CN105931408A - Overhead transmission line forest fire density prediction method - Google Patents

Abstract

The invention discloses an overhead transmission line forest fire density prediction method. The method includes the following steps that: S1, a target area which an overhead transmission line passes through is divided into grids; and S2, the hot point density of each grid at a corresponding period in the further is predicted according to the historical satellite monitored hot point density of each grid. According to the overhead transmission line forest fire density prediction method of the invention, latest data are utilized to predict forest fire density at the corresponding period in a rolling manner; since prediction is carried out real time based on the latest data, prediction accuracy is high; and forest fire fine prediction of a power grid can be carried out, and prediction spatial resolution can achieve 2.5*2.5 km. Thus, forest fire prevention and control of the power grid can be effectively guided.

Description

The Forecasting Methodology of the mountain fire density of overhead transmission line

Technical field

The present invention relates to power system prevent and reduce natural disasters technical field, particularly relate to the Forecasting Methodology of the mountain fire density of overhead transmission line.

Background technology

Mankind's activity field, mountain area frequently is extensively passed through in overhead transmission line corridor, and the productive life such as burnt the grass on waste land by the people, visit a grave is used The impact of fire custom, easily there is mountain fire on a large scale in line corridor, cause a plurality of circuit to trip powers failure simultaneously, causes electric time serious Net collapse.Existing mountain fire disposal options is mostly passively carried out after mountain fire occurs, it is difficult to transfer enough manpower and materials in time Preventing and treating, disposal efficiency is the highest.In order to improve the respond of electrical network reply burst mountain fire, need badly and carry out the prediction of electrical network mountain fire Early warning works.

At present, meteorological department or forest department to the prediction of forest fire mainly from weather conditions, it is judged that following certain on a large scale The probability that regional fire occurs.And overhead transmission line mountain fire is due to following two reason, it is impossible to only carry out greatly from weather angle Horizon prediction: one, mountain fire occurs multi-point and wide-ranging, and circuit distribution is intricate, generally predicts bulk zone, it is impossible to Conscientiously concrete mountain fire preventing and controlling are instructed；Its two, mountain fire occur affected greatly by artificial burning things which may cause a fire disaster factor, relative weather condition this For well-known factor, people are more concerned with artificial burning things which may cause a fire disaster factor.

Therefore, in order to realize the prediction that becomes more meticulous of overhead transmission line mountain fire, need estimation range mesh refinement, improve prediction space Resolution.Meanwhile, mountain fire generation " probability " is quantified as mountain fire and " number of times " occurs, the practicality of prediction to be increased further Add.

Summary of the invention

Present invention aim at providing the Forecasting Methodology of the mountain fire density of a kind of overhead transmission line, to solve current forest fire Prediction mainly strong from weather conditions directiveness and artificial burning things which may cause a fire disaster factor technical problem can not be predicted.

For achieving the above object, the invention provides the Forecasting Methodology of the mountain fire density of a kind of overhead transmission line, including following step Rapid:

S1: the target area passed through by overhead transmission line is divided into grid；

S2: monitor hotspot density according to the historical satellite of each grid, it was predicted that the hotspot density of each grid same period in future.

Further improvements in methods as the present invention:

After step S2 completes, method also includes:

S3: according to the hotspot density of the following same period, and according to overhead transmission line mountain fire principle of grading, issue electrical network mountain fire early warning Information.

Overhead transmission line mountain fire principle of grading includes following Pyatyi:

One-level, average daily hotspot density 0～1 10^-4·km^-2, without hazardous area；

Two grades, average daily hotspot density 1～2 10^-4·km^-2, low hazardous area；

Three grades, average daily hotspot density 2～5 10^-4·km^-2, relatively hazardous district；

Level Four, average daily hotspot density 5～10 10^-4·km^-2, hazardous area；

Pyatyi, average daily hotspot density 10～∞ 10^-4·km^-2, high-risk danger zone.

Step S1, comprises the following steps:

S101: according to the shape of the target area that overhead transmission line passes through, increases neighboring area and supplements target area into rectangle；

S102: rectangle being divided into m row n arrange, obtains the grid of m × n γ × γ longitude and latitude, base latitude is γ₀。

Step S2 comprises the following steps:

S201: set grid satellite monitoring focus number under the conditions of certain weather, underground properties as f, this value history value same period For f₁, f₂..., f_t..., obtain the average of M number by data order pointwise passage, obtain moving average:

$Foreca\left(t\right)=\frac{\underset{i=t-M+1}{\overset{t}{\Σ}}f\left(i\right)}{M}=Foreca(t-1)+\frac{f\left(t\right)-f(t-M)}{M}---\left(1\right)$

Wherein, M is rolling average item number, M≤t,；Foreca_tIt it is the moving average in t cycle；f_tIt is that t periodic fever is counted Observation.

In formula (1), when t moves forward a cycle, it is increased by a new data, removes a legacy data, constantly substitute to obtain prediction Formula is:

$\hat{f}(t+1)=Foreca\left(t\right)---\left(2\right)$

S202: according to the area S of each grid of m row_m, in conjunction with formula (2), obtain m row each grid forecasting heat Dot densityFor:

$d\hat{e}{n}_m(t+1)=\frac{{\hat{f}}_m(t+1)}{S_m}\≈\frac{3.243\underset{i=t-M+1}{\overset{t}{\Σ}}{f}_m\left(i\right)}{{\mathrm{\πMR}}_0{\mathrm{\γ}}^2\left(cos\right({\mathrm{\γ}}_0+(m-1)\mathrm{\γ})+cos({\mathrm{\γ}}_0+m\mathrm{\γ}))}---\left(9\right)$

In formula, earth mean radius R₀=6371km,For prediction hotspot density, unit is a km-²。

The area of each grid of m row is calculated by equation below:

$S_m=a_m{\stackrel{\‾}{b}}_m=0.308{\mathrm{\πR}}_0{\mathrm{\γ}}^2\left(cos\right({\mathrm{\γ}}_0+\left(m-1\right)\mathrm{\γ})+cos({\mathrm{\γ}}_0+m\mathrm{\γ}\left)\right)---\left(8\right)$

Wherein,It is the equal wide of each grid in m row, a_mIt it is the length of side of each grid in m row.

M≥10。

After once having predicted, according to real satellite monitoring focus number to prediction hotspot densityIt is modified, repaiies On the occasion of den_m' (t+1) participates in predicting next time.

The method have the advantages that

The Forecasting Methodology of the mountain fire density of the overhead transmission line of the present invention, utilizes latest data rolling forecast mountain fire same period density, Constantly tell old taking in the fresh, it was predicted that accuracy rate is high, electrical network mountain fire can be carried out and become more meticulous prediction, it was predicted that spatial resolution up to 2.5 × 2.5km, Electrical network mountain fire can be effectively instructed to prevent and treat.

In addition to objects, features and advantages described above, the present invention also has other objects, features and advantages.Below With reference to the accompanying drawings, the present invention is further detailed explanation.

Accompanying drawing explanation

The accompanying drawing of the part constituting the application is used for providing a further understanding of the present invention, the illustrative examples of the present invention and Its explanation is used for explaining the present invention, is not intended that inappropriate limitation of the present invention.In the accompanying drawings:

Fig. 1 is the schematic flow sheet of the Forecasting Methodology of the mountain fire density of the overhead transmission line of the preferred embodiment of the present invention；

Fig. 2 is the schematic diagram of the stress and strain model of the target area of the preferred embodiment of the present invention；

Fig. 3 is that the length of side of 1 ° × 1 ° longitude and latitude grid (Northern Hemisphere) of the preferred embodiment of the present invention calculates schematic diagram；

Fig. 4 is that the overhead transmission line mountain fire generation density of the preferred embodiment of the present invention becomes more meticulous forecast model schematic diagram；

Fig. 5 is that the overhead transmission line mountain fire generation density of the preferred embodiment of the present invention becomes more meticulous prediction principle schematic diagram；

Fig. 6 is the electrical network mountain fire density forecast calculation result figure in 4 days April in 2014 of the preferred embodiment of the present invention.

Detailed description of the invention

Below in conjunction with accompanying drawing, embodiments of the invention are described in detail, but the present invention can be defined by the claims and cover Multitude of different ways implement.

See Fig. 1, the Forecasting Methodology of the mountain fire density of the overhead transmission line of the present invention, comprise the following steps:

S1: the target area passed through by overhead transmission line is divided into grid；

S2: monitor hotspot density according to the historical satellite of each grid, it was predicted that the hotspot density of each grid same period in future.

Satellite monitoring focus number is mainly affected by weather, time period, underground properties, therefore similar weather, underlying surface spy Under the conditions of levying, the hotspot density same period in future can be predicted according to historical satellite monitoring hotspot density.Above-mentioned steps utilizes up-to-date number According to (historical satellite monitoring hotspot density data are constantly updated) rolling forecast mountain fire same period density, constantly tell old taking in the fresh, it was predicted that accurate Really rate is high, can carry out electrical network mountain fire and become more meticulous prediction, it was predicted that spatial resolution, up to 2.5 × 2.5km, can effectively instruct electrical network mountain Fire preventing and treating.

In actual applications, the method is the most extendible as follows:

S1: see Fig. 2, according to the shape of the target area that overhead transmission line passes through, increases neighboring area and is supplemented target area For rectangle；Rectangle being divided into m row n arrange, obtains the grid of m × n γ × γ longitude and latitude, base latitude is γ₀.Predict each net Do not flare up in lattice and count, following mountain fire generation density.

S2: setting grid satellite monitoring focus number under the conditions of certain weather, underground properties as f, this value history value same period is f₁, f₂..., f_t..., obtain the average of M number by data order pointwise passage, obtain moving average:

$Foreca\left(t\right)=\frac{\underset{i=t-M+1}{\overset{t}{\Σ}}f\left(i\right)}{M}=Foreca(t-1)+\frac{f\left(t\right)-f(t-M)}{M}---\left(1\right)$

Wherein, M is rolling average item number, and M≤t generally takes M >=10；Foreca_tIt it is the moving average in t cycle；f_tFor The observation that t periodic fever is counted.

In formula (1), when t moves forward a cycle, it is increased by a new data, removes a legacy data, constantly substitute to obtain prediction Formula is:

$\hat{f}(t+1)=Foreca\left(t\right)---\left(2\right)$

The earth is considered as standard ball, and along with the increase of latitude, the parallel of latitude constantly reduces, and circle of longitude size is fixed.Knownly Ball mean radius R₀=6371km.Ignore the impact of surface relief degree, from geometric knowledge, along the arbitrary meridian of earth surface Cross over distance d of 1 ° of latitude process₁For constant (as shown in Figure 3):

$d_1=\frac{2{\mathrm{\πR}}_0}{360}\≈111km---\left(3\right)$

Along the arbitrary latitude line of earth surface cross over 1 ° of longitude distance d of process₂Relevant with latitude α:

$d_2=\frac{2{\mathrm{\πR}}_{0}cos\mathrm{\α}}{360}=\frac{{\mathrm{\πR}}_{0}cos\mathrm{\α}}{180}---\left(4\right)$

From formula (3), in m row, each grid length of side a_mFor:

a_m=d₁γ≈111γ (5)

Ignore the length of side and the length difference of the lower length of side on single grid, from formula (4), in m row, hem width under each grid b_m1With upper hem width b_m2It is respectively as follows:

$\left\{\begin{array}{c}{b}_{m1}=\frac{{\mathrm{\πR}}_0\mathrm{\γ}cos({\mathrm{\γ}}_0+(m-1)\mathrm{\γ})}{180}\\ b_{m2}=\frac{{\mathrm{\πR}}_0\mathrm{\γ}cos({\mathrm{\γ}}_0+m\mathrm{\γ})}{180}\end{array}\right.---\left(6\right)$

Then in m row, each grid is the widestFor:

${\stackrel{\‾}{b}}_m=\frac{b_{m1}+b_{m2}}{2}=\frac{{\mathrm{\πR}}_0\mathrm{\γ}\left(cos\right({\mathrm{\γ}}_0+(m-1)\mathrm{\γ})+cos({\mathrm{\γ}}_0+m\mathrm{\γ}))}{360}---\left(7\right)$

Then the area of each grid of m row is:

$S_m=a_m{\stackrel{\‾}{b}}_m=0.308{\mathrm{\πR}}_0{\mathrm{\γ}}^2\left(cos\right({\mathrm{\γ}}_0+\left(m-1\right)\mathrm{\γ})+cos({\mathrm{\γ}}_0+m\mathrm{\γ}\left)\right)---\left(8\right)$

Area S according to each grid of m row_m, in conjunction with formula (2), obtain m row each grid forecasting hotspot densityFor:

$d\hat{e}{n}_m(t+1)=\frac{{\hat{f}}_m(t+1)}{S_m}\≈\frac{3.243\underset{i=t-M+1}{\overset{t}{\Σ}}{f}_m\left(i\right)}{{\mathrm{\πMR}}_0{\mathrm{\γ}}^2\left(cos\right({\mathrm{\γ}}_0+(m-1)\mathrm{\γ})+cos({\mathrm{\γ}}_0+m\mathrm{\γ}))}---\left(9\right)$

In formula,For prediction hotspot density, unit is a km^-2。

Operational capability according to computer selects the size of γ with application demand.Such as, γ=0.0225 ° is made, it was predicted that spatial resolution Up to 2.5 × 2.5km, this is the full accuracy of current operationization prediction.

In order to keep the accuracy of subsequent prediction, after the period predicted each time, focus number pair should be monitored according to real satelliteIt is modified, correction value den_m' (t+1) participates in predicting next time.Forecast model and schematic diagram are respectively such as Fig. 4, figure Shown in 5.

S3: according to the mountain fire generation density (hotspot density i.e. predicted of the following same period), and according to overhead transmission line Road mountain fire principle of grading, issues electrical network mountain fire early warning information.

Overhead transmission line mountain fire principle of grading is with reference to table 1:

Overhead transmission line mountain fire prediction in the province such as Hunan, Jiangxi, Hubei during using said method in 2014 Ching Ming Festival.

During Clear and Bright in 2014, State Grid Hunan Electric Power Company has issued Hunan, Jiangxi to State Grid Corporation of China at center of preventing and reducing natural disasters The orange early warning of mountain fire of two provinces, and give suggestion and measure targetedly, the Ching Ming Festival of effectively directing Guo Wang company during frame Empty transmission line forest fire preventing and controlling.Hunan Province, under the guidance that mountain fire forecasts, takes on-the-spot fire suppression measures in time, creates The record of the whole province's electrical network mountain fire zero tripping operation during Clear and Bright without rain day.Detailed process is as follows:

Analysis weather finds, the Ching Ming Festival of 2014 during Hunan, Jiangxi weather fine, utilize history 10 years (M=10) during Clear and Bright Hunan under the conditions of weather is fine, Jiangxi day hotspot density data, when using mountain fire generation density to identical land-surface characteristics area Between sequential forecasting models, calculate two province's various places mountain fire generation density.Make γ=0.0225 °, from formula (5), a_m≈ 2.5km, the most in advance Survey spatial resolution up to 2.5 × 2.5km.

Utilize electrical network mountain fire density forecast Chao Suan center (calculate speed 130 TFlops/second) calculate Hunan except Zhangjiajie, the western Hunan, Most area outside Changsha, and the middle and south, Jiangxi most area April 4 to 5 average daily mountain fire generation density at two grades Above, a lot of areas have exceeded 5 10^-4·km^-2(level Four), local has exceeded 10 10^-4·km^-2(Pyatyi), such as accompanying drawing 6 Shown in.

Then, offer a sacrifice to gods or ancestors customs in conjunction with two provinces, give early warning suggestion: owing to Hunan, Jiangxi weather on April 4 to 5 are fine, At a time when burning incense and offer sacrifices at the graves of one's ancestors on "Qingming" the high-incidence season, occur mountain fire probability big near overhead transmission line, it is proposed that overhead transmission line is issued in Hunan, Jiangxi provinces The orange early warning of mountain fire.By checking, that a situation arises is the most identical with early warning conclusion for actual mountain fire.

The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, for those skilled in the art For, the present invention can have various modifications and variations.All within the spirit and principles in the present invention, any amendment of being made, etc. With replacement, improvement etc., should be included within the scope of the present invention.

Claims (8)

1. the Forecasting Methodology of the mountain fire density of an overhead transmission line, it is characterised in that comprise the following steps:

S1: the target area passed through by overhead transmission line is divided into grid；

S2: monitor hotspot density according to the historical satellite of each grid, it was predicted that the hotspot density of described each grid same period in future.

The Forecasting Methodology of the mountain fire density of overhead transmission line the most according to claim 1, it is characterised in that described step After S2 completes, described method also includes:

S3: according to the hotspot density of the described following same period, and according to overhead transmission line mountain fire principle of grading, issue electrical network mountain fire Early warning information.

The Forecasting Methodology of the mountain fire density of overhead transmission line the most according to claim 2, it is characterised in that described built on stilts Transmission line forest fire principle of grading includes following Pyatyi:

One-level, average daily hotspot density 0～1 10^-4·km^-2, without hazardous area；

Two grades, average daily hotspot density 1～2 10^-4·km^-2, low hazardous area；

Three grades, average daily hotspot density 2～5 10^-4·km^-2, relatively hazardous district；

Level Four, average daily hotspot density 5～10 10^-4·km^-2, hazardous area；

Pyatyi, average daily hotspot density 10～∞ 10^-4·km^-2, high-risk danger zone.

The Forecasting Methodology of the mountain fire density of overhead transmission line the most according to any one of claim 1 to 3, its feature exists In, described step S1, comprise the following steps:

S101: according to the shape of the target area that overhead transmission line passes through, described target area is supplemented and is by increase neighboring area Rectangle；

S102: rectangle being divided into m row n arrange, obtains the grid of m × n γ × γ longitude and latitude, base latitude is γ₀。

The Forecasting Methodology of the mountain fire density of overhead transmission line the most according to claim 4, it is characterised in that described step S2 comprises the following steps:

S201: set grid satellite monitoring focus number under the conditions of certain weather, underground properties as f, this value history value same period For f₁, f₂..., f_t..., obtain the average of M number by data order pointwise passage, obtain moving average:

$Foreca\left(t\right)=\frac{\underset{i=t-M+1}{\overset{t}{\Σ}}f\left(i\right)}{M}=Foreca(t-1)+\frac{f\left(t\right)-f(t-M)}{M}---\left(1\right)$

Wherein, M is rolling average item number, M≤t；Foreca_tIt it is the moving average in t cycle；f_tIt is that t periodic fever is counted Observation.

In formula (1), when t moves forward a cycle, it is increased by a new data, removes a legacy data, constantly substitute to obtain prediction Formula is:

$\hat{f}(t+1)=Foreca\left(t\right)---\left(2\right)$

S202: according to the area S of each grid of m row_m, in conjunction with formula (2), obtain m row each grid forecasting heat Dot densityFor:

$d\hat{e}{n}_m(t+1)=\frac{{\hat{f}}_m(t+1)}{S_m}\≈\frac{3.243\underset{i=t-M+1}{\overset{t}{\Σ}}{f}_m\left(i\right)}{{\mathrm{\πMR}}_0{\mathrm{\γ}}^2\left(cos\right({\mathrm{\γ}}_0+\left(m-1\right)\mathrm{\γ})+cos({\mathrm{\γ}}_0+m\mathrm{\γ}\left)\right)}---\left(9\right)$

In formula, earth mean radius R₀=6371km,For prediction hotspot density, unit is a km^-2。

The Forecasting Methodology of the mountain fire density of overhead transmission line the most according to claim 5, it is characterised in that described m The area of each grid of row is calculated by equation below:

$S_m=a_m{\stackrel{\‾}{b}}_m=0.308{\mathrm{\πR}}_0{\mathrm{\γ}}^2\left(cos\right({\mathrm{\γ}}_0+\left(m-1\right)\mathrm{\γ})+cos({\mathrm{\γ}}_0+m\mathrm{\γ}\left)\right)---\left(8\right)$

Wherein,It is the equal wide of each grid in m row, a_mIt it is the length of side of each grid in m row.

The Forecasting Methodology of the mountain fire density of overhead transmission line the most according to claim 5, it is characterised in that described M >=10.

The Forecasting Methodology of the mountain fire density of overhead transmission line the most according to claim 5, it is characterised in that the most pre- After survey completes, according to real satellite monitoring focus number to described prediction hotspot densityIt is modified, correction value den_m' (t+1) participates in predicting next time.