CN108196087B - Data processing apparatus - Google Patents
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- CN108196087B CN108196087B CN201711462821.7A CN201711462821A CN108196087B CN 108196087 B CN108196087 B CN 108196087B CN 201711462821 A CN201711462821 A CN 201711462821A CN 108196087 B CN108196087 B CN 108196087B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
- G01P5/00—Measuring speed of fluids, e.g. of air stream; Measuring speed of bodies relative to fluids, e.g. of ship, of aircraft
- G01P5/001—Full-field flow measurement, e.g. determining flow velocity and direction in a whole region at the same time, flow visualisation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
Abstract
The embodiment of the application discloses a data processing device, which is used for revising target data to be revised in wind measurement data according to influence factors, and improving the effectiveness and accuracy of the wind measurement data. The data processing device of the embodiment of the application comprises: a processor, a memory, an input-output device, and a bus; the processor, the memory and the input and output equipment are respectively connected with the bus; the input and output equipment is used for acquiring anemometry data; the processor is used for determining target data to be revised in the wind measuring data according to a tower shadow parameter table, and the tower shadow parameter table contains parameters of influences of wind measuring equipment on various wind conditions; determining an influence factor corresponding to the target data according to the tower shadow parameter table, wherein the influence factor is a parameter of influence of the wind measuring equipment on each wind condition; revising the target data according to the influence factor.
Description
Technical Field
The application relates to the technical field of wind resource analysis, in particular to a data processing device.
Background
Important facilities such as nuclear power, chemical engineering and wind power plants, wind resistance safety design and production operation of tall buildings and the like all need to measure local wind conditions.
At present, a special anemometer tower is required to be arranged for measuring wind conditions, anemometer equipment is arranged on the anemometer tower, wind conditions are observed for a period of time or a long time, and local anemometer data are obtained through observation of the anemometer equipment on the anemometer tower and are used for later-stage wind resource analysis.
When the wind condition is measured, the wind measuring equipment is arranged on the wind measuring tower to observe the wind condition, but at the moment, wind flows through the wind measuring tower, the change of a flow field is generated when the wind measuring equipment encounters the wind measuring equipment, the direction and the size of a wind vector are influenced, so that the difference between the wind measuring data measured by the measuring equipment and the actual data of the wind condition is larger, the validity of the wind measuring data is influenced, and the accuracy of the wind measuring data is reduced.
Disclosure of Invention
The embodiment of the application provides a data processing device, which is used for revising target data to be revised in wind measurement data according to influence factors, and improving the effectiveness and accuracy of the wind measurement data.
An embodiment of the present application provides a data processing apparatus, including:
a processor, a memory, an input-output device, and a bus;
the processor, the memory and the input and output equipment are respectively connected with the bus;
the input and output equipment is used for acquiring anemometry data;
the processor is used for determining target data to be revised in the wind measuring data according to a tower shadow parameter table, and the tower shadow parameter table contains parameters of influences of wind measuring equipment on various wind conditions; determining an influence factor corresponding to the target data according to the tower shadow parameter table, wherein the influence factor is a parameter of influence of the wind measuring equipment on each wind condition; revising the target data according to the influence factor.
In one possible implementation, the processor is further configured to:
acquiring a topographic map file corresponding to the position of the anemometer tower;
and generating a tower shadow parameter table according to the topographic map file, wherein the tower shadow parameter table contains parameters of the influence of the wind measuring equipment on each wind condition.
In another possible implementation manner, the processor is specifically configured to:
analyzing the topographic map file to obtain a topographic model;
establishing a physical model of the position of the anemometer tower according to the terrain model;
calculating flow field distribution of the position of the anemometer tower under different wind speeds and wind directions according to the physical model of the position of the anemometer tower to obtain a first calculation result;
establishing a physical model of the position of the anemometer tower provided with the anemometer according to the terrain model;
calculating the flow field distribution of the position of the anemometry tower provided with the anemometry equipment under different wind speeds and wind directions according to the physical model of the position of the anemometry tower provided with the anemometry equipment to obtain a second calculation result;
and generating the tower shadow parameter table according to the first calculation result and the second calculation result, wherein the tower shadow parameter table contains parameters of the influence of the wind measuring equipment on each wind condition.
In another possible implementation manner, the processor is specifically configured to:
determining each group of wind speed and wind direction values in the wind measurement data from the wind measurement data;
acquiring influence factors corresponding to each group of wind speed and wind direction values in the wind measurement data from the tower shadow parameter table, wherein the influence factors have corresponding relations with each group of wind speed and wind direction values, and each group of wind speed and wind direction values corresponds to one influence factor;
and determining each group of wind speed in the wind measuring data with the influence value larger than the preset influence value and the data corresponding to the influence factor corresponding to the wind direction value as the target data to be revised.
In another possible implementation manner, the processor is specifically configured to:
determining from the target data each set of wind speed and wind direction values in the target data;
and acquiring influence factors corresponding to each group of wind speed and wind direction values in the target data from the tower shadow parameter table, wherein the influence factors have corresponding relations with each group of wind speed and wind direction values, and each group of wind speed and wind direction values corresponds to one influence factor.
In another possible implementation manner, the processor is further configured to:
displaying a prompt message whether to approve revision of the target data to a user, wherein the prompt message comprises a revision value of revising the target data by the data processing device when the data processing device acquires the revision approval message of the user, and the revision value is an increment obtained by subtracting the target data from the revised target data obtained by revising the target data by the data processing device;
and if the data processing device acquires the revision agreement message of the user, triggering the processor to revise the target data according to the influence factor.
In another possible implementation manner, the processor is further configured to:
classifying the wind measuring data to obtain first data and second data, wherein the first data are data reaching a preset standard reaching value, and the second data are data not reaching the preset standard reaching value;
establishing an operation model according to a data group in the first data, wherein the data group is data of each wind measuring height corresponding to each wind measuring time in the first data and reaching the preset standard reaching value;
calculating to obtain corrected second data according to the operation model and first data which has the same wind measuring time with the second data and reaches the preset standard reaching value;
and determining the first data and the corrected second data as corrected wind measuring data.
In another possible implementation manner, the processor is specifically configured to:
and determining target data to be revised in the corrected wind measuring data according to the tower shadow parameter table.
In another possible implementation manner, the data processing apparatus includes a terminal or a server.
In another possible implementation, the anemometry data includes a wind speed of a wind condition and a wind direction value of the wind condition.
According to the technical scheme, the embodiment of the application has the following advantages:
according to the technical scheme, the input and output equipment acquires the wind measuring data; the processor can determine target data to be revised in the wind measurement data according to a tower shadow parameter table, wherein the tower shadow parameter table contains parameters of influences of wind measurement equipment on various wind conditions; then the processor can determine an influence factor corresponding to the target data according to the tower shadow parameter table, wherein the influence factor is a parameter of the influence of the wind measuring equipment on each wind condition; the processor may revise the target data based on the impact factor. Therefore, the target data to be revised in the wind measuring data can be analyzed and determined by the processor according to the tower shadow parameter table, then the influence factor corresponding to the target data can be determined by the processor according to the tower shadow parameter table, the influence factor is a parameter of influence of the wind measuring equipment on each wind condition, and then the target data to be revised can be revised by the processor according to the influence factor, so that the effectiveness and the accuracy of the wind measuring data are improved.
Drawings
FIG. 1 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a terminal in an embodiment of the present application.
Detailed Description
The embodiment of the application provides a data processing device, which is used for revising target data to be revised in wind measurement data according to influence factors, and improving the effectiveness and accuracy of the wind measurement data.
In the data processing process, the data processing device is used for acquiring the wind measurement data, processing and analyzing the wind measurement data and the like. The wind measurement data can be wind condition data of the places where important facilities such as nuclear power, chemical engineering or wind power plants are located, and then the wind measurement data are analyzed and processed through the data processing device and used for subsequently selecting the sites of the important facilities for reference. For example, in the site selection process of the wind farm, the wind condition of the location where the wind farm is built needs to be observed for a long time or a period of time, at this time, the wind condition can be observed through the wind measuring equipment by building the wind measuring tower and installing the wind measuring equipment, local wind measuring data is obtained, and the wind measuring data is analyzed and processed through the data processing device, so that the optimal place where the wind farm is built is reasonably selected.
It should be noted that the data processing apparatus may be a terminal, on which a corresponding data processing application app is installed, or may be a server, and is not limited herein. In the following embodiments, only an example in which a data processing apparatus is a terminal will be described. The terminal may be a computer, a tablet, or the like, and is not limited herein.
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a data processing apparatus in an embodiment of the present application, and a schematic structural diagram of the data processing apparatus in the embodiment of the present application is described below, where the data processing apparatus 100 includes:
a processor 101, a memory 102, an input-output device 103, and a bus 104;
the processor 101, the memory 102 and the input/output device 103 are respectively connected with the bus 104;
the input and output device 103 is used for acquiring anemometry data;
the wind conditions of the site of the nuclear power, chemical industry or wind power plant may be measured by building a wind measuring tower at the site, installing a wind measuring device on the wind measuring tower, and observing the local wind conditions by the wind measuring device to record measured wind speeds at different times in the local area and wind direction values of the wind speeds. The user inputs the wind measurement data measured by the wind measurement device into the input and output device, and then the input and output device can obtain the wind measurement data, or the data processing device establishes a connection with the wind measurement device, and the wind measurement device sends the wind measurement data into the data processing device, and then the input and output device receives the wind measurement data, and the specific details are not limited herein.
The processor 101 is configured to determine target data to be revised in the wind measurement data according to a tower shadow parameter table, where the tower shadow parameter table includes parameters of influences of the wind measurement device on various wind conditions; determining an influence factor corresponding to the target data according to the tower shadow parameter table, wherein the influence factor is a parameter of influence of the wind measuring equipment on each wind condition; revising the target data according to the influence factor.
In this embodiment, the processor 101 may determine the target data to be modified of the anemometry data according to a preset tower shadow parameter table, or may generate a tower shadow parameter table according to a topographic map file, and then determine the target data to be modified of the anemometry data according to the generated tower shadow parameter table, which is not limited herein.
It should be noted that the tower shadow parameter table is shown in table 1, wherein the vertical column is the wind speed (unit: m/s), and the wind speed value after the wind measuring equipment is installed is taken as a reference; the horizontal column is the wind direction (unit: degree); a [ m ] [ n ] is an influence factor corresponding to the nth wind speed of the mth wind direction value, and is shown in table 1:
TABLE 1
| 0° | 5° | … | 355° | |
| 3m/s | a[1][1] | a[1][2] | … | a[1][n] |
| 3.5m/s | a[2][1] | a[2][2] | … | a[2][n] |
| … | … | … | … | … |
| 15m/s | a[m][1] | a[m][2] | … | a[m][n] |
Note: the positive north direction is recorded as an initial angle and zero degree;
the angles (0-355) were recorded clockwise with 5 ° spacing.
In this embodiment, the processor 101 may determine each group of wind speeds and wind direction values in the wind measurement data, and then obtain an influence factor corresponding to each group of wind speeds and wind direction values in the wind measurement data from table 1, where the tower shadow parameter table includes parameters of influences of the wind measurement device on each wind condition, the influence factor is a parameter of influences of the wind measurement device on each wind condition, the influence factor has a corresponding relationship with each group of wind speeds and wind direction values, and each group of wind speeds and wind direction values corresponds to one influence factor; then, the processor 101 may determine whether the influence factor corresponding to each group of wind speed and wind direction values is greater than a preset influence value, and if the influence factor corresponding to each group of wind speed and wind direction values is greater than the preset influence value, the processor 101 may determine that the data corresponding to the influence factor is the target data to be revised. For example, if the processor 101 determines that a group of wind speed and wind direction values in the wind measurement data is (3m/s, 0 °), the influence factor corresponding to the group of data can be determined to be a [1] [1] from table 1, and then it is determined whether a [1] [1] is greater than a preset influence value, and if so, the processor 101 can determine that the group of data is to-be-revised data.
In this embodiment, the processor 101 may determine the impact factor corresponding to the target data according to the tower shadow parameter table. Specifically, the processor 101 may determine each set of wind speed and wind direction values in the target data from the target data, and then obtain the impact factors corresponding to each set of wind speed and wind direction values in the target data from the tower shadow parameter table. For example, if the processor 101 determines that a set of wind speed and wind direction values in the target data is (3.5m/s, 5), then the set of data may be determined from Table 1 to have an impact factor a [2] [2 ].
In this embodiment, after determining the impact factor corresponding to the target data, the processor 101 may revise the target data according to the impact factor. Specifically, the processor 101 may multiply the impact factor by the target data, the impact factor being positively correlated with the target data; if the impact factor is in a negative correlation with the target data, the processor 101 may divide the wind speed in the target data by the impact factor to obtain revised data, which is not limited herein.
In this embodiment, the input/output device 103 acquires anemometry data; the processor 101 may determine target data to be revised in the anemometry data according to a tower shadow parameter table, where the tower shadow parameter table contains parameters of influences of the anemometry equipment on each wind condition; then, the processor 101 may determine an influence factor corresponding to the target data according to the tower shadow parameter table, where the influence factor is a parameter of influence of the wind measuring device on each wind condition; the processor 101 may revise the target data according to the impact factor. Therefore, the processor 101 may determine, according to the tower shadow parameter table, target data to be revised in the anemometry data through analysis, and then the processor 101 may determine, according to the tower shadow parameter table, an influence factor corresponding to the target data, where the influence factor is a parameter of influence of the anemometry device on each wind condition, and then the processor 101 may revise the target data to be revised according to the influence factor, thereby improving validity and accuracy of the anemometry data.
In the embodiment of the present application, the data processing apparatus may be a terminal or a server, and is not limited herein.
In the embodiment of the application, the terminal can analyze, process and correct the integrity of the wind measurement data and the rationality of the wind measurement data, analyze and revise the influence of the wind measurement data on the wind measurement equipment on the wind measurement tower, or analyze and revise the influence of the wind measurement equipment on the wind measurement tower by directly analyzing the wind measurement data, and the specific point is not limited. In the following embodiments, only the terminal analyzes and corrects the integrity of the wind measurement data and the rationality of the wind measurement data, and then analyzes and corrects the influence of the wind measurement data on the wind measurement equipment on the wind measurement tower.
In this embodiment of the application, the terminal may generate the tower shadow parameter table according to the obtained topographic map file, and then obtain the impact factor corresponding to the anemometry data according to the tower shadow parameter table, where a schematic structural diagram in this embodiment of the application is described below.
Referring to fig. 2, fig. 2 is a schematic structural diagram of a terminal in an embodiment of the present application. For convenience of understanding, a schematic structural diagram of the terminal in the embodiment of the present application is described below, and the terminal 200 includes:
a processor 201, a memory 202, an input-output device 203, and a bus 204;
the processor 201, the memory 202 and the input/output device 203 are respectively connected with the bus 204;
the input and output device 203 is used for acquiring anemometry data;
it should be noted that the input/output device 203 is similar to the aforementioned input/output device 103 in fig. 1, and detailed description thereof is omitted here.
The processor 201 is configured to classify the anemometry data to obtain first data and second data.
In this embodiment, the processor 201 may perform classification processing on the anemometry data to obtain first data and second data. Specifically, the processor 201 may use a national standard as a determination standard, and determine, according to a formula established by the national standard, first data that reaches a preset standard value and second data that does not reach the preset standard value in the wind measurement data.
The processor 201 is configured to build an operational model based on the data set of the first data.
In this embodiment, the processor 201 may establish an operation model according to a data set in the first data, where the data set is data of each wind measurement height corresponding to each wind measurement time in the first data, and the relationship between the input and the output is determined by establishing the operation model.
The processor 201 is configured to calculate and obtain the modified second data according to the operation model and the first data which is the same anemometry time as the second data and both of which reach the preset standard value.
In this embodiment, after the processor 201 determines the operation model, the relationship between input and output is determined, and the processor 201 may calculate, according to the input-output relationship determined by the operation model, first data that reaches a preset standard value with second data as input data to obtain modified second data.
The processor 201 is configured to determine the first data and the modified second data as modified anemometry data.
In this embodiment, after the processor 201 finishes correcting the second data, it may be determined that the first data and the corrected second data are corrected anemometry data.
The processor 201 is configured to obtain a topographic map file corresponding to a position where the anemometer tower is located.
In this embodiment, the processor 201 obtains a topographic map file corresponding to the position where the anemometer tower is located, where it should be noted that the topographic map file may be a topographic map file of the position where the anemometer tower is located, which is input by a user, or the processor 201 obtains the topographic map file corresponding to the position where the anemometer tower is located from a map by positioning, and this is not limited here.
The processor 201 is configured to parse the topographic map file to obtain a topographic model.
In this embodiment, after the processor 201 obtains the topographic map file, the topographic map file may be analyzed to obtain a topographic model. The processor 201 may identify contour lines and height values on the topographic map, and convert the topographic map file into a topographic model, which may be a three-dimensional topographic map or a planar map, and is not limited herein.
The processor 201 is configured to establish a physical model of the position of the anemometer tower according to the terrain model.
In this embodiment, after the processor 201 obtains the terrain model, a physical model of the position of the anemometer tower corresponding to the terrain model is established through an algorithm preset in the memory 202.
The processor 201 is configured to simulate and reduce a flow field at the position of the anemometer tower in the physical model of the position of the anemometer tower, so as to obtain flow field distribution at the position of the anemometer tower after reduction.
In this embodiment, the processor 201 performs simulated reduction on the flow field of the position of the anemometer tower in the physical model of the position of the anemometer tower to obtain the flow field distribution of the reduced position of the anemometer tower, which may specifically be that the processor 201 performs simulated reduction on the flow field of the position of the anemometer tower by using a Computational Fluid Dynamics (CFD) simulation technique, or may perform simulated reduction on the flow field of the position of the anemometer tower by using other manners, which is not limited herein.
The processor 201 is configured to calculate a flow field distribution of a position where the anemometer tower is located under different wind speeds and wind directions, and obtain a first calculation result.
In this embodiment, after the processor 201 performs simulation reduction on the flow field of the anemometer tower to obtain the reduced flow field of the position where the anemometer tower is located, based on the reduced flow field of the position where the anemometer tower is located, the processor 201 may calculate the flow field distribution of the positions where the anemometer tower is located at different wind speed and wind direction values to obtain a first calculation result.
The processor 201 is configured to establish a physical model of a flow field at a position where a wind measuring tower provided with a wind measuring device is located according to the terrain model.
In this embodiment, the processor 201 establishes a physical model of a flow field at a position where the anemometer tower provided with the anemometer device is located, which corresponds to the terrain model, according to an algorithm preset in the memory 202.
The processor 201 is configured to simulate and restore a flow field at a position of the anemometry tower with the anemometry device installed therein in the physical model of the position of the anemometry tower with the anemometry device installed therein, so as to obtain a flow field distribution at the position of the anemometry tower with the anemometry device installed therein after restoration.
In this embodiment, the processor 201 simulates and restores a flow field at a position of the anemometry tower provided with the anemometry equipment in the physical model of the position of the anemometry tower provided with the anemometry equipment to obtain a restored flow field distribution at the position of the anemometry tower provided with the anemometry equipment, specifically, the processor 201 simulates and restores the flow field at the position of the anemometry tower provided with the anemometry equipment by using a CFD simulation technique, and also simulates and restores the flow field at the position of the anemometry tower provided with the anemometry equipment by using other methods, which is not limited herein.
The processor 201 is configured to calculate a flow field distribution at a position of the anemometer tower where the anemometer is installed under different wind speeds and wind directions, and obtain a second calculation result.
In this embodiment, after the processor 201 performs simulation reduction on the position of the anemometry tower with the anemometry device installed therein to obtain the flow field of the reduced position of the anemometry tower with the anemometry device installed therein, based on the flow field of the reduced position of the anemometry tower with the anemometry device installed therein, the processor 201 may calculate the flow field distribution of the positions of the anemometry towers with the anemometry devices installed therein at different wind speed and wind direction values to obtain a second calculation result.
The processor 201 is configured to generate a tower shadow parameter table according to the first calculation result and the second calculation result.
In this embodiment, the processor 201 determines a relationship ratio between the first calculation result and the second calculation result by processing the first calculation result and the second calculation result; for example, if a set of wind speed and wind direction values are (3.5m/s, 5 °), the first calculation result shows that the airflow at the position of the wind measuring tower under the condition of the wind speed and wind direction values is a, the second calculation result shows that the airflow at the position of the wind measuring tower with the wind measuring equipment under the condition of the wind speed and wind direction values is b, then the processor 201 may determine that the relationship ratio between the first calculation result and the second calculation result is a/b, then the processor 201 may determine that the influence factors corresponding to the wind speed and wind direction values are the relationship ratio a/b, then the processor 201 may generate a tower shadow parameter table by determining the influence factors of multiple sets of data, where the tower shadow parameter table includes parameters of influences of the wind measuring equipment on various wind conditions, as in table 1, and the wind speed value of the wind measuring tower with the wind measuring equipment installed is used as a reference, each group of wind speed and wind direction values are correspondingly provided with an influence factor.
In this embodiment, the process of analyzing and correcting the integrity and the rationality of the wind measurement data by the processor 201 and the process of generating the tower shadow parameter table by the processor 201 according to the topographic map file do not have a fixed execution sequence, the process of analyzing and correcting the integrity and the rationality of the wind measurement data by the processor 201 may be performed first, the process of generating the tower shadow parameter table by the processor 201 according to the topographic map file may be performed simultaneously according to the situation, and the process of analyzing and correcting the integrity and the rationality of the wind measurement data and the process of generating the tower shadow parameter table according to the topographic map file may be performed at the same time, and is not limited herein.
The processor 201 is configured to determine each group of wind speed and wind direction values in the corrected wind measurement data from the corrected wind measurement data.
In this embodiment, after the processor 201 finishes correcting the wind measurement data, each group of wind speed and wind direction value in the wind measurement data may be determined from the corrected wind measurement data, for example, the processor 201 may determine a data group at a certain time in the wind measurement data, the wind speed and wind direction value in the data group is (3.5m/s, 5 °), and the processor 201 may determine all data groups included in the wind measurement data.
The processor 201 is configured to obtain the influence factors corresponding to each group of wind speed and wind direction value in the corrected wind measurement data from the tower shadow parameter table.
In this embodiment, the processor 201 obtains the influence factor corresponding to each group of wind speed and wind direction value in the corrected wind measurement data from the tower shadow parameter table, specifically, for example, if the processor 201 determines that a group of data in the wind measurement data is (3.5m/s, 5 °), then the processor 201 may look up the influence factor corresponding to the group of data from the tower shadow parameter table, as shown in table 1, the processor 201 may determine that the influence factor corresponding to (3.5m/s, 5 °) is a [2] [2], and obtain the influence factor a [2] [2] from the tower shadow parameter table.
The processor 201 is configured to determine, as target data to be revised, data corresponding to each group of wind speeds and influence factors corresponding to wind direction values in the corrected wind measurement data that are greater than a preset influence value.
In this embodiment, after the processor 201 determines each group of wind speed and wind direction value in the wind measurement data, the processor 201 may determine whether an influence factor corresponding to each group of wind speed and wind direction value is greater than a preset influence value, if the processor 201 determines that the influence factor is greater than the preset influence value, the processor 201 may determine that the group of data is to-be-revised data, the processor 201 determines each group of wind speed and wind direction value in the wind measurement data, and determines that the data corresponding to the influence factor corresponding to each group of wind speed and wind direction value in the revised wind measurement data that is greater than the preset influence value is to-be-revised target data after the determination. For example, the processor 201 determines the data group (3.5m/s, 0 °), at this time, the processor 201 may determine, from the tower shadow parameter table, that the impact factor corresponding to the data group is a [2] [1], and the impact value preset in the memory 202 is c, at this time, the terminal needs to determine whether a [2] [1] is greater than c, and if a [2] [1] is greater than c, the processor 201 may determine that the data group (3.5m/s, 0 °) is the data to be revised.
The processor 201 is configured to determine from the target data each set of wind speed and wind direction values in the target data.
In this embodiment, after the processor 201 determines the target data to be revised, data of each set of wind speed and wind direction values of the target data may be determined, for example, the processor 201 may determine the data set to be (3m/s, 0 °) from the target data, where the target data includes the data set of (3m/s, 0 °).
The processor 201 is configured to obtain the influence factors corresponding to each group of wind speed and wind direction values in the target data from the tower shadow parameter table.
In this embodiment, the processor 201 may obtain the corresponding impact factor from the tower shadow parameter table according to each group of wind speed and wind direction values of the target data determined in step 218. For example, if the processor 201 determines that a group of data in the target data is (3m/s, 0 °), the processor 201 may obtain the impact factor corresponding to the group of data at (3m/s, 0 °) as a [1] [1] from table 1.
The processor 201 is configured to display a prompt message to the user whether the revision is approved.
In this embodiment, after the processor 201 determines the influence factor corresponding to the target data to be revised, the processor 201 may display a prompt message indicating whether to approve the revision to the user, where the prompt message includes a revision value revised by the target data to be revised when the processor 201 acquires the message of approving the revision from the user, and the revision value is an increment obtained by subtracting the target data from the revised target data obtained by revising the target data by the processor 201. For example, the terminal determines that a group of wind speed and wind direction values to be revised are (3m/s, 0 °), then, determines that the influence factor corresponding to the group of data is a [1] [1] from the tower shadow parameter table, and then, the revised value may be 3 × a [1] [1] -3. The terminal can remind the user terminal to revise the wind measuring data by displaying the prompt message to the user, and the user can decide whether to revise according to whether the corresponding revision value is reasonable or not, so that the user experience is improved.
If the processor 201 obtains the user's approval to revise the message, the processor 201 revises the target data according to the impact factor. Specifically, the processor 201 may multiply the impact factor by the target data to obtain revised target data, where the impact factor is positively correlated with the target data. For example, the processor 201 determines the data set (3m/s, 0 °), then the processor 201 may obtain the impact factor corresponding to the data set from the tower shadow parameter table as a [1] [1], and then the processor 201 may revise the wind speed 3m/s, that is, multiply the wind speed 3m/s by a [1] [1 ]; if the impact factor is inversely related to the target data, the processor 201 may divide the wind speed by the impact factor to obtain revised data, which is not limited herein.
If the processor 201 acquires the revision rejection message of the user, the processor 201 performs other operations. For example, the processor 201 may prompt the user with the revised value again, or the processor 201 may retest once again and display the result to the user again, which is not limited herein.
In this embodiment, the processor 201 may not display a prompt message indicating whether to approve the revision to the user, that is, after the processor 201 determines the influence factor corresponding to the target data to be revised, the processor 201 revises the target data directly according to the influence factor, which is not limited herein.
In this embodiment, the input/output device 203 acquires anemometry data; the processor 201 may determine target data to be revised in the anemometry data according to a tower shadow parameter table, where the tower shadow parameter table contains parameters of influences of the anemometry equipment on various wind conditions; then, the processor 201 may determine an influence factor corresponding to the target data according to the tower shadow parameter table, where the influence factor is a parameter of influence of the anemometry device on each wind condition; the processor 201 can revise the target data according to the impact factor. Therefore, the processor 201 can determine target data to be revised in the anemometry data according to the tower shadow parameter table, and then the processor 201 can determine an influence factor corresponding to the target data according to the tower shadow parameter table, wherein the influence factor is a parameter of influence of the anemometry equipment on each wind condition, so that the processor 201 can revise the target data to be revised according to the influence factor, and therefore, the effectiveness and the accuracy of the anemometry data are improved.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (7)
1. A data processing apparatus, characterized in that the data processing apparatus comprises:
a processor, a memory, an input-output device, and a bus;
the processor, the memory and the input and output equipment are respectively connected with the bus;
the input and output equipment is used for acquiring wind measurement data, and the wind measurement data comprises a plurality of wind conditions, and each wind condition comprises a wind speed and a wind direction value;
the processor is used for acquiring a topographic map file corresponding to the position of the anemometer tower; generating a tower shadow parameter table according to the topographic map file, wherein the tower shadow parameter table contains parameters of influences of wind measuring equipment on various wind conditions; determining target data to be revised in the anemometry data according to a tower shadow parameter table; determining an influence factor corresponding to the target data according to the tower shadow parameter table, wherein the influence factor is a parameter of influence of the wind measuring equipment on each wind condition; revising the target data according to the influence factors;
the processor is specifically configured to:
analyzing the topographic map file to obtain a topographic model;
establishing a physical model of the position of the anemometer tower according to the terrain model;
calculating flow field distribution of the position of the anemometer tower under different wind speeds and wind directions according to the physical model of the position of the anemometer tower to obtain a first calculation result;
establishing a physical model of the position of the anemometer tower provided with the anemometer according to the terrain model;
calculating the flow field distribution of the position of the anemometry tower provided with the anemometry equipment under different wind speeds and wind directions according to the physical model of the position of the anemometry tower provided with the anemometry equipment to obtain a second calculation result;
and generating the tower shadow parameter table according to the first calculation result and the second calculation result, wherein the tower shadow parameter table contains parameters of the influence of the wind measuring equipment on each wind condition.
2. The data processing apparatus of claim 1, wherein the processor is specifically configured to:
determining each group of wind speed and wind direction values in the wind measurement data from the wind measurement data;
acquiring influence factors corresponding to each group of wind speed and wind direction values in the wind measurement data from the tower shadow parameter table, wherein the influence factors have corresponding relations with each group of wind speed and wind direction values, and each group of wind speed and wind direction values corresponds to one influence factor;
and determining each group of wind speed in the wind measuring data with the influence value larger than the preset influence value and the data corresponding to the influence factor corresponding to the wind direction value as the target data to be revised.
3. The data processing apparatus of claim 1, wherein the processor is specifically configured to:
determining from the target data each set of wind speed and wind direction values in the target data;
and acquiring influence factors corresponding to each group of wind speed and wind direction values in the target data from the tower shadow parameter table, wherein the influence factors have corresponding relations with each group of wind speed and wind direction values, and each group of wind speed and wind direction values corresponds to one influence factor.
4. The data processing apparatus of claim 1, wherein the processor is further configured to:
displaying a prompt message whether to approve revision of the target data to a user, wherein the prompt message comprises a revision value of revising the target data by the data processing device when the data processing device acquires the revision approval message of the user, and the revision value is an increment obtained by subtracting the target data from the revised target data obtained by revising the target data by the data processing device;
and if the data processing device acquires the revision agreement message of the user, triggering the processor to revise the target data according to the influence factor.
5. The data processing apparatus of claim 1, wherein the processor is further configured to:
classifying the wind measuring data to obtain first data and second data, wherein the first data are data reaching a preset standard reaching value, and the second data are data not reaching the preset standard reaching value;
establishing an operation model according to a data group in the first data, wherein the data group is data of each wind measuring height corresponding to each wind measuring time in the first data and reaching the preset standard reaching value;
calculating to obtain corrected second data according to the operation model and first data which has the same wind measuring time with the second data and reaches the preset standard reaching value;
and determining the first data and the corrected second data as corrected wind measuring data.
6. The data processing apparatus of claim 5, wherein the processor is specifically configured to:
and determining target data to be revised in the corrected wind measuring data according to the tower shadow parameter table.
7. The data processing apparatus of any of claims 1 or 4 to 6, wherein the data processing apparatus comprises a terminal or a server.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0720141A (en) * | 1993-06-30 | 1995-01-24 | Chiyoda Corp | Wind direction and velocity meter |
| DE102013100515A1 (en) * | 2013-01-18 | 2014-07-24 | Christoph Lucks | Method for controlling wind power plant or wind farm, involves carrying out measurement of wind speed and wind direction, and carrying out adjustment of rotor blades, according to pitch angle and azimuth orientation of rotor plane |
| CN104156575A (en) * | 2014-07-28 | 2014-11-19 | 国家电网公司 | Method for calculating theoretical power of wind farm on basis of extrapolation of anemometer tower data |
| CN106707166A (en) * | 2017-01-05 | 2017-05-24 | 云南电网有限责任公司电力科学研究院 | Method for evaluating output characteristic of wind power plant |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202196406U (en) * | 2011-06-27 | 2012-04-18 | 内蒙古电力勘测设计院 | Wind farm design expert system |
| CN104331621B (en) * | 2014-11-05 | 2017-11-28 | 中国大唐集团新能源股份有限公司 | A kind of wind-resources computational methods |
| CN105824891B (en) * | 2016-03-11 | 2019-02-26 | 中能电力科技开发有限公司 | The method that anemometer tower data upload automatically |
| CN106597008A (en) * | 2016-12-05 | 2017-04-26 | 北京普华亿能风电技术有限公司 | Wind measuring method resistant to wind shadow of an anemometer tower |
-
2017
- 2017-12-28 CN CN201711462821.7A patent/CN108196087B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0720141A (en) * | 1993-06-30 | 1995-01-24 | Chiyoda Corp | Wind direction and velocity meter |
| DE102013100515A1 (en) * | 2013-01-18 | 2014-07-24 | Christoph Lucks | Method for controlling wind power plant or wind farm, involves carrying out measurement of wind speed and wind direction, and carrying out adjustment of rotor blades, according to pitch angle and azimuth orientation of rotor plane |
| CN104156575A (en) * | 2014-07-28 | 2014-11-19 | 国家电网公司 | Method for calculating theoretical power of wind farm on basis of extrapolation of anemometer tower data |
| CN106707166A (en) * | 2017-01-05 | 2017-05-24 | 云南电网有限责任公司电力科学研究院 | Method for evaluating output characteristic of wind power plant |
Non-Patent Citations (2)
| Title |
|---|
| Measurement and Simulation of the Flow Field around a Triangular Lattice Meteorological Mast;Matthew Stickland 等;《Journal of Energy and Power Engineering》;20130630;第7卷(第10期);第1934-1939页 * |
| 海上风电场风能资源观测和评估关键技术研究;王海龙 等;《电力勘测设计》;20160731;第234-238、243页 * |
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