CN110210769A - A kind of transmission line forest fire sprawling Risk Forecast Method and system - Google Patents
A kind of transmission line forest fire sprawling Risk Forecast Method and system Download PDFInfo
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Abstract
The present invention relates to electrical engineering technical field, a kind of transmission line forest fire sprawling Risk Forecast Method and system are disclosed, to effectively realize the prediction to mountain fire sprawling, scientific guidance transmission line forest fire preventing and controlling ensure power network safety operation；The method of the present invention includes obtaining the mountain fire fire point monitoring location information of transmission line of electricity, obtains nearest electric power line pole tower information with a distance from mountain fire fire point, the linear distance between computing electric power line shaft tower and mountain fire fire point；Linear distance is compared with the distance threshold of setting, if linear distance is less than distance threshold, calculates the weather information prediction data of close region within the set time around mountain fire fire point by Numerical Prediction Models；Obtain the geographic position data of close region around mountain fire fire point；Weather information prediction data and geographic position data input mountain fire are spread into computation model, obtain mountain fire sprawling predictive information.
Description
Technical field
The present invention relates to electrical engineering technical field more particularly to a kind of transmission line forest fire sprawling Risk Forecast Method and
System.
Background technique
In recent years, mountain fire disaster in China's increases severely, and per year over 70000, mountain fire easily reduces air insulation, causes transmission line of electricity
Tripping occurs to have a power failure.A lot of UHV transmission line mountain fire trip accidents have had occurred in China, constitute weight to electric power netting safe running
It threatens.Influence risk for accurate judgement mountain fire disaster to route needs to carry out in advance transmission line forest fire sprawling and calculates.Mesh
Preceding research work focuses primarily upon the simulation test of mountain fire sprawling, and is mostly based on ideal laboratory environment, climing to mountain fire
It is less that the prediction prolonged calculates the work carried out.
Therefore, how to effectively realize becomes a urgent problem to the prediction of mountain fire sprawling.
Summary of the invention
It is an object of that present invention to provide a kind of transmission line forest fire sprawling Risk Forecast Method and systems, to effectively realize
Prediction to mountain fire sprawling, scientific guidance transmission line forest fire preventing and controlling ensure power network safety operation.
To achieve the above object, the present invention provides a kind of transmission line forest fires to spread Risk Forecast Method, including following
Step:
S1: the mountain fire fire point monitoring location information of transmission line of electricity is obtained, recently defeated is obtained from the mountain fire fire point with a distance from
Electric wire line pole tower information calculates the linear distance between the electric power line pole tower and the mountain fire fire point；
S2: the linear distance is compared with the distance threshold of setting, if the linear distance is less than the distance
Threshold value then enters S3；
S3: the weather information of close region within the set time around the mountain fire fire point is calculated by Numerical Prediction Models
Prediction data；Obtain the geographic position data of close region around the mountain fire fire point；
S4: the weather information prediction data and geographic position data input mountain fire are spread into computation model, obtained
Mountain fire spreads predictive information.
Preferably, the mountain fire sprawling predictive information includes mountain fire sprawling routing information, dust concentration information and flame
Elevation information.
Preferably, in the S2, the range of the distance threshold is 500m-1000m.
Preferably, in the S3, the weather prognosis data include wind speed information, wind direction information, precipitation information, humidity
Information and temperature information.
Preferably, the geographic position data includes terrain information and vegetation information.
Preferably, it is trained according to the history mountain fire of the mountain fire fire point to spread data for mountain fire sprawling computation model
Arrive, the history mountain fire of mountain fire fire point sprawling data include the history location information of mountain fire fire point, history sprawling routing information,
History dust concentration information and history flame height information.
Preferably, after the step S4 is completed, the method also includes steps:
S5: according to transmission line forest fire tripping computation model, mountain fire disaster is calculated to the degree of risk of transmission line of electricity, and will
The degree of risk is divided at least five grade, respectively weaker, weak, medium, strong and extremely strong.
Preferably, the transmission line forest fire tripping computation model is obtained according to the training of mountain fire history Tripping data, described
Mountain fire history Tripping data includes history mountain fire sprawling data and spreads the transmission line of electricity tripping under data in the history mountain fire
Data.
As a general technical idea, the present invention also provides a kind of transmission line forest fires to spread Risk Forecast System, packet
The computer program that includes memory, processor and storage on a memory and can run on a processor, the processor are held
The step of realizing the above method when row computer program.
The invention has the following advantages:
A kind of transmission line forest fire sprawling Risk Forecast Method and system provided by the invention, can predict to calculate power transmission line
Road mountain fire spreading trend and path, scientific guidance transmission line forest fire preventing and controlling ensure bulk power grid safe and stable operation, implement
It is convenient, it is easy to operate, there is very high practical value.
Below with reference to accompanying drawings, the present invention is described in further detail.
Detailed description of the invention
The attached drawing constituted part of this application is used to provide further understanding of the present invention, schematic reality of the invention
It applies example and its explanation is used to explain the present invention, do not constitute improper limitations of the present invention.In the accompanying drawings:
Fig. 1 is the transmission line forest fire sprawling Risk Forecast Method flow chart of the preferred embodiment of the present invention.
Specific embodiment
The embodiment of the present invention is described in detail below in conjunction with attached drawing, but the present invention can be defined by the claims
Implement with the multitude of different ways of covering.
Embodiment 1
As shown in Figure 1, the present embodiment provides a kind of transmission line forest fires to spread Risk Forecast Method, comprising the following steps:
S1: the mountain fire fire point monitoring location information of transmission line of electricity is obtained, nearest power transmission line with a distance from mountain fire fire point is obtained
Line pole tower information, the linear distance between computing electric power line shaft tower and mountain fire fire point；
S2: linear distance is compared with the distance threshold of setting, if linear distance is less than distance threshold, is entered
S3；
S3: the weather information of close region within the set time around mountain fire fire point is calculated by Numerical Prediction Models and is predicted
Data；Obtain the geographic position data of close region around mountain fire fire point；
S4: weather information prediction data and geographic position data input mountain fire are spread into computation model, obtain mountain fire sprawling
Predictive information.
Above-mentioned transmission line forest fire spreads Risk Forecast Method, can predict computing electric power line mountain fire spreading trend and
Path, scientific guidance transmission line forest fire preventing and controlling ensure bulk power grid safe and stable operation, easy to implement, easy to operate, tool
There is very high practical value.
In the present embodiment, mountain fire sprawling predictive information includes mountain fire sprawling routing information, dust concentration information and flame
Elevation information.
As the present embodiment preferred embodiment, in S2, the range of distance threshold is 500m-1000m.
As the present embodiment preferred embodiment, in S3, weather prognosis data include wind speed information, wind direction information, drop
Water amount information, humidity information and temperature information.Geographic position data includes terrain information and vegetation information.
As the present embodiment preferred embodiment, mountain fire spreads computation model and is spread according to the history mountain fire of mountain fire fire point
Data training obtains, and the history mountain fire sprawling data of mountain fire fire point include the history location information of mountain fire fire point, history sprawling road
Diameter information, history dust concentration information and history flame height information.
As disposable embodiment, after step S4 is completed, method is further comprised the steps of:
S5: according to transmission line forest fire tripping computation model, mountain fire disaster is calculated to the degree of risk of transmission line of electricity, and will
The degree of risk is divided at least five grade, respectively weaker, weak, medium, strong and extremely strong.Wherein, transmission line forest fire is jumped
Lock computation model according to mountain fire history Tripping data training obtain, mountain fire history Tripping data include history mountain fire sprawling data with
And the transmission line of electricity Tripping data under data is spread in the history mountain fire.
Specifically, it in the present embodiment, is prevented and reduced natural disasters the transmission of electricity of Construction of National Key Laboratories according to power grid power transmission and transforming equipment
The mountain fire fire point that route mountain fire monitoring and warning system obtains transmission line of electricity monitors location information.
In practice, 220kV cigarette print line mountain fire fire point nearby is monitored, fire point distance line distance is 869m, it is preferable that
Distance threshold is set as 1000m in the present embodiment, further, calculates following 24 hours wind speed, wind direction, drop near the fire point
The weather prognosis such as water, relative humidity, temperature nearby pass by the meteorological datas such as 2 days precipitation, temperature as a result, reading the fire point,
Read the geographic information datas such as landform, vegetation near fire point, in a practical situation, near the fire point 24 hours futures substantially without
Precipitation.The weather information prediction data of the fire point and geographic position data input mountain fire are spread into computation model, are somebody's turn to do
The sprawling path of fire point.The fire point is calculated to the degree of risk of transmission line of electricity, according to calculate structure decision whether need to carry out and
When fire extinguishing handle.
Embodiment 2
With above method embodiment correspondingly, the present embodiment provides a kind of transmission line forest fire spread risk profile system
System including memory, processor and stores the computer program that can be run on a memory and on a processor, and processor is held
The step of above method is realized when row computer program.
The foregoing is only a preferred embodiment of the present invention, is not intended to restrict the invention, for the skill of this field
For art personnel, the invention may be variously modified and varied.All within the spirits and principles of the present invention, made any to repair
Change, equivalent replacement, improvement etc., should all be included in the protection scope of the present invention.
Claims (9)
1. a kind of transmission line forest fire spreads Risk Forecast Method, which comprises the following steps:
S1: the mountain fire fire point monitoring location information of transmission line of electricity is obtained, nearest power transmission line with a distance from the mountain fire fire point is obtained
Line pole tower information calculates the linear distance between the electric power line pole tower and the mountain fire fire point；
S2: the linear distance is compared with the distance threshold of setting, if the linear distance is less than the distance threshold,
Then enter S3；
S3: the weather information of close region within the set time around the mountain fire fire point is calculated by Numerical Prediction Models and is predicted
Data；Obtain the geographic position data of close region around the mountain fire fire point；
S4: the weather information prediction data and geographic position data input mountain fire are spread into computation model, obtain mountain fire
Spread predictive information.
2. transmission line forest fire according to claim 1 spreads Risk Forecast Method, which is characterized in that the mountain fire sprawling
Predictive information includes mountain fire sprawling routing information, dust concentration information and flame height information.
3. transmission line forest fire according to claim 1 spreads Risk Forecast Method, which is characterized in that in the S2, institute
The range for stating distance threshold is 500m-1000m.
4. transmission line forest fire according to claim 1 spreads Risk Forecast Method, which is characterized in that in the S3, institute
Stating weather prognosis data includes wind speed information, wind direction information, precipitation information, humidity information and temperature information.
5. transmission line forest fire according to claim 1 spreads Risk Forecast Method, which is characterized in that the geographical location
Data include terrain information and vegetation information.
6. transmission line forest fire according to claim 1 spreads Risk Forecast Method, which is characterized in that the mountain fire sprawling
Computation model spreads data training according to the history mountain fire of the mountain fire fire point and obtains, the history mountain fire sprawling of the mountain fire fire point
Data include the history location information of mountain fire fire point, history sprawling routing information, history dust concentration information and history flame
Elevation information.
7. transmission line forest fire according to claim 1 spreads Risk Forecast Method, which is characterized in that the step S4 is complete
At later, the method also includes steps:
S5: tripping computation model according to transmission line forest fire, calculate mountain fire disaster to the degree of risk of transmission line of electricity, and by the wind
Dangerous degree is divided at least five grade, respectively weaker, weak, medium, strong and extremely strong.
8. transmission line forest fire according to claim 6 spreads Risk Forecast Method, which is characterized in that the transmission line of electricity
Mountain fire tripping computation model is obtained according to the training of mountain fire history Tripping data, and the mountain fire history Tripping data includes history mountain fire
It spreads data and spreads the transmission line of electricity Tripping data under data in the history mountain fire.
9. a kind of transmission line forest fire spreads Risk Forecast System, including memory, processor and storage are on a memory simultaneously
The computer program that can be run on a processor, which is characterized in that the processor is realized when executing the computer program
The step of stating claim 1 to 8 any the method.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111126846A (en) * | 2019-12-24 | 2020-05-08 | 广东电网有限责任公司 | Method for evaluating differentiation state of overhead transmission line |
| CN111949754A (en) * | 2020-08-18 | 2020-11-17 | 丽水学院 | Power transmission line forest fire emergency point site selection method based on graph theory |
| CN112817572A (en) * | 2019-11-15 | 2021-05-18 | 内蒙古电力(集团)有限责任公司内蒙古电力科学研究院分公司 | Power transmission line forest fire early warning method |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102708646A (en) * | 2012-06-01 | 2012-10-03 | 湖南省电力公司科学研究院 | Satellite-monitoring-based fire alarming method for mountain power transmission line |
| CN104376510A (en) * | 2014-12-05 | 2015-02-25 | 国家电网公司 | Method of predicting and accessing level of wildfire-caused trip risk in power transmission lines |
| CN105160412A (en) * | 2015-06-23 | 2015-12-16 | 国家电网公司 | Method for evaluating probability of forest fire fault tripping of power transmission line |
| CN105279884A (en) * | 2014-07-04 | 2016-01-27 | 国家电网公司 | Transmission line mountain fire spread warning method with combination of public network weather |
| CN105787602A (en) * | 2016-03-16 | 2016-07-20 | 华北电力大学 | Power transmission line wildfire dynamic forecasting and early warning method based on sequential variation |
| CN106021666A (en) * | 2016-05-10 | 2016-10-12 | 四川大学 | Mountain fire disaster early-warning method for overhead power transmission line |
| CN108831116A (en) * | 2018-06-22 | 2018-11-16 | 国网湖南省电力有限公司 | Transmission line forest fire spreads the bearing calibration of behavior multistage, system and storage medium |
| CN109472421A (en) * | 2018-11-22 | 2019-03-15 | 广东电网有限责任公司 | A kind of power grid mountain fire sprawling method for early warning and device |
| CN109670260A (en) * | 2018-12-27 | 2019-04-23 | 广东电网有限责任公司 | A kind of mountain fire sprawling Area Prediction method, apparatus and equipment |
-
2019
- 2019-06-06 CN CN201910491565.7A patent/CN110210769A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102708646A (en) * | 2012-06-01 | 2012-10-03 | 湖南省电力公司科学研究院 | Satellite-monitoring-based fire alarming method for mountain power transmission line |
| CN105279884A (en) * | 2014-07-04 | 2016-01-27 | 国家电网公司 | Transmission line mountain fire spread warning method with combination of public network weather |
| CN104376510A (en) * | 2014-12-05 | 2015-02-25 | 国家电网公司 | Method of predicting and accessing level of wildfire-caused trip risk in power transmission lines |
| CN105160412A (en) * | 2015-06-23 | 2015-12-16 | 国家电网公司 | Method for evaluating probability of forest fire fault tripping of power transmission line |
| CN105787602A (en) * | 2016-03-16 | 2016-07-20 | 华北电力大学 | Power transmission line wildfire dynamic forecasting and early warning method based on sequential variation |
| CN106021666A (en) * | 2016-05-10 | 2016-10-12 | 四川大学 | Mountain fire disaster early-warning method for overhead power transmission line |
| CN108831116A (en) * | 2018-06-22 | 2018-11-16 | 国网湖南省电力有限公司 | Transmission line forest fire spreads the bearing calibration of behavior multistage, system and storage medium |
| CN109472421A (en) * | 2018-11-22 | 2019-03-15 | 广东电网有限责任公司 | A kind of power grid mountain fire sprawling method for early warning and device |
| CN109670260A (en) * | 2018-12-27 | 2019-04-23 | 广东电网有限责任公司 | A kind of mountain fire sprawling Area Prediction method, apparatus and equipment |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112817572A (en) * | 2019-11-15 | 2021-05-18 | 内蒙古电力(集团)有限责任公司内蒙古电力科学研究院分公司 | Power transmission line forest fire early warning method |
| CN111126846A (en) * | 2019-12-24 | 2020-05-08 | 广东电网有限责任公司 | Method for evaluating differentiation state of overhead transmission line |
| CN111949754A (en) * | 2020-08-18 | 2020-11-17 | 丽水学院 | Power transmission line forest fire emergency point site selection method based on graph theory |
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