Power transmission line disaster early warning method and system

Abstract

The invention discloses a power transmission line disaster early warning method and system, and relates to the technical field of power transmission line monitoring, and the method comprises the following steps: 1, collecting historical satellite data, and calculating historical prediction meteorological data according to the historical satellite data; 2, collecting current on-site meteorological data, and calculating compensation parameters in combination with historical predicted meteorological data; 3, calculating future meteorological data according to the field meteorological data, and compensating the future meteorological data according to the compensation parameters to obtain future meteorological correction data; 4, calculating and predicting the icing thickness according to future meteorological correction data; and step 5, performing early warning judgment according to the predicted icing thickness and future meteorological correction data, and generating icing, gale, rainstorm and snowstorm meteorological early warning information. According to the invention, historical data and real-time local data can be combined to automatically correct and accurately pre-judge meteorological data near the power transmission line, meteorological disaster early warning is realized, and the influence of meteorological disasters on the power transmission line is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of power transmission line monitoring, and more particularly to a power transmission line disaster early warning method and system. Background Art

[0002] With the development of electric power technology, the laying range of transmission lines is getting wider and wider, and the monitoring requirements for transmission lines are getting higher and higher. Due to the different locations of electricity consumption, the transmission lines are in different environments and are subjected to different environmental tests. If disasters cannot be discovered and dealt with in time, serious power transmission accidents will occur. The existing transmission line detection system can generally only monitor ice cover, but does not have the function of meteorological disaster monitoring and early warning, and the early warning accuracy is low.

[0003] Therefore, how to achieve accurate early warning of power transmission line disasters is an urgent problem that technical personnel in this field need to solve. Summary of the invention

[0004] In view of this, the present invention provides a transmission line disaster warning method and system, which can automatically correct and accurately predict meteorological data near the transmission line, realize meteorological disaster warning, reduce the impact of meteorological disasters on the transmission line, and assist in the rapid handling of transmission line disasters.

[0005] In order to achieve the above object, the present invention adopts the following technical solution:

[0006] A transmission line disaster early warning method comprises the following steps:

[0007] Step 1: Collect historical satellite data and historical forecast meteorological data calculated based on the historical satellite data;

[0008] Step 2: Collect current on-site meteorological data and calculate compensation parameters in combination with the historical forecast meteorological data;

[0009] Step 3: Calculating future meteorological data according to the on-site meteorological data, and compensating the future meteorological data according to the compensation parameters to obtain future meteorological correction data;

[0010] Step 4: Calculate the predicted ice thickness based on the future meteorological correction data;

[0011] Step 5: Perform warning judgment based on the predicted ice thickness and the future meteorological correction data to generate meteorological warning information.

[0012] Preferably, the specific steps of step 2 include:

[0013] Step 21: Difference the on-site meteorological data and the historical forecast meteorological data, and calculate the difference percentage;

[0014] Step 22: Calculate the average value according to the difference percentage and the array quantity of the historical forecast meteorological data to obtain the compensation parameter.

[0015] Preferably, the historical forecast meteorological data includes the current temperature, humidity, wind direction, wind speed, rainfall and snowfall predicted within a preset historical number of days; the temperature difference percentage, humidity difference percentage, wind direction difference percentage, wind speed difference percentage, rainfall difference percentage and snowfall difference percentage between the on-site meteorological data and the predicted value of each day in the historical forecast meteorological data are calculated, and then the average value of each difference percentage is calculated based on the preset historical number of days as a compensation parameter.

[0016] Preferably, the future meteorological data within a preset number of future days are predicted based on the on-site meteorological data, and the future meteorological data include the temperature, humidity, wind direction, wind speed, rainfall and snowfall for each day in the future days, and the average value of the corresponding difference percentages is subtracted to obtain the future meteorological correction data.

[0017] Preferably, the calculation formula for predicting ice thickness is:

[0018]

[0019] Wherein, D represents the predicted ice thickness; T represents the process time of rainfall and / or snowfall in the future meteorological data; ρ j represents the precipitation rate at the jth time, which is calculated based on the rainfall and / or snowfall and process time; ρ 0 and ρ i is the preset parameter; V j W represents the horizontal wind speed perpendicular to the transmission line at the jth time, and the horizontal wind speed is calculated based on the wind speed and wind direction; j It represents the liquid water content at the jth time, and the liquid water content is calculated based on the humidity. The direction and trend of the clouds are inferred from the satellite images based on the on-site meteorological data and the meteorological forecast experience to derive the time of rainfall or snowfall.

[0020] Preferably, in step 5, whether heavy rain will occur is determined based on the rainfall in the future meteorological correction data and the set rainfall threshold, whether heavy snow will occur is determined based on the snowfall and the set snowfall threshold, whether dancing wind deviation will occur is determined based on the wind direction, wind speed and the set wind constraint conditions, and whether an icing disaster will occur is determined based on the predicted ice thickness and the set ice threshold, and the meteorological warning information is generated based on the judgment results.

[0021] A transmission line disaster warning system, comprising a data acquisition module, a meteorological correction module, an ice calculation module and a meteorological warning module;

[0022] The data acquisition module collects historical satellite data and current on-site meteorological data, as well as historical forecast meteorological data calculated based on the historical satellite data;

[0023] The meteorological correction module calculates compensation parameters according to the on-site meteorological data and the historical forecast meteorological data; calculates future meteorological data according to the on-site meteorological data, and compensates the future meteorological data according to the compensation parameters to obtain future meteorological correction data;

[0024] The ice cover calculation module calculates and predicts the ice cover thickness according to the future meteorological correction data;

[0025] The meteorological warning module makes a warning judgment based on the predicted ice thickness and the future meteorological correction data, and generates meteorological warning information.

[0026] It can be seen from the above technical solution that compared with the prior art, the present invention discloses a transmission line disaster warning method and system, which collects on-site meteorological data through camera sensors, meteorological sensors, and millimeter wave sensors, and combines historical meteorological data to correct the predicted future meteorological data, thereby achieving accurate early warning of future meteorological disasters. It has the ability to process past accumulated data and current data to predict the future state that is about to occur, and achieve meteorological early warning of icing, strong winds, heavy rain, and blizzards, thereby avoiding losses caused by meteorological disasters. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0028] Figure 1 A schematic flow chart of a power transmission line disaster warning method provided by the present invention. DETAILED DESCRIPTION

[0029] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] The embodiment of the present invention discloses a transmission line disaster warning method. The present invention obtains basic meteorological data based on multi-source monitoring means of macroscopic satellite remote sensing data and microscopic regional data, demarcates key areas, and uses machine learning and other algorithms to achieve refined, key monitoring, and key forecasting. The service granularity is refined to the transmission line level and the tower level, and monitoring, forecasting, and warning services for typical power grid meteorological disasters such as lightning, rainstorms, forest fires, ice cover, and dancing wind deviation are realized.

[0031] In a specific embodiment, the early warning method is as follows Figure 1 As shown, the following steps are included:

[0032] S1: Collect historical satellite data and historical forecast meteorological data calculated based on the historical satellite data; the historical forecast meteorological data includes the current temperature, humidity, wind direction, wind speed, rainfall and snowfall predicted within a preset number of historical days;

[0033] S2: Collect current on-site meteorological data and calculate compensation parameters based on historical forecast meteorological data;

[0034] S21: Make a difference between the on-site meteorological data and the historical forecast meteorological data, and calculate the difference percentage; calculate the temperature difference percentage, humidity difference percentage, wind direction difference percentage, wind speed difference percentage, precipitation difference percentage, and snowfall difference percentage for each day in the historical days;

[0035] S22: Calculate the average value according to the difference percentage and the preset historical days of historical forecast meteorological data to obtain a compensation parameter;

[0036] S3: Calculate future meteorological data according to the on-site meteorological data, and compensate the future meteorological data according to the compensation parameters to obtain future meteorological correction data;

[0037] S4: Calculate the predicted ice thickness based on future meteorological correction data;

[0038] The calculation formula for predicting ice thickness is:

[0039]

[0040] In the formula, D is the predicted ice thickness in millimeters (mm); T is the duration of the rainfall or sleet process in hours (h); ρ j is the precipitation rate of the process, in millimeters per hour (mm / h); ρ 0 =1g / cm3; ρ i=0.9g / cm3; V is the horizontal wind speed perpendicular to the conductor, in meters per second (m / s). The maximum wind speed at the target location is directly taken from the color spot map, and the wind direction at the target location is obtained from the line map, so as to calculate the horizontal wind speed perpendicular to the conductor (the color spot map is predicted at intervals of 3 hours, and the line map is predicted at intervals of 1 hour); W is the liquid water content, which is 0.067P4846.g / m3;

[0041] S5: Make warning judgments based on the predicted ice thickness and future meteorological correction data, and generate meteorological warning information; judge whether heavy rain will occur based on the rainfall in the future meteorological correction data and the set rainfall threshold, judge whether heavy snow will occur based on the snowfall and the set snowfall threshold, judge whether dancing wind deviation will occur based on the wind direction, wind speed and the set wind constraints, judge whether icing disasters will occur based on the ice thickness and the set ice threshold, and generate meteorological warning information based on the judgment results.

[0042] Furthermore, if there is ice thickness 12 hours before the statistical time, even if the current time does not meet the ice growth conditions, it is necessary to calculate whether the ice still exists. The method is: the cumulative temperature from the last ice time to the calculation time is greater than 3℃, if the cumulative temperature is greater than 3℃, the ice is considered to have melted, otherwise the time is still marked as the ice thickness of the last time.

[0043] On the other hand, in a specific embodiment, the changing state of the meteorology can be known from the satellite cloud map and the future weather state can be inferred. Generally, the temperature, humidity, wind direction, wind speed drop, and rainfall and snow volume for the next 14 days can be inferred. However, the above data are inaccurate for small locations in the observation area because they are large-scale predictions. For example, it is predicted that it will rain in Beijing, but it actually does not rain in Chaoyang District. The device of the present invention actually captures the real data of the above location on site, and compares it with the predicted data of the previous 14 days to obtain the difference. The difference percentage of the previous 14 days prediction can be obtained, and then these numbers can be averaged to obtain the compensation parameter. The compensation parameters are then corrected with the data predicted for the next 14 days calculated using the satellite cloud image collected on the day and then substituted into the snow cover formula to predict the ice thickness for the next 14 days. The value for these 14 days will be stored in the system database, and the predicted data (13, 12...1) will be added every day until the value for the day is reached. The predicted data will then be compared with the actual status of the equipment on the day to determine the accuracy of the predicted data, and the future data predicted for the day will be adjusted to improve the accuracy of the prediction. By repeating the above logic, the predicted data will be infinitely close to the actual value, achieving an application effect with high prediction accuracy. For example: today is the 5th. Assuming that the data of each day can predict the weather data of the next three days, and the 2nd corresponds to a forecast data of the 5th, the 3rd corresponds to a forecast data of the 5th, and the 4th corresponds to a forecast data of the 5th, the forecast data of the 5th corresponding to 2-4 are compared with the actual data of the 5th to calculate the difference percentage, and the average difference percentage of the three days is calculated as the compensation parameter; the actual data of the 5th is used to predict the future data of the 6th, 7th and 8th in the next three days, and the future data of the 6th to 8th are corrected with the compensation parameters, and the corrected future data are used to calculate the ice thickness and meteorological warning; the actual data of the 6th uses the forecast data of the 3rd to 5th to calculate the compensation parameters, and then the predicted future data of the 7th to 9th are corrected, and the corrected data are used to calculate the ice thickness and meteorological warning; and so on, the difference between the forecast and the actual data of each day is continuously narrowed, thereby continuously improving the prediction accuracy.

[0044] On the other hand, in a specific embodiment, a power transmission line disaster warning system includes a data acquisition module, a meteorological correction module, an ice calculation module and a meteorological warning module;

[0045] A data collection module collects historical satellite data and current on-site meteorological data, as well as historical forecast meteorological data calculated based on historical satellite data;

[0046] The meteorological correction module calculates compensation parameters based on on-site meteorological data and historical forecast meteorological data; calculates future meteorological data based on on-site meteorological data, and compensates the future meteorological data based on the compensation parameters to obtain future meteorological correction data;

[0047] Ice calculation module, which calculates and predicts ice thickness based on future meteorological correction data;

[0048] The meteorological warning module makes warning judgments based on the predicted ice thickness and future meteorological correction data and generates meteorological warning information.

[0049] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0050] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A power transmission line disaster early warning method, characterized in that: The following steps are involved: Step 1: Collect historical satellite data and historical forecast meteorological data calculated based on the historical satellite data; Step 2: Collect current on-site meteorological data and calculate compensation parameters in combination with the historical forecast meteorological data; Step 3: Calculating future meteorological data according to the on-site meteorological data, and compensating the future meteorological data according to the compensation parameters to obtain future meteorological correction data; Step 4: Calculate the predicted ice thickness based on the future meteorological correction data; Step 5: Perform warning judgment based on the predicted ice thickness and the future meteorological correction data to generate meteorological warning information.

2. A power transmission line disaster early warning method according to claim 1, characterized in that: The specific steps of step 2 include: Step 21: Difference the on-site meteorological data and the historical forecast meteorological data, and calculate the difference percentage; Step 22: Calculate the average value according to the difference percentage and the array quantity of the historical forecast meteorological data to obtain the compensation parameter.

3. A power transmission line disaster early warning method according to claim 2, characterized in that: The historical forecast meteorological data includes the current temperature, humidity, wind direction, wind speed, rainfall and snowfall predicted within a preset historical number of days; the temperature difference percentage, humidity difference percentage, wind direction difference percentage, wind speed difference percentage, rainfall difference percentage and snowfall difference percentage between the on-site meteorological data and the predicted value of each day in the historical forecast meteorological data are calculated, and then the average value of each difference percentage is calculated based on the preset historical number of days as a compensation parameter.

4. A power transmission line disaster early warning method according to claim 3, characterized in that: The future meteorological data within a preset number of future days are predicted based on the on-site meteorological data. The future meteorological data include the temperature, humidity, wind direction, wind speed, rainfall and snowfall for each day in the future days, and the average value of the corresponding difference percentages is subtracted to obtain the future meteorological correction data.

5. A power transmission line disaster early warning method according to claim 1, characterized in that: The calculation formula for predicting ice thickness is: Where D represents the predicted ice thickness; T represents the process time of rainfall and / or snowfall in the future meteorological data; ρ j represents the precipitation rate at the jth time, which is calculated based on the rainfall and / or snowfall and process time; ρ0 and ρ j is the preset parameter; V j W represents the horizontal wind speed perpendicular to the transmission line at the jth time, and the horizontal wind speed is calculated based on the wind speed and wind direction; j Represents the liquid water content at the jth time, and the liquid water content is calculated based on the humidity.

6. A power transmission line disaster early warning method according to claim 1, characterized in that: In step 5, whether heavy rain will occur is determined based on the rainfall in the future meteorological correction data and the set rainfall threshold, whether heavy snow will occur is determined based on the snowfall and the set snowfall threshold, whether dancing wind deviation will occur is determined based on the wind direction, wind speed and the set wind constraint conditions, and whether an icing disaster will occur is determined based on the predicted ice thickness and the set ice threshold, and the meteorological warning information is generated based on the judgment results.

7. A power transmission line disaster warning system, characterized in that: It includes data acquisition module, meteorological correction module, ice calculation module and meteorological warning module; The data acquisition module collects historical satellite data and current on-site meteorological data, as well as historical forecast meteorological data calculated based on the historical satellite data; The meteorological correction module calculates compensation parameters according to the on-site meteorological data and the historical forecast meteorological data; calculates future meteorological data according to the on-site meteorological data, and compensates the future meteorological data according to the compensation parameters to obtain future meteorological correction data; The ice cover calculation module calculates and predicts the ice cover thickness according to the future meteorological correction data; The meteorological warning module makes a warning judgment based on the predicted ice thickness and the future meteorological correction data, and generates meteorological warning information.

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