CN114117316A - Dynamic wind zone drawing method and system based on multiple data sources - Google Patents
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Abstract
The invention provides a dynamic wind zone drawing method and system based on multiple data sources, wherein a wind speed prediction parameter value is calculated according to historical wind speed data; storing meteorological observation data to form a data set; updating the current wind speed related parameters in real time according to meteorological observation data; predicting the wind speed by using a dynamic prediction model according to the updated current wind speed related parameter, based on a wind speed prediction parameter value and in combination with the size of the data set; and drawing a typhoon influence area according to the predicted wind speed, and marking downburst in the area where the downburst has occurred once to form a wind area thematic map. The method and the device can realize the synchronous update of the manufacturing of the wind zone thematic map and the current production condition, improve the timeliness and the accuracy of drawing the wind zone thematic map, reduce the manual calculation process, improve the efficiency and reduce the cost.
Description
Technical Field
The invention belongs to the technical field of drawing of wind zone thematic maps, and particularly relates to a dynamic wind zone drawing method and system based on multiple data sources.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
Typhoon, tornado and other severe weather frequently occur, which causes serious damage to power transmission equipment and threatens the safe operation of a power grid. Therefore, it is very important to make wind prevention and disaster reduction work well, improve the capability of resisting various disasters and ensure the efficient, stable and safe operation of the power system. In order to effectively prevent various disasters, various regional disaster early warning thematic maps are required in power grid planning, damage to a specific region possibly caused by extreme weather is predicted by making a wind region thematic map, and wind prevention and disaster reduction work in the power field can be effectively carried out.
The traditional wind district thematic map drawing mode is based on a statistical theory, the annual maximum wind speed is counted by means of the historical wind speed records provided by the meteorological monitoring stations, the effective wind speed is calculated by means of the actual monitoring conditions of the monitoring stations, the data are the only data sources, and then the predicted wind speed of each meteorological station is calculated by means of a set complex mathematical model.
To the inventors' knowledge, this approach suffers from the following disadvantages: 1. due to the complexity of the model, a common parameter table needs to be inquired, but the table can only provide a few fixed discrete values, the numerical accuracy is low, and the level of operators is not uniform, so that the calculation result is easy to deviate. 2. For convenience, some monitoring stations limit original data of predicted wind speed to last ten years to twenty years, and ignore earlier data, so that data recorded in the past year is difficult to reflect in actual production, and meanwhile, data in different regions are difficult to form a unified calculation standard. 3. Limited by technical conditions, the time for making a new thematic map of a wind area is long, the mapping period is generally about one year, and the requirement on the professional level of technicians is high, so that the updating speed of the thematic map lags behind the current production situation.
Disclosure of Invention
The invention aims to solve the problems and provides a dynamic wind zone drawing method and system based on multiple data sources.
According to some embodiments, the invention adopts the following technical scheme:
a dynamic wind zone drawing method based on multiple data sources comprises the following steps:
calculating a wind speed prediction parameter value according to historical wind speed data;
storing meteorological observation data to form a data set;
updating the current wind speed related parameters in real time according to meteorological observation data;
predicting the wind speed by using a dynamic prediction model according to the updated current wind speed related parameter, based on a wind speed prediction parameter value and in combination with the size of the data set;
and drawing a typhoon influence area according to the predicted wind speed, and marking downburst in the area where the downburst has occurred once to form a wind area thematic map.
As an alternative embodiment, the specific process of calculating the wind speed prediction parameter value comprises the following steps: wind speed prediction parameter value C1、C2The calculation formula of (2) is as follows:
wherein: n is the number of years the wind speed data set contains,
is the mean value of zi;
in an alternative embodiment, when storing the meteorological observation data, the data observed by the meteorological station is stored as key value pairs, and the non-standard data is standardized.
As a further limited embodiment, the process of normalizing the unnormalized data includes:
wherein: v is the wind speed, z is the actual height of the anemometer, vzIs the observed wind speed of the anemometer, and alpha is the regional roughness index.
As an alternative embodiment, the current wind speed related parameter comprises a wind speed value and maximum wind speed data.
As an alternative embodiment, when the wind speed is predicted by using the dynamic prediction model, the wind speed prediction is not performed on the area where the downburst has occurred;
for other areas, with observation stations, acquiring the data observation period of an observation point where each observation station is located, the longitude and latitude of the observation point and the historical maximum wind speed, and predicting according to the historical maximum wind speed; calculating the predicted wind speed by using an inverse distance weighted average algorithm without an observation station;
after the predicted wind speeds of all the longitude and latitude areas are obtained, the same and adjacent wind speed points are connected into an equal wind speed line and marked on a map.
As an alternative embodiment, when the wind speed is predicted by using a dynamic prediction model, acquiring data of a strong wind tower falling event in the electric power data, including a line name, a tower serial number and the wind speed when falling the tower, converting the line and tower information into tower longitude and latitude information, acquiring three-dimensional information of longitude, latitude and wind speed, and drawing a strong wind tower falling mark on a corresponding longitude and latitude position on a static map;
or comparing the three-dimensional information with the predicted wind speed acquired before the latitude and longitude, and if the inverted tower wind speed is less than the regional prediction maximum value, marking the inverted tower position on the thematic map without modifying the predicted wind speed; and if the wind speed of the inverted tower is greater than the regional prediction maximum value, marking the position of the inverted tower, and modifying the predicted maximum wind speed according to the wind speed data of the position of the inverted tower.
As an alternative implementation, when the wind speed is predicted by using the dynamic prediction model, the extreme value I-shaped distribution function is used as the probability model, and the relevant parameters of the model are dynamically adjusted according to the actual situation; when the data set is larger than the set size, n-1 degrees of freedom are adopted, otherwise, n degrees of freedom are used.
A dynamic wind zone rendering system based on multiple data sources, comprising:
a parameter calculation module configured to calculate a wind speed prediction parameter value from the historical wind speed data;
the observation data acquisition module is configured to store meteorological observation data to form a data set;
the parameter updating module is configured to update the current wind speed related parameter in real time according to meteorological observation data;
the dynamic prediction module is configured to predict the wind speed by using the dynamic prediction model according to the updated related parameters of the current wind speed, based on the wind speed prediction parameter values and in combination with the size of the data set;
and the dynamic drawing module is configured to draw a typhoon influence area according to the predicted wind speed, and mark a downburst area in which the downburst area occurs to form a blast area thematic map.
A computer readable storage medium storing computer instructions which, when executed by a processor, perform the steps of the above method.
An electronic device comprising a memory and a processor and computer instructions stored on the memory and executed on the processor, the computer instructions, when executed by the processor, performing the steps of the above method.
Compared with the prior art, the invention has the beneficial effects that:
the method can update data in real time, display the latest prediction result, provide more accurate theoretical basis and data support for the power department to do windproof and disaster reduction work, and has the advantages of high drawing speed, high data accuracy and timely update.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
FIG. 1 is a schematic flow diagram of at least one embodiment.
The specific implementation mode is as follows:
the invention is further described with reference to the following figures and examples.
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The first embodiment is as follows:
as shown in fig. 1, a dynamic wind zone rendering method based on multiple data sources utilizes multiple information channels and dynamic presentation to implement the rendering of a wind zone, the multiple information channels utilize multiple data such as historical data and meteorological data and automatically complete computation, and the dynamic means that the data sources are more diverse, the data models are more flexible to use, and the results are updated at any time.
The method specifically comprises the following steps:
firstly, automatically calculating the future wind speed
(1) And automatically calculating a basic wind speed prediction parameter value. When calculating the basic wind speed prediction data, the present embodiment does not use the traditional calculation method, i.e. referring to a single and fixed parameter table to obtain the main parameters C1 and C2, but uses a program to automatically calculate the obtained parameters according to the data situation.
Taking the calculation method of the basic wind as an example, the traditional thematic map drawing needs a plotter to select corresponding parameters C1 and C2 according to the number of years of wind speed records in the meteorological station (i.e. the n value in the following table), then estimate the reproduction period parameter (i.e. the T value in the following table) and bring the parameters into a calculation formula:
however, because the precision of the table is limited, the parameters can only be accurate to 5 bits after the decimal point, and errors are easy to occur in the calculation result.
The embodiment adopts automatic calculation, can update relevant parameters in real time, and has digital precision above 11 decimal points, so that interference factors of data calculation can be eliminated, and data results are more stable. Meanwhile, the parameters of C1 and C2 can be calculated in real time, and the concrete formula groups are as follows:
the formula for calculating the parameter z in the above formula is:
where n is the number of years the wind speed data set contains.
(2) And establishing unified management data of the data warehouse. The calculation of the traditional thematic map needs long-term and continuous observation data, the time consumption is long, the efficiency is low, the discrete data appearing in the past year or the latest data just obtained can be accessed into the probability model in real time based on the thought of 'big data', the calculation can be carried out according to a set statistical strategy, all effective data in a database of the meteorological monitoring station in each region can be fully utilized by the meteorological monitoring station in each region, the latest data set can be obtained in time along with the real-time data modification, the accuracy of data calculation is ensured, and future wind speed prediction is effectively carried out.
By adopting the MongoDB, data observed by the meteorological station can be stored as key value pairs, the mode is more flexible, the difficult situation that the traditional sql database stores nonstandard data can be avoided, especially the factors influencing the thematic map of a wind area are complex due to the fact that the source of the current wind speed data is not uniform, and the adaptability is stronger in an actual scene, and the following formula is used for uniformly calculating the nonstandard data:
wherein: v is the wind speed, z is the actual height of the anemometer, vzFor the observed wind speed of the anemometer, α is the roughness index of the open platform area, which is 0.15 in this embodiment.
Secondly, realizing dynamic update of wind speed prediction data
1. Specific updating method and flow
(1) New data redrawing method
The data of the method mainly come from meteorological monitoring departments at various places, and reference meteorological data provided by power departments are rarely used. Data provided by meteorological departments are divided into three categories: basic wind, typhoon and downburst, wherein the process of analyzing and predicting the wind speed of the basic wind is mainly explained.
Processing downburst data: the invention can access and process the data of time, position, wind speed, hazard and the like of the occurrence of downburst. Due to the particularity of the meteorological features of downburst, the meteorological department is difficult to provide accurate wind speed, mark wind speed, damage and the like when downburst occurs, and can directly mark on a map.
Processing typhoon data: under the restriction of factors such as technology, the difficulty of separating specific typhoon data is high when typhoon crosses the boundary, and the acquisition of the typhoon data is a key of drawing, which needs to be provided by a meteorological department, and if the typhoon data does not exist, the acquisition difficulty is high.
Processing basic wind data: the method comprises the steps of firstly, acquiring the historical basic wind speed data of meteorological monitoring stations in each region, writing the data into a database, wherein the data is formed by recording the longitude and latitude of meteorological observation points and the obtained wind speed, and then inquiring by using the database to acquire the data observation period and the historical maximum wind speed of each observation point. Secondly, the program needs to consider the average reproduction period set by the user, for example, the period is 30 years, 50 years or 100 years, the setting of the period can be changed at any time according to the observation requirement of the user, and the reproduction period can influence the prediction period of the wind area map, such as '30-year-one-meeting'. The program automatically substitutes the data into the formula only by accessing the meteorological monitoring data in one area, thereby calculating the predicted value of the basic wind, and after the basic wind speed of the whole province is completely substituted into the formula, the three-dimensional data with longitude, latitude and wind speed can be obtained. And for longitude and latitude points of an area not covered by the observation station, the predicted wind speed in the whole province range can be calculated by using an inverse distance weighted average algorithm. And finally, after the predicted wind speeds of all the longitude and latitude points on the map are obtained, connecting the same and adjacent wind speed points into an equal wind speed line, recording the wind speed represented by the equal wind speed line, marking different colors on the area contained by the equal wind speed line according to the specified wind speed grade, and drawing the area on the bottom layer of the map.
(2) Method of supplementing data points
The supplemental data point method is used after the standard base map of the at least one static map is obtained using the new data redraw method. The supplement data point method mainly utilizes data of the power department, dynamically adjusts the data generated by the new data redrawing method, overcomes the defect that the new data redrawing method cannot dynamically present the business requirements of the power department on wind speed prediction, and focuses on the phenomenon of tower collapse due to strong wind of the power transmission line.
Generally, the tower is inverted because the local and then instant wind speed is greater than the predicted maximum wind speed, and is mainly the predicted maximum wind speed greater than the design life, for example, a tower with a design service life of ten years is designed, the design requirement is to resist the strong wind of '30 year meeting', the actual inverted instantaneous wind speed reaches the level of '200 year meeting', but the factors of construction level, illegal use, artificial damage and the like are not excluded, so that the instantaneous wind speed during tower inversion is probably lower than the predicted wind speed.
The power department needs to input data of a strong wind tower falling event into a database, the main contents of the data comprise a line name, a tower serial number, wind speed during tower falling and the like, information of the line and the tower is converted into longitude and latitude information of the tower by inquiring an information database of the transmission tower, then three-dimensional information of longitude, latitude and wind speed is acquired, and a strong wind tower falling mark is drawn on a corresponding longitude and latitude position on a static map. In addition, by comparing the three-dimensional information with the predicted wind speed acquired before the latitude and longitude, whether the tower-falling wind speed is greater than the regional prediction maximum can be analyzed: if the wind speed of the inverted tower is less than the regional prediction maximum value, the inverted tower is probably not because the wind speed is high, and only the inverted tower position needs to be marked on the thematic map without modifying the predicted wind speed; if the wind speed of the inverted tower is greater than the regional prediction maximum value, the inverted tower is probably because the design wind speed is lower than the actual wind speed, the position of the inverted tower needs to be marked, and the predicted maximum wind speed graph needs to be modified in the following way:
and inquiring the area near the tower position of the inverted tower, such as a meteorological station within a radius of 100 kilometers, and acquiring the maximum predicted wind speed value acquired by the meteorological station through a new data redrawing method. And then, inserting the wind speed data of the tower falling position as a 'maximum wind speed predicted value of a tower falling area' into the longitude and latitude position of the tower on the map, wherein a certain wind speed value can be measured by using the tower falling province. And calculating wind speed prediction data of areas which are not covered by monitoring stations around the tower and the nearby meteorological stations and new predicted wind speeds in the whole area by using an inverse distance weighted average algorithm. And finally, re-connecting the new predicted wind speed points according to the existing equal wind speed line levels on the map, and drawing the equal wind speed line. If the new wind speed is higher than the area of the original map, it can be overlaid with a higher level of color.
2. Advantages of the invention
(1) The data sources are dynamic. The calculation data is not only provided by the meteorological department alone, but also multi-channel data acquisition from the meteorological department and the electric power department is realized. On one hand, a meteorological department can dynamically provide monitoring data, and then the data are divided into three types of conventional wind, typhoon and downburst according to meteorological types; the method is divided into county and district level, village and town level and the like according to the weather station level. On the other hand, the power department can monitor relevant data through own meteorological monitoring equipment and access the model for calculation. The data mainly monitored by the power department is the maximum wind speed of the power transmission line in the area with the tower falling after the wind disaster occurs, the data plays a vital role in predicting the wind disaster, the local wind area grade can be predicted through the maximum wind speed of the area with the tower falling in the strong wind, the local wind area grade is generally not lower than the maximum wind speed of the area with the tower falling in the strong wind, meanwhile, the maximum wind speed of the area with the tower falling in the strong wind can be recorded in the local maximum wind speed data set, parameters of the whole model are influenced, and therefore future wind speed prediction is influenced.
(2) The mathematical model is dynamic. Typhoon and downburst are common disastrous winds but have complex causes, and the wind speed is calculated by using more mathematical models, so that the wind speed is difficult to predict, particularly the downburst. The embodiment can mark downburst on a thematic map of an area where the downburst has occurred, and specific wind speed can not be predicted.
Taking the prediction of the normal wind (also called the fundamental wind) as an example, the wind speed calculation uses an extreme value type I distribution function f (x) ═ exp { -exp [ - α (x-u) ] } as a probability model.
The corresponding predicted wind speed is calculated using the following set of equations:
wherein Xr is the predicted wind speed, T is the mean reproduction period of the maximum value, α is the scale function of the distribution of the gunn-bell probability distribution model (i.e., extreme value I-type probability distribution), S is the sample mean square error of the finite samples (here, the historical wind speed data set), the parameter meanings of α in the whole text are consistent, and C is1And C2The parameters are obtained from the above mentioned formula, and n refers to the number of years of observation data.
Meanwhile, the related data can be dynamically adjusted according to the actual situation. For example, when calculating the standard deviation of a data set, n-1 degrees of freedom may be used when the number of data set samples is large, and n degrees of freedom may be used when the data set is small. In addition, since the accuracy of the establishment of the prediction model is related to the length of the observation year, for an observation station with a digital station establishment history of only ten years or even shorter, if the observation station wants to achieve the effect of long-term observation by using the observation data of limited years at hand, the calculation can be performed by using a k-fold data set.
(3) The resulting presentation is dynamic. Any change to the data set and the mathematical model affects the final wind zone thematic map, especially the change to the data set, and meanwhile, each region of meteorological station generates new data every day or even every hour, and some disaster accidents have the characteristic of irregular occurrence, which leads to the continuous change of the data of the wind zone thematic map. If the production cycle is as long as one year according to the traditional drawing method, the production cycle is difficult to be updated synchronously with the current actual production situation. By using the embodiment, data can be updated in real time, the latest prediction result can be displayed, and more accurate theoretical basis and data support can be provided for the power department to make wind-proof and disaster-reduction work.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like which do not require the inventive efforts of those skilled in the art are included in the spirit and principle of the present invention.
Claims (10)
1. A dynamic wind zone drawing method based on multiple data sources is characterized by comprising the following steps: the method comprises the following steps:
calculating a wind speed prediction parameter value according to historical wind speed data;
storing meteorological observation data to form a data set;
updating the current wind speed related parameters in real time according to meteorological observation data;
predicting the wind speed by using a dynamic prediction model according to the updated current wind speed related parameter, based on a wind speed prediction parameter value and in combination with the size of the data set;
and drawing a typhoon influence area according to the predicted wind speed, and marking downburst in the area where the downburst has occurred once to form a wind area thematic map.
2. The method for dynamic wind zone rendering based on multiple data sources as claimed in claim 1, wherein: the specific process for calculating the wind speed prediction parameter value comprises the following steps: wind speed prediction parameter value C1、C2The calculation formula of (2) is as follows:
wherein: n is the number of years the wind speed data set contains,
is the mean value of zi;
3. the method for dynamic wind zone rendering based on multiple data sources as claimed in claim 1, wherein: when the meteorological observation data are stored, the data observed by the meteorological station are stored as key value pairs, and the non-standard data are subjected to standardization processing;
or, the current wind speed related parameter includes a wind speed value and maximum wind speed data.
4. The method for rendering a dynamic wind zone based on multiple data sources as claimed in claim 3, wherein: the process of standardizing the non-standard data comprises the following steps:
wherein: v is the wind speed, z is the actual height of the anemometer, vzIs the observed wind speed of the anemometer, and alpha is the regional roughness index.
5. The method for dynamic wind zone rendering based on multiple data sources as claimed in claim 1, wherein: when the dynamic prediction model is used for predicting the wind speed, the wind speed prediction is not carried out on the area where the downburst occurs;
for other areas, with observation stations, acquiring the data observation period of an observation point where each observation station is located, the longitude and latitude of the observation point and the historical maximum wind speed, and predicting according to the historical maximum wind speed; calculating the predicted wind speed by using an inverse distance weighted average algorithm without an observation station;
after the predicted wind speeds of all the longitude and latitude areas are obtained, the same and adjacent wind speed points are connected into an equal wind speed line and marked on a map.
6. The method for dynamic wind zone rendering based on multiple data sources as claimed in claim 1, wherein:
when the wind speed is predicted by using the dynamic prediction model, acquiring data of a strong wind tower falling event in the power data, including a line name, a tower serial number and the wind speed when the tower falls, converting the line and tower information into tower longitude and latitude information, acquiring three-dimensional information of longitude, latitude and wind speed, and drawing a strong wind tower falling mark on a corresponding longitude and latitude position on a static map;
or comparing the three-dimensional information with the predicted wind speed acquired before the latitude and longitude, and if the inverted tower wind speed is less than the regional prediction maximum value, marking the inverted tower position on the thematic map without modifying the predicted wind speed; and if the wind speed of the inverted tower is greater than the regional prediction maximum value, marking the position of the inverted tower, and modifying the predicted maximum wind speed according to the wind speed data of the position of the inverted tower.
7. The method for dynamic wind zone rendering based on multiple data sources as claimed in claim 1, wherein: when the wind speed is predicted by using the dynamic prediction model, taking an extreme value I-shaped distribution function as a probability model, and dynamically adjusting relevant parameters of the model according to actual conditions; when the data set is larger than the set size, n-1 degrees of freedom are adopted, otherwise, n degrees of freedom are used.
8. A dynamic wind zone drawing system based on multiple data sources is characterized in that: the method comprises the following steps:
a parameter calculation module configured to calculate a wind speed prediction parameter value from the historical wind speed data;
the observation data acquisition module is configured to store meteorological observation data to form a data set;
the parameter updating module is configured to update the current wind speed related parameter in real time according to meteorological observation data;
the dynamic prediction module is configured to predict the wind speed by using the dynamic prediction model according to the updated related parameters of the current wind speed, based on the wind speed prediction parameter values and in combination with the size of the data set;
and the dynamic drawing module is configured to draw a typhoon influence area according to the predicted wind speed, and mark a downburst area in which the downburst area occurs to form a blast area thematic map.
9. A computer-readable storage medium characterized by: for storing computer instructions which, when executed by a processor, perform the steps of the method of any one of claims 1 to 7.
10. An electronic device, characterized by: comprising a memory and a processor and computer instructions stored on the memory and executed on the processor, which when executed by the processor, perform the steps of the method of any one of claims 1 to 7.
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