CN114595643B - High-resolution mountain wind field measurement method coupling multi-point anemometer and microscale steady-state simulation - Google Patents

High-resolution mountain wind field measurement method coupling multi-point anemometer and microscale steady-state simulation Download PDF

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CN114595643B
CN114595643B CN202210212742.5A CN202210212742A CN114595643B CN 114595643 B CN114595643 B CN 114595643B CN 202210212742 A CN202210212742 A CN 202210212742A CN 114595643 B CN114595643 B CN 114595643B
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闫渤文
黄国庆
郭超明
张楠
周绪红
杨庆山
程旭
彭留留
苏延文
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Abstract

The invention discloses a high-resolution mountain wind field measurement method for coupling a multi-point anemometer and microscale steady-state simulation, which comprises the following steps of: 1) Adopting a single-point iteration method to solve the inflow wind direction angle of the measured data of each anemometer; 2) According to the inflow wind direction angle, the inflow wind speed is obtained according to the logarithmic wind profile; 3) Calculating the speed in the wind field by using the inflow wind speed and interpolating to obtain the speed of the position of each anemometer; 4) Adopting a PI control method for iterative optimization, calculating an error, and judging whether the error e meets a convergence condition or not: if yes, stopping iteration, and determining a wind profile as an inflow condition of the wind field according to the inflow wind speed corresponding to the current iteration step; if not, executing the step 5); 5) Introducing PI control parameters to obtain inflow wind speed of the nth iteration: 6) Let n=n+1, and loop step 3). According to the invention, through coupling the multi-point anemometer and micro-scale steady-state simulation, the inflow wind direction angle matched with the actual measurement and the shape of the wind section are obtained through iterative optimization, so that the actual measurement wind field is matched with the simulated wind field.

Description

High-resolution mountain wind field measurement method coupling multi-point anemometer and microscale steady-state simulation
Technical Field
The invention belongs to the technical field of wind field measurement, and particularly relates to a high-resolution mountain wind field measurement method for coupling a multi-point anemometer and microscale steady-state simulation.
Background
In recent years, along with the proposal of double-carbon targets in China, the requirements of clean energy sources such as wind energy and the like are continuously increased, and the accurate assessment of wind resources is an important ring in wind energy development. In the current method for evaluating wind resources, the CFD numerical method is widely adopted due to low cost and high efficiency. The CFD numerical calculation method is accurate for solving the flat ground wind field, but for the wind field with complex terrain, the wind speed simulated by the CFD numerical calculation method and the actually measured wind speed are not matched due to obvious terrain effect, so that a method is needed to be provided for solving the problem.
At present, the matched inflow wind speed is generally found through single-point actually measured wind speed, so that the wind speed of the whole flow field is matched with the actually measured wind speed. However, this method has the following disadvantages: first, the effect of the method is to be verified; second, the method assumes that the inflow wind profile is logarithmic, and when the topographical effect is significant, the actual inflow wind profile is not necessarily logarithmic, and therefore the accuracy of the method is limited.
Disclosure of Invention
In view of the above, the invention aims to provide a high-resolution mountain wind field measurement method for coupling a multi-point anemometer and micro-scale steady-state simulation, which adopts a strategy of iterative optimization of multi-point measured wind speeds so as to solve the problem that the measured wind speeds are not matched with numerical simulation wind speeds.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a high-resolution mountain wind field measurement method for coupling a multi-point anemometer and microscale steady-state simulation comprises the following steps:
1) Adopting a single-point iteration method to solve the inflow wind direction angle of the measured data of each anemometer;
2) Obtaining an inflow wind speed (u in,vin) according to the logarithmic wind profile according to the inflow wind direction angle;
3) Calculating the speed u (i, j, k) in the wind field by using the inflow wind speed (u in,vin), and interpolating the u (i, j, k) to obtain the speed (u z,vz) of each anemometer at the height z;
4) Iterative optimization is performed by adopting a PI control method, and an error is calculated:
Wherein e represents an error; n represents the number of iterations; z represents the height at which the anemometer is located; (u z ref, ) A measured wind speed being an anemometer of height z; judging whether the error e meets the convergence condition: if yes, stopping iteration, and determining a wind profile as an inflow condition of the wind field by using the inflow wind speed (u in,vin) corresponding to the current iteration step; if not, executing the step 5);
5) Introducing PI control parameters:
Wherein, Is a proportionality coefficient; /(I)Is an integral coefficient and acts to reduce the factor/>Steady state errors generated when the regulation is insufficient; e (z, j) represents the error at the z-altitude anemometer for the jth iteration;
obtaining the inflow wind speed of the n+1th iteration:
(uin,vin)n+1＝λPI,t(z,n)+(uin,vin)n
6) Let n=n+1, and loop step 3).
Further, in the step 1), the method for solving the inflow wind direction angle of the measured data is as follows:
(1) Generating an initial APG chart (Anemometer PHASE GRAPH, an anemometer phase chart), setting a speed measured value at any anemometer position as (U 0,v0), normalizing the speed measured value by a model of the anemometer position as (U 0,V0), and representing the point in the APG chart by P 0;
(2) Judging whether the distance between at least one point and the point P 0 on the APG curve is smaller than or equal to a set threshold value: if so, using the point T 0 closest to the point P 0 on the APG curve as the approximation of the point P 0, obtaining the inflow wind direction angle from the inflow speed (U T0,VT0) corresponding to the point T 0 The inflow wind direction angle theta 0 is approximately equal to the inflow wind direction angle corresponding to the point P 0; if not, executing the step (3);
(3) Point P i is projected onto the APG curve segment nearest to it, the projected point is denoted T m, and the two endpoints of the APG curve segment are denoted T 1m and T 2m:
wherein r m ranges from [0,1], which describes the relative position of point T m on the APG curve segment;
(4) Calculating the component of the magnitude of the dimensionless boundary wind speed:
Wherein, And/>The non-dimensional parameters of the boundary wind speed in the longitudinal direction and the transverse direction of the horizontal plane are respectively represented; (U B1m,VB1m) is the boundary velocity corresponding to point T 1m on the APG map, and (U B2m,VB2m) is the boundary velocity corresponding to point T 2m on the APG map;
(5) Using Calculating dimensionless flow field/>
(6) For dimensionless flow fieldInterpolation calculation is performed to obtain dimensionless speed of anemometer position
(7) Calculation ofModulus/>And use it as a pair/>And/>Normalizing to obtain (U Am,VAm)、(UBm,VBm);
(8) Inserting a point Pm with a coordinate of (U Am,VAm) into the APG graph, wherein the inflow speed corresponding to the point Pm is (U Bm,VBm); determining whether the distance between the point P m and the initial point P 0 is less than or equal to a set threshold; if yes, stopping iteration, and executing the step (9); if not, m=m+1, and P m is used for replacing P i to circularly execute the step (3);
(9) Obtaining the wind direction angle of the inflow according to the inflow speed (U Bm,VBm) corresponding to the point Pm The incoming wind direction angle θ m is approximately the wind direction angle corresponding to point P 0.
Further, in the step (1), the method for generating the initial APG map includes:
① The log rate inflow conditions were dimensionless with u ref、zref:
Wherein u ref represents a reference wind speed; z ref represents a reference height; representing dimensionless height/> A longitudinal dimensionless wind speed at the horizontal plane; /(I)Representing dimensionless height/>A transverse dimensionless wind speed at the horizontal plane; /(I)Representing a dimensionless height; z ref represents a reference height; z 0 represents the ground roughness length;
② Calculating the non-dimensionalized inflow velocity component at the reference height z ref:
③ Numerical calculation of dimensionless flow fields, dimensionless velocity vectors for each grid node A representation;
④ For dimensionless velocity vectors Interpolation calculation is carried out to obtain a dimensionless flow field of the anemometer position
⑤ Calculation ofModulus/>Due to the similarity of the flow fields, the entire velocity field can be scaled linearly/>To normalize, there are:
Wherein, (U A,VA) is a coordinate point in the APG graph, and corresponding (U B,VB) corresponds to the inflow wind speed, and the inflow wind direction angle is:
In step ②, a plurality of inflow wind angles are selected, and a plurality of coordinate points are obtained to generate an initial APG map, wherein the inflow wind angle of each coordinate point in the initial APG map is known.
Further, the incoming wind direction angle selected in step ② is uniformly covered by 0-360 °.
The invention has the beneficial effects that:
the invention relates to a high-resolution mountain wind field measuring method for coupling a multi-point anemometer and microscale steady-state simulation, which utilizes a single-point iterative optimization and multi-point PI control method to obtain the shape of an inflow wind section through iterative optimization, and the principle is as follows: after the inflow wind direction angle is obtained through a single-point iteration method, the CFD calculates a simulated wind section at the wind measuring tower, the real wind section at the wind measuring tower can be obtained through multi-point measured data, on the basis of the PI control method, errors of the two wind sections are continuously overlapped on the inflow wind section calculated through the CFD, and the circulation iteration is performed until the errors are smaller than or equal to a threshold value, and the corresponding real inflow wind section at the moment can be obtained; the introduction of the PI control method makes iteration softer so as to ensure better convergence. Finally, the actually measured wind speed is matched with the simulated wind speed, and the method is particularly suitable for application scenes when the real inflow wind profile is not the log-rate wind profile due to the topographic effect in the wind field with complex topography.
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In order to make the objects, technical solutions and advantageous effects of the present invention more clear, the present invention provides the following drawings for description:
fig. 1 is a schematic diagram of a generated initial APG map.
Fig. 2 is a graph showing the relationship among measured wind profile, inflow wind profile, and calculated wind profile.
Detailed Description
The present invention will be further described with reference to the accompanying drawings and specific examples, which are not intended to limit the invention, so that those skilled in the art may better understand the invention and practice it.
The embodiment of the high-resolution mountain wind field measuring method for coupling a multi-point anemometer and micro-scale steady-state simulation comprises the following steps:
1) Adopting a single-point iteration method to solve the inflow wind direction angle of the measured data of each anemometer;
specifically, in this embodiment, the method for solving the inflow wind direction angle of the measured data is as follows:
(1) Generating an initial APG chart (Anemometer PHASE GRAPH, an anemometer phase chart), setting a speed measured value at any anemometer position as (U 0,v0), normalizing the speed measured value by a model of the anemometer position as (U 0,V0), and representing the point in the APG chart by P 0;
specifically, in this embodiment, the method for generating the initial APG map includes:
① The log rate inflow conditions were dimensionless with u ref、zref:
Wherein u ref represents a reference wind speed; z ref represents a reference height; representing dimensionless height/> A longitudinal dimensionless wind speed at the horizontal plane; /(I)Representing dimensionless height/>A transverse dimensionless wind speed at the horizontal plane; /(I)Representing a dimensionless height; z ref represents a reference height; z 0 represents the ground roughness length;
② Calculating the non-dimensionalized inflow velocity component at the reference height z ref:
③ Numerical calculation of dimensionless flow fields, dimensionless velocity vectors for each grid node A representation;
④ For dimensionless velocity vectors Interpolation calculation is carried out to obtain a dimensionless flow field of the anemometer position
⑤ Calculation ofModulus/>Due to the similarity of the flow fields, the entire velocity field can be scaled linearly/>To normalize, there are:
Wherein, (U A,VA) is a coordinate point in the APG graph, and corresponding (U B,VB) corresponds to the inflow wind speed, and the inflow wind direction angle is: In step ②, a plurality of inflow wind angles are selected, and a plurality of coordinate points are obtained to generate an initial APG map, wherein the inflow wind angle of each coordinate point in the initial APG map is known. In step ②, the inflow wind direction angles selected in step ② are uniformly covered by [0 °,360 ° ], in step ②, 16 inflow wind direction angles are selected, and 16 inflow wind direction angles are uniformly covered by [0 °,360 ° ], i.e., the angle values of the 16 inflow wind direction angles are 0 °, 22.5 °, 45 °, … …, 337.5 °, respectively.
(2) Judging whether the distance between at least one point and the point P 0 on the APG curve is smaller than or equal to a set threshold value: if so, using the point T 0 closest to the point P 0 on the APG curve as the approximation of the point P 0, obtaining the inflow wind direction angle from the inflow speed (U T0,VT0) corresponding to the point T 0 The inflow wind direction angle theta 0 is approximately equal to the inflow wind direction angle corresponding to the point P 0; if not, executing the step (3).
(3) Point P i is projected onto the APG curve segment nearest to it, the projected point is denoted T m, and the two endpoints of the APG curve segment are denoted T 1m and T 2m:
Where r m ranges from [0,1], which describes the relative position of point T m on the APG curve segment.
(4) Calculating the component of the magnitude of the dimensionless boundary wind speed:
Wherein, And/>The non-dimensional parameters of the boundary wind speed in the longitudinal direction and the transverse direction of the horizontal plane are respectively represented; (U B1m,VB1m) is the boundary velocity corresponding to the point T 1m on the APG map, and (U B2m,VB2m) is the boundary velocity corresponding to the point T 2m on the APG map.
(5) UsingCalculating dimensionless flow field/>
(6) For dimensionless flow fieldInterpolation calculation is performed to obtain dimensionless speed of anemometer position
(7) Calculation ofModulus/>And use it as a pair/>And/>Normalization was performed to obtain (U Am,VAm)、(UBm,VBm).
(8) Inserting a point P m with a coordinate of (U Am,VAm) into the APG graph, wherein the inflow speed corresponding to the point P m is (U Bm,VBm); determining whether the distance between the point P m and the initial point P 0 is less than or equal to a set threshold; if yes, stopping iteration, and executing the step (9); if not, then m=m+1, and P m is substituted for P i to cycle through step (3).
(9) Obtaining the wind direction angle of the inflow according to the inflow speed (U Bm,VBm) corresponding to the point P m The incoming wind direction angle θ m is approximately the wind direction angle corresponding to point P 0.
2) Obtaining an inflow wind speed (u in,vin) according to the logarithmic wind profile according to the inflow wind direction angle;
3) Calculating the speed u (i, j, k) in the wind field by using the inflow wind speed (u in,vin), and interpolating the u (i, j, k) to obtain the speed (u z,vz) of the position of each anemometer;
4) Iterative optimization is performed by adopting a PI control method, and an error is calculated:
Wherein e represents an error; n represents the number of iterations; z represents the height at which the anemometer is located; (u z ref, ) Measuring the wind speed for an anemometer with a height z; judging whether the error e meets the convergence condition: if yes, stopping iteration, and determining a wind profile as an inflow condition of the wind field by using the inflow wind speed (u in,vin) corresponding to the current iteration step; if not, executing the step 5);
5) Introducing PI control parameters:
Wherein, Is a proportionality coefficient; /(I)Is an integral coefficient and acts to reduce the factor/>Steady state errors generated when the regulation is insufficient; e (z, j) represents the error at the z-altitude anemometer for the jth iteration;
obtaining the inflow wind speed of the n+1th iteration:
(uin,vin)n+1＝λPI,t(z,n)+(uin,vin)n
6) Let n=n+1, and loop step 3).
According to the high-resolution mountain wind field measuring method coupling the multi-point anemometer and the micro-scale steady-state simulation, the shape of the inflow wind profile is obtained through iteration optimization by using a PI control method, so that the measured wind speed is matched with the simulated wind speed, and the method is particularly suitable for application scenes when the real inflow wind profile is not the log-rate wind profile due to the topographic effect in the wind field with complex topography.
The above-described embodiments are merely preferred embodiments for fully explaining the present invention, and the scope of the present invention is not limited thereto. Equivalent substitutions and modifications will occur to those skilled in the art based on the present invention, and are intended to be within the scope of the present invention. The protection scope of the invention is subject to the claims.

Claims (4)

1. A high-resolution mountain wind field measurement method for coupling a multi-point anemometer and microscale steady-state simulation is characterized by comprising the following steps of: the method comprises the following steps:
1) Adopting a single-point iteration method to solve the inflow wind direction angle of the measured data of each anemometer;
2) Obtaining an inflow wind speed (u in,vin) according to the logarithmic wind profile according to the inflow wind direction angle;
3) Calculating the speed u (i, j, k) in the wind field by using the inflow wind speed (u in,vin), and interpolating the u (i, j, k) to obtain the speed (u z,vz) of each anemometer at the height z;
4) Iterative optimization is performed by adopting a PI control method, and an error is calculated:
Wherein e represents an error; n represents the number of iterations; z represents the height at which the anemometer is located; A measured wind speed being an anemometer of height z; judging whether the error e meets the convergence condition: if yes, stopping iteration, and determining a wind profile as an inflow condition of the wind field by using the inflow wind speed (u in,vin) corresponding to the current iteration step; if not, executing the step 5);
5) Introducing PI control parameters:
Wherein, Is a proportionality coefficient; /(I)Is an integral coefficient and acts to reduce the factor/>Steady state errors generated when the regulation is insufficient; e (z, j) represents the error at the z-altitude anemometer for the jth iteration;
obtaining the inflow wind speed of the n+1th iteration:
(uin,vin)n+1＝λPI,t(z,n)+(uin,vin)n
6) Let n=n+1, and loop through step 3) until the convergence condition is satisfied).
2. The high resolution mountain range measurement method of coupling a multipoint anemometer and microscale steady state simulation of claim 1, wherein: in the step 1), the solution method of the inflow wind direction angle of the measured data is as follows:
(1) Generating an initial APG chart (Anemometer PHASE GRAPH, an anemometer phase chart), setting a speed measured value at any anemometer position as (U 0,v0), normalizing the speed measured value by a model of the anemometer position as (U 0,V0), and representing the point in the APG chart by P 0;
(2) Judging whether the distance between at least one point and the point P 0 on the APG curve is smaller than or equal to a set threshold value: if so, using the point T 0 closest to the point P 0 on the APG curve as the approximation of the point P 0, obtaining the inflow wind direction angle from the inflow speed (U T0,VT0) corresponding to the point T 0 The inflow wind direction angle theta 0 is approximately equal to the inflow wind direction angle corresponding to the point P 0; if not, executing the step (3);
(3) Point P i is projected onto the APG curve segment nearest to it, the projected point is denoted T m, and the two endpoints of the APG curve segment are denoted T 1m and T 2m:
wherein r m ranges from [0,1], which describes the relative position of point T m on the APG curve segment;
(4) Calculating the component of the magnitude of the dimensionless boundary wind speed:
Wherein, And/>The non-dimensional parameters of the boundary wind speed in the longitudinal direction and the transverse direction of the horizontal plane are respectively represented; (U B1m,VB1m) is the boundary velocity corresponding to point T 1m on the APG map, and (U B2m,VB2m) is the boundary velocity corresponding to point T 2m on the APG map;
(5) Using Calculating dimensionless flow field/>
(6) For dimensionless flow fieldInterpolation calculation is carried out to obtain dimensionless speed/>, of the position of the anemometer
(7) Calculation ofModulus/>And use it as a pair/>And/>Normalizing to obtain (U Am,VAm)、(UBm,VBm);
(8) Inserting a point P m with a coordinate of (U Am,VAm) into the APG graph, wherein the inflow speed corresponding to the point P m is (U Bm,VBm); determining whether the distance between the point P m and the initial point P 0 is less than or equal to a set threshold; if yes, stopping iteration, and executing the step (9); if not, m=m+1, and P m is used for replacing P i to circularly execute the step (3);
(9) Obtaining the wind direction angle of the inflow according to the inflow speed (U Bm,VBm) corresponding to the point P m The incoming wind direction angle θ m is approximately the wind direction angle corresponding to point P 0.
3. The high resolution mountain range measurement method of coupling a multipoint anemometer and microscale steady state simulation of claim 2, wherein: in the step (1), the method for generating the initial APG map includes:
① The log rate inflow conditions were dimensionless with u ref、zref:
Wherein u ref represents a reference wind speed; z re f represents a reference height; representing dimensionless height/> A longitudinal dimensionless wind speed at the horizontal plane; /(I)Representing dimensionless height/>A transverse dimensionless wind speed at the horizontal plane; /(I)Representing a dimensionless height; z ref represents a reference height; z 0 represents the ground roughness length;
② Calculating the non-dimensionalized inflow velocity component at the reference height z ref:
③ Numerical calculation of dimensionless flow fields, dimensionless velocity vectors for each grid node A representation;
④ For dimensionless velocity vectors Interpolation calculation is carried out to obtain a dimensionless flow field of the anemometer position
⑤ Calculation ofModulus/>Due to the similarity of the flow fields, the entire velocity field can be scaled linearly/>To normalize, there are:
Wherein, (U A,VA) is a coordinate point in the APG graph, and corresponding (U B,VB) corresponds to the inflow wind speed, and the inflow wind direction angle is:
In step ②, a plurality of inflow wind angles are selected, and a plurality of coordinate points are obtained to generate an initial APG map, wherein the inflow wind angle of each coordinate point in the initial APG map is known.
4. The high resolution mountain range measurement method of coupling a multipoint anemometer and microscale steady state simulation of claim 3 wherein: the inflow wind direction angle selected in step ② is uniformly covered by 0-360 degrees.
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