CN110989037A - A power grid micro-meteorological disaster monitoring and early warning system and its early warning method - Google Patents
A power grid micro-meteorological disaster monitoring and early warning system and its early warning method Download PDFInfo
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 93
- 238000000034 method Methods 0.000 title claims abstract description 21
- 239000004576 sand Substances 0.000 claims abstract description 20
- 239000000428 dust Substances 0.000 claims abstract description 17
- 230000008014 freezing Effects 0.000 claims abstract description 15
- 238000007710 freezing Methods 0.000 claims abstract description 15
- 238000004458 analytical method Methods 0.000 claims abstract description 11
- 238000012545 processing Methods 0.000 claims abstract description 8
- 238000013500 data storage Methods 0.000 claims abstract description 7
- 238000003012 network analysis Methods 0.000 claims abstract description 7
- 238000001514 detection method Methods 0.000 claims description 4
- 239000003897 fog Substances 0.000 claims description 3
- 239000012212 insulator Substances 0.000 claims description 3
- 230000005540 biological transmission Effects 0.000 abstract description 7
- 239000004020 conductor Substances 0.000 description 6
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- 208000025274 Lightning injury Diseases 0.000 description 2
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- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
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Abstract
本发明公开了一种电网微气象灾害监测预警系统及其预警方法，包括气象监测平台和气象预警平台，气象监测平台与气象预警平台之间实时传输，气象监测平台包括风灾监测模块、舞动监测模块、冰冻监测模块、污雾监测模块和沙尘监测模块，气象预警平台包括数据储存模块、数据处理模块、网络生成模块、网络分析模块和预警模块，气象监测平台对气象进行监测，气象预警平台对监测到的数据进行处理；本发明通过气象监测平台对风力、舞动、冰冻、污雾和沙尘进行实时监测，通过气象预警平台对检测到的数据进行储存分析，能够根据不同的地形做出不同的分析，分析全面，判断结果精准，将分析结果生成气象网络，能够在有危险时及时进行报警。
The invention discloses a power grid micro-meteorological disaster monitoring and early warning system and its early warning method, comprising a meteorological monitoring platform and a meteorological early warning platform, real-time transmission between the meteorological monitoring platform and the meteorological early warning platform, and the meteorological monitoring platform includes a wind disaster monitoring module and a dancing monitoring module. , freezing monitoring module, pollution fog monitoring module and dust monitoring module, the meteorological early warning platform includes data storage module, data processing module, network generation module, network analysis module and early warning module, the meteorological monitoring platform monitors the weather, and the meteorological early warning platform The monitored data is processed; the present invention conducts real-time monitoring on wind, galloping, freezing, foul fog and sand dust through the meteorological monitoring platform, and stores and analyzes the detected data through the meteorological early warning platform, which can make different The analysis is comprehensive, the judgment results are accurate, and the analysis results are generated into a meteorological network, which can alarm in time when there is danger.
Description
Technical Field
The invention relates to the technical field of meteorological disaster monitoring, in particular to a power grid micro-meteorological disaster monitoring and early warning system and an early warning method thereof.
Background
The power industry is a weather high-sensitivity and high-demand industry, and the production, construction and operation of the power industry are greatly influenced by environmental weather factors. Microclimate refers to the change of small-range meteorological elements (meteorological elements include temperature, humidity, wind speed and direction, air pressure, rain and snow amount and the like) in the near-ground atmosphere and the upper soil layer caused by some structural characteristics (such as microtopography), and the small-range meteorological elements are characterized in individual weather phenomena (such as wind, fog, frost, rime and the like), but the change of the elements cannot cause the climate characteristics determined by a large-scale process (advection and frontal surface) to change greatly.
The transmission line coverage area of China is wide, the transmission distance is long, the terrain of the passing area of the line is complex, the elevation is very different, the meteorological change is obvious, and the microclimate characteristic is prominent. The weather conditions of special terrain areas such as valleys, air ports, rivers, goafs and the like along the line cause the accident potential hazards such as tower collapse, line breakage, hardware wear and the like caused by ice coating, wind deflection, pollution flashover, lightning stroke and the like of the line. The frequently-occurring power grid microclimate disaster accidents show that microclimate, strong wind, rainstorm, pollution flashover, lightning stroke, ice coating and other meteorological disasters and secondary geological disasters in a micro-terrain area seriously threaten the stable operation of a power grid system and cause huge economic loss.
Microclimate refers to the small-scale climatic features in the near-ground atmosphere and in the upper soil due to some structural features of the underlying surface, which are generally expressed in the numerical values of individual weather phenomena (such as wind, fog, frost, rime, etc.). However, the change of the elements does not cause great change of weather and climate characteristics determined by a large-scale process (advection and frontal surface), and microclimate disaster events bring serious influence to the power grid, and may cause the conditions of tripping of power transmission and distribution lines, circuit damage, interphase flashings, conductor waving, broken line tower collapse, damage and interruption of communication transmission networks and the like, so that the detection and early warning of microclimate are made to have important significance for the normal use of the power grid. At present, the microclimate monitoring and early warning technology in China is relatively immature, real-time monitoring and processing of microclimate are difficult to achieve, timely alarming cannot be achieved, the regional pertinence is strong, the conditions of landform, climate, vegetation and the like of provinces and cities are different, the analysis of microclimate disaster area rules is not comprehensive, and the microclimate disaster related theory cannot be generally used in the whole network range.
Based on the above, the invention designs a power grid micro-meteorological disaster monitoring and early warning system and an early warning method thereof, so as to solve the above mentioned problems.
Disclosure of Invention
The present invention has been made to solve the above-mentioned problems occurring in the prior art.
In order to achieve the purpose, the invention provides the following technical scheme: a power grid micro-meteorological disaster monitoring and early warning system comprises a meteorological monitoring platform and a meteorological early warning platform, wherein the meteorological monitoring platform and the meteorological early warning platform are transmitted in real time, the meteorological monitoring platform monitors weather, and the meteorological early warning platform processes monitored data;
the meteorological monitoring platform comprises a wind disaster monitoring module, a galloping monitoring module, a freezing monitoring module, a dirty fog monitoring module and a sand monitoring module;
the weather early warning platform comprises a data storage module, a data processing module, a network generation module, a network analysis module and an early warning module.
Preferably, the wind disaster monitoring module is a strong wind three-dimensional monitoring system, and the strong wind is subjected to omnibearing real-time observation through a wind cloud series meteorological satellite, a multi-Doppler radar weather observation network, a high-density ground automatic station, an automatic rainfall station, high-altitude detection, mobile observation (mobile GPS sounding, mobile Doppler radar and mobile wind profile) and the like, and the elements such as the activity rule, the generation condition, the physical quantity field and the like of the strong wind are obtained through analysis, so that the space-time distribution characteristic of the strong wind is obtained.
Preferably, the galloping monitoring module detects the vibration condition of the wire, the galloping monitoring module detects according to a dynamic stability mechanism, and the wire galloping is judged by icing the wire, wind excitation and structural parameters of the wire.
Preferably, the freezing monitoring module monitors the wire icing condition through a Lenhard model, the circuit icing has obvious regional characteristics, the icing types formed under different weather conditions are different, and the main monitoring types are rime, rime and wet snow.
Preferably, the dirty fog monitoring module detects leakage current of the wire insulator.
Preferably, the sand monitoring module judges and identifies a sand target through high-resolution digital data and a low-resolution analog cloud picture of a meteorological satellite, judges and identifies the sand target by adopting a multispectral classification and image interpretation method, mainly adopts a visible light channel and a near-infrared channel as main channels, combines the main characteristics of a sand storm on the cloud picture, and displays the generation, development and transmission process of the sand storm by using GMS data.
A power grid micro-meteorological disaster monitoring and early warning method comprises the following steps:
s1, monitoring weather such as wind disasters, galloping, freezing, dirty fog, sand and dust through the weather monitoring platform;
s2, the weather monitoring platform transmits the monitored data to the weather early warning platform in real time, the data storage module stores the monitored data, the data processing module processes the data, the network generation module generates the processed data into a weather network, the network analysis module analyzes the generated weather network, and the early warning module judges whether to alarm according to the analysis result
Preferably, the network generation module generates network images of the wind power, waving, freezing, dirty fog and dust real-time condition network.
Compared with the prior art, the invention has the beneficial effects that: the invention monitors wind power, waving, freezing, dirty fog and dust in real time through the meteorological monitoring platform, stores and analyzes the detected data through the meteorological early warning platform, can make different analyses according to different terrains, has comprehensive analysis and accurate judgment result, generates the analysis result into a meteorological network, can give an alarm in time when in danger, and is very convenient to use.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of the system of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the invention provides a power grid micro-meteorological disaster monitoring and early warning system, which comprises a meteorological monitoring platform and a meteorological early warning platform, wherein the meteorological monitoring platform and the meteorological early warning platform are transmitted in real time, the meteorological monitoring platform monitors the weather, and the meteorological early warning platform processes the monitored data;
the meteorological monitoring platform comprises a wind disaster monitoring module, a galloping monitoring module, a freezing monitoring module, a dirty fog monitoring module and a sand monitoring module;
the weather early warning platform comprises a data storage module, a data processing module, a network generation module, a network analysis module and an early warning module.
The wind disaster monitoring module is a strong wind three-dimensional monitoring system, and carries out omnibearing real-time observation on strong wind through a wind cloud series meteorological satellite, a multi-Doppler radar weather observation network, a high-density ground automatic station, an automatic rainfall station, high-altitude detection, mobile observation (mobile GPS exploration, mobile Doppler radar and mobile wind profile) and the like, and obtains elements such as the activity rule, the generation condition, the physical quantity field and the like of the strong wind through analysis, so as to obtain the space-time distribution characteristics of the strong wind.
The conductor galloping monitoring module detects the vibration condition of the conductor, detects the conductor galloping monitoring module according to a dynamic stability mechanism, and judges the conductor galloping through ice coating, wind excitation and structural parameters of the conductor.
The freezing monitoring module monitors the wire icing condition through a Lenhard model, circuit icing has obvious regional characteristics, icing types formed under different weather conditions are different, and the main monitoring types are rime, rime and wet snow.
The monitoring module of the dirty fog detects the leakage current of the wire insulator; the sand and dust monitoring module judges and identifies a sand and dust target through high-resolution digital data and a low-resolution analog cloud picture of a meteorological satellite, and judges and identifies the sand and dust target by adopting a multispectral classification and image interpretation method, wherein the adopted channel mainly comprises a visible light channel and a near infrared channel, and the GMS data is utilized to display the generation, development and transmission process of the sand and dust storm by combining the main characteristics of the sand and dust storm on the cloud picture.
A power grid micro-meteorological disaster monitoring and early warning method comprises the following steps:
s1, monitoring weather such as wind disasters, galloping, freezing, dirty fog, sand and dust through the weather monitoring platform;
s2, the weather monitoring platform transmits the monitored data to the weather early warning platform in real time, the data storage module stores the monitored data, the data processing module processes the data, the network generation module generates the processed data into a weather network, the network analysis module analyzes the generated weather network, and the early warning module judges whether to alarm according to the analysis result.
The network generation module generates network images of the wind power, waving, freezing, dirty fog and dust real-time condition network.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise embodiments disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (8)
1. The utility model provides a little meteorological disaster monitoring early warning system of electric wire netting which characterized in that: the system comprises a weather monitoring platform and a weather early warning platform, wherein the weather monitoring platform and the weather early warning platform are transmitted in real time, the weather monitoring platform monitors weather, and the weather early warning platform processes monitored data;
the meteorological monitoring platform comprises a wind disaster monitoring module, a galloping monitoring module, a freezing monitoring module, a dirty fog monitoring module and a sand monitoring module;
the weather early warning platform comprises a data storage module, a data processing module, a network generation module, a network analysis module and an early warning module.
2. The power grid microclimate disaster monitoring and early warning system according to claim 1, characterized in that: the wind disaster monitoring module is a strong wind three-dimensional monitoring system and carries out omnibearing real-time observation on strong wind through a wind and cloud series meteorological satellite, a multi-Doppler radar weather observation network, a high-density ground automatic station, an automatic rainfall station, high-altitude detection, mobile observation and the like.
3. The power grid microclimate disaster monitoring and early warning system according to claim 1, characterized in that: the galloping monitoring module detects the vibration condition of the lead, and the galloping monitoring module detects according to a dynamic stability mechanism.
4. The power grid microclimate disaster monitoring and early warning system according to claim 1, characterized in that: the freezing monitoring module monitors the icing condition of the lead through a Lenhard model, and the main monitoring types are rime, rime and wet snow.
5. The power grid microclimate disaster monitoring and early warning system according to claim 1, characterized in that: and the dirty fog monitoring module detects the leakage current of the wire insulator.
6. The power grid microclimate disaster monitoring and early warning system according to claim 1, characterized in that: the sand and dust monitoring module judges and identifies a sand and dust target through high-resolution digital data and a low-resolution analog cloud picture of a meteorological satellite, and judges and identifies the sand and dust target by adopting a multispectral classification and image interpretation method, wherein the adopted channel mainly comprises a visible light channel and a near-infrared channel.
7. The power grid microclimate disaster monitoring and early warning method is characterized in that the early warning method of the power grid microclimate disaster monitoring and early warning system based on any one of claims 1-6 comprises the following steps:
s1, monitoring weather such as wind disasters, galloping, freezing, dirty fog, sand and dust through the weather monitoring platform;
s2, the weather monitoring platform transmits the monitored data to the weather early warning platform in real time, the data storage module stores the monitored data, the data processing module processes the data, the network generation module generates the processed data into a weather network, the network analysis module analyzes the generated weather network, and the early warning module judges whether to alarm according to the analysis result.
8. The power grid microclimate disaster monitoring and early warning method according to claim 7, characterized in that: the network generation module generates network images of the wind power, waving, freezing, dirty fog and dust real-time condition network.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103592580A (en) * | 2013-10-18 | 2014-02-19 | 国网山东省电力公司日照供电公司 | Insulator haze and pollution flashover online monitoring system and method |
| CN104319874A (en) * | 2014-09-12 | 2015-01-28 | 国家电网公司 | On-line monitoring system and method for status of power transmission line of intelligent power grid |
| CN106033556A (en) * | 2015-03-16 | 2016-10-19 | 国家电网公司 | A micro-meteorological disaster monitoring and early warning system for power grid and its early warning method |
| CN109784683A (en) * | 2018-12-27 | 2019-05-21 | 国网湖南省电力有限公司 | A kind of power grid wide area meteorological disaster integrated campaign method |
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- 2019-10-29 CN CN201911034768.XA patent/CN110989037A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103592580A (en) * | 2013-10-18 | 2014-02-19 | 国网山东省电力公司日照供电公司 | Insulator haze and pollution flashover online monitoring system and method |
| CN104319874A (en) * | 2014-09-12 | 2015-01-28 | 国家电网公司 | On-line monitoring system and method for status of power transmission line of intelligent power grid |
| CN106033556A (en) * | 2015-03-16 | 2016-10-19 | 国家电网公司 | A micro-meteorological disaster monitoring and early warning system for power grid and its early warning method |
| CN109784683A (en) * | 2018-12-27 | 2019-05-21 | 国网湖南省电力有限公司 | A kind of power grid wide area meteorological disaster integrated campaign method |
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