A power grid risk visualization method and system based on meteorological early warning

Abstract

The application discloses a power grid risk visualization method and system based on meteorological early warning, relates to the technical field of power grid risk, obtains meteorological data of each sub-region and meteorological early warning of a monitoring region in each high-risk time in the past in the monitoring region through a database, analyzes minimum early warning values and maximum early warning values of the meteorological data of each sub-region under different meteorological early warnings, obtains meteorological data of each sub-region in the monitoring region in the future one week, analyzes whether the power grid risk of the monitoring region in the future one week is high, obtains a risk monitoring region if the power grid risk of the monitoring region in the future one week is high, analyzes repair priorities of power grids of each sub-region in the risk monitoring region, simultaneously labels the risk monitoring region and the repair priorities of each sub-region in the risk monitoring region in a panoramic map of the monitoring region, and performs early warning, so that the influence of the power grid risk is effectively reduced, and the effectiveness of power grid risk analysis is ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power grid risk, in particular to a power grid risk visualization method and system based on meteorological warning. BACKGROUND

[0002] In recent years, global warming has led to a high incidence of extreme weather events, and disasters such as heavy rain, typhoons, high temperatures, and cold waves have occurred frequently, seriously threatening the safe and stable operation of the power grid. There is a close correlation between meteorological warnings and power grid risks, and changes in meteorological conditions will directly or indirectly affect the safe and stable operation of the power grid. Power grid risk management based on meteorological warnings has become an important means of disaster prevention and mitigation for power systems.

[0003] The traditional power grid risk visualization method and system analyze whether the power grid risk is too high according to the unified fixed value of each meteorological data after receiving the meteorological warning, and when the power grid risk is too high, each region with a high power grid risk is displayed on the terminal and a warning is given. Obviously, this power grid risk visualization method and system has the following shortcomings: 1. The traditional power grid risk visualization method and system analyze whether the power grid risk is too high according to the unified fixed value after receiving the meteorological warning, but in actual situations, the resistance of different regions of the power grid is different, so when using a unified fixed value to analyze whether the power grid risk of each region is too high, the effectiveness of the power grid risk analysis cannot be guaranteed.

[0004] 2. The traditional power grid risk visualization method and system only mark each region with a high power grid risk when visualizing the warning, and lack analysis and feedback of the repair priority of each region with a high power grid risk. When maintenance personnel receive feedback information to repair each region with a high power grid risk, the impact of the power grid risk cannot be effectively reduced. SUMMARY

[0005] In view of the above technical deficiencies, the purpose of the present application is to provide a power grid risk visualization method and system based on meteorological warning.

[0006] To solve the above technical problems, the present application adopts the following technical solutions: In a first aspect, the present application provides a power grid risk visualization method based on meteorological warning, comprising the following steps: S1, data acquisition: dividing the monitoring area into each sub-region according to the preset area threshold, and obtaining each meteorological data of each sub-region and the meteorological warning of the monitoring area from the database during each high risk of the power grid history.

[0007] S2, data analysis: obtaining the high-risk area of the power grid from the database at each time of the historical high-risk of the power grid, comparing the high-risk area of the power grid with each sub-area in each historical high-risk of the power grid, regarding each sub-area having an overlapping part with the high-risk area of the power grid as each risk sub-area, and clustering each risk sub-area to obtain a risk monitoring area, obtaining the risk monitoring area at each time of the historical high-risk of the power grid in this way, clustering the risk monitoring area at each time of the historical high-risk of the power grid to obtain a total risk monitoring area, comparing the total risk monitoring area with the monitoring area, and analyzing the minimum warning value and the maximum warning value of each meteorological data of each sub-area in the monitoring area under different meteorological warnings according to the comparison result.

[0008] S3, risk analysis: obtaining the meteorological warning report of the monitoring area in the future one week, and judging whether there is a meteorological warning in each sub-area in the monitoring area in the future one week, when there is no meteorological warning in the monitoring area in the future one week, it represents that the power grid risk of the monitoring area in the future one week is low, when there is a meteorological warning in the monitoring area, it is analyzed whether the power grid risk of each sub-area is too high, if the power grid risk of each sub-area is low, it represents that the power grid risk of the monitoring area in the future one week is low, if there is a sub-area with too high power grid risk, it represents that the power grid risk of the monitoring area in the future one week is too high, at this time, the risk monitoring area is obtained, the main power grid area is obtained from the database, and each sub-area in the risk monitoring area is compared with the main power grid area, each sub-area in the risk monitoring area having an overlapping part with the main power grid area is called each main sub-area, at the same time, the total number of power transmission users of the power grid of each sub-area in the risk monitoring area is obtained from the database, according to the total number of power transmission users of the power grid of each sub-area in the risk monitoring area and the main power grid area, the repair priority of the power grid of each sub-area in the risk monitoring area is obtained, and a visual warning is performed.

[0009] S4, visual warning: obtaining the panorama of the monitoring area, when the power grid risk of the monitoring area is too high, marking the risk monitoring area in the panorama of the monitoring area, and standardizing the repair priority of each sub-area in the risk monitoring area, feeding back the marked image, and performing a warning.

[0010] In the second aspect, the application provides a power grid risk visualization system based on meteorological warning, comprising the following modules: a data acquisition module for dividing the monitoring area into each sub-area according to a preset area threshold, and obtaining each meteorological data of each sub-area and the meteorological warning of the monitoring area at each time of the historical high-risk of the power grid from the database.

[0011] The data analysis module is used to obtain the high-risk areas of the power grid during each historical high-risk period from the database. In each historical high-risk period of the power grid, the high-risk areas of the power grid are compared with each sub-region. Sub-regions that overlap with the high-risk areas of the power grid are called risk sub-regions. The risk sub-regions are then clustered to obtain the risk monitoring areas. This method is used to obtain the risk monitoring areas during each historical high-risk period of the power grid. The risk monitoring areas during each historical high-risk period of the power grid are then clustered to obtain the total risk monitoring area. The total risk monitoring area is compared with the monitoring areas, and based on the comparison results, the minimum and maximum warning values ​​of each meteorological data under different meteorological warnings are analyzed for each sub-region within the monitoring area.

[0012] The risk analysis module is used to obtain meteorological warning reports for the monitoring area for the next week and determine whether there are meteorological warnings for each sub-area within the monitoring area for the next week. When there are no meteorological warnings for the monitoring area for the next week, it means that the power grid risk in the monitoring area is low for the next week. When there are meteorological warnings for the monitoring area, it analyzes whether the power grid risk of each sub-area is too high. If the power grid risk of each sub-area is low, it means that the power grid risk of the monitoring area for the next week is low. If there are sub-areas with excessive power grid risk, it means that the power grid risk of the monitoring area for the next week is too high. At this time, the risk monitoring area is obtained, and the main power grid area is obtained from the database. Each sub-area within the risk monitoring area is compared with the main power grid area. Sub-areas within the risk monitoring area that overlap with the main power grid area are called major sub-areas. At the same time, the total number of transmission users of each sub-area power grid within the risk monitoring area is obtained from the database. Based on the total number of transmission users of each sub-area power grid within the risk monitoring area and the main power grid area, the repair priority of each sub-area power grid within the risk monitoring area is obtained and analyzed, and a visual warning is provided.

[0013] The visualization and early warning module is used to obtain a panoramic view of the monitoring area. When the power grid risk in the monitoring area is too high, the risk monitoring area is marked on the panoramic view of the monitoring area, and the emergency repair priority of each sub-area within the risk monitoring area is marked. The marked image is then fed back, and an early warning is issued.

[0014] The database is used to store meteorological data for each sub-region during historical high-risk periods of the power grid, meteorological warnings for the monitored areas, high-risk areas of the power grid, standard numerical ranges for each meteorological data, geomorphological features of each sub-region, and the main power grid area.

[0015] The beneficial effects of this invention are as follows: 1. This invention provides a power grid risk visualization method and system based on meteorological early warning. By acquiring meteorological data of each sub-region during historical high-risk periods of the power grid within the monitoring area and meteorological early warnings of the monitoring area from the database, the minimum and maximum early warning values ​​of each meteorological data of each sub-region under different meteorological early warnings are analyzed. Meteorological data of each sub-region within the monitoring area for the next week are also acquired, and the power grid risk of the monitoring area for the next week is analyzed. If the power grid risk of the monitoring area for the next week is high, the risk monitoring area is acquired, and the emergency repair priority of each sub-region of the power grid within the risk monitoring area is analyzed. At the same time, the risk monitoring area and the emergency repair priority of each sub-region within the risk monitoring area are marked on the panoramic map of the monitoring area, and an early warning is issued. This effectively reduces the impact of power grid risk and ensures the effectiveness of power grid risk analysis.

[0016] This invention retrieves high-risk areas of the power grid during historical high-risk periods from a database. Within each historical high-risk period, the high-risk areas are compared with their sub-regions. Sub-regions overlapping with the high-risk areas are designated as risk sub-regions. These risk sub-regions are then clustered to obtain risk monitoring areas. This method is used to obtain risk monitoring areas during historical high-risk periods of the power grid. These risk monitoring areas are then clustered to obtain a total risk monitoring area. The total risk monitoring area is compared with the monitoring areas, and based on the comparison results, the minimum and maximum warning values ​​of meteorological data for each sub-region under different weather warnings are analyzed. Based on these minimum and maximum warning values, the power grid risk in the monitoring area is analyzed, ensuring the effectiveness of the power grid risk analysis.

[0017] When the power grid risk in a monitored area is too high, this invention retrieves the main power grid area from a database and compares each sub-region within the risk monitoring area with the main power grid area. Sub-regions within the risk monitoring area that overlap with the main power grid area are designated as major sub-regions. Simultaneously, the total number of transmission users in each sub-region of the risk monitoring area is retrieved from the database. Based on the total number of transmission users in each sub-region of the risk monitoring area and the main power grid area, the emergency repair priority of each sub-region of the risk monitoring area is obtained and analyzed. The risk monitoring area is then marked on the panoramic map of the monitoring area, and the emergency repair priority of each sub-region within the risk monitoring area is standardized, effectively reducing the impact of power grid risks. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the implementation steps of the method of the present invention.

[0020] Figure 2 This is a schematic diagram of the system structure connection of the present invention. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Please see Figure 1 As shown, the present invention provides a power grid risk visualization method based on meteorological early warning, including: S1, data acquisition: dividing the monitoring area into sub-regions according to a preset area threshold, and acquiring meteorological data of each sub-region and meteorological early warning of the monitoring area from the database during each high-risk period of the power grid in history.

[0023] It should be noted that the preset area threshold is a critical value used to determine whether the division of sub-regions is reasonable, and it is set by relevant staff.

[0024] It should also be noted that meteorological data includes rainfall, temperature, wind speed, and humidity.

[0025] Among them, meteorological warnings include yellow alerts for strong winds, orange alerts for strong winds, yellow alerts for high temperatures, and orange alerts for high temperatures.

[0026] S2. Data Analysis: Obtain the high-risk areas of the power grid during each historical high-risk period from the database. Compare the high-risk areas with their sub-regions during each historical high-risk period. Sub-regions that overlap with the high-risk areas of the power grid are called risk sub-regions. Cluster these risk sub-regions to obtain the risk monitoring areas. Use this method to obtain the risk monitoring areas during each historical high-risk period of the power grid. Cluster these risk monitoring areas to obtain the total risk monitoring area. Compare the total risk monitoring area with the monitoring areas, and analyze the minimum and maximum warning values ​​of various meteorological data for each sub-region under different meteorological warnings based on the comparison results.

[0027] It should be noted that when the values ​​of all meteorological data are within the standard range, no weather warning will be issued. A weather warning will be issued when the value of a certain meteorological data is less than the minimum value of the standard range or greater than the maximum value of the standard range. Therefore, each meteorological data has a minimum warning value and a maximum warning value.

[0028] In a specific embodiment, the analysis of the minimum and maximum warning values ​​of meteorological data for each sub-region under different meteorological warnings within the monitoring area is carried out as follows: The meteorological warnings of the monitoring area are used as the meteorological warnings for each sub-region. When the comparison result shows that the total risk monitoring area is the same as the monitoring area, the minimum and maximum warning values ​​of meteorological data for each sub-region under different meteorological warnings within the total risk monitoring area are analyzed based on the meteorological data and meteorological warnings of each sub-region within the risk monitoring area during each historical high-risk period of the power grid. When the comparison result shows that the total risk monitoring area is smaller than the monitoring area, each sub-region not within the total risk monitoring area is referred to as a secondary marked sub-region. Based on the minimum and maximum warning values ​​of meteorological data for each sub-region under different meteorological warnings within the total risk monitoring area, the minimum and maximum warning values ​​of meteorological data for each secondary sub-region under different meteorological warnings are analyzed. This method is used to analyze the minimum and maximum warning values ​​of meteorological data for each sub-region under different meteorological warnings.

[0029] The above-mentioned analysis of the minimum and maximum warning values ​​of meteorological data for each sub-region under different meteorological warnings within the total risk monitoring area is carried out as follows: Each sub-region within the total risk monitoring area is referred to as a marked sub-region. Each marked sub-region is compared with the risk monitoring area during each historical high-risk period of the power grid. If a marked sub-region is within the risk monitoring area during a historical high-risk period of the power grid, then that historical high-risk period of the power grid is referred to as the marked historical high-risk period of that marked sub-region. The marked historical high-risk periods of each marked sub-region are obtained in this way.

[0030] In each marked sub-region, the historical high-risk weather warnings for each marker are obtained and compared. Markers with the same historical high-risk weather warnings are grouped into a power grid high-risk group. This method is used to obtain each power grid high-risk group in each marked sub-region.

[0031] In each power grid risk group within each marked sub-region, obtain the meteorological warning for the power grid risk group, as well as the lower and upper limits of each meteorological data within the marked sub-region. Compare the lower limits of each meteorological data, and the largest lower limit value among all meteorological data is called the minimum warning value for each meteorological data under the given meteorological warning. Compare the upper limits of each meteorological data, and the smallest upper limit value among all meteorological data is called the maximum warning value for each meteorological data under the given meteorological warning. Using this method, analyze the minimum and maximum warning values ​​of each meteorological data in each sub-region within the total risk monitoring area under different meteorological warnings.

[0032] The above process for obtaining the lower and upper limits of meteorological data within each marked sub-region is as follows: The standard value range of each meteorological data is obtained from the database. Within each power grid risk group of each marked sub-region, the values ​​of each meteorological data within the marked sub-region at historical high-risk times are obtained and compared with the standard value range of each meteorological data. Values ​​less than the minimum value of the standard value range are called lower limit values, and values ​​higher than the maximum value of the standard value range are called upper limit values. This method is used to obtain the lower and upper limits of each meteorological data within the marked sub-region.

[0033] The above-mentioned analysis of the minimum and maximum warning values ​​of meteorological data for each secondary sub-region under different weather warnings is specifically carried out as follows: The geomorphic features of each sub-region are obtained from the database. The geomorphic features of each marked sub-region are compared with the geomorphic features of each secondary marked sub-region. The marked sub-regions whose geomorphic features are identical to those of a certain secondary marked sub-region are called the marked regions of that secondary marked sub-region. The marked regions of each secondary marked region are obtained in this way, and the maximum lower limit and minimum upper limit values ​​of meteorological data for each secondary marked sub-region under different weather warnings are obtained.

[0034] It should be noted that the landform features include mountains, plateaus, hills, plains and basins, etc. GlobalMapper software is used to obtain the landform features of each sub-region and store them in the database.

[0035] It should also be noted that the method for obtaining the maximum lower limit and minimum upper limit of meteorological data for each secondary marked sub-region under different weather warnings is the same as the method for obtaining the maximum lower limit and minimum upper limit of meteorological data for each marked sub-region.

[0036] Obtain the minimum and maximum warning values ​​for each meteorological data point in each secondary-marked sub-region under different weather warnings. Calculate the average of the minimum and maximum warning values ​​for each meteorological data point under each weather warning. Also, obtain the maximum lower limit and minimum upper limit indicators for each meteorological data point in each secondary-marked sub-region under different weather warnings. If the maximum lower limit indicator for a certain meteorological data point in a secondary-marked sub-region under a certain weather warning is 1, then the minimum warning value for that meteorological data point in that secondary-marked sub-region under that weather warning is the maximum lower limit value for that meteorological data point in that secondary-marked sub-region under that weather warning. If the value is 0, then the minimum warning value of the meteorological data in the secondary-marked sub-region under the weather warning is the average of the minimum warning values ​​of the meteorological data under the weather warning. If the minimum upper limit value of a certain meteorological data in a certain secondary-marked sub-region under a certain weather warning is 1, then the maximum warning value of the meteorological data in the secondary-marked sub-region under the weather warning is the minimum upper limit value. If the minimum upper limit value of a certain meteorological data in a certain secondary-marked sub-region under a certain weather warning is 0, then the maximum warning value of the meteorological data in the secondary-marked sub-region under the weather warning is the average of the maximum warning values ​​of the meteorological data under the weather warning. This method is used to analyze the minimum and maximum warning values ​​of the meteorological data in each secondary sub-region under different weather warnings.

[0037] It should be noted that the maximum lower limit value of each meteorological data point is compared with the average of the minimum warning values ​​of that meteorological data point. If the maximum lower limit value of a certain meteorological data point is greater than the average of the minimum warning values ​​of that meteorological data point, then the usage index of the maximum lower limit value of that meteorological data point is 0. If the maximum lower limit value of a certain meteorological data point is less than the average of the minimum warning values ​​of that meteorological data point, then the usage index of the maximum lower limit value of that meteorological data point is 1. Similarly, the minimum upper limit value of each meteorological data point is compared with the average of the maximum warning values ​​of that meteorological data point. If the minimum upper limit value of a certain meteorological data point is greater than the average of the maximum warning values ​​of that meteorological data point, then the usage index of the maximum lower limit value of that meteorological data point is 1. If the minimum upper limit value of a certain meteorological data point is less than the average of the maximum warning values ​​of that meteorological data point, then the usage index of the maximum lower limit value of that meteorological data point is 0.

[0038] S3. Risk Analysis: Obtain meteorological warning reports for the monitoring area for the next week and determine whether there are meteorological warnings for each sub-area within the monitoring area for the next week. When there are no meteorological warnings for the monitoring area for the next week, it means that the power grid risk in the monitoring area is low for the next week. When there are meteorological warnings for the monitoring area, analyze whether the power grid risk of each sub-area is too high. If the power grid risk of each sub-area is low, it means that the power grid risk of the monitoring area for the next week is low. If there are sub-areas with excessive power grid risk, it means that the power grid risk of the monitoring area for the next week is too high. At this time, obtain the risk monitoring area and obtain the main power grid area from the database. Compare each sub-area within the risk monitoring area with the main power grid area. Sub-areas within the risk monitoring area that overlap with the main power grid area are called major sub-areas. At the same time, obtain the total number of transmission users of each sub-area power grid within the risk monitoring area from the database. Based on the total number of transmission users of each sub-area power grid within the risk monitoring area and the main power grid area, obtain and analyze the emergency repair priority of each sub-area power grid within the risk monitoring area, and provide visual warnings.

[0039] It should be noted that this method and system are connected to the meteorological forecasting system to obtain the meteorological warning report for the next week in the monitoring area from the meteorological forecasting system. The meteorological warning report includes the meteorological warning, meteorological data for each sub-area in the monitoring area for the next week, and the warning date.

[0040] It should also be noted that when a weather warning report shows a weather warning, it means that there will be a weather warning in the monitored area for the next week. If a weather warning report does not show a weather warning, it means that there will be no weather warning in the monitored area for the next week.

[0041] It should be noted that the transmission users of a sub-regional power grid refer to users connected to that sub-regional power grid, and the sub-regional power grid provides electricity to its transmission users.

[0042] It should also be noted that normalizing the total number of transmission users in each sub-region of the power grid within the risk monitoring area results in... In the formula Representing the risk monitoring area The main grid return value for each sub-regional power grid, when that sub-region is a primary sub-region. When the sub-region is not the primary sub-region , Representing the risk monitoring area The total number of transmission users in each sub-regional power grid. Representing the risk monitoring area Emergency repair priorities for individual regional power grids. This represents the number of each sub-region within the risk monitoring area. It is a positive integer.

[0043] In a specific embodiment, the process of analyzing whether the power grid risk of each sub-region is too high is as follows: Meteorological warnings for the monitored area are obtained, and the minimum and maximum warning values ​​of each meteorological data point for each sub-region under the given warning are obtained. Simultaneously, the date of the meteorological warning for each sub-region is obtained, and the values ​​of each meteorological data point for each sub-region on that date are analyzed. Based on the values ​​of each meteorological data point for each sub-region on that date and the minimum and maximum warning values ​​of each meteorological data point for each sub-region under the given warning, the power grid risk value of each sub-region is obtained. If the power grid risk value of a sub-region is 1, it indicates that the power grid risk of that sub-region is too high; if the power grid risk value of a sub-region is 0, it indicates that the power grid risk of that sub-region is low. This method is used to analyze whether the power grid risk of each sub-region is too high.

[0044] It should be noted that in each sub-region, the value of each meteorological data is compared with the minimum and maximum warning values ​​of each meteorological data. If there is a meteorological data with a value less than the minimum warning value or a value greater than the maximum warning value, the power grid risk value of that sub-region is 1. If the value of each meteorological data is less than the maximum warning value of each meteorological data and greater than the minimum warning value of each meteorological data, the power grid risk value of that sub-region is 0. The power grid risk value of each sub-region is obtained in this way.

[0045] S4. Visualized Early Warning: Obtain a panoramic view of the monitoring area. When the power grid risk in the monitoring area is too high, mark the risk monitoring area on the panoramic view of the monitoring area, and standardize the emergency repair priority of each sub-area within the risk monitoring area. Feedback the marked image and issue an early warning at the same time.

[0046] Please see Figure 2 As shown, the present invention provides a power grid risk visualization system based on meteorological early warning, including: a data acquisition module for dividing the monitoring area into sub-regions according to a preset area threshold, and acquiring meteorological data of each sub-region and meteorological early warning of the monitoring area from the database during each high-risk period of the power grid in history.

[0047] The data analysis module is used to obtain the high-risk areas of the power grid during each historical high-risk period from the database. In each historical high-risk period of the power grid, the high-risk areas of the power grid are compared with each sub-region. Sub-regions that overlap with the high-risk areas of the power grid are called risk sub-regions. The risk sub-regions are then clustered to obtain the risk monitoring areas. This method is used to obtain the risk monitoring areas during each historical high-risk period of the power grid. The risk monitoring areas during each historical high-risk period of the power grid are then clustered to obtain the total risk monitoring area. The total risk monitoring area is compared with the monitoring areas, and based on the comparison results, the minimum and maximum warning values ​​of each meteorological data under different meteorological warnings are analyzed for each sub-region within the monitoring area.

[0048] The risk analysis module is used to obtain meteorological warning reports for the monitoring area for the next week and determine whether there are meteorological warnings for each sub-area within the monitoring area for the next week. When there are no meteorological warnings for the monitoring area for the next week, it means that the power grid risk in the monitoring area is low for the next week. When there are meteorological warnings for the monitoring area, it analyzes whether the power grid risk of each sub-area is too high. If the power grid risk of each sub-area is low, it means that the power grid risk of the monitoring area for the next week is low. If there are sub-areas with excessive power grid risk, it means that the power grid risk of the monitoring area for the next week is too high. At this time, the risk monitoring area is obtained, and the main power grid area is obtained from the database. Each sub-area within the risk monitoring area is compared with the main power grid area. Sub-areas within the risk monitoring area that overlap with the main power grid area are called major sub-areas. At the same time, the total number of transmission users of each sub-area power grid within the risk monitoring area is obtained from the database. Based on the total number of transmission users of each sub-area power grid within the risk monitoring area and the main power grid area, the repair priority of each sub-area power grid within the risk monitoring area is obtained and analyzed, and a visual warning is provided.

[0049] The visualization and early warning module is used to obtain a panoramic view of the monitoring area. When the power grid risk in the monitoring area is too high, the risk monitoring area is marked on the panoramic view of the monitoring area, and the emergency repair priority of each sub-area power grid in the risk monitoring area is specified. The marked image is fed back and an early warning is issued at the same time.

[0050] The database is used to store meteorological data for each sub-region during historical high-risk periods of the power grid, meteorological warnings for the monitored areas, high-risk areas of the power grid, standard numerical ranges for each meteorological data, geomorphological features of each sub-region, and the main power grid area.

[0051] This invention retrieves meteorological data for each sub-region during historical high-risk periods of the power grid within a monitoring area from a database, along with meteorological warnings for the monitoring area. It analyzes the minimum and maximum warning values ​​for each sub-region under different meteorological warnings, and obtains meteorological data for each sub-region within the monitoring area for the next week. The analysis assesses whether the power grid risk in the monitoring area is high within the next week. If the power grid risk is high within the next week, a risk monitoring area is identified, and the emergency repair priority for each sub-region within the risk monitoring area is analyzed. Simultaneously, the risk monitoring area and the emergency repair priority for each sub-region within the risk monitoring area are marked on a panoramic map of the monitoring area, and warnings are issued. This effectively reduces the impact of power grid risks and ensures the effectiveness of power grid risk analysis.

[0052] The above description is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the protection scope of the present invention.

Claims

1. A method for power grid risk visualization based on weather warning, characterized in that, Comprising the following steps: S1, data acquisition: according to the preset area threshold, the monitoring area is divided into each sub-region, and the historical meteorological data of each sub-region and the meteorological warning of the monitoring area are obtained from the database; S2, data analysis: obtain the high-risk area of the power grid from the database in each high-risk period of the power grid history, compare the high-risk area of the power grid with each sub-region in each high-risk period of the power grid history, and call each sub-region that has an overlapping part with the high-risk area of the power grid as each risk sub-region. Cluster each risk sub-region to obtain a risk monitoring area. Obtain the risk monitoring area in each high-risk period of the power grid history by the above method, and cluster the risk monitoring area in each high-risk period of the power grid history to obtain a total risk monitoring area. Compare the total risk monitoring area with the monitoring area, and call the meteorological warning of the monitoring area as the meteorological warning of each sub-region. When the comparison result is that the total risk monitoring area is the same as the monitoring area, analyze the minimum warning value and the maximum warning value of each meteorological data of each sub-region in the total risk monitoring area under different meteorological warnings according to each meteorological data and the meteorological warning of each sub-region in the risk monitoring area in each high-risk period of the power grid history. When the comparison result is that the total risk monitoring area is smaller than the monitoring area, call each sub-region in the total risk monitoring area as each marked sub-region, and call each sub-region that is not in the total risk monitoring area as each secondary marked sub-region. Obtain the topographic features of each sub-region from the database, compare the topographic features of each marked sub-region with the topographic features of each secondary marked sub-region, and call each marked sub-region that has the same topographic features as a secondary marked sub-region as the marked area of the secondary marked sub-region. Obtain each marked area of each secondary marked sub-region by the above method, and obtain the maximum lower limit value and the minimum upper limit data of each meteorological data of each secondary marked sub-region under different meteorological warnings. Obtain the minimum warning value and the maximum warning value of each meteorological data of each marked area of each secondary marked sub-region under the meteorological warning under different meteorological warnings, calculate the average of the minimum warning value and the maximum warning value of each meteorological data under the meteorological warning, and obtain the maximum lower limit value usage index and the minimum upper limit data usage index of each meteorological data of each secondary marked sub-region under different meteorological warnings. If the maximum lower limit value usage index of a certain meteorological data of a certain secondary marked sub-region under a certain meteorological warning is 1, the minimum warning value of the meteorological data of the secondary marked sub-region under the meteorological warning is the maximum lower limit value of the meteorological data of the secondary marked sub-region under the meteorological warning. If the maximum lower limit value usage index of a certain meteorological data of a certain secondary marked sub-region under a certain meteorological warning is 0, the minimum warning value of the meteorological data of the secondary marked sub-region under the meteorological warning is the average of the minimum warning value of the meteorological data under the meteorological warning. If the minimum upper limit data usage index of a certain meteorological data of a certain secondary marked sub-region under a certain meteorological warning is 1, the maximum warning value of the meteorological data of the secondary marked sub-region under the meteorological warning is the minimum upper limit data. If the minimum upper limit data usage index of a certain meteorological data of a certain secondary marked sub-region under a certain meteorological warning is 0,The maximum warning value of the meteorological data under the meteorological warning of the secondary marking sub-region is the average value of the maximum warning value of the meteorological data under the meteorological warning, and the minimum warning value and the maximum warning value of each meteorological data under different meteorological warnings of each sub-region are analyzed in this way. S3, risk analysis: obtain the meteorological data of each sub-region in the monitoring area in the future one week, and analyze whether the power grid risk of the monitoring area in the future one week is high, if the power grid risk of the monitoring area in the future one week is high, obtain the risk monitoring area, and analyze the repair priority of each sub-region in the risk monitoring area, and carry out visual warning; S4, visual warning: obtain the panorama of the monitoring area, mark the risk monitoring area in the panorama of the monitoring area when the power grid risk of the monitoring area is too high, mark the repair priority of each sub-region in the risk monitoring area, feed back the marked image, and carry out warning.

2. The method of claim 1, wherein, The minimum warning value and the maximum warning value of each meteorological data of each sub-region in the total risk monitoring area under different meteorological warnings are analyzed, and the specific process is as follows: Compare each marked sub-region with the risk monitoring area in each historical high risk of the power grid, if a certain marked sub-region is in the risk monitoring area of the power grid in a historical high risk, the historical high risk of the power grid is called the marked historical high risk of the marked sub-region, and the method is used to obtain each marked historical high risk of each marked sub-region; In each marked sub-region, obtain the meteorological warning of each marked historical high risk, and compare them, divide each marked historical high risk with the same meteorological warning into a power grid high risk group, and obtain each power grid high risk group of each marked sub-region by the method; In each power grid risk group of each marked sub-region, obtain the meteorological warning of the power grid risk group, and the lower limit value and the upper limit value of each meteorological data in the marked sub-region, compare the lower limit value of each meteorological data, the maximum lower limit value of each meteorological data is called the minimum warning value of each meteorological data under the meteorological warning, compare the upper limit value of each meteorological data, the minimum upper limit value of each meteorological data is called the maximum warning value of each meteorological data under the meteorological warning, and the method is used to analyze the minimum warning value and the maximum warning value of each meteorological data of each sub-region in the total risk monitoring area under different meteorological warnings.

3. The method of claim 2, wherein, The lower limit value and the upper limit value of each meteorological data in the marked sub-region are obtained, and the specific process is as follows: Obtain the standard value range of each meteorological data from the database, obtain the value of each meteorological data in each marked historical high risk in each power grid risk group of each marked sub-region, and compare it with the standard value range of each meteorological data, the value less than the minimum value of the standard value range is called the lower limit value, and the value higher than the maximum value of the standard value range is called the upper limit value, and the method is used to obtain the lower limit value and the upper limit value of each meteorological data in the marked sub-region.

4. The method of claim 1, wherein, The risk analysis, the specific process is as follows: The meteorological warning report of the monitoring area in the next week is obtained, and it is judged whether there is a meteorological warning in each sub-region of the monitoring area in the next week. When there is no meteorological warning in the monitoring area in the next week, it means that the power grid risk of the monitoring area in the next week is low. When there is a meteorological warning in the monitoring area, it is analyzed whether the power grid risk of each sub-region is too high. If the power grid risk of each sub-region is low, it means that the power grid risk of the monitoring area in the next week is low. If there is a sub-region with too high power grid risk, it means that the power grid risk of the monitoring area in the next week is too high. At this time, the risk monitoring area is obtained, and the repair priority of the power grid of each sub-region in the risk monitoring area is analyzed, and visual warning is performed.

5. The method of claim 4, wherein, The specific process of analyzing whether the power grid risk of each sub-region is too high is as follows: The meteorological warning of the monitoring area is obtained, and the minimum warning value and the maximum warning value of each meteorological data of each sub-region under the meteorological warning are obtained. At the same time, the meteorological warning date of each sub-region is obtained, and the numerical value of each meteorological data of each sub-region on the meteorological warning date is analyzed. According to the numerical value of each meteorological data of each sub-region on the meteorological warning date and the minimum warning value and the maximum warning value of each meteorological data of each sub-region under the meteorological warning, the power grid risk value of each sub-region is obtained. If the power grid risk value of a sub-region is 1, it means that the power grid risk of the sub-region is too high. If the power grid risk value of a sub-region is 0, it means that the power grid risk of the sub-region is low. In this way, whether the power grid risk of each sub-region is too high is analyzed.

6. The method of claim 4, wherein, The specific process of analyzing the repair priority of the power grid of each sub-region in the risk monitoring area is as follows: The main power grid area is obtained from the database, and each sub-region in the risk monitoring area is compared with the main power grid area. Each sub-region in the risk monitoring area which has an overlapping part with the main power grid area is called each main sub-region. At the same time, the total number of power transmission users of the power grid of each sub-region in the risk monitoring area is obtained from the database. According to the total number of power transmission users of the power grid of each sub-region in the risk monitoring area and the main power grid area, the repair priority of the power grid of each sub-region in the risk monitoring area is obtained.

7. A power grid risk visualization system for performing the method of any one of claims 1-6, wherein, It includes: The data acquisition module is used to divide the monitoring area into each sub-region according to the preset area threshold, and obtain each meteorological data of each sub-region and the meteorological warning of the monitoring area in each high risk history of the power grid from the database; The data analysis module is used to obtain the high-risk areas of the power grid from the database at each time of the historical high risks of the power grid. In the historical high risks of the power grid, the high-risk areas of the power grid are compared with each sub-area, each sub-area that has an overlapping part with the high-risk areas of the power grid is referred to as a risk sub-area, and each risk sub-area is clustered to obtain a risk monitoring area. In this way, the risk monitoring areas at each time of the historical high risks of the power grid are obtained. The risk monitoring areas at each time of the historical high risks of the power grid are clustered to obtain a total risk monitoring area. The total risk monitoring area is compared with the monitoring area. The meteorological warning of the monitoring area is used as the meteorological warning of each sub-area. When the comparison result is that the total risk monitoring area is the same as the monitoring area, the minimum warning value and the maximum warning value of each meteorological data of each sub-area in the total risk monitoring area under different meteorological warnings are analyzed according to each meteorological data and the meteorological warning of each sub-area in the risk monitoring area at each time of the historical high risks of the power grid. When the comparison result is that the total risk monitoring area is smaller than the monitoring area, each sub-area in the total risk monitoring area is referred to as a marked sub-area, and each sub-area that is not in the total risk monitoring area is referred to as a secondary marked sub-area. The landform features of each sub-area are obtained from the database. The landform features of each marked sub-area are compared with the landform features of each secondary marked sub-area. Each marked sub-area that has the same landform features as a secondary marked sub-area is referred to as a marked area of the secondary marked sub-area. In this way, each marked area of each secondary marked sub-area is obtained, and the maximum lower limit value and the minimum upper limit data of each meteorological data of each secondary marked sub-area under different meteorological warnings are obtained. The minimum warning value and the maximum warning value of each meteorological data of each marked area of each secondary marked sub-area under the meteorological warning under different meteorological warnings are obtained. The minimum warning value average and the maximum warning value average of each meteorological data under the meteorological warning are calculated. The maximum lower limit value use index and the minimum upper limit data use index of each meteorological data of each secondary marked sub-area under different meteorological warnings are obtained. If the maximum lower limit value use index of a certain meteorological data of a certain secondary marked sub-area under a certain meteorological warning is 1, the minimum warning value of the meteorological data of the secondary marked sub-area under the meteorological warning is the maximum lower limit value of the meteorological data of the secondary marked sub-area under the meteorological warning. If the maximum lower limit value use index of a certain meteorological data of a certain secondary marked sub-area under a certain meteorological warning is 0, the minimum warning value of the meteorological data of the secondary marked sub-area under the meteorological warning is the minimum warning value average of the meteorological data under the meteorological warning. If the minimum upper limit data use index of a certain meteorological data of a certain secondary marked sub-area under a certain meteorological warning is 1, the maximum warning value of the meteorological data of the secondary marked sub-area under the meteorological warning is the minimum upper limit data. If the minimum upper limit data use index of a certain meteorological data of a certain secondary marked sub-area under a certain meteorological warning is 0,The maximum warning value of the meteorological data under the meteorological warning of the secondary marking sub-region is the average value of the maximum warning value of the meteorological data under the meteorological warning, and the minimum warning value and the maximum warning value of each meteorological data under different meteorological warnings of each sub-region are analyzed in this way. The risk analysis module is used to obtain each meteorological data of each sub-region of the monitoring area in the next week, and analyze whether the power grid risk of the monitoring area in the next week is high. If the power grid risk of the monitoring area in the next week is high, the risk monitoring area is obtained, and the repair priority of the power grid of each sub-region in the risk monitoring area is analyzed, and visual warning is performed at the same time; The visual warning module is used to obtain the panoramic map of the monitoring area. When the power grid risk of the monitoring area is too high, the risk monitoring area is marked in the panoramic map of the monitoring area, and the repair priority of each sub-region in the risk monitoring area is marked. The marked image is fed back, and warning is performed at the same time; The database is used for storing meteorological data of each sub-region in each high-risk period of power grid history, meteorological early warning of monitoring region and high-risk region of power grid, and standard numerical range of meteorological data, topographic features of each sub-region and main power grid region.

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