1=R 2The first-stage impeller is a main impeller, and the second-stage impellers are the same as the main impeller in shape and are in one-to-one correspondence in size; if it isR 1>R 2The first-stage impeller is a main impeller, and the second-stage impeller is obtained by reducing the main impeller in proportion; if it isR 1<R 2The second-stage impeller is a main impeller, and the first-stage impeller is obtained by reducing the main impeller in proportion.
4. The method for optimizing the design of the double-impeller horizontal-axis wind turbine as claimed in claim 3, wherein the solving process in the step S2 comprises the following steps:
s21, initializing a DRWT design optimization model, wherein,R 1=R 2、θ 1=θ 2、ω 1=ω 2、D=1/3R 1；
s22, solving the initialization model of the step S21 by matching with a genetic algorithm or other optimization algorithms, and changing the design variables of the DRWT within the range of constraint conditions;
s23, calculating the load borne by the DRWT two-stage impeller and the output power of the DRWT after the design variables are changed in the step S22, and judging whether constraint conditions are met; if yes, continuing optimization; otherwise, return to step S22;
s24, if the calculation parameters in the step S23 meet the constraint conditions, judging whether the optimization algorithm is converged, if so, outputting the design variable parameters of the optimized DRWT; otherwise, return to step S22 to cycle back and forth.
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| KR20180006662A (en) * | 2016-07-11 | 2018-01-19 | 변복용 | Wind generator |
| GB201617584D0 (en) * | 2016-10-17 | 2016-11-30 | Romax Technology Limited | Determining loads on a wind turbine |
| CN107194118B (en) * | 2017-06-19 | 2020-09-18 | 南京航空航天大学 | Pneumatic-thermal collaborative optimization method for turbine blade fan-shaped hole air film cooling structure |
| CN108416075A (en) * | 2017-08-29 | 2018-08-17 | 沈阳工业大学 | Wind energy conversion system aerodynamics model modeling method based on CFD technologies |
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