CN113313342A - Method and system for analyzing power grid equipment fault probability caused by multiple natural disasters - Google Patents
Method and system for analyzing power grid equipment fault probability caused by multiple natural disasters Download PDFInfo
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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 waterlogging and frequent geological disasters seriously threaten the operation of a power grid. At present, the dispatching automation system of the area mainly takes monitoring and analysis of the self working condition of the power grid as a main part, and dispatching personnel are difficult to perceive the external environment condition and analyze the influence of the external environment condition on the power grid, and difficult to pre-judge 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 features of influences of the typical external disasters in the Xishuangbanna area, the perception capability of regional power grid dispatching operation personnel 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 within 10 days; calculating the maximum hourly rainfall on the day; calculating the probability of occurrence of rainstorm disasters based on 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 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 is calculated 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 accumulative rainfall within 10 days is set as R, and the R calculation formula is as follows:
in the formula: rnRepresenting the rainfall of the nth day, and sigma representing summation operation;
the maximum hourly rainfall on the day is set as RhWherein R ishThe calculation formula is as follows:
Rh＝max(ra，rb)
in the formula: r isaThe measured weather data represents the rainfall within 24 hours (hour by hour); r isbFor weather forecast data, max (r) is the forecast rainfall 3 hours in the futurea，rb) Represents by raOr rbMaximum 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 P (R) is as follows:
P(R)＝-6*10-6*R3+0.016R2-0.031R+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(Rh)＝-2*10-6*Rh 5+4*10-4*Rh 4-0.025Rh 3+0.56Rh 2-0.71Rh+3.52
wherein R ishRepresents 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(Rh)
wherein R is the effective accumulated rainfall within 10 days, RhRepresents 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 the relative weight of the terrain, and k1 is the 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 standing book 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
Is (j)1，w1) The longitude and latitude of the power grid equipment is set as (j)2，w2)；
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 a1The calculation formula is as follows:
in the formula: vdThe maximum design wind speed of the power grid equipment line; vmThe maximum wind power actually suffered by the power grid equipment line; v1＝βVd， β＝0.8；k1Is the coefficient of the first stage, taken as 0.03; k is a radical of2Is 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-Tw)ln P/E′H
in the formula: p is the pressure intensity; t iswIs the wet bulb temperature; h relative humidity; e' is an empirical coefficient and takes 0.045 ℃;
setting the accumulated ice weight variation as dM when constructing the accumulated ice weight variation modeltWherein, the change stage of the ice accretion weight variation model comprises: maintenance phase, rime ice accumulation phase, thermal ice melting phase,Sublimation de-icing Phases；
dM in maintenance phaset＝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:
dMt＝[(Pρw)2+(3.6V×0.067P0.846)2]0.5
in the formula: rhowIs the density of water; p is precipitation intensity; v is wind speed;
when in the stage of rime ice deposition, the increase amount is according toMakkonenModel calculation, the calculation formula is as follows:
dMt＝3600α1QVDt-1
in the formula: q is the liquid water content; alpha is alpha1Is the collision rate; v is wind speed; dt-1For the last momentCoating(s)Ice thickness;
when in the stage of thermal ice melting, the ice melting amount is according toFarzanehCalculating the formula, wherein the calculation formula is as follows:
dMt＝-87-80Tt
wherein T istThe temperature at the current time; 87 and 80 are both empirical values;
while in sublimationStage of de-icingIn time, its accumulated ice weight change dMt-7, wherein-7 is an empirical value;
setting the thickness of accumulated ice as DtThe calculation formula is as follows:
wherein: dt-1The ice accretion diameter of the wire at time (t-1); rhotRepresenting the accumulated ice density change of the electric wire at time t; dMtThe weight change amount of the accumulated ice is obtained;
the calculation method for deducing the maximum icing thickness of the power grid equipment comprises the following steps:
judgment of DtWhether or not it is greater than Dt-1When D is presenttIs greater than Dt-1Thickness of ice coating at maximum Dm＝DtWhen D is presenttIs less than Dt-1Time of maximumCoating(s)Thickness of ice Dm＝Dt-1；
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 weightdThe probability is calculated as follows:
in the formula: ddIs the maximum design of the power grid equipment lineCoating(s)Ice thickness; dmThe maximum wind power actually suffered by the power grid equipment line; d1＝βDd，β＝0.8；k1Is the coefficient of the first stage, taken as 0.03; k is a radical of2Is the coefficient of the second stage, taken to be 0.02.
Further, the lightning disaster risk probability calculation is performed 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 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 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 isavThe average height of the lightning conductor is taken from the height of the lightning conductor; n is a power grid lineHundred kilometersThe number of lightning strokes is calculated by the formula that N is 0.015ThWherein T is the annual lightning of the current regionDaily statisticsThe value h is the height of the power grid equipment; s is the area of the current area falling mines; 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 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.
The invention also relates to an electronic device comprising a memory, a processor and a computer program running on the memory and on the processor, which when executed by the processor implements the steps of the method of any of the preceding claims 1 to 5.
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 is 0.12, u is 0.15 when the terrain is a country, u is 0.22 when the terrain is an city, u is 0.3 when the terrain is a big city, and u is a mountain peak or a mountain 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; 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 larger than 2.5H, 2.5H is taken, and when the terrain is an intermountain basin or a valley bottom, u is 0.75-0.85, and when the terrain is a valley mouth and a peak mouth consistent with the wind direction, u is 1.2-1.5.
In one embodiment of the method of the invention, the sea refers to offshore sea and pirate, coast, lakeshore and desert areas, the countryside refers to the field, countryside, jungle, hilly and relatively sparse towns, the city refers to a local urban area with dense building groups, the metropolitan refers to a local urban area with dense building groups and higher houses.
Compared with the prior art, the invention has the beneficial effects that:
the method analyzes the power grid equipment fault probability caused by various natural disasters, typical external disasters and time-space laws and key characteristics of influences of the external disasters improve the perception capability of regional power grid dispatching operation personnel on external environment information and influences of the external environment information, can realize fusion of the external environment information and the power grid information, quantitatively evaluates the influences of the external disasters from an equipment level and a power grid operation level, carries out panoramic visual display on the operation information, risk information, the external environment information and the like of the power grid, automatically provides corresponding operation mode adjustment suggestions aiming at the operation risk of the power grid, and improves the analysis decision-making capability and the automation level of the dispatching operation professional for dealing with the disaster risk.
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 risk probability assessment of lightning disaster.
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 or similar reference numerals refer to the same or similar elements or elements having the same or similar function 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 describing the present invention and simplifying the description, but do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed 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 "under," "below," and "beneath" a second feature includes a first feature that is directly under and obliquely below the second feature, or simply means that the first feature is less high 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.
The collector collects data related to natural disasters. 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 disaster based on the GIS map, and automatically counts the meteorological conditions of all regions in the past 24 hours by combining with administrative region division, and a meteorological monitoring and early warning grid is 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 (3) on-line evaluating the probability of power grid equipment faults caused by rainstorm disasters, strong wind disasters, icing disasters and lightning disasters, and generating a power grid equipment fault alarm grid on a GIS map.
The various natural disasters of this embodiment mainly include rainstorm disasters, gale disasters, icing disasters, and lightning disasters.
As shown in fig. 2, the rainstorm disaster risk probability assessment process includes:
step S11: calculating the effective accumulated rainfall within 10 days;
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 standing book 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 meteorological station as (j) when calculating the distance between the meteorological station and the power grid equipment1，w1) The longitude and latitude of the power grid equipment are set as (j)2，w2)。
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 power grid equipment lead; 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 haveThe land form of the flat or slightly fluctuating land form is subdivided into sea, village, city, major city, the said land form of the said major country is the mountain peak or hillside, inter-mountain basin or valley bottom, valley mouth and hill mouth consistent with wind direction, wherein the sea refers to offshore sea surface and pirate, coast, lakeshore and desert area, the said country refers to the field, countryside, jungle, hills and sparser villages of the house, the said city refers to the city area of the dense building group, the said major city refers to the city area of the dense building group and the higher city area of the house, the said land form is the said land form of the dense building group, the said major city refers to the city area of the dense building group and the higher city of the house, the said land form is the said land form of the said major country is the said land form of the mountainAt seau is 0.12, u is 0.15 when the terrain is a village, u is 0.22 when the terrain is an city, u is 0.3 when the terrain is a big city, and the terrain is a mountain peak or a mountain 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; 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, and when the terrain is an intermountain basin or a valley bottom, u is 0.75-0.85, and when the terrain is a valley mouth and a peak mouth consistent with the wind direction, u is 1.2-1.5.
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 a1The calculation formula is as follows:
in the formula: vd is the maximum design wind speed of the power grid equipment line; vmThe maximum wind power actually suffered by the power grid equipment line; v1＝βVd， β＝0.8；k1Is a coefficient of the first stage, and may be 0.03; k is a radical of2Is 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 calculating the formula as follows:
I＝(0-Tw)ln P/E′H
in the formula: p is pressure (unit: hP)a)；TwWet 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 modeltWherein the ice accretion weight variation model is divided into 5 variation stages including: maintenance phase, rime ice accumulation phase, thermal ice melting phase,Sublimation Stage of de-icingdM while in the maintenance phaset0; 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:
dMt＝[(Pρw)2+(3.6V×0.067P0.846)2]0.5
in the formula: rhowIs the density of water (unit: 1.0 gcm)-3) (ii) a P is precipitation intensity (unit: mm. h)-1) (ii) a V is wind speed (unit: m.s)-1)：
When in the stage of rime ice deposition, the increase amount is according toMakkonenModel calculation, the calculation formula is as follows:
dMt＝3600α1QVDt-1
in the formula: q is the liquid water content (unit: g.m)-3)；α1Is the collision rate; v is the wind speed (unit: m.s)-1)；Dt-1For the last momentCoating(s)Ice thickness;
when in the stage of thermal ice melting, the ice melting amount is according toFarzanehCalculating the formula, wherein the calculation formula is as follows:
dMt＝-87-80Tt
in the formula TtAt the current timeAir temperature (unit:. degree. C.); 87 and 80 are both empirical values;
when in useIs atSublimationStage of de-icingIn time, its accumulated ice weight change dMt-7, wherein-7 is an empirical value.
The step S33 sets the thickness of the accumulated ice to DtThe calculation formula is as follows:
in the formula: dt-1The diameter of the ice accumulated on the wire (unit: mm) at time (t-1); rhotThe density of ice accumulated on the wire at time t (unit: g cm)-3)；dMtThe 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 DtWhether or not it is greater than Dt-1When D is presenttIs greater than Dt-1Time of maximumCoating(s)Thickness of ice Dm＝DtWhen Dt is smaller than Dt-1Time of maximumCoating(s)Thickness of ice Dm＝Dt-1；
Step S35: and deducing the probability of the fault when the power grid equipment is coated with ice.
Deducing the maximum of the grid equipmentCoating(s)Thickness of ice, said step S34 according toCoating(s)And calculating the probability of failure when the power grid equipment is iced 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 weightdThe probability is calculated as follows:
in the formula: ddIs the maximum design of the power grid equipment lineCoating(s)Ice thickness; dmThe maximum wind power actually suffered by the power grid equipment line; d1＝βDd，β＝0.8；k1Is the coefficient of the first stage, taken as 0.03; k is a radical of2Is 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;
using mercator projection in calculating thunderfall areageodeSicAreAnd (4) inputting the radius of the earth and the longitude and latitude of the area to be calculated by the function, and outputting the area S of the current area for lightning strike.
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 l 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 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 isavThe average height of the lightning conductor is taken from the height of the lightning conductor: n is a power grid lineHundred kilometersThe number of lightning strokes is calculated by the formula that N is 0.015ThWherein T is the annual lightning of the current regionDaily statisticsThe value h is the height of the power grid equipment; s is the area of the current area falling mines; and l is the length of the power grid line.
Step S44: and outputting the fault 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 the modules can be realized in the form that software is called 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. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the application to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable devices. The computer instructions may be stored on 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, computer, server, or data center to another website, 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, discrete hardware components.
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 of the process, and that the scope of the preferred embodiments of the present invention includes additional implementations 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 embodiments 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 power grid equipment failure caused by various natural disasters is characterized by comprising the following steps of: 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 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 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 is calculated 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.
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: rnRepresenting the rainfall of the nth day, and sigma representing summation operation;
the maximum hourly rainfall on the day is set as RhWherein R ishThe calculation formula is as follows:
Rh＝max(ra，rb)
in the formula: r isaData measured for meteorology, representing a drop in 24 hoursRainfall (hourly); r isbFor weather forecast data, the rainfall, max (r), is forecasted for 3 hours in the futurea，rb) Represents by raOr rbMaximum 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 P (R) is as follows:
P(R)＝-6*10-6*R3+0.016R2-0.031R+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(Rh)＝-2*10-6*Rh 5+4*10-4*Rh 4-0.025Rh 3+0.56Rh 2-0.71Rh+3.52
wherein R ishRepresents 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(Rh)
wherein R is the effective accumulated rainfall within 10 days, RhRepresents 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 the relative weight of the terrain, and k1 is the 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.
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，w1) The longitude and latitude of the power grid equipment is set as (j)2，w2)；
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 a1The calculation formula is as follows:
in the formula: vdThe maximum design wind speed of the power grid equipment line; vmThe maximum wind power actually suffered by the power grid equipment line; v1＝βVd，β＝0.8；k1Is the coefficient of the first stage, taken as 0.03; k is a radical of2Is the coefficient of the second stage, taken as 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 calculating the formula as follows:
I＝(0-Tw)ln P/E′H
in the formula: p is the pressure intensity; t iswIs the wet bulb temperature; h relative humidity; e' is an empirical coefficient and takes 0.045 ℃;
setting the accumulated ice weight variation as dM when constructing the accumulated ice weight variation modeltWherein, the change stage of the ice accretion weight variation model comprises: maintenance phase, rime ice accumulation phase, thermal ice melting phase,Stage of sublimation and de-icing；
dM in maintenance phaset＝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: rhowIs the density of water; p is precipitation intensity; v is wind speed;
when in the stage of rime ice deposition, the increase amount is according toMakkonenModel calculation, the calculation formula is as follows:
dMt＝3600α1QVDt-1
in the formula: q is the liquid water content; alpha is alpha1Is the collision rate; v is wind speed; dt-1For the last momentCoating(s)Ice thickness;
when in the stage of thermal ice melting, the ice melting amount is according to aFarznehCalculating the formula, wherein the calculation formula is as follows:
dMt＝-87-80Tt
wherein T istThe temperature at the current time; 87 and 80 are both empirical values;
while in sublimationStage of de-icingIn time, its accumulated ice weight change dMt-7, wherein-7 is an empirical value;
setting the thickness of accumulated ice as DtThe calculation formula is as follows:
wherein: dt-1The ice accretion diameter of the wire at time (t-1); rhotRepresents the ice accretion density of the wire at time t; dMtIs 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 DtWhether or not it is greater than Dt-1When D is presenttIs greater than Dt-1Time of maximumCoating(s)Thickness of ice Dm＝DtWhen D is presenttIs less than Dt-1Time of maximumCoating(s)Thickness of ice Dm＝Dt-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 weightdThe probability is calculated as follows:
in the formula: ddIs the maximum design of the power grid equipment lineCoating(s)Ice thickness; dmThe maximum wind power actually suffered by the power grid equipment line; d1＝βDd，β＝0.8；k1Is the coefficient of the first stage, taken as 0.03; k is a radical of2Is 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 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 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 isavThe average height of the lightning conductor is taken as the height of the lightning conductor; n is a power grid lineHundred kilometersThe number of lightning strokes is calculated by the formula that N is 0.015ThWherein 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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| CN116153019A (en) * | 2023-02-13 | 2023-05-23 | 深圳崎点数据有限公司 | Cloud computing-based power grid disaster early warning system |
| CN117688475A (en) * | 2024-02-04 | 2024-03-12 | 山东电工时代能源科技有限公司 | Disaster prediction-based energy network assessment method, system, terminal and storage medium |
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