CN116595393A - Gridding wind field information extraction method, system, terminal and storage medium - Google Patents
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Abstract
The invention relates to a method, a system, a terminal and a storage medium for extracting information of a gridding wind field, wherein the method comprises the following steps: the wind power data and the air pollution data collected in the selected area are respectively gridded and filled by a set spatial interpolation algorithm to form a wind field and a pollution field which are closely spread in space, and the wind field and the pollution field share a set of grid frames and are overlapped; defining a plurality of adjacent grids in the grid framework to form a mode, and calculating a matching score between the two modes which can be completely overlapped in shape only through translation; the invention provides a calculation expression for describing the representativeness of a wind field mode (rather than a single place) of a space area, which can be used for evaluating and describing a typical air duct and describing the dominant wind direction of a specific place, and solves the problem that the effective extraction and expression of small-scale gridding wind field information are difficult at present.
Description
Technical Field
The invention relates to the technical field of meteorological wind field information, in particular to a grid wind field information extraction method, a grid wind field information extraction system, a grid wind field information extraction terminal and a storage medium.
Background
The meteorological wind field information has important significance for judging the change of the air pollution situation, and the small wind sensor which is arranged in a gridding way can provide fine-granularity wind speed and wind direction information and generate a small-scale microscopic wind field through interpolation reconstruction. For the description of wind power characteristics, one of the classical methods is to use a wind rose diagram, wherein the wind rose diagram can reflect the proportion of each incoming wind in a certain time at a certain place, but the wind rose diagram aims at the measurement of single-point wind power information, and is not accurate and representative for the description of wind field information under the condition of small scale (hundred meters or sub hundred meters) of cities. Visualization is realized on a plurality of small-scale wind fields at present, and certain help is also provided for the situation change of air pollution (as shown in fig. 1), but effective extraction and expression modes for small-scale gridding wind field information are still lacking at present.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a gridding wind field information extraction method, a gridding wind field information extraction system, a gridding wind field information extraction terminal and a computer readable storage medium aiming at the defects in the prior art.
The technical scheme adopted for solving the technical problems is as follows:
a gridding wind field information extraction method is constructed, which comprises the following steps:
the wind power data and the air pollution data collected in the selected area are respectively gridded and filled by a set spatial interpolation algorithm to form a wind field and a pollution field which are closely spread in space, and the wind field and the pollution field share a set of grid frames and are overlapped;
a number of adjacent grids in the grid framework are defined to form a pattern and a matching score is calculated between the two patterns which can be completely coincident in shape by only translation.
The invention discloses a gridding wind field information extraction method, wherein the matching score calculation adopts the formula:
wherein K is the number of grids contained in each of the two patterns with the same shape, the wind field information of each unit is represented by a vector (x, y), the matching score is represented by a matching score, the wind field vector of the ith grid of pattern 1 is (xi, 1, yi, 1), and the wind field vector of the ith grid of pattern 2 is (xi, 2, yi, 2); the interval of the matching score is [ -1,1], the closer to 1, the more similar the two patterns are in terms of wind direction characteristics.
The invention discloses a gridding wind field information extraction method, which comprises the following steps:
transmission channel representativeness calculation:
selecting a set of regional grid formation patterns between the target site and the potential source of pollution;
calculating a matching score time sequence of the pattern and the selected grid composition pattern in the [ T1, T2] time period;
the distribution and duty cycle of the typical period of high match score is obtained from the match score time series.
The invention discloses a gridding wind field information extraction method, which comprises the following steps:
and (3) calculating dominant wind direction characteristics:
setting a mode with a positive direction and a length of 1 in all grid cell vectors in the grid framework as a given mode;
and calculating the matching score of the target place and the mode of the azimuth corresponding to the given mode, and solving the average value of the matching score in a set time period to obtain the dominant wind direction characteristics of the eight azimuth of the target place.
The grid wind field information extraction system is applied to the grid wind field information extraction method, and comprises a data acquisition unit, a grid frame generation unit and a matching score calculation unit;
the data acquisition unit acquires wind power data and air pollution data in a selected area;
the grid frame generating unit is used for respectively carrying out grid filling on the collected wind power data and the air pollution data through a set spatial interpolation algorithm to form a wind field and a pollution field which are closely paved in space, and the wind field and the pollution field share one set of grid frame and are overlapped;
the matching score calculating unit defines a mode formed by a plurality of adjacent grids in the grid framework, and calculates a matching score between the two modes which can be completely overlapped in shape only through translation.
The grid wind field information extraction system provided by the invention, wherein the matching score calculation unit calculates the matching score by adopting the formula:
wherein K is the number of grids contained in each of the two patterns with the same shape, the wind field information of each unit is represented by a vector (x, y), the matching score is represented by a matching score, the wind field vector of the ith grid of pattern 1 is (xi, 1, yi, 1), and the wind field vector of the ith grid of pattern 2 is (xi, 2, yi, 2); the interval of the matching score is [ -1,1], the closer to 1, the more similar the two patterns are in terms of wind direction characteristics.
The invention relates to a gridding wind field information extraction system, wherein the system further comprises a transmission channel representativeness calculation unit;
the transmission channel representativeness calculating unit selects a group of regional grid formation modes between a target site and a potential pollution source, calculates a matching score time sequence of the mode and the selected grid formation mode in the [ T1, T2] time period, and obtains the distribution and the duty ratio of a high matching score representativeness period according to the matching score time sequence.
The invention relates to a gridding wind field information extraction system, wherein the system further comprises a dominant wind direction characteristic calculation unit;
the dominant wind direction characteristic calculation unit sets a mode with a positive satisfying direction and a length of 1 in all grid cell vectors in the grid framework as a given mode; and calculating the matching score of the target place and the mode of the azimuth corresponding to the given mode, and solving the average value of the matching score in a set time period to obtain the dominant wind direction characteristics of the eight azimuth of the target place.
A gridded wind farm information extraction terminal comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method as described above when executing the computer program.
A computer readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the steps of the method as described above.
The invention has the beneficial effects that: the invention provides a calculation expression for describing the representativeness of a wind field mode (rather than a single place) of a space area, which can be used for evaluating and describing a typical air duct and describing the dominant wind direction of a specific place, and solves the problem that the effective extraction and expression of small-scale gridding wind field information are difficult at present.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the present invention will be further described with reference to the accompanying drawings and embodiments, in which the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained by those skilled in the art without inventive effort:
FIG. 1 is a schematic diagram of a prior art small scale wind farm visualization;
FIG. 2 is a flowchart of a method for extracting information of a grid-type wind farm according to a preferred embodiment of the present invention;
FIG. 3 is a diagram of a grid framework construction of a method for extracting information of a grid-type wind field according to a preferred embodiment of the present invention;
FIG. 4 is a schematic diagram showing a matching score calculation of a pair of rectangular grid arrays with a length N and a width M according to a grid wind field information extraction method according to a preferred embodiment of the present invention;
FIG. 5 is a schematic diagram showing the calculation of matching scores of mode pairs with the same arbitrary shape, generalized to the method for extracting information of a gridded wind field according to the preferred embodiment of the present invention;
FIG. 6 is a flowchart of a method for extracting information of a grid-type wind farm according to a preferred embodiment of the present invention;
FIG. 7 is a schematic diagram of a method for extracting information of a grid-type wind farm according to a preferred embodiment of the present invention;
FIG. 8 is a flowchart of a grid-like wind farm information extraction method according to a preferred embodiment of the present invention;
FIG. 9 is a diagram showing two principle of application of the method for extracting information of a grid-type wind field according to the preferred embodiment of the present invention;
FIG. 10 is a schematic block diagram of a gridding wind farm information extraction system according to a preferred embodiment of the present invention;
FIG. 11 is a schematic block diagram of an application of the grid-type wind farm information extraction system according to the preferred embodiment of the present invention;
FIG. 12 is a block diagram of two principle applications of the grid-type wind farm information extraction system according to the preferred embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the following description will be made in detail with reference to the technical solutions in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by a person skilled in the art without any inventive effort, are intended to be within the scope of the present invention, based on the embodiments of the present invention.
The method for extracting information of a grid-type wind field according to the preferred embodiment of the present invention, as shown in fig. 2, and referring to fig. 3 to 5, comprises the following steps:
s01: the wind power data and the air pollution data collected in the selected area are respectively gridded and filled by a set spatial interpolation algorithm to form a wind field and a pollution field which are closely spread in space, and the wind field and the pollution field share a set of grid frames and are overlapped;
as shown in fig. 3, in the sensing system in one area, the positions of the collected wind power data (wind speed and wind direction) and the pollution data, which are subject to the installation of the sensors, are not fully covered in space, so that grid filling is required by a certain spatial interpolation algorithm, a wind field and a pollution field which are closely spread in space are formed, and the two parts share the same grid frame and are overlapped;
s02: defining a plurality of adjacent grids in the grid framework to form a mode, and calculating a matching score between the two modes which can be completely overlapped in shape only through translation;
the wind field information of each unit is represented by a vector (x, y), the vector length representing the wind speed and the vector direction representing the wind direction.
Defining several adjacent grids to form a 'pattern', and calculating 'matching score' between patterns of the same shape (the shapes can be completely overlapped only by translation), wherein the matching score is used for measuring the similarity of the two patterns on wind direction characteristics.
The matching score calculation for both modes, similar to convolution or correlation operations in image processing, is essentially an average of the normalized inner products of vectors within all corresponding grid cells for both modes of the same shape. The interval of the match score is [ -1,1], the closer to 1, the more similar the two patterns are explained.
Fig. 4 shows the calculation of the matching score of a pair of rectangular grid arrays with length N and width M, and the calculation method is practically generalized to any pattern pair with the same shape. Generally, the calculation method is as shown in fig. 5:
the matching score calculation may use the formula:
wherein K is the number of grids contained in each of the two patterns with the same shape, the wind field information of each unit is represented by a vector (x, y), the matching score is represented by a matching score, the wind field vector of the ith grid of pattern 1 is (xi, 1, yi, 1), and the wind field vector of the ith grid of pattern 2 is (xi, 2, yi, 2); the interval of the matching score is [ -1,1], the closer to 1, the more similar the two patterns are in terms of wind direction characteristics.
The invention provides a calculation expression for describing the representativeness of a wind field mode (rather than a single place) of a space area, which can be used for evaluating and describing a typical air duct and describing the dominant wind direction of a specific place, and solves the problem that the effective extraction and expression of small-scale gridding wind field information are difficult at present.
According to the obtained grid framework and the matching score, the following two application modes are available:
application one: as shown in fig. 6 and 7, the transmission channel representativeness calculation:
s031: selecting a set of regional grid formation patterns between the target site and the potential source of pollution; calculating a matching score time sequence of the pattern and the selected grid composition pattern in the [ T1, T2] time period; obtaining the distribution and the duty ratio of a high matching score typical period according to the matching score time sequence;
a set of regional grids is selected to form a pattern between the target site (five-pointed star) and the potential source of contamination (triangle). A wind field pattern is observed at a certain time, and the presence of the pattern is judged as typical. I.e. calculate a time series of matching scores for the pattern with the selected grid formation pattern over a period of time T1, T2. After the time series is obtained, the distribution and the duty ratio of the typical period of the high matching score can be obtained; for example, to calculate the representativeness of northeast wind patterns in the region during [ T1, T2], all grids in the patterns can be assigned (-1, -1), characterizing northeast wind characteristics, and calculating matching scores for each moment in time during [ T1, T2] with the actual observed microscopic wind pattern; further, a time period with a matching score higher than 0.9 is intercepted in the [ T1, T2] time period, and is taken as a time period of typical northeast wind influence. .
And (2) application II: as shown in fig. 8 and 9, dominant wind direction feature calculation:
setting a mode with a positive direction and a length of 1 in all grid cell vectors in the grid framework as a given mode; calculating the matching score of the target place and the mode of the azimuth corresponding to the given mode, and solving the average value of the matching score in a set time period to obtain the dominant wind direction characteristics of eight azimuth of the target place;
all the grid cell vectors meet a given mode with positive directions (east, south, west, north, southeast, northeast, southwest and northwest) and length of 1, match scores of modes of the target site and the corresponding directions of the given mode are calculated, an average value of the scores in a period of time is obtained, and the dominant wind direction characteristics of eight directions of the target site (five-pointed star) can be obtained.
The wind direction characteristics of the eight directions are the dominant wind direction characteristics of the eight directions, the wind direction characteristics of the eight directions corresponding to the adjacent areas and the influence of the wind directions on the target position are reflected, but the wind direction characteristics of the target position are not the wind direction characteristics of the target position, and the wind direction characteristics may be obviously different in small space scale; the method describes microscopic wind direction characteristics of adjacent areas of all directions of the target site, and is helpful for more finely describing regional weather information.
The gridding wind field information extraction system is applied to the gridding wind field information extraction method as described above, and as shown in fig. 10, comprises a data acquisition unit 1, a grid frame generation unit 2 and a matching score calculation unit 3;
the data acquisition unit 1 acquires wind power data and air pollution data in a selected area;
the grid frame generating unit 2 is used for respectively carrying out grid filling on the collected wind power data and the air pollution data through a set spatial interpolation algorithm to form a wind field and a pollution field which are closely paved in space, and the wind field and the pollution field share one set of grid frame and are overlapped;
a matching score calculating unit 3 for defining a pattern formed by a plurality of adjacent grids in the grid frame and calculating a matching score between two patterns which can be completely overlapped in shape by only translation;
in a sensing system in one area, the positions of the collected wind power data (wind speed and wind direction) and pollution data, which are subjected to sensor installation, are not fully covered in space, so that grid filling is needed through a certain spatial interpolation algorithm, and a space-closely-paved wind field and a pollution field are formed, and the wind field and the pollution field share the same grid framework and are overlapped;
the wind field information of each unit is represented by a vector (x, y), the vector length representing the wind speed and the vector direction representing the wind direction.
Defining several adjacent grids to form a 'pattern', and calculating 'matching score' between patterns of the same shape (the shapes can be completely overlapped only by translation), wherein the matching score is used for measuring the similarity of the two patterns on wind direction characteristics.
The matching score calculation for both modes, similar to convolution or correlation operations in image processing, is essentially an average of the normalized inner products of vectors within all corresponding grid cells for both modes of the same shape. The interval of the match score is [ -1,1], the closer to 1, the more similar the two patterns are explained.
The matching score calculation may use the formula:
wherein K is the number of grids contained in each of the two patterns with the same shape, the wind field information of each unit is represented by a vector (x, y), the matching score is represented by a matching score, the wind field vector of the ith grid of pattern 1 is (xi, 1, yi, 1), and the wind field vector of the ith grid of pattern 2 is (xi, 2, yi, 2); the interval of the matching score is [ -1,1], the closer to 1, the more similar the two patterns are in terms of wind direction characteristics.
The invention provides a calculation expression for describing the representativeness of a wind field mode (rather than a single place) of a space area, which can be used for evaluating and describing a typical air duct and describing the dominant wind direction of a specific place, and solves the problem that the effective extraction and expression of small-scale gridding wind field information are difficult at present.
Application one: referring also to fig. 7 as shown in fig. 11, the system further includes a transmission channel representativeness calculation unit 4;
the transmission channel representativeness calculating unit 4 selects a set of regional mesh constituent patterns between the target site and the potential pollution source, calculates a matching score time series of the pattern and the selected mesh constituent patterns in [ T1, T2] time periods, and obtains the distribution and the duty ratio of the representative period of the high matching score according to the matching score time series.
A set of regional grids is selected to form a pattern between the target site (five-pointed star) and the potential source of contamination (triangle). A wind field pattern is observed at a certain time, and the presence of the pattern is judged as typical. I.e. calculate a time series of matching scores for the pattern with the selected grid formation pattern over a period of time T1, T2. After this time series is obtained, the distribution and duty cycle of the typical period of high matching score can be obtained.
And (2) application II: referring also to fig. 9 as shown in fig. 12, the system further comprises a dominant wind direction feature calculation unit 5;
a dominant wind direction feature calculation unit that sets a pattern having a positive satisfying direction and a length of 1 among all grid cell vectors in the grid frame as a given pattern; and calculating the matching score of the target place and the mode of the azimuth corresponding to the given mode, and solving the average value of the matching score in a set time period to obtain the dominant wind direction characteristics of the eight azimuth of the target place.
All the grid cell vectors meet a given mode with positive directions (east, south, west, north, southeast, northeast, southwest and northwest) and length of 1, match scores of modes of the target site and the corresponding directions of the given mode are calculated, an average value of the scores in a period of time is obtained, and the dominant wind direction characteristics of eight directions of the target site (five-pointed star) can be obtained.
In distinction to the wind rose, the dominant wind direction features of the eight directions, which correspond to the wind direction features of the adjacent areas and the influence of these directions on the target location, rather than the wind direction features of the target location itself, may differ significantly on a small spatial scale
A gridding wind field information extraction terminal comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the steps of the method are realized when the processor executes the computer program.
A computer readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the steps of the method as described above.
It will be understood that modifications and variations will be apparent to those skilled in the art from the foregoing description, and it is intended that all such modifications and variations be included within the scope of the following claims.
Claims (10)
1. The gridding wind field information extraction method is characterized by comprising the following steps of:
the wind power data and the air pollution data collected in the selected area are respectively gridded and filled by a set spatial interpolation algorithm to form a wind field and a pollution field which are closely spread in space, and the wind field and the pollution field share a set of grid frames and are overlapped;
a number of adjacent grids in the grid framework are defined to form a pattern and a matching score is calculated between the two patterns which can be completely coincident in shape by only translation.
2. The method for extracting information from a meshed wind field according to claim 1, wherein the matching score is calculated by using the formula:
wherein K is the number of grids contained in each of the two patterns with the same shape, the wind field information of each unit is represented by a vector (x, y), the matching score is represented by a matching score, the wind field vector of the ith grid of pattern 1 is (xi, 1, yi, 1), and the wind field vector of the ith grid of pattern 2 is (xi, 2, yi, 2); the interval of the matching score is [ -1,1], the closer to 1, the more similar the two patterns are in terms of wind direction characteristics.
3. The gridding wind farm information extraction method according to claim 1 or 2, wherein the method further comprises the steps of:
transmission channel representativeness calculation:
selecting a set of regional grid formation patterns between the target site and the potential source of pollution;
calculating a matching score time sequence of the pattern and the selected grid composition pattern in the [ T1, T2] time period;
the distribution and duty cycle of the typical period of high match score is obtained from the match score time series.
4. The gridding wind farm information extraction method according to claim 1 or 2, wherein the method further comprises the steps of:
and (3) calculating dominant wind direction characteristics:
setting a mode with a positive direction and a length of 1 in all grid cell vectors in the grid framework as a given mode;
and calculating the matching score of the target place and the mode of the azimuth corresponding to the given mode, and solving the average value of the matching score in a set time period to obtain the dominant wind direction characteristics of the eight azimuth of the target place.
5. A gridding wind field information extraction system applied to the gridding wind field information extraction method according to any one of claims 1 to 4, characterized by comprising a data acquisition unit, a grid frame generation unit and a matching score calculation unit;
the data acquisition unit acquires wind power data and air pollution data in a selected area;
the grid frame generating unit is used for respectively carrying out grid filling on the collected wind power data and the air pollution data through a set spatial interpolation algorithm to form a wind field and a pollution field which are closely paved in space, and the wind field and the pollution field share one set of grid frame and are overlapped;
the matching score calculating unit defines a mode formed by a plurality of adjacent grids in the grid framework, and calculates a matching score between the two modes which can be completely overlapped in shape only through translation.
6. The gridding wind farm information extraction system according to claim 5, wherein the matching score calculation unit performs matching score calculation using the formula:
wherein K is the number of grids contained in each of the two patterns with the same shape, the wind field information of each unit is represented by a vector (x, y), the matching score is represented by a matching score, the wind field vector of the ith grid of pattern 1 is (xi, 1, yi, 1), and the wind field vector of the ith grid of pattern 2 is (xi, 2, yi, 2); the interval of the matching score is [ -1,1], the closer to 1, the more similar the two patterns are in terms of wind direction characteristics.
7. The gridding wind farm information extraction system according to claim 5 or 6, further comprising a transmission channel representativeness calculation unit;
the transmission channel representativeness calculating unit selects a group of regional grid formation modes between a target site and a potential pollution source, calculates a matching score time sequence of the mode and the selected grid formation mode in the [ T1, T2] time period, and obtains the distribution and the duty ratio of a high matching score representativeness period according to the matching score time sequence.
8. The gridding wind farm information extraction system according to claim 5 or 6, further comprising a dominant wind direction feature calculation unit;
the dominant wind direction characteristic calculation unit sets a mode with a positive satisfying direction and a length of 1 in all grid cell vectors in the grid framework as a given mode; and calculating the matching score of the target place and the mode of the azimuth corresponding to the given mode, and solving the average value of the matching score in a set time period to obtain the dominant wind direction characteristics of the eight azimuth of the target place.
9. A gridded wind farm information extraction terminal comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method according to any of claims 1 to 4 when the computer program is executed.
10. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any one of claims 1 to 4.
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