CN102721986A - Power grid ice coating long-term forecasting method on basis of subtropical anticyclone factor - Google Patents

Abstract

The invention introduces a power grid ice coating long-term forecasting method on the basis of a subtropical anticyclone factor. The method comprises the following steps of: (1) collecting historical subtropical anticyclone parameters and ice coating data; (2) searching an ice coating forecasting factor and calculating a related coefficient; (3) searching an ice coating characteristic region; (4) carrying out statistics on an occurrence probability table of different degrees of ice coating; (5) acquiring the ice coating occurrence probability of the ice coating characteristic region; and (6) calculating the total occurrence probability of different degrees of ice coating. The method has the advantages that 1, the occurrence probabilities of different degrees of power grid ice coating in next quarter (winter) can be forecast one month in advance; 2, the operability is strong; 3, the forecasting accuracy is high; and 4, the difficult problem for forecasting the power grid ice coating for a long time is solved. According to the forecasting conclusion, a corresponding emergency disposal predetermined plan can be timely made, the advanced response of the power grid ice coating is implemented and the loss caused by the power grid ice coating is reduced.

Description

Electrical network icing Long-term forecasting method based on the subtropical high factor

Technical field

The invention belongs to the power transmission and distribution technical field, relate in particular to a kind of electrical network icing Long-term forecasting method based on the subtropical high factor.

Background technology

The electrical network icing is one of disaster of serious harm power network safety operation; Serious icing can cause the mechanical property of electrical network and electric property sharply to descend; Cause power grid accidents such as tower, broken string, conductor galloping and icing flashover, social stability and people's production are constituted a serious threat with life.

At present, the emphasis of electrical network icing Study on Forecast and exploitation is mainly considered the electrical network microprocess that icing increases under specific meteorological condition both at home and abroad, and (Chinese translation is " Lai Anghade " like representative Lenhard.) model, Goodwin (Chinese translation for " Ginnifer Goodwin) model, Chaine (Chinese translation be " expressing gratitude for a favour ") model and Makkonen (Chinese translation is " wheat is agree ") model; the short-term forecasting of the content polyphyly electrical network icing rate of rise of these models; be fit to specified conditions short-term icing prediction down; for example one month future or a season at the most, about temperature than usual higher or on the low side, prediction that precipitation is on the high side or on the low side.And it is more permanent to satisfy the time that meteorological department carries out, long-term for example in a year or so, about the requirement of the prediction of weather and electrical network icing situation, especially based on the requirement of the Long-term forecasting of the electrical network icing situation of the subtropical high factor.For guaranteeing that power grid security passes the winter, ride out the antifreeze ice-melt phase, realize the reply in advance of electrical network icing; Significantly reducing broken string of falling the tower and tripping operation accident takes place; The work of carrying out the long-term forecasting of electrical network icing is imperative, resists the ability of ice and snow disaster in the hope of promoting electrical network, improves the reliability of mains supply; (abbreviation of English " Gross Domestic Product ", Chinese translation is " gross domestic product (GDP) " to GDP to reduce power failure.) loss, maintain social stability.

Summary of the invention

The technical matters that the present invention will solve is: to the backward situation of current electrical network icing long-term forecasting work; A kind of electrical network icing Long-term forecasting method based on the subtropical high factor is provided; Use this method can forecast following four months electrical network icing degree in winter, this method thinking novelty, clear process, accuracy rate height, practical.

Solution of the present invention is: long-pending this a kind of electrical network icing Long-term forecasting method based on the subtropical high factor that is provided; System considers the index of Western Pacific's subtropical high and changes the influence to electrical network icing in winter; The crestal line based on subtropical high, ridge point, facial index and the intensity index of setting up is as the electrical network icing forecasting procedure of icing predictor; The size of the crestal line through judging the prediction time and position, area index and the intensity index of ridge point draws the forecast conclusion of electrical network icing occurrence degree in winter.Specifically, this method is to be following step:

(1). collect historical secondary high parameter and icing data.Crestal line parameter, ridge point parameter, area index, intensity index through internet hunt warm property high-pressure system every month of subtropical region, Western Pacific over 50 years are placed on record; Collect local average icing number of days over the years over 50 years through local meteorological department.According to this average icing number of days, use conventional method that local following four months icing degree is carried out classification;

(2). find out the icing predictor and calculate related coefficient.Utilize step (1) the historical secondary high parameter that obtains and icing data and to the hierarchical analysis of local following four months icing degree, use conventional method find out with the stronger secondary high parameter of icing correlativity as the icing predictor.Formula calculates calculated as described below then:

$R_X=\frac{n\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x}_i{d}_i-\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x}_i\·\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{d}_i}{\sqrt{n\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x_i}^2-{\left(\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x}_i\right)}^2}\·\sqrt{n\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{d_i}^2-{\left(\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{d}_i\right)}^2}}$

In the formula, R _XBe the parameter X (containing secondary high crestal line parameter, secondary high ridge point parameter, secondary high area index and secondary high strength index) of Western Pacific's subtropical high and the related coefficient of average icing number of days; N is historical year umber; x _iBe the value of secondary high parameter, wherein i is the time sequence number; d _iAverage icing number of days for a certain time;

(3). find out the icing characteristic area.Obtain crestal line parameter, ridge point parameter, area index, the intensity index of warm property high-pressure system every month of subtropical region, Western Pacific over 50 years of placing on record according to step (1); With the locality of collecting average icing number of days over the years over 50 years through local meteorological department; And the rating information of local following four months icing degree; Use point that conventional method draws icing predictor and icing degree apart from graph of a relation, and then use conventional clustering method from paint and apart from graph of a relation, find out the icing characteristic area;

(4). count icing probability of happening table in various degree.Obtain apart from graph of a relation and icing characteristic area according to step (3), use conventional mathematical statistics method to count different icing characteristic areas icing probability of happening table in various degree;

(5). obtain the icing probability of happening of icing characteristic area.From step (4) the different icing characteristic areas that obtain in various degree the icing probability of happening table; Use conventional method to select each predictor and influence down the probability of happening of icing in various degree; Judge the icing characteristic area of living in of the predictor based on secondary high parameter in prediction time, obtain the icing probability of happening of corresponding icing characteristic area:

Especially severe icing probability of happening D _j

Serious icing probability of happening M _j

Moderate icing probability of happening L _j

Slight icing probability of happening S _j

Above-mentioned j is the predictor number;

(6). calculate the general probability of icing generation in various degree.Formula calculates total probability of happening of various degree icing calculated as described below:

Total probability of happening of especially severe icing $D=\frac{1}{n}\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{D}_j;$

Total probability of happening of serious icing $M=\frac{1}{n}\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{M}_j;$

Total probability of happening of moderate icing $L=\frac{1}{n}\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{L}_j;$

Total probability of happening of slight icing $S=\frac{1}{n}\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{S}_j.$

More than in four formulas, n is historical year umber; J is the predictor number.

The invention has the beneficial effects as follows:

1, can be one month earlier the probability of happening of the icing of electrical network in various degree in a following season (winter) be predicted;

2, workable;

3, forecast accuracy is high;

4, solved the difficult problem of electrical network icing long-term forecasting.Based on the prediction conclusion, can in time carry out corresponding emergency disposal prediction scheme, realize the reply in advance of electrical network icing, reduce the loss that the electrical network icing is caused.

Embodiment

Embodiment 1:

(1). crestal line parameter, ridge point parameter, area index, intensity index through internet hunt warm property high-pressure system every month of subtropical region, Western Pacific over 50 years are placed on record; Collect local average icing number of days over the years over 50 years through local meteorological department.According to this average icing number of days, use conventional method that local following four months icing degree is carried out classification;

(2). utilize step (1) the historical secondary high parameter that obtains and icing data and to the hierarchical analysis of local following four months icing degree, use conventional method find out with the stronger secondary high parameter of icing correlativity as the icing predictor.Formula calculates calculated as described below then:

$R_X=\frac{n\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x}_i{d}_i-\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x}_i\·\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{d}_i}{\sqrt{n\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x_i}^2-{\left(\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x}_i\right)}^2}\·\sqrt{n\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{d_i}^2-{\left(\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{d}_i\right)}^2}}$

In the formula, R _XBe the parameter X (containing secondary high crestal line parameter, secondary high ridge point parameter, secondary high area index and secondary high strength index) of Western Pacific's subtropical high and the related coefficient of average icing number of days; N is historical year umber; x _iBe the value of secondary high parameter, wherein i is the time sequence number; d _iAverage icing number of days for a certain time;

(3). obtain crestal line parameter, ridge point parameter, area index, the intensity index of warm property high-pressure system every month of subtropical region, Western Pacific over 50 years of placing on record according to step (1); With the locality of collecting average icing number of days over the years over 50 years through local meteorological department; And the rating information of local following four months icing degree; Use point that conventional method draws icing predictor and icing degree apart from graph of a relation, and then use conventional clustering method from paint and apart from graph of a relation, find out the icing characteristic area;

(4). obtain apart from graph of a relation and icing characteristic area according to step (3), use conventional mathematical statistics method to count different icing characteristic areas icing probability of happening table in various degree;

(5). from step (4) the different icing characteristic areas that obtain in various degree the icing probability of happening table; Use conventional method to select each predictor and influence down the probability of happening of icing in various degree; Judge the icing characteristic area of living in of the predictor based on secondary high parameter in prediction time; Obtain the icing probability of happening of corresponding icing characteristic area, the icing probability of happening of establishing the corresponding icing characteristic area that is obtained is:

Especially severe icing probability of happening D _j

Above-mentioned j is the predictor number;

(6). formula calculates the especially severe icing probability of happening D of the corresponding icing characteristic area that step (5) obtained calculated as described below _jTotal probability of happening:

Total probability of happening of especially severe icing $D=\frac{1}{n}\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{D}_j;$

In the formula, n is historical year umber; J is the predictor number.

Embodiment 2:

Step (1)～(4) are with embodiment 1;

(5). from step (4) the different icing characteristic areas that obtain in various degree the icing probability of happening table; Use conventional method to select each predictor and influence down the probability of happening of icing in various degree; Judge the icing characteristic area of living in of the predictor based on secondary high parameter in prediction time; Obtain the icing probability of happening of corresponding icing characteristic area, the icing probability of happening of establishing the corresponding icing characteristic area that is obtained is:

Slight icing probability of happening S _j

Above-mentioned j is the predictor number;

(6). formula calculates the slight icing probability of happening S of the corresponding icing characteristic area that step (5) obtained calculated as described below _jTotal probability of happening:

Total probability of happening of slight icing $S=\frac{1}{n}\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{S}_j,$

In the formula, n is historical year umber; J is the predictor number.

Claims (1)

1. electrical network icing Long-term forecasting method based on the subtropical high factor, this method is following step:

(1). crestal line parameter, ridge point parameter, area index, intensity index through internet hunt warm property high-pressure system every month of subtropical region, Western Pacific over 50 years are placed on record; Collect local average icing number of days over the years over 50 years through local meteorological department.According to this average icing number of days, use conventional method that local following four months icing degree is carried out classification;

(2). utilize step (1) the historical secondary high parameter that obtains and icing data and to the hierarchical analysis of local following four months icing degree, use conventional method find out with the stronger secondary high parameter of icing correlativity as the icing predictor.Formula calculates calculated as described below then:

$R_X=\frac{n\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x}_i{d}_i-\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x}_i\·\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{d}_i}{\sqrt{n\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x_i}^2-{\left(\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x}_i\right)}^2}\·\sqrt{n\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{d_i}^2-{\left(\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{d}_i\right)}^2}}$

In the formula, R _XBe the parameter X (containing secondary high crestal line parameter, secondary high ridge point parameter, secondary high area index and secondary high strength index) of Western Pacific's subtropical high and the related coefficient of average icing number of days; N is historical year umber; x _iBe the value of secondary high parameter, wherein i is the time sequence number; d _iAverage icing number of days for a certain time;

(3). obtain crestal line parameter, ridge point parameter, area index, the intensity index of warm property high-pressure system every month of subtropical region, Western Pacific over 50 years of placing on record according to step (1); With the locality of collecting average icing number of days over the years over 50 years through local meteorological department; And the rating information of local following four months icing degree; Use point that conventional method draws icing predictor and icing degree apart from graph of a relation, and then use conventional clustering method from paint and apart from graph of a relation, find out the icing characteristic area;

(4). obtain apart from graph of a relation and icing characteristic area according to step (3), use conventional mathematical statistics method to count different icing characteristic areas icing probability of happening table in various degree;

(5). from step (4) the different icing characteristic areas that obtain in various degree the icing probability of happening table; Use conventional method to select each predictor and influence down the probability of happening of icing in various degree; Judge the icing characteristic area of living in of the predictor based on secondary high parameter in prediction time, obtain the icing probability of happening of corresponding icing characteristic area:

Especially severe icing probability of happening D _j

Serious icing probability of happening M _j

Moderate icing probability of happening L _j

Slight icing probability of happening S _j

Above-mentioned j is the predictor number;

(6). formula calculates total probability of happening of various degree icing calculated as described below:

Total probability of happening of especially severe icing $D=\frac{1}{n}\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{D}_j;$

Total probability of happening of serious icing $M=\frac{1}{n}\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{M}_j;$

Total probability of happening of moderate icing $L=\frac{1}{n}\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{L}_j;$

Total probability of happening of slight icing $S=\frac{1}{n}\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{S}_j,$

More than in four formulas, n is historical year umber; J is the predictor number.