CN113313342B - Method and system for analyzing failure probability of power grid equipment caused by multiple natural disasters - Google Patents
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Abstract
The invention relates to a method and a system for analyzing the probability of power grid equipment failure caused by various natural disasters, wherein the method comprises the steps of calculating the probability of storm disasters, gale disasters, icing disasters and thunder and lightning disasters.
Description
Technical Field
The invention relates to the field of equipment disaster early warning, in particular to a system and a method for evaluating the probability of power grid equipment failure caused by various natural disasters.
Background
In Xishuangbanna areas, high temperature and raininess in rainy season, dry season, complex terrain conditions, strong wind, mountain fire, rainstorm, thunder and lightning, flood and frequent geological disasters seriously threaten the operation of a power grid. At present, the dispatching automation system of the region mainly takes monitoring and analysis of the working condition of the power grid as a main part, and dispatching personnel are difficult to sense the external environment condition and analyze the influence of the external environment condition on the power grid, and difficult to prejudge and formulate a reasonable operation and maintenance mode under severe weather conditions. In the research at home and abroad, the influence of common disasters such as thunder, icing, typhoon and the like on the power grid above the province level is mostly researched, the monitoring and influence analysis methods of disasters such as heavy rainstorm, geology and the like in the area are less researched, and the research on the disaster prevention emergency decision technology facing the characteristics of the power grid in the area is lacked.
Therefore, in order to master typical external disasters and time-space laws and key characteristics of influences of the external disasters in the Xishuangbanna area, the perception capability of regional power grid dispatching operators on external environment information and influences of the external environment information is improved, and the probability analysis and evaluation of power grid equipment faults caused by various natural disasters are necessary.
Disclosure of Invention
In order to solve the problems, the invention provides a method and a system for analyzing the failure probability of power grid equipment caused by various natural disasters, which can better analyze the failure probability of the power grid equipment caused by the disasters.
The technical scheme of the invention is as follows:
the method for analyzing the probability of the power grid equipment failure caused by various natural disasters comprises the following steps of calculating the probability of the power grid equipment failure caused by rainstorm disasters, gale disasters, icing disasters and thunder disasters, wherein the method comprises the following steps of:
the rainstorm disaster risk probability calculation is carried out as follows:
calculating the effective accumulated rainfall in 10 days; calculating the maximum hourly rainfall on the day; calculating the occurrence probability of the rainstorm disaster based on the effective accumulated rainfall fitting; calculating the occurrence probability of the rainstorm disaster fitted by the maximum rainfall at the same day; calculating the probability of inducing rainstorm disasters; calculating a risk evaluation index; calculating the probability of the power grid equipment failure;
the calculation of the risk probability of the gale disaster is carried out as follows:
calculating the distance between the meteorological station and the power grid equipment; calculating the wind speed borne by the power grid equipment; calculating the probability of line fault by using a piecewise linear formula;
the icing disaster risk probability calculation is carried out as follows:
calculating the ice content of the water condensate; constructing an accumulated ice weight variation model; calculating the thickness of accumulated ice; acquiring the maximum icing thickness of the power grid equipment; calculating the probability of faults when the power grid equipment is coated with ice;
the lightning disaster risk probability calculation is carried out as follows:
calculating the area of landmine; calculating the length of a power grid line in the area; calculating the tripping probability of the power grid line; and calculating the fault probability of the power grid equipment caused by the lightning disaster.
Further:
in the calculation of the risk probability of the rainstorm disaster, the effective accumulated rainfall within 10 days is set as R, and the R calculation formula is as follows:
in the formula: r is n Representing the rainfall of the nth day, and sigma representing summation operation;
the maximum hourly rainfall on the day is set as R h Wherein R is h The calculation formula is as follows:
R h ＝max(r a ，r b )
in the formula: r is a radical of hydrogen a The measured weather data represents the rainfall within 24 hours (hour by hour); r is b For weather forecast data, the rainfall, max (r), is forecasted for 3 hours in the future a ，r b ) Represents by r a Or r b The maximum value of (a);
the probability of occurrence of a rainstorm disaster fitted to the effective cumulative rainfall is set as P (R), and the calculation formula of the P (R) is as follows:
P(R)＝-6*10 -6 *R 3 +0.016R 2 -0.031R+1.035
wherein R is the effective accumulated rainfall in 10 days;
the occurrence probability of the rainstorm disaster fitted to the maximum rainfall in the day is set as P (R) h ) Of P (R) h ) The calculation formula of (a) is as follows:
P(R h )＝-2*10 -6 *R h 5 +4*10 -4 *R h 4 -0.025R h 3 +0.56R h 2 -0.71R h +3.52
wherein R is h Represents the maximum hourly rainfall on the day;
let P be the probability of inducing a rainstorm disaster, and the calculation formula is as follows:
P＝0.8P(R)+0.2P(R h )
wherein R is the effective accumulated rainfall within 10 days, R h Represents the maximum hourly rainfall on the day;
the risk evaluation index is set as U, and the calculation formula is as follows:
U＝w1*k1+w2*k2+w3*k3
w1 is relative weight of the terrain, and k1 is a standing book value of the terrain where the power grid equipment is located; w2 is the relative weight of the type of the power grid equipment, and k2 is the ledger value of the foundation hidden danger of the power grid equipment; w3 is the relative weight of the geology, and k3 is the ledger value of the geology where the power grid equipment is located;
setting the probability of the power grid equipment failure as K, wherein the calculation formula is as follows:
K＝1-(1-U)*(1-P)
in the formula: p is the probability of inducing the rainstorm disaster, and U is the evaluation index of the risk of the rainstorm disaster of the power grid equipment.
Further:
in the calculation of the risk probability of the gale disaster, when the distance between the meteorological station and the power grid equipment is calculated, the longitude and latitude of the meteorological station are set as (j) 1 ，w 1 ) The longitude and latitude of the power grid equipment is set as (j) 2 ，w 2 )；
Setting the wind speed of the power grid equipment to be
Wherein h is the height of a wire of the power grid equipment; u is a bottom surface roughness index; v is the meteorological wind speed;
setting the probability of evaluating the line fault by a piecewise linear formula as a 1 The calculation formula is as follows:
in the formula: v d The maximum design wind speed of the power grid equipment line; v m The maximum wind power actually suffered by the power grid equipment line; v 1 ＝βV d ，β＝0.8；k 1 Is the coefficient of the first stage, taken as 0.03; k is a radical of 2 Is the coefficient of the second stage, taken as 0.02;
further, the icing disaster risk probability calculation is performed as follows:
setting the ice content of the hydrogel as I, and calculating the formula as follows:
I＝(0-T w )ln P/E′H
in the formula: p is the pressure intensity; t is w Is the wet bulb temperature; h relative humidity(ii) a E' is an empirical coefficient and takes 0.045 ℃;
setting the accumulated ice weight variation as dM when constructing the accumulated ice weight variation model t Wherein, the change stage of the ice accretion weight variation model comprises: maintenance phase, rime ice accumulation phase, thermal ice melting phase,Sublimation deicing step Segment of；
dM in maintenance phase t ＝0；
When the ice accretion stage of the rime is in, the growth amount is calculated according to a Jones simple model, and the calculation formula is as follows:
dM t ＝[(Pρ w ) 2 +(3.6V×0.067P 0.846 ) 2 ] 0.5
in the formula: rho w Is the density of water; p is the precipitation intensity; v is wind speed;
when the ice fog is in the ice accretion stage, the growth amount is calculated according to a Makkonen model, and the calculation formula is as follows:
dM t ＝3600α 1 QVD t-1
in the formula: q is the liquid water content; alpha is alpha 1 Is the collision rate; v is wind speed; d t-1 The thickness of the ice coating at the last moment;
when the ice melting is in the stage of thermal ice melting, the ice melting amount is calculated according to a Farzaneh formula, and the calculation formula is as follows:
dM t ＝-87-80T t
wherein T is t The temperature at the current time; 87 and 80 are both empirical values;
while in sublimationStage of de-icingIn time, its accumulated ice weight change dM t = -7, wherein-7 is an empirical value;
setting the thickness of accumulated ice as D t The calculation formula is as follows:
wherein: d t-1 The ice accretion diameter of the wire at time (t-1); ρ is a unit of a gradient t Represents the time of tThe ice density of the wire; dM t Is the weight variation of the accumulated ice;
the calculation method for deducing the maximum icing thickness of the power grid equipment comprises the following steps:
judgment of D t Whether or not it is greater than D t-1 When D is present t Is greater than D t-1 Time of maximumCover withThickness of ice D m ＝D t When D is present t Is less than D t-1 Time maximumCoating(s)Thickness of ice D m ＝D t-1 ；
According toCoating(s)Calculating the probability a of failure when the power grid equipment is coated with ice according to the variation of the ice thickness and the weight d The probability is calculated as follows:
in the formula: d d Is the maximum design of the power grid equipment lineCover withIce thickness; d m The maximum wind power actually suffered by the power grid equipment line; d 1 ＝βD d ，β＝0.8；k 1 Is the coefficient of the first stage, taken as 0.03; k is a radical of formula 2 Is the coefficient of the second stage, taken to be 0.02.
Further, the lightning disaster risk probability calculation is carried out as follows:
when the lightning area is calculated, inputting the radius of the earth and the longitude and latitude of the area to be calculated by using a geodesic arc function projected by a mercator, and outputting the lightning area S of the current area;
calculating the length of the power grid line in the area, inputting the longitude and latitude of all power grid equipment in the current power grid line, acquiring the distance between adjacent power grid equipment based on an ES (extended search engine), adding, and outputtingAdded value1 is the length of the power grid line;
setting the tripping probability of the power grid line as P, and the calculation method is as follows:
wherein: alpha is a coefficient of adjustment, alpha is,and is a constant static value; n is the number of lightning strikes; b is the width between the lightning conductors, and the value of the width is taken as the sum of the distance between the left lightning conductor and the distance between the right lightning conductor in the power grid equipment; h is av The average height of the lightning conductor is taken as the height of the lightning conductor; n is the number of lightning strokes of a power grid line in hundred kilometers, and the calculation formula is N =0.015 Th Wherein T is the annual lightning daily statistic value of the current area and h is the height of the power grid equipment; s is the area of the current area falling lightning; l is the length of the power grid line;
and outputting the fault probability of the power grid equipment caused by the lightning disaster.
Further, the device comprises a collector, a processor and a display;
a collector collects data related to natural disasters;
the processor calculates the probability of the power grid equipment failure caused by the corresponding natural disaster according to the collected data and the method of one of claims 1 to 5, and generates a power grid equipment failure warning grid on a GIS map;
and the display is used for displaying the weather monitoring information and the weather early warning information of the natural disaster based on the GIS map and generating a weather monitoring and early warning grid on the GIS map.
The invention also relates to an electronic device comprising a memory, a processor and a computer program that is executable on the memory and on the processor, the processor implementing the computer program when executing it, as claimed in any of the claims 1 to 5The method describedStep (2).
A non-transitory computer-readable storage medium of the present invention has stored thereon a computer program which, when executed by a processor, implements the steps of the above-described method.
In one embodiment of the method of the invention, the value of u depends on different topographies, wherein the topographies are: flat or slightly fluctuant terrain and mountain terrain, wherein the flat or slightly fluctuant terrain is subdivided into sea, villages, cities and big cities, the mountain terrain comprises peaks or hills, inter-mountain basins or valley bottoms, valleys and mountains consistent with wind directions, and the terrain is mountain peaks or hillsAt seau =0.12, and u =0 when the terrain is rural.15, u =0.22 when the terrain is city, u =0.3 when the terrain is big city, and the terrain is mountain peak or hillside
In the formula: tan alpha is the slope of a mountain peak or a mountain slope on the windward side, and when tan alpha is larger than 0.3, 0.3 is taken; k is 2.2 when the peak is a mountain peak, and k is 1.4 when the slope is an uphill; h is the total height (m) of a mountain peak or an ascending slope; and z is the height (m) of the wind speed position from the ground of the power grid equipment calculated by the power grid equipment, when z is greater than 2.5H, 2.5H is taken, u = 0.75-0.85 when the terrain is a mountain basin or a valley bottom, and u = 1.2-1.5 when the terrain is a valley mouth and a peak mouth consistent with the wind direction.
In one embodiment of the method of the invention, the sea refers to offshore sea and pirates, coasts, lakesides and desert areas, the villages refer to fields, villages, jungles, hills and towns where houses are relatively sparse, the cities refer to urban districts of dense building groups, the big cities refer to urban districts of dense building groups and higher houses.
Compared with the prior art, the invention has the beneficial effects that:
according to the method, the power grid equipment failure probability caused by various natural disasters is analyzed, the typical external disasters and the time-space laws and key characteristics of the influences of the external disasters are improved, the perception capability of regional power grid dispatching operators on external environment information and the influences of the external environment information is improved, the fusion of the external environment information and the power grid information can be realized, the influences of the external disasters are quantitatively evaluated from an equipment level and a power grid operation level, the power grid self operation information, the risk information, the external environment information and the like are displayed in a panoramic and visual mode, corresponding operation mode adjustment suggestions are automatically given according to the power grid operation risks, and the analysis decision-making capability and the automation level of the dispatching operation major handling the disaster risks are improved.
The invention comprehensively analyzes various kinds of power grid operation information such as alarm information and information protection information and external information such as weather, disaster prediction and actual measurement at the same time, identifies and processes unstructured and semi-structured data in the power grid operation information, and accurately analyzes and judges information such as probability, space-time range and type of fault by means of a mechanism model of equipment fault caused by comprehensive disaster, historical data learning and the like.
The invention considers constraints such as disaster dynamic influence, power grid operation, disaster relief material demand matching and the like, and a multi-target nonlinear optimization model of uncertain factors such as delivery path, time and the like, provides a solving method, and effectively improves the professional emergency analysis decision-making capability of dispatching operation, thereby reducing the influence of the power grid equipment after disaster on each region and reducing the risk to the minimum.
Drawings
FIG. 1 is a block diagram of the architecture of the system of the present invention;
FIG. 2 is a flow chart of a rainstorm disaster risk probability assessment;
FIG. 3 is a flow chart of risk probability assessment of a gale disaster;
FIG. 4 is a flow chart of the risk probability assessment of icing disaster;
fig. 5 is a flow chart of lightning disaster risk probability assessment.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", and the like, indicate orientations and positional relationships based on those shown in the drawings, and are used only for convenience of description and simplicity of description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be considered as limiting the present invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
In the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," "secured," and the like are to be construed broadly and can, for example, be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In the present invention, unless otherwise expressly stated or limited, "above" or "below" a first feature means that the first and second features are in direct contact, or that the first and second features are not in direct contact but are in contact with each other via another feature therebetween. Also, the first feature being "on," "above" and "over" the second feature includes the first feature being directly on and obliquely above the second feature, or merely indicating that the first feature is at a higher level than the second feature. A first feature being "under," "below," and "beneath" a second feature includes the first feature being directly under and obliquely below the second feature, or simply meaning that the first feature is at a lesser elevation than the second feature.
Example 1
As shown in fig. 1, the power grid equipment failure probability analysis system caused by multiple natural disasters of this embodiment includes a collector, a processor, and a display.
And the collector collects the data related to the natural disaster. The processor calculates the probability of power grid equipment failure caused by corresponding natural disasters according to the acquired data, and generates a power grid equipment failure alarm grid on a GIS map; and the display is used for displaying the weather monitoring information and the weather early warning information of the natural disaster based on the GIS map and generating a weather monitoring and early warning grid on the GIS map.
According to the embodiment, various data can be acquired through automatic acquisition, manual input and other modes, the processor displays the meteorological monitoring information and the meteorological early warning information of the natural disasters based on the GIS map, and the meteorological conditions of all regions in the past 24 hours are automatically counted by combining administrative region division, and meteorological monitoring and early warning grids are generated on the GIS map.
The processor analyzes the time-space characteristics of thunder, rainstorm, gale weather and geological disasters of the Xishuangbanna power grid based on historical data, induces and analyzes the failure or damage condition and the characteristics of power grid equipment caused by the disasters, analyzes the failure probability of the power grid equipment caused by the disasters based on the mechanism of the power grid equipment caused by the disasters, and can perform online early warning on the equipment with higher failure probability; and evaluating the probability of power grid equipment faults caused by rainstorm disasters, gale disasters, icing disasters and lightning disasters on line, and generating a power grid equipment fault alarm grid on a GIS map.
The various natural disasters of the embodiment mainly comprise rainstorm disasters, gale disasters, icing disasters and thunder and lightning disasters.
As shown in fig. 2, the rainstorm disaster risk probability assessment process includes:
step S11: calculating the effective accumulated rainfall in 10 days;
the effective cumulative rainfall for 10 days (including the current day, n = 10) is set as R, and the R calculation formula is as follows:
in the formula: r is n Representing the amount of rainfall on day n.
Step S12: calculating the maximum hourly rainfall on the day;
the maximum hourly rainfall on the day is set as R h R of which h The calculation formula is as follows:
R h ＝max(r a ，r b )
in the formula: r is a Representing the rainfall in 24 hours (hourly) for the meteorological actual measurement data; r is a radical of hydrogen b The weather forecast data represents 3-hour future forecast rainfall (hourly).
Step S13: calculating the occurrence probability of the rainstorm disaster based on the effective accumulated rainfall fitting;
the probability of occurrence of a rainstorm disaster fitted to the effective cumulative rainfall is set as P (R), and the calculation formula of the P (R) is as follows:
P(R)＝-6*10 -6 *R 3 +0.016R 2 -0.031R+1.035
step S14; calculating the occurrence probability of the rainstorm disaster fitted by the maximum rainfall in the day;
the probability of occurrence of a storm disaster that is fitted to the maximum amount of rainfall in the day is P (R) h ) Of P (R) h ) The calculation formula of (c) is as follows:
P(R h )＝-2*10 -6 *R h 5 +4*10 -4 *R h 4 -0.025R h 3 +0.56R h 2 -0.71R h +3.52
step S15: calculating the probability of inducing rainstorm disasters;
let P be the probability of inducing a rainstorm disaster, and the calculation formula is as follows:
P＝0.8P(R)+0.2P(R h )
step S16: calculating a risk evaluation index;
the risk evaluation index is set as U, and the calculation formula is as follows:
U＝w1*k1+w2*k2+w3*k3
in the formula: w1 is the relative weight of the terrain, and k1 is the ledger value of the terrain where the power grid equipment is located; w2 is the relative weight of the type of the power grid equipment, and k2 is the ledger value of the foundation hidden danger of the power grid equipment; w3 is the relative weight of geology, and k3 is the ledger value of the geology that the power grid equipment is located.
Step S17: and deducing the probability of the power grid equipment failure.
Setting the probability of the power grid equipment failure as K, wherein the calculation formula is as follows:
K＝1-(1-U)*(1-P)
in the formula: p is the probability of inducing the rainstorm disaster, and U is the evaluation index of the risk of the rainstorm disaster of the power grid equipment.
As shown in fig. 3, the procedure for assessing the risk probability of a gale disaster includes:
step S21: calculating the distance between the meteorological station and the power grid equipment;
setting the longitude and latitude of the weather station as (j) when calculating the distance between the weather station and the power grid equipment 1 ，w 1 ) Setting the longitude and latitude of the power grid equipment as (j) 2 ，w 2 )。
Step S22: calculating the wind speed borne by the power grid equipment;
setting the wind speed of the power grid equipment to be
H is the height (m) of the lead of the power grid equipment; u is a bottom surface roughness index; and v is the meteorological wind speed.
Where the value of u depends on different topographies, where the topography is:
flat or slightly undulating terrain and mountain terrain, the flat or slightly undulating terrain is subdivided into sea, village, city and metropolitan area, the mountain terrain is divided into mountain peaks or hills, mountain basins or valley bottoms, valley mouths and mountain mouths consistent with wind directions, the sea refers to offshore sea surface and pirates, coast, lakeshore and desert area, the countryside refers to field, countryside, jungle, hill and town where houses are sparser, the city refers to city of dense building group, the metropolitan area refers to city of dense building group and higher city, the terrain is divided into mountain peaks or hills, the valley mouths and mountain mouths are consistent with wind directions, the city refers to city of dense building group, the countryside refers to town where houses are sparser, and the terrain is divided into city of dense building group and higher city groupAt seau =0.12, the terrain is rural u =0.15, the terrain is urban u =0.22, the terrain is metropolitan u =0.3, and the terrain is a mountain peak or a hill slope
In the formula: tan alpha is the slope of a mountain peak or a mountain slope on the windward side, and when tan alpha is larger than 0.3, 0.3 is taken; when it is a mountain peakk is 2.2, and when the slope is an ascending slope, k is 1.4; h is the total height (m) of a mountain peak or an ascending slope; and z is the height (m) of the wind speed position from the ground of the power grid equipment calculated by the power grid equipment, when z is greater than 2.5H, 2.5H is taken, u = 0.75-0.85 when the landform is an interstation basin or a valley bottom, and u = 1.2-1.5 when the landform is a valley mouth and a peak mouth consistent with the wind direction.
Step S23: and evaluating the probability of the line fault by utilizing a piecewise linear formula.
Setting the probability of evaluating the line fault by a piecewise linear formula as a 1 The calculation formula is as follows:
in the formula: v d The maximum design wind speed of the power grid equipment line; v m The maximum wind power actually suffered by the power grid equipment line; v 1 ＝βV d ，β＝0.8；k 1 Is a coefficient of the first stage, and may be 0.03; k is a radical of formula 2 Is a coefficient of the second stage, and may be 0.02.
As shown in fig. 4, the process of assessing the risk probability of icing disaster includes:
step S31: calculating the ice content of the water condensate;
setting the ice content of the hydrogel as I, and the calculation formula is as follows:
I＝(0-T w )lnP/E′H
in the formula: p is pressure (unit: hP) a )；T w Wet bulb temperature (unit:. Degree. C.); h relative humidity (unit:%); e' is an empirical coefficient which may be taken to be 0.045 ℃.
Step S32: constructing an accumulated ice weight variation model;
setting the accumulated ice weight variation as dM when constructing the accumulated ice weight variation model t Wherein the ice accretion weight variation model is divided into 5 variation stages including: maintenance phase, rime ice accumulation phase, thermal ice melting phase and sublimation ice removing phase, when in the maintenance phase, dM t =0; when the ice-accumulating stage is in the rime, the growth amount is calculated according to a Jones simple modelThe calculation formula is as follows:
dM t ＝[(Pρ w ) 2 +(3.6V×0.067P 0.846 ) 2 ] 0.5
in the formula: rho w Is the density of water (unit: 1.0 gcm) -3 ) (ii) a P is precipitation strength (unit: mm. H) -1 ) (ii) a V is the wind speed (unit: m.s) -1 )：
When the ice deposition stage of the rime is in, the growth amount is calculated according to a Makkonen model, and the calculation formula is as follows:
dM t ＝3600α 1 QVD t-1
in the formula: q is the liquid water content (unit: g.m) -3 )；α 1 Is the collision rate; v is the wind speed (unit: m.s) -1 )；D t-1 For the last momentCover withIce thickness;
when the ice melting state is in a thermal ice melting stage, the ice melting amount is calculated according to a Farzaneh formula, and the calculation formula is as follows:
dM t ＝-87-80T t
in the formula T t The temperature (unit:. Degree. C.) at the present time; 87 and 80 are both empirical values;
when in the sublimation and deicing stage, the accumulated ice weight change dM t = 7, where-7 is an empirical value.
The step S33 sets the thickness of the accumulated ice to D t The calculation formula is as follows:
in the formula: d t-1 The diameter of the ice accumulated on the wire (unit: mm) at time (t-1); rho t Represents the ice density of the wire at time t (unit: g. Cm) -3 )；dM t The amount of change in the weight of accumulated ice.
Step S33: calculating the thickness of accumulated ice;
step S34: obtaining the maximum of the power grid equipmentCoating(s)Ice thickness;
the calculation method for deducing the maximum icing thickness of the power grid equipment comprises the following steps:
judgment of D t Whether or not it is greater than D t-1 When D is present t Is greater than D t-1 Time of maximumCoating(s)Thickness of ice D m ＝D t When D is present t Is less than D t-1 Time of maximumCover withThickness of ice D m ＝D t-1 ；
Step S35: and deducing the probability of the fault when the power grid equipment is coated with ice.
Deriving grid plant maximumCoating(s)Thickness of ice, said step S34 being in accordance withCover withAnd calculating the probability of faults when the power grid equipment is coated with ice according to the ice thickness and weight variation.
According toCoating(s)Calculating the probability a of failure when the power grid equipment is coated with ice according to the variation of ice thickness and weight d The probability is calculated as follows:
in the formula: d d Is the maximum design of the power grid equipment lineCoating(s)Ice thickness; d m The maximum wind power actually suffered by the power grid equipment line; d 1 ＝βD d ，β＝0.8；k 1 Is the coefficient of the first stage, taken to be 0.03; k is a radical of formula 2 Is the coefficient of the second stage, taken to be 0.02.
As shown in fig. 5, the lightning disaster risk probability assessment process includes:
step S41: calculating the area of landmine;
and when the lightning area is calculated, the geodetSecurieAree function of the mercator projection is utilized, the radius of the earth and the longitude and latitude of the area to be calculated are input, and the lightning area S of the current area is output.
Step S42: calculating the length of a power grid line in the area;
calculating the length of the power grid line in the area by inputting the longitude and latitude of all the power grid devices in the current power grid line, acquiring the distance between the adjacent power grid devices based on an ES (extended search engine), adding the distances, and outputtingAdded valueAnd 1 is the length of the power grid line.
Step S43: calculating the tripping probability of the power grid line;
setting the tripping probability of the power grid line as P, and the calculation method is as follows:
in the formula: alpha is an adjusting coefficient and is a constant static value; n is the number of lightning strikes; b is the width between the lightning conductors, and the value is taken from the sum of the distances between the left lightning conductor and the right lightning conductor in the power grid equipment; h is av The average height of the lightning conductor is taken as the height of the lightning conductor; n is the lightning stroke number of hundred kilometers of the power grid line, and the calculation formula is N =0.015 Th Wherein T is the annual lightning daily statistic value of the current area and h is the height of the power grid equipment; s is the area of the current area falling mines; and 1 is the length of the power grid line.
Step S44: and outputting the failure probability of the power grid equipment caused by the lightning disaster.
It should be noted that the division of the modules of the above apparatus is only a logical division, and the actual implementation may be wholly or partially integrated into one physical entity, or may be physically separated. And these modules can all be implemented in the form of software invoked by a processing element; or may be implemented entirely in hardware; and part of the modules can be realized in the form of calling software by the processing element, and part of the modules can be realized in the form of hardware.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. The procedures or functions described in accordance with the embodiments of the application are all or partially generated when the computer program instructions are loaded and executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a readable storage medium or transmitted from one readable storage medium to another readable storage medium, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The readable storage medium may be any available medium that can be accessed by a computer or a data storage device including one or more available media integrated servers, data centers, and the like. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid State Disk (SSD)), among others.
The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component.
It should be noted that any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps in the process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., 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.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made in the above embodiments by those of ordinary skill in the art without departing from the principle and spirit of the present invention.
Claims (8)
1. The method for analyzing the probability of the power grid equipment failure caused by various natural disasters is characterized by comprising the following steps: including rainstorm calamity, strong wind calamity, icing calamity and thunder and lightning calamity fault probability calculation, wherein:
the rainstorm disaster risk probability calculation is carried out as follows:
calculating the effective accumulated rainfall within 10 days; calculating the maximum hourly rainfall on the day; calculating the occurrence probability of the rainstorm disaster based on the effective accumulated rainfall fitting; calculating the occurrence probability of the rainstorm disaster fitted by the maximum rainfall in the day; calculating the probability of inducing the rainstorm disaster; calculating a risk evaluation index; calculating the probability of the power grid equipment failure;
the calculation of the risk probability of the gale disaster is carried out as follows:
calculating the distance between the weather station and the power grid equipment; calculating the wind speed borne by the power grid equipment; calculating the probability of line faults by using a piecewise linear formula;
the icing disaster risk probability calculation is carried out as follows:
calculating the ice content of the water condensate; constructing an accumulated ice weight variation model; calculating the thickness of accumulated ice; acquiring the maximum icing thickness of the power grid equipment; calculating the probability of faults when the power grid equipment is coated with ice;
the lightning disaster risk probability calculation is carried out as follows:
calculating the area of the landed mine; calculating the length of a power grid line in the area; calculating the tripping probability of the power grid line; and calculating the fault probability of the power grid equipment caused by the lightning disaster.
2. The method of claim 1, wherein:
in the calculation of the risk probability of the rainstorm disaster, the effective accumulative rainfall within 10 days is set as R, and the R calculation formula is as follows:
in the formula: r n Representing the rainfall of the nth day, and sigma representing summation operation;
the maximum small rainfall on the day is set as R h Wherein R is h The calculation formula is as follows:
R h ＝max(r a ，r b )
in the formula: r is a Representing the rainfall in 24 hours (hourly) for the meteorological actual measurement data; r is b For weather forecast data, the rainfall, max (r), is forecasted for 3 hours in the future a ，r b ) Is represented by r a Or r b Maximum value of (d);
the probability of occurrence of a rainstorm disaster fitted to the effective cumulative rainfall is set as P (R), and the calculation formula of the P (R) is as follows:
P(R)＝-6*10 -6 *R 3 +0.016R 2 -0.031R+1.035
wherein R is the effective accumulated rainfall within 10 days;
the probability of occurrence of a storm disaster that is fitted to the maximum amount of rainfall in the day is P (R) h ) Of P (R) h ) The calculation formula of (a) is as follows:
P(R h )＝-2*10-6*R h 5 +4*10 -4 *R h 4 -0.025R h 3 +0.56R h 2 -0.71R h +3.52
wherein R is h Represents the maximum hourly rainfall on the day;
the rainstorm disaster induction probability is P, and the calculation formula is as follows:
P＝0.8P(R)+0.2P(R h )
wherein R is the effective accumulated rainfall within 10 days, R h Represents the maximum hourly rainfall on the day;
the risk evaluation index is set as U, and the calculation formula is as follows:
U＝w1*k1+w2*k2+w3*k3
w1 is relative weight of the terrain, and k1 is a standing book value of the terrain where the power grid equipment is located; w2 is the relative weight of the type of the power grid equipment, and k2 is the ledger value of the foundation hidden danger of the power grid equipment; w3 is the relative weight of the geology, and k3 is the ledger value of the geology where the power grid equipment is located;
setting the probability of the power grid equipment failure as K, wherein the calculation formula is as follows:
K＝1-(1-U)*(1-P)
in the formula: p is the probability of inducing the rainstorm disaster, and U is the evaluation index of the rainstorm disaster risk of the power grid equipment.
3. The method of claim 1, wherein:
in the calculation of the risk probability of the gale disaster, when the distance between the meteorological station and the power grid equipment is calculated, the longitude and latitude of the meteorological station are set as (j) 1 ，w 1 ) The longitude and latitude of the power grid equipment is set as (j) 2 ，w 2 )；
Setting the wind speed of the power grid equipment to be
Wherein h is the height of a wire of the power grid equipment; u is a bottom surface roughness index; v is the meteorological wind speed;
setting the probability of evaluating the line fault by a piecewise linear formula as a 1 The calculation formula is as follows:
in the formula: v d Is a line of a power grid equipmentMaximum design wind speed; v m The maximum wind power actually suffered by the power grid equipment line; v 1 ＝βV d ，β＝0.8；k 1 Is the coefficient of the first stage, taken to be 0.03; k is a radical of 2 Is the coefficient of the second stage, taken to be 0.02;
4. the method of claim 1, wherein: the icing disaster risk probability calculation is carried out as follows:
setting the ice content of the hydrogel as I, and the calculation formula is as follows:
I＝(0-T w )ln P/E′H
in the formula: p is pressure intensity; t is a unit of w Is the wet bulb temperature; h relative humidity; e' is an empirical coefficient and takes 0.045 ℃;
when the accumulated ice weight variation model is constructed, the accumulated ice weight variation is set as dM t Wherein, the change stage of the ice accretion weight variation model comprises: maintenance stage, rime ice accumulation stage, thermal ice melting stage,Stage of sublimation and de-icing；
dM in maintenance phase t ＝0；
When the ice accretion stage of the rime is in, the growth amount is calculated according to a Jones simple model, and the calculation formula is as follows:
in the formula: ρ is a unit of a gradient w Is the density of water; p is precipitation intensity; v is wind speed;
when in the rime ice deposition stage, the amount of increase is according toMakkonenModel calculation, which has the following calculation formula:
dM t ＝3600α 1 QVD t-1
in the formula: q is the liquid water content; alpha (alpha) ("alpha") 1 Is the collision rate; v is wind speed; d t-1 For the last momentCoating(s)Ice thickness;
when in the stage of thermal ice melting, the ice melting amount is according to a FarznehFormula calculation of which formulaThe following were used:
dM t ＝-87-80T t
wherein T is t The temperature at the current time; 87 and 80 are both empirical values;
while in sublimationStage of de-icingWhile, its accumulated ice weight change dM t = -7, wherein-7 is an empirical value;
the thickness of the accumulated ice is set as D t The calculation formula is as follows:
wherein: d t-1 The ice accretion diameter of the wire at time (t-1); ρ is a unit of a gradient t Represents the ice accretion density of the wire at time t; dM t Is the weight variation of the accumulated ice;
the calculation method for deducing the maximum icing thickness of the power grid equipment comprises the following steps:
judgment of D t Whether or not it is greater than D t-1 When D is present t Is greater than D t-1 Time of maximumCoating(s)Thickness of ice D m ＝D t When D is present t Is less than D t-1 Time of maximumCoating(s)Thickness of ice D m ＝D t-1 ；
According toCoating(s)Calculating the probability alpha of failure when the power grid equipment is coated with ice according to the variation of ice thickness and weight d The probability is calculated as follows:
in the formula: d d Is the maximum design of the power grid equipment lineCoating(s)Ice thickness; d m The maximum wind power actually suffered by the power grid equipment line; d 1 ＝βD d ，β＝0.8；k 1 Is the coefficient of the first stage, taken as 0.03; k is a radical of formula 2 Is the coefficient of the second stage, taken to be 0.02.
5. The method of claim 1, wherein: the lightning disaster risk probability is calculated as follows:
using mercator projection when calculating the area of lightning strikegeodeSicAreInputting the radius of the earth and the longitude and latitude of the area to be calculated by a function, and outputting the area S of the current area;
calculating the length of the power grid line in the area, inputting the longitude and latitude of all power grid equipment in the current power grid line, acquiring the distance between adjacent power grid equipment based on an ES (extended search engine), adding, and outputtingSum value1 is the length of the power grid line;
setting the tripping probability of the power grid line as P, and the calculation method is as follows:
wherein: alpha is an adjusting coefficient and is a constant static value; n is the number of lightning strikes; b is the width between the lightning conductors, and the values are taken from the middle distance of the left lightning conductor and the right lightning conductor in the power grid equipmentIntermediate distance countingAnd; h is av The average height of the lightning conductor is taken as the height of the lightning conductor; n is the line of the power gridHundred kilometersThe number of lightning strokes is calculated by the formula of N =0.015 Th Wherein T is the annual lightning daily statistic value of the current area and h is the height of the power grid equipment; s is the area of the current area falling mines; 1 is the length of the power grid line; and outputting the fault probability of the power grid equipment caused by the lightning disaster.
6. A power grid equipment fault probability analysis system caused by multiple natural disasters is characterized in that: comprises a collector, a processor and a display;
a collector collects data related to natural disasters;
the processor calculates the probability of the power grid equipment fault caused by the corresponding natural disaster according to the collected data and the method of one of claims 1 to 5, and generates a power grid equipment fault alarm grid on a GIS map;
and the display is used for displaying the weather monitoring information and the weather early warning information of the natural disaster based on the GIS map and generating a weather monitoring and early warning grid on the GIS map.
7. An electronic device comprising a memory, a processor, and a computer program that is executable on the memory and on the processor, wherein: the processor, when executing the computer program, realizes the steps of the method of any of the preceding claims 1 to 5.
8. A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that: the computer program, when being executed by a processor, realizes the steps of the method as claimed in any one of claims 1 to 5.
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| CN104318320A (en) * | 2014-10-11 | 2015-01-28 | 中国南方电网有限责任公司 | Static safety analysis based power grid meteorological disaster risk assessment method and device |
| CN107169645A (en) * | 2017-05-09 | 2017-09-15 | 云南电力调度控制中心 | A kind of transmission line malfunction probability online evaluation method of meter and Rainfall Disaster influence |
| CN108898258A (en) * | 2018-07-06 | 2018-11-27 | 广州供电局有限公司 | The analysis method and system of cascading failure in power system risk under Lightning Disaster weather |
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| CN104318320A (en) * | 2014-10-11 | 2015-01-28 | 中国南方电网有限责任公司 | Static safety analysis based power grid meteorological disaster risk assessment method and device |
| CN107169645A (en) * | 2017-05-09 | 2017-09-15 | 云南电力调度控制中心 | A kind of transmission line malfunction probability online evaluation method of meter and Rainfall Disaster influence |
| CN108898258A (en) * | 2018-07-06 | 2018-11-27 | 广州供电局有限公司 | The analysis method and system of cascading failure in power system risk under Lightning Disaster weather |
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