CN117172001A - Wake flow calculation method and device based on laser radar and fan monitoring data - Google Patents
Wake flow calculation method and device based on laser radar and fan monitoring data Download PDFInfo
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Abstract
The application provides a wake flow calculation method and a wake flow calculation device based on laser radar and fan monitoring data, wherein the calculation method comprises the following steps: selecting a front exhaust fan and a rear exhaust fan in the main wind direction of the wind power plant, installing an airborne laser radar on the front exhaust fan, and recording data acquisition and monitoring control system data and airborne laser radar data of the front exhaust fan and data acquisition and monitoring control system data of the rear exhaust fan; cleaning data; calculating the radial distance and the actual wake loss coefficient at the position of the rear exhaust fan based on the cleaned data; fitting the radial distance and the actual wake loss coefficient in a parabolic manner; and calculating wake loss coefficients according to the distribution of the wake loss coefficients in the radial direction, and further calculating the wind speed of the rear exhaust fan. The wake flow calculation method disclosed by the application is more in line with an actual flow field, and can calculate the downstream wind speed more accurately, so that support is provided for the cooperative control of the field group machine unit to reduce wake flow loss.
Description
Technical Field
The application relates to the technical field of wind power generation, in particular to a wake flow calculation method and device based on laser radar and wind turbine monitoring data.
Background
In a wind power generation station, wake flow generated by a front exhaust wind generating set of an incoming wind direction can reduce the wind speed of a downstream flow field, so that the generated energy of a rear exhaust fan is reduced. At present, the wind power industry provides a technical scheme of whole farm collaborative yaw, and aims to reduce the overall wake loss, thereby achieving the purpose of improving the generated energy. In order to achieve collaborative yaw optimization, the wake loss caused by the front exhaust fan to the rear exhaust fan is calculated based on the wind speed of the front exhaust fan, and then the minimum solution of the wake loss is obtained based on different yaw angles.
Currently, there have been many literature studies on wake loss models, including the well-known Jensen model, which calculate wake loss by obtaining the velocity of the wake centerline through conservation of linearized momentum deficit flux. Barthlmie then proposes an exponential function fitting method, franksen et al add a wake loss profile of the top-hat shape on its basis, thereby taking into account the downstream wake area, and Bastankhah et al better conform to the wake diffusion profile by using a gaussian shape instead of the top-hat shape. In addition, some documents use a large vortex simulation method to directly calculate the flow field, so as to obtain wake loss.
In the calculation methods, the large vortex simulation is used as unsteady state numerical simulation, has high requirements on calculation resources, and is not suitable for wind power engineering application with high timeliness requirements. The model of Jensen et al has certain universality, but the assumed top-hat or gaussian wake loss distribution in the radial direction does not necessarily conform to the flow field characteristics of an actual wind farm.
Therefore, the inventor designs a wake calculation method and a wake calculation device based on laser radar and fan monitoring data, and based on the Jensen model, wake loss profiles are directly fitted based on actual measurement data such as a wind turbine generator set SCADA system and airborne laser radar data, so that a more accurate wake model is provided.
Disclosure of Invention
The method aims to solve the technical problems that in the prior art, the requirement of large vortex simulation as unsteady state numerical simulation on calculation resources is high, and the method is not suitable for wind power engineering application with high timeliness requirement; the model of Jensen and the like has certain universality, but the assumed top-hat or Gaussian wake loss distribution in the radial direction does not necessarily accord with the defect of the flow field characteristic of an actual wind power plant, and provides a wake calculation method and device based on laser radar and wind turbine monitoring data.
The application solves the technical problems by the following technical proposal:
the application provides a wake flow calculation method based on laser radar and fan monitoring data, which is characterized by comprising the following steps: s is S 1 The method comprises the steps of selecting a front exhaust fan and a rear exhaust fan of a wind power plant in the main wind direction, installing an airborne laser radar on the front exhaust fan, and recording data acquisition and monitoring control system data and airborne laser radar data of the front exhaust fan and data acquisition and monitoring control system data of the rear exhaust fan; s is S 2 Data are cleaned; s is S 3 Calculating radial distance based on the cleaned data and the position of the rear exhaust fanIs used for the actual wake loss coefficient;
S 4 fitting said radial distance and said actual wake loss coefficient in a parabolic fashion; s is S 5 And calculating the wake loss coefficient according to the distribution of the wake loss coefficient in the radial direction, and further calculating the wind speed of the rear exhaust fan.
According to one embodiment of the application, the step S 1 The data tag recorded in (a) includes: time, wind speed of a data acquisition and monitoring control system, wind direction of the data acquisition and monitoring control system and wind speed of a laser radar, the time of data sampling is longer than or equal to 3 months, and the frequency of data sampling is longer than or equal to 10 minutes once.
According to one embodiment of the application, the step S 2 The method comprises the following steps: s is S 21 Aligning the time sequences of the data of the two units; s is S 22 Clearing data points below the cut-in wind speed and above the cut-out wind speed; s is S 23 Clearing a point from the cut-in wind speed to the cut-out wind speed, wherein the active power is smaller than 0; s is S 24 And clearing data points with the included angle between the wind direction and the connecting line of the two selected fans exceeding +/-15 degrees.
According to one embodiment of the application, the step S 3 The calculation formula of the actual wake loss coefficient is as follows:wherein u is 0 Free incoming flow wind speed recorded by airborne laser radar of front exhaust fan, u 1, actual measurement The actual wind speed recorded by the control system is collected and monitored for the data of the rear exhaust fan.
According to one embodiment of the application, the step S 4 The middle fitting formula is: f (r/D) =a ×
(r/D-b) 2 +c, wherein f (r/D) represents the distribution of wake loss coefficients in the radial direction, as a function of the variable r/D; r is the radial distance; d is the diameter of the fan impeller; a. b and c are parabolic shape parameters; in the fitting, the value of a is (- ≡0.0), and the value of c is (0.0, 1.0)]。
According to one embodiment of the application, the steps areS 5 The calculation formula of the wind speed of the middle and rear exhaust fans is as follows:
u 1 ＝u 0 * (1-wake loss factor);
wherein u is 1 The wind speed of the rear exhaust fan is calculated; d (D) w Is the wake diameter at the post exhaust fan point; c (C) t For the front row unit u 0 Thrust coefficient at wind speed; k is the wake expansion coefficient; x is the projection length of the straight line distance between the front and rear fans on the wind direction; i is the turbulence intensity.
The application also provides a wake flow calculation device based on the laser radar and the fan monitoring data, which is characterized in that the wake flow calculation device based on the laser radar and the fan monitoring data comprises: the data acquisition module is used for recording data acquisition and monitoring control system data of the front exhaust fan, airborne laser radar data and data acquisition and monitoring control system data of the rear exhaust fan; the preprocessing module is used for cleaning the data, and calculating the radial distance and the actual wake loss coefficient at the position of the rear exhaust fan based on the cleaned data; a fitting module for fitting the radial distance and the actual wake loss coefficient in a parabolic manner; and the calculation module is used for calculating wake loss coefficients according to the distribution of the wake loss coefficients in the radial direction, and further calculating the wind speed of the rear exhaust fan.
According to one embodiment of the present application, the fitting formula set in the fitting module is: f (r/D) =a (r/D-b) 2 +c, wherein f (r/D) represents the distribution of wake loss coefficients in the radial direction, as a function of the variable r/D; r is the radial distance; d is the diameter of the fan impeller; a. b,c is a parabolic shape parameter; in the fitting, the value of a is (- ≡0.0), and the value of c is (0.0, 1.0)]。
According to one embodiment of the present application, a calculation formula of the wind speed of the rear exhaust fan set in the calculation module is:
k=0.383pi+0.0037; wherein u is 1 The wind speed of the rear exhaust fan is calculated; d (D) w Is the wake diameter at the post exhaust fan point; c (C) t For the front row unit u 0 Thrust coefficient at wind speed; k is the wake expansion coefficient; x is the projection length of the straight line distance between the front and rear fans on the wind direction; i is the turbulence intensity.
The application also provides electronic equipment which is characterized by comprising a processor and a memory, wherein the memory stores a program or instructions, and the processor executes the program or instructions to enable the electronic equipment to execute the wake flow calculation method based on the laser radar and the fan monitoring data.
The application also provides a readable storage medium, which is characterized in that the readable storage medium is stored with a program or instructions, and when the program or instructions are run on electronic equipment, the electronic equipment executes the wake flow calculation method based on the laser radar and the fan monitoring data.
The application has the positive progress effects that:
1. because the wake flow calculation method of the application innovates a downstream fan wake flow loss coefficient profile fitting method based on SCADA data (namely data acquisition and monitoring control system) of the wind generating set and airborne laser radar data, wherein only the front exhaust fan needs to be provided with the airborne laser radar, and the rest data can be obtained from the SCADA system (namely data acquisition and monitoring control system) of the fan, so the cost is controllable.
2. According to the wake flow calculation method, radial wake flow loss distribution is innovatively added into an original wake flow model, so that the method is more in line with an actual flow field, and can calculate the downstream wind speed more accurately, and support is provided for the cooperative control of a field group machine unit to reduce wake flow loss.
Drawings
The above and other features, properties and advantages of the present application will become more apparent from the following description of embodiments taken in conjunction with the accompanying drawings in which like reference characters designate like features throughout the drawings, and in which:
FIG. 1 is an exemplary schematic diagram of a downstream fan wind speed loss coefficient fitting result of a wake calculation method based on laser radar and fan monitoring data.
FIG. 2 is a schematic diagram comparing jensen model with the predicted wind speed scatter plot of the present model of the wake calculation method based on lidar and fan monitoring data of the present application.
FIG. 3 is a schematic diagram comparing jensen model with the predicted wind speed time series chart of the model in the wake calculation method based on laser radar and fan monitoring data.
Detailed Description
In order to make the above objects, features and advantages of the present application more comprehensible, embodiments accompanied with figures are described in detail below.
Embodiments of the present application will now be described in detail with reference to the accompanying drawings. Reference will now be made in detail to the preferred embodiments of the present application, examples of which are illustrated in the accompanying drawings. Wherever possible, the same reference numbers will be used throughout the drawings to refer to the same or like parts. Furthermore, although terms used in the present application are selected from publicly known and commonly used terms, some terms mentioned in the present specification may be selected by the applicant at his or her discretion, the detailed meanings of which are described in relevant parts of the description herein. Furthermore, it is required that the present application is understood, not simply by the actual terms used but by the meaning of each term lying within.
The application provides a wake flow calculation method based on laser radar and fan monitoring data, which comprises the following steps:
step S 1 The method comprises the steps of selecting a front exhaust fan and a rear exhaust fan of a wind power plant in the main wind direction, installing an airborne laser radar on the front exhaust fan, and recording SCADA data (namely data acquisition and monitoring control system data) and airborne laser radar data of the front exhaust fan and SCADA data (namely data acquisition and monitoring control system data) of the rear exhaust fan.
Step S 2 And (5) cleaning data.
Step S 3 Based on the cleaned data, a radial distance (i.e. the projected length of the two fan wires on the orthogonal vector of the wind direction) is calculated, as well as the actual wake loss coefficient at the position of the rear exhaust fan.
Step S 4 Fitting the radial distance and the actual wake loss coefficient in a parabolic fashion.
Step S 5 And calculating the wake loss coefficient according to the distribution of the wake loss coefficient in the radial direction, and further calculating the wind speed of the rear exhaust fan.
Compared with the data of an anemometer and a wind vane (arranged above the tail of the engine room) acquired by a SCADA system (namely a data acquisition and monitoring control system) of the wind generating set, the laser radar measures the wind speed and the wind direction in front of the engine room (generally 80-120 meters, depending on the performance of the laser radar), is not blocked by the damping effect of a fan and an impeller, can be regarded as free incoming wind speed, and is more accurate.
As a preferred embodiment of the wake calculation method of the present application, step S 1 The data tag recorded in (a) includes: time, SCADA wind speed (namely the wind speed of a data acquisition and monitoring control system), SCADA wind direction (namely the wind direction of the data acquisition and monitoring control system) and laser radar wind speed, wherein the data sampling time is not less than 3 months so as to meet the data quantity and complete modeling as soon as possibleA demand; the data sampling frequency is not less than 10 minutes.
As a preferred embodiment of the wake calculation method of the present application, step S 2 The cleaning data includes the following steps:
step S 21 Aligning the time sequences of the data of the two units;
step S 22 Clearing data points below the cut-in wind speed and above the cut-out wind speed;
step S 23 Clearing a point from the cut-in wind speed to the cut-out wind speed, wherein the active power is smaller than 0;
step S 24 And clearing data points with the included angle between the wind direction and the connecting line of the two selected fans exceeding +/-15 degrees.
As a preferred embodiment of the wake calculation method of the present application, step S 3 For calculating the radial distance (namely the projection length of two fan connecting lines on the wind direction orthogonal vector) and the actual wake loss coefficient at the downstream fan position, the calculation formula is as follows:
wherein u is 0 Free incoming flow wind speed recorded by airborne laser radar of front exhaust fan, u 1, actual measurement The actual wind speed recorded for the SCADA system (i.e. the data acquisition and monitoring control system) of the rear exhaust fan.
As a preferred embodiment of the wake calculation method of the present application, step S 4 Fitting the radial distance and the actual wake loss coefficient according to a parabolic form, wherein a fitting formula is as follows:
f(r/D)＝a*(r/D-b) 2 +c
wherein f (r/D) represents the distribution of wake loss coefficients in the radial direction and is a function of r/D as a variable; r is the radial distance, namely the projection length of the two fan connecting lines on the wind direction orthogonal vector; d is the diameter of the fan impeller; a. b and c are parabolic parameters, and are obtained based on data fitting.
In the fitting, the value range of a is (- ≡0.0), and the value range of c is (0.0, 1.0).
As a preferred embodiment of the wake calculation method of the present application, step S 5 In order to distribute wake loss coefficients in the radial direction, the wake loss coefficients are obtained by taking the following formula, and the wind speed of the rear exhaust fan is further calculated:
u 1 ＝u 0 * (1-wake loss factor)
k＝0.3837I+0.0037
Wherein u is 1 The calculated wind speed of the rear exhaust fan; d (D) w Wake diameter at the rear exhaust fan point; c (C) t Is a front row unit u 0 The thrust coefficient under the wind speed can be obtained according to a thrust coefficient curve provided by a fan manufacturer; k is the wake expansion coefficient; x is the projection length of the straight line distance between the front and rear fans on the wind direction; i is the turbulence intensity, which can be obtained from the turbulence intensity corresponding to the turbulence level of the wind farm.
Because the wake flow calculation method of the application innovates a downstream fan wake flow loss coefficient profile fitting method based on SCADA data (namely data acquisition and monitoring control system) of the wind generating set and airborne laser radar data, wherein only the front exhaust fan needs to be provided with the airborne laser radar, and the rest data can be obtained from the SCADA system (namely data acquisition and monitoring control system) of the fan, so the cost is controllable.
According to the wake flow calculation method, radial wake flow loss distribution is innovatively added into an original wake flow model, so that the method is more in line with an actual flow field, and can calculate the downstream wind speed more accurately, and support is provided for the cooperative control of a field group machine unit to reduce wake flow loss.
The method provided by the application has the advantages that a certain wind power plant in the inner Mongolian Liao is proved, 2 sets of front and back wind power plants on the main wind direction (310-350 ℃) of the wind power plant are selected, and a continuous wave airborne laser radar is arranged on each 2 sets of the wind power plants.
Compared with the data of an anemometer and a wind vane (arranged above the tail of the engine room) acquired by a SCADA system (namely a data acquisition and monitoring control system) of the wind generating set, the laser radar measures the wind speed and the wind direction in front of the engine room (generally 80-120 meters, depending on the performance of the laser radar), is not blocked by the damping effect of a fan and an impeller, can be regarded as free incoming wind speed, and is more accurate.
The laser radar data of the front-row unit are substituted into the method for fitting the wake loss coefficient profile, and the laser radar data of the rear-row unit are used for verifying the calculation result of the method.
The direction of the straight line connecting line of the two fans is 324.82 degrees, the straight line distance is 1153 meters, and the diameter of the impeller is 82 meters. According to IEC61400 standard, the turbulence intensity of the wind power plant is C class, and the corresponding 0.12 is selected as the value of the turbulence intensity I. 2023, 1/5/31/1 was selected.
As shown in fig. 1, the vertical axis represents the wake loss coefficient, the horizontal axis represents the radial distance, and the wake loss is maximum when the radial distance is 0 (i.e., when the two fans overlap in the wind direction), and gradually decreases when it deviates. In the past, a Gaussian section model is assumed, and when the radial distance reaches 3 times of the impeller diameter, the wake flow influence is almost 0; the measured data shows that when the radial distance reaches approximately 4 times the impeller diameter, the wake effect decays to 0. Therefore, the data fitting section of the application is more in line with actual measured data and is more in line with actual wind field rules.
As shown in fig. 2 and fig. 3, compared with the traditional jensen model, the correlation between the wind speed of the rear exhaust fan calculated by the model and the actual wind speed is higher, and the calculation result of the model is more similar to the actual wind speed.
The application also provides a wake flow calculation device based on the laser radar and the fan monitoring data, the calculation device adopts the wake flow calculation method in the embodiment of the method of the application, and the calculation device comprises the following steps:
the data acquisition module is used for recording data acquisition and monitoring control system data of the front exhaust fan, airborne laser radar data and data acquisition and monitoring control system data of the rear exhaust fan;
the preprocessing module is used for cleaning the data, and calculating the radial distance and the actual wake loss coefficient at the position of the rear exhaust fan based on the cleaned data;
a fitting module for fitting the radial distance and the actual wake loss coefficient in a parabolic manner;
and the calculation module is used for calculating wake loss coefficients according to the distribution of the wake loss coefficients in the radial direction, and further calculating the wind speed of the rear exhaust fan.
As a preferred embodiment of the wake calculation device of the present application, the fitting module fits the radial distance and the actual wake loss coefficient in a parabolic form, and the fitting formula is:
f(r/D)＝a*(r/D-b) 2 +c
wherein f (r/D) represents the distribution of wake loss coefficients in the radial direction and is a function of r/D as a variable; r is the radial distance, namely the projection length of the two fan connecting lines on the wind direction orthogonal vector; d is the diameter of the fan impeller; a. b and c are parabolic parameters, and are obtained based on data fitting.
In the fitting, the value range of a is (- ≡0.0), and the value range of c is (0.0, 1.0).
As a preferred embodiment of the wake calculation device of the present application, the calculation module brings the distribution of wake loss coefficients in the radial direction into the following formula to obtain the wake loss coefficients, and further calculates the post-exhaust fan wind speed:
y 1 ＝u 0 * (1-wake loss factor)
k＝0.3837I+0.0037
Wherein u is 1 The calculated wind speed of the rear exhaust fan; d (D) w Wake diameter at the rear exhaust fan point; c (C) t Is a front row unit u 0 The thrust coefficient under the wind speed can be obtained according to a thrust coefficient curve provided by a fan manufacturer; k is the wake expansion coefficient; x is the projection length of the straight line distance between the front and rear fans on the wind direction; i is the turbulence intensity, which can be obtained from the turbulence intensity corresponding to the turbulence level of the wind farm.
The wake calculation device adopts the wake calculation method, and the wake calculation method innovates a downstream fan wake flow speed loss coefficient profile fitting method based on SCADA data (namely data acquisition and monitoring control system data) of the wind generating set and airborne laser radar data, wherein only a front exhaust fan needs to be provided with the airborne laser radar, and other data can be obtained from an SCADA system (namely data acquisition and monitoring control system) of the fan, so that the cost is controllable.
The wake flow calculation device adopts the wake flow calculation method, and the radial wake flow loss distribution is innovatively added into the original wake flow model, so that the wake flow calculation device is more in line with an actual flow field, and can calculate the downstream wind speed more accurately, thereby providing support for the cooperative control of a field group machine unit to reduce the wake flow loss.
The application also provides electronic equipment, which comprises a processor and a memory, wherein the memory stores programs or instructions, and the processor executes the programs or instructions to enable the electronic equipment to execute the wake flow calculation method based on the laser radar and the fan monitoring data.
The electronic equipment adopts the wake flow calculation method, and the wake flow calculation method innovates a downstream fan wake flow speed loss coefficient profile fitting method based on SCADA data (namely data acquisition and monitoring control system data) of the wind generating set and airborne laser radar data, wherein only the front exhaust fan needs to be provided with the airborne laser radar, and the rest data can be obtained from an SCADA system (namely data acquisition and monitoring control system) of the fan, so that the cost is controllable.
The electronic equipment adopts the wake flow calculation method, and the radial wake flow loss distribution is innovatively added into the original wake flow model, so that the electronic equipment is more in line with an actual flow field, and can calculate the downstream wind speed more accurately, thereby providing support for the cooperative control of a field group machine unit to reduce the wake flow loss.
The application also provides a readable storage medium, wherein the readable storage medium is stored with a program or instructions, and when the program or instructions run on electronic equipment, the electronic equipment executes the wake flow calculation method based on the laser radar and the fan monitoring data.
The readable storage medium adopts the wake calculation method of the application, and the wake calculation method innovates a downstream fan wake flow speed loss coefficient profile fitting method based on SCADA data (namely data acquisition and monitoring control system data) of the wind generating set and airborne laser radar data, wherein only a front exhaust fan needs to be provided with the airborne laser radar, and the rest data can be obtained from an SCADA system (namely data acquisition and monitoring control system) of the fan, so that the cost is controllable.
The readable storage medium adopts the wake flow calculation method, and the radial wake flow loss distribution is innovatively added into the original wake flow model, so that the method is more in line with an actual flow field, and can calculate the downstream wind speed more accurately, thereby providing support for the cooperative control of a field group machine unit to reduce the wake flow loss.
While specific embodiments of the application have been described above, it will be appreciated by those skilled in the art that these are by way of example only, and the scope of the application is defined by the appended claims. Various changes and modifications to these embodiments may be made by those skilled in the art without departing from the principles and spirit of the application, but such changes and modifications fall within the scope of the application.
Claims (11)
1. The wake flow calculation method based on the laser radar and the fan monitoring data is characterized by comprising the following steps of:
S 1 the method comprises the steps of selecting a front exhaust fan and a rear exhaust fan of a wind power plant in the main wind direction, installing an airborne laser radar on the front exhaust fan, and recording data acquisition and monitoring control system data and airborne laser radar data of the front exhaust fan and data acquisition and monitoring control system data of the rear exhaust fan;
S 2 data are cleaned;
S 3 calculating a radial distance and an actual wake loss coefficient at the position of the rear exhaust fan based on the cleaned data;
S 4 fitting said radial distance and said actual wake loss coefficient in a parabolic fashion;
S 5 and calculating the wake loss coefficient according to the distribution of the wake loss coefficient in the radial direction, and further calculating the wind speed of the rear exhaust fan.
2. The wake calculation method based on lidar and fan monitoring data according to claim 1, wherein the step S 1 The data tag recorded in (a) includes: time, wind speed of a data acquisition and monitoring control system, wind direction of the data acquisition and monitoring control system and wind speed of a laser radar, the time of data sampling is longer than or equal to 3 months, and the frequency of data sampling is longer than or equal to 10 minutes once.
3. The wake calculation method based on lidar and fan monitoring data according to claim 1, wherein the step S 2 The method comprises the following steps:
S 21 aligning the time sequences of the data of the two units;
S 22 clearing data points below the cut-in wind speed and above the cut-out wind speed;
S 23 clearing a point from the cut-in wind speed to the cut-out wind speed, wherein the active power is smaller than 0;
S 24 and clearing data points with the included angle between the wind direction and the connecting line of the two selected fans exceeding +/-15 degrees.
4. The wake calculation method based on lidar and fan monitoring data according to claim 1, wherein the step S 3 The calculation formula of the actual wake loss coefficient is as follows:
wherein u is 0 Free incoming flow wind speed recorded by airborne laser radar of front exhaust fan, u 1, actual measurement The actual wind speed recorded by the control system is collected and monitored for the data of the rear exhaust fan.
5. The wake calculation method based on lidar and fan monitoring data according to claim 1, wherein the step S 4 The middle fitting formula is:
f(r/D)＝a*(r/D-b) 2 +c
wherein f (r/D) represents the distribution of wake loss coefficients in the radial direction and is a function of r/D as a variable; r is the radial distance; d is the diameter of the fan impeller; a. b and c are parabolic shape parameters;
in the fitting, the value range of a is (- ≡0.0), and the value range of c is (0.0, 1.0).
6. The wake calculation method based on lidar and fan monitoring data according to claim 1, wherein the step S 5 The calculation formula of the wind speed of the middle and rear exhaust fans is as follows:
u 1 ＝u 0 * (1-wake loss factor)
k＝0.3837I+0.0037
Wherein u is 1 The wind speed of the rear exhaust fan is calculated; d (D) w Is the wake diameter at the post exhaust fan point; c (C) t For the front row unit u 0 Thrust coefficient at wind speed; k is the wake expansion coefficient; x is the projection length of the straight line distance between the front and rear fans on the wind direction; i is the turbulence intensity.
7. A wake calculation device based on lidar and fan monitoring data, wherein the calculation device adopts the wake calculation method based on lidar and fan monitoring data according to claims 1 to 6, and the calculation device comprises:
the data acquisition module is used for recording data acquisition and monitoring control system data of the front exhaust fan, airborne laser radar data and data acquisition and monitoring control system data of the rear exhaust fan;
the preprocessing module is used for cleaning the data, and calculating the radial distance and the actual wake loss coefficient at the position of the rear exhaust fan based on the cleaned data;
a fitting module for fitting the radial distance and the actual wake loss coefficient in a parabolic manner;
and the calculation module is used for calculating wake loss coefficients according to the distribution of the wake loss coefficients in the radial direction, and further calculating the wind speed of the rear exhaust fan.
8. The wake computation device based on lidar and fan monitoring data of claim 7, wherein the fitting formula set in the fitting module is:
f(r/D)＝a*(r/D-b) 2 +c
wherein f (r/D) represents the distribution of wake loss coefficients in the radial direction and is a function of r/D as a variable; r is the radial distance; d is the diameter of the fan impeller; a. b and c are parabolic shape parameters;
in the fitting, the value range of a is (- ≡0.0), and the value range of c is (0.0, 1.0).
9. The wake flow calculating device based on laser radar and fan monitoring data according to claim 7, wherein a calculation formula of a rear exhaust fan wind speed set in the calculating module is:
y 1 ＝u 0 * (1-wake loss factor)
k＝0.3837I+0.0037
Wherein u is 1 The wind speed of the rear exhaust fan is calculated; d (D) w Is the wake diameter at the post exhaust fan point; c (C) t For the front row unit u 0 Thrust coefficient at wind speed; k is the wake expansion coefficient; x is the projection length of the straight line distance between the front and rear fans on the wind direction; i is the turbulence intensity.
10. An electronic device comprising a processor and a memory, the memory storing a program or instructions that, when executed by the processor, cause the electronic device to perform the wake calculation method of any one of claims 1-6 based on lidar and fan monitoring data.
11. A readable storage medium, characterized in that it has stored thereon a program or instructions which, when run on an electronic device, performs the wake calculation method based on lidar and fan monitoring data according to any of claims 1-6.
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| CN202311133705.6A CN117172001A (en) | 2023-09-04 | 2023-09-04 | Wake flow calculation method and device based on laser radar and fan monitoring data |
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| CN202311133705.6A CN117172001A (en) | 2023-09-04 | 2023-09-04 | Wake flow calculation method and device based on laser radar and fan monitoring data |
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