CN111612315A - Novel power grid disastrous gale early warning method - Google Patents
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Abstract
The invention discloses a novel power grid disastrous gale early warning method. The invention relates to the field of wind disaster early warning, disaster prevention and reduction of a power grid; the method is realized by the following steps: the method comprises the steps of calculating a power downscaling model of original meteorological forecast data, carrying out gridding postprocessing on refined meteorological data output by applying power downscaling, matching with line tower information to obtain strong wind forecast data of a line tower at a grid point, comparing the strong wind forecast data with a tower design wind resistance grade to judge an early warning grade, judging the early warning grade according to the ratio of actual wind speed to the design wind resistance grade, generating highest-grade early warning information when the actual wind speed in the grid point to which the tower belongs reaches more than 100% of the designed wind resistance speed of the tower, and displaying through a power grid GIS platform. According to the method, the power downscaling model of the meteorological forecast data is used for realizing the fine matching of the power grid tower and the grid data.
Description
Technical Field
The invention relates to the field of power grid wind disaster early warning, disaster prevention and reduction, in particular to a novel power grid disastrous gale early warning method which can generate line early warning information aiming at the disastrous gale by combining with power grid actual business.
Background
Years of operation experience of the power grid shows that various power transmission and transformation equipment are exposed to the atmospheric environment for a long time and are easy to be attacked by various meteorological disasters such as thunderstorms, wind disasters, geological disasters and the like to cause faults; the meteorological disasters do not have the characteristics of multiple disaster types, different damage degrees and the like due to factors such as regions, climate and the like; one of the meteorological disasters that is extremely harmful to the safety of the power transmission line is a wind disaster, such as a strong gust, squall line, typhoon, and the like. The damage to the transmission towers can be caused, such as the blowing off of the wires, the blowing down of the towers and the like, the vibration of the wires, the windage yaw discharge and the like are further caused, and the tripping of lines and the like are caused under the action of strong wind or squall wind; compared with tripping caused by other meteorological disasters such as thunder and lightning, windage yaw discharge can continuously and repeatedly occur if wind force is not weakened, the reclosing success rate after the line is tripped due to the windage yaw discharge is low, double images influence the safe operation of the power transmission network, and large-area paralysis of the power grid can be caused.
The existing power grid disastrous gale early warning methods comprise two methods, one is to give out early warning grade according to weather forecast information, the method covers large areas, but the specific landform and geomorphology have different destructive power on gale formation and production; for example, in a leeward area and a windward area, in adjacent places at the same time, the risks of invasion by strong wind are greatly different, for example, the condition of abnormally large wind force often occurs at a certain tower point due to the influence of mountain terrain, so that the method cannot give accurate strong wind early warning information; the other method is to adopt microclimate conditions such as a local radar and the like to give out a strong wind early warning level, but the method does not consider the difference between the terrain and the wind resistance of the facility installation and the wind resistance of the electric facility, and the given early warning result is not accurate.
Disclosure of Invention
Aiming at the problems, the invention provides a novel power grid disastrous gale early warning method. According to the method, on the basis of considering the large-range meteorological conditions, the local microclimate conditions, the terrain and terrain, the facility installation, the wind resistance of the power facility and other factors are comprehensively considered, and the accurate high wind early warning level is further given after calculation, so that corresponding protective measures can be conveniently carried out by workers according to different early warning levels.
The technical scheme of the invention is as follows: a novel power grid disastrous gale early warning method comprises the following specific steps:
step (1.1), acquiring meteorological information: carrying out power downscaling processing on the meteorological wind speed numerical forecast data;
step (1.2), the data after the power downscaling is subjected to gridding data processing and is matched with the information of the electric power facility, so that wind speed data in a grid point of the electric power facility are obtained;
step (1.3), making early warning signals of different levels according to wind resistance strength, a false alarm rate and a false alarm rate of historical early warning information designed by the power facility, and generating line disaster early warning aiming at the windy weather;
and (1.4) finally, releasing through a platform system.
Further, the power downscaling in the step (1.1): the method is characterized in that a global climate mode with lower resolution is nested into a regional climate mode with high resolution, a global mode is utilized to provide a primary boundary value condition for the regional climate mode, and high-resolution prediction information describing regional climate characteristics is obtained.
Further, the data for power downscaling in step (1.1) includes: acquiring information of wide-range meteorological conditions, local microclimate conditions, terrain and topography, facility installation and wind resistance of the power facility;
wherein the wide-range meteorological conditions are obtained through weather forecast data;
the local microclimate condition is obtained by a meteorological radar and a wind power and wind speed sensor which are arranged around the electric power facility;
the terrain and the facility installation, including the height of the position of the electric facility, the mountain orientation and whether the periphery of the electric facility has house, tree or rock protection measures, are obtained through a power grid information database;
and the information of the wind resistance capability of the electric power facility is obtained from a power grid electric power facility information database.
Further, forecasting the gale level of the location of the electric power facility according to the large-scale meteorological conditions, the local microclimate conditions, the terrain and the facility installation conditions; by means of combination of modeling and numerical simulation, a strong wind numerical forecasting model of the position of the power facility is established, and strong wind field distribution prediction under complex terrain conditions is achieved.
Further, in the step (1.3), the wind resistance level of the electric power facility is compared with the wind resistance level of the predicted position of the electric power facility to determine whether to perform early warning and the risk level of the corresponding early warning.
Further, the coverage range of the large-scale meteorological conditions comprises the first level of a city, a district, a county or a village;
the precision range of the local microclimate condition is in the range of dozens of meters;
the information of the wind resistance of the power facility comprises the maximum wind resistance level and the duration of the normal work of the power facility in the open air.
Further, in the step (1.3), the false alarm rate and the false alarm rate of the historical early warning information of the location of the electric power facility are saved, and the threshold value is corrected according to the false alarm rate and the false alarm rate.
Further, in the step (1.4), the platform system is a power grid GIS platform system.
The invention has the beneficial effects that: the method can obtain the early warning information of the disastrous gale weather line at the power grid line tower level, and provides favorable support for power grid transmission and distribution service, operation and maintenance and other aspects; compared with the traditional method for carrying out power grid disastrous gale early warning by simply using weather forecast or microclimate conditions, the invention also provides a novel power grid disastrous gale early warning method, which comprehensively considers factors such as local microclimate conditions, terrain and terrain, facility installation, wind resistance of power facilities and the like on the basis of considering large-range meteorological conditions, and further gives accurate gale early warning levels after calculation, so that workers can make corresponding protective measures on the power facilities according to different early warning levels to reduce loss, thus improving gale disaster forecast prediction capability and having important theoretical significance and application value for disaster prevention and reduction work.
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Fig. 1 is a schematic structural view of the present invention.
Detailed Description
The technical scheme of the invention is further explained in detail by combining the attached drawings:
the invention discloses a novel power grid disastrous gale early warning method, which comprises the following specific steps of:
step (1.1), acquiring meteorological information: carrying out power downscaling processing on the meteorological wind speed numerical forecast data;
step (1.2), the data after the power downscaling is subjected to gridding data processing and is matched with the information of the electric power facility, so that wind speed data in a grid point of the electric power facility are obtained;
step (1.3), making early warning signals of different levels according to wind resistance strength, a false alarm rate and a false alarm rate of historical early warning information designed by the power facility, and generating line disaster early warning aiming at the windy weather;
and (1.4) finally, releasing through a platform system.
Further, the power downscaling in the step (1.1): the method is characterized in that a global climate mode with lower resolution is nested into a regional climate mode with high resolution, a global mode is utilized to provide a primary boundary value condition for the regional climate mode, and high-resolution prediction information describing regional climate characteristics is obtained.
Further, the data for power downscaling in step (1.1) includes: acquiring information of wide-range meteorological conditions, local microclimate conditions, terrain and topography, facility installation and wind resistance of the power facility;
wherein the wide-range meteorological conditions are obtained through weather forecast data;
the local microclimate condition is obtained by a meteorological radar and a wind power and wind speed sensor which are arranged around the electric power facility;
the terrain and the facility installation, including the height of the position of the electric facility, the mountain orientation and whether the periphery of the electric facility has house, tree or rock protection measures, are obtained through a power grid information database;
the information of the wind resistance capability of the electric power facility is obtained from a power grid electric power facility information database;
such as the maximum wind rating and duration that the power facility can function properly in open air.
Further, forecasting the gale level of the location of the electric power facility according to the large-scale meteorological conditions, the local microclimate conditions, the terrain and the facility installation conditions; establishing a strong wind numerical forecasting model of the position of the power facility by means of combining modeling and numerical simulation, and realizing strong wind field distribution prediction under the condition of complex terrain;
the method specifically comprises the following steps: the method comprises the steps of taking a high wind grade of large-scale weather forecast as a basis, taking local microclimate conditions as an adjusting factor alpha, obtaining more accurate wind direction and wind speed information of the location of the electric power facility according to the adjusting factor, further calculating a wind speed correction coefficient beta of terrain topography and facility installation conditions according to predicted wind direction, basic information and the like, wherein when the electric power facility is located on an upwind slope or has higher altitude, the correction coefficient is larger than 1, when the electric power facility is located on a leeward slope, a basin or the periphery of the electric power facility is provided with protective measures, the correction coefficient is smaller than 1, further correcting the predicted wind speed v provided by weather forecast data according to the correction factor, and calculating the wind speed of the location of the electric power facility adopting specific protection, namely the adjusted wind speed.
In the step (1.3), comparing the wind resistance level of the electric power facility with the wind resistance level of the predicted place where the electric power facility is located to determine whether to perform early warning and the risk level of the corresponding early warning;
comparing the adjusted gale grade of the location of the electric power facility with the wind resistance grade of the electric power facility, calculating an early warning index a,
specifically, the wind speed is used as an index to judge the wind power level; setting a threshold value, and if the wind resistance grade of the power facility is higher than the adjusted gale grade by 1, judging that the gale early warning grade is low and performing yellow early warning; if the wind speed is lower than the fixed threshold 2, judging that the grade of the strong wind early warning is high, and performing red early warning; if the wind is in the middle of the two thresholds, judging that the grade of the strong wind early warning is moderate, and performing orange early warning;
the early warning characteristic parameters including the predicted wind circle radius, wind direction and wind speed are further given, so that electric power department workers can make corresponding decisions and treatments on the electric power facilities according to different early warning levels to reduce loss, for example, for I-level early warning, the electric power workers are required to perform station protection on the electric power facilities; for the level II early warning, the inspection tour of the line is enhanced; for III-level early warning, no protective measures are needed; as described in table 1;
| index of early warning | Early warning level |
| a≤1 | Level I warning (Red warning) |
| 1＜a＜3 | II level warning (orange warning) |
| a≥3 | Grade III warning (yellow warning) |
Further, the coverage range of the large-scale meteorological conditions comprises the first level of a city, a district, a county or a village; at present, the meteorological forecast monitoring in most areas of China is controlled to the level of the villages and the towns;
the precision range of the local microclimate condition is in the range of dozens of meters; normally in the range of 10 m to 100 m;
the information of the wind resistance of the power facility comprises the maximum wind resistance level and the duration of the normal work of the power facility in the open air.
Further, in the step (1.3), the false alarm rate and the false alarm rate of the historical early warning information of the location of the electric power facility are saved, and the threshold value is corrected according to the false alarm rate and the false alarm rate.
Further, the platform system is a power grid GIS platform system.
Example 1:
in one implementation mode, a certain city power grid adopts the novel power grid disastrous gale early warning method provided by the invention to carry out early warning on power facilities in the city range in a certain gale process; the city meteorological station can provide short-term wind speed and direction forecast every 2h in the whole city range (particularly to the towns), and the designed highest wind speed resistance of a certain tower in a certain area of the city is v032m/s, and the highest wind resistance grade is 11 grade; the early warning process comprises the following steps: firstly, the basic wind speed v is obtained through weather forecastbThe wind speed is 8 grades at 20m/s, and further a wind speed adjusting factor α caused by microclimate is obtained according to a meteorological radar and the like around the tower, and more accurate wind is obtained after calculationVelocity vb1And (4) further calculating a wind speed correction coefficient β under specific terrain conditions according to the recorded tower foundation information, for example, the tower is positioned on an upwind slope and no protective measures are taken around the tower, and further calculating the adjusted wind speed vb1The wind power level is 10, the early warning index is 1 according to calculation, and the table shows that if the wind power at the position of the line is not corrected, the line cannot become an I-level early warning line, and actually, the line may fail due to the influence of strong wind weather, and the I-level early warning information should be sent out. Therefore, the novel power grid strong wind early warning method provided by the invention can enable related personnel of the power grid to make a highly targeted preventive control measure as soon as possible, and ensure the safe and stable operation of the power system.
Example 2:
in another embodiment, a tower located in the basin can resist a maximum wind velocity v032m/s, the highest wind resistance level is 11, and weather forecast shows that the wind speed of the area reaches v in a certain periodb30m/s, the wind power level is 11, if the traditional early warning method is adopted, I-level early warning is carried out, but because the tower is in the basin and the terrain correction coefficient is small, the adjusted wind speed is further calculated according to the conditions such as microclimate conditions and the like to be vb120m/s, the wind power level is 8, the calculated early warning index is 3, the early warning index is III, and the station protection of power workers is not needed actually, so the method can save manpower and material resources; furthermore, historical early warning data of a certain area adopting the early warning method can be counted, and then the threshold value is corrected according to indexes such as a false alarm rate, a false alarm rate and the like, for example, the threshold 2 can be properly adjusted to be lower when the false alarm rate is higher, and the threshold 1 or the threshold 2 can be properly adjusted to be higher when the false alarm rate is higher.
According to the above, the present invention can be variously modified; the presently disclosed subject matter can be implemented in various forms and examples, and this application can be applied to a wide variety of applications; all applications, modifications and variations that are claimed in the claims are within the scope of the application.
Similarly, it should be noted that in the preceding description of embodiments of the invention, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments; this method of disclosure, however, is not intended to suggest that the claimed subject matter requires more features than are expressly recited in the claims; indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.
Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of embodiments of the present invention; other variations are possible within the scope of the invention; thus, by way of example, and not limitation, alternative configurations of embodiments of the invention may be considered consistent with the teachings of the present invention; accordingly, the embodiments of the invention are not limited to the embodiments explicitly described and depicted.
Claims (8)
1. A novel power grid disastrous gale early warning method is characterized by comprising the following specific steps:
step (1.1), acquiring meteorological information: carrying out power downscaling processing on the meteorological wind speed numerical forecast data;
step (1.2), the data after the power downscaling is subjected to gridding data processing and is matched with the information of the electric power facility, so that wind speed data in a grid point of the electric power facility are obtained;
step (1.3), making early warning signals of different levels according to wind resistance strength, a false alarm rate and a false alarm rate of historical early warning information designed by the power facility, and generating line disaster early warning aiming at the windy weather;
and (1.4) finally, releasing through a platform system.
2. The novel power grid disastrous gale early warning method according to claim 1, characterized in that:
the power downscaling in the step (1.1): the method is characterized in that a global climate mode with lower resolution is nested into a regional climate mode with high resolution, a global mode is utilized to provide a primary boundary value condition for the regional climate mode, and high-resolution prediction information describing regional climate characteristics is obtained.
3. The novel power grid disastrous gale early warning method according to claim 1, characterized in that:
the data for the power downscaling in step (1.1) comprises: acquiring information of wide-range meteorological conditions, local microclimate conditions, terrain and topography, facility installation and wind resistance of the power facility;
wherein the wide-range meteorological conditions are obtained through weather forecast data;
the local microclimate condition is obtained by a meteorological radar and a wind power and wind speed sensor which are arranged around the electric power facility;
the terrain and the facility installation, including the height of the position of the electric facility, the mountain orientation and whether the periphery of the electric facility has house, tree or rock protection measures, are obtained through a power grid information database;
and the information of the wind resistance capability of the electric power facility is obtained from a power grid electric power facility information database.
4. The novel power grid disastrous gale early warning method according to claim 3, characterized in that:
predicting the grade of the gale of the location of the electric power facility according to the large-scale meteorological conditions, the local microclimate conditions, the terrain and the facility installation conditions; by means of combination of modeling and numerical simulation, a strong wind numerical forecasting model of the position of the power facility is established, and strong wind field distribution prediction under complex terrain conditions is achieved.
5. The novel power grid disastrous gale early warning method according to claim 1, characterized in that: in the step (1.3), the wind resistance level of the electric power facility is compared with the wind resistance level of the predicted position of the electric power facility to determine whether to perform early warning and the risk level of the corresponding early warning.
6. The novel power grid disastrous gale early warning method according to claim 3, characterized in that: the coverage range of the large-scale meteorological conditions comprises the first level of a city, a district, a county or a village;
the precision range of the local microclimate condition is in the range of dozens of meters;
the information of the wind resistance of the power facility comprises the maximum wind resistance level and the duration of the normal work of the power facility in the open air.
7. The novel power grid disastrous gale early warning method according to claims 4 and 5, characterized in that: in the step (1.3), the false alarm rate and the false alarm rate of the historical early warning information of the location of the electric power facility are saved, and the threshold value is corrected according to the false alarm rate and the false alarm rate.
8. The novel power grid disastrous gale early warning method according to claim 1, characterized in that: in the step (1.4), the platform system is a power grid GIS platform system.
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112507633A (en) * | 2020-12-03 | 2021-03-16 | 广东电网有限责任公司电力科学研究院 | Method and system for predicting and early warning wind speed of transmission tower |
| CN113011645A (en) * | 2021-03-15 | 2021-06-22 | 国网河南省电力公司电力科学研究院 | Power grid strong wind disaster early warning method and device based on deep learning |
| CN113298295A (en) * | 2021-05-06 | 2021-08-24 | 国网河南省电力公司电力科学研究院 | Meteorological forecast system for power production |
| CN113313291A (en) * | 2021-05-06 | 2021-08-27 | 国网河南省电力公司电力科学研究院 | Power grid wind disaster ensemble forecasting and verifying method based on initial disturbance |
| CN113554266A (en) * | 2021-06-08 | 2021-10-26 | 国网湖南省电力有限公司 | Power grid damage risk early warning method and system caused by strong wind under typhoon condition |
| CN114254831A (en) * | 2021-12-22 | 2022-03-29 | 国网江苏省电力有限公司盐城供电分公司 | Early warning method for wind power grid |
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| CN115765158A (en) * | 2022-10-28 | 2023-03-07 | 国网四川省电力公司攀枝花供电公司 | GIS-based power grid disaster monitoring and early warning system |
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| CN112507633A (en) * | 2020-12-03 | 2021-03-16 | 广东电网有限责任公司电力科学研究院 | Method and system for predicting and early warning wind speed of transmission tower |
| CN113011645A (en) * | 2021-03-15 | 2021-06-22 | 国网河南省电力公司电力科学研究院 | Power grid strong wind disaster early warning method and device based on deep learning |
| CN113298295A (en) * | 2021-05-06 | 2021-08-24 | 国网河南省电力公司电力科学研究院 | Meteorological forecast system for power production |
| CN113313291A (en) * | 2021-05-06 | 2021-08-27 | 国网河南省电力公司电力科学研究院 | Power grid wind disaster ensemble forecasting and verifying method based on initial disturbance |
| CN113554266A (en) * | 2021-06-08 | 2021-10-26 | 国网湖南省电力有限公司 | Power grid damage risk early warning method and system caused by strong wind under typhoon condition |
| CN113554266B (en) * | 2021-06-08 | 2024-01-30 | 国网湖南省电力有限公司 | Early warning method and system for risk of damage to power grid caused by strong wind under typhoon condition |
| CN114254831A (en) * | 2021-12-22 | 2022-03-29 | 国网江苏省电力有限公司盐城供电分公司 | Early warning method for wind power grid |
| CN114723120A (en) * | 2022-03-30 | 2022-07-08 | 北京城市气象研究院 | Near-ground wind speed forecasting method and device |
| CN115765158A (en) * | 2022-10-28 | 2023-03-07 | 国网四川省电力公司攀枝花供电公司 | GIS-based power grid disaster monitoring and early warning system |
| CN118501986B (en) * | 2024-07-17 | 2024-11-15 | 南京气象科技创新研究院 | Disaster high wind space structure forecasting improvement method based on multi-mode integration |
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