Method and system for calculating probability of power line breakage and tower collapse under typhoon disasters

Abstract

The invention discloses a method and system for calculating the probability of power line breakage and tower collapse under typhoon disasters, and the method comprises the steps: obtaining wind speed and rainfall data under the typhoon disasters, carrying out the correlation analysis, obtaining a correlation result, carrying out the modeling of the wind speed data and the rainfall data, and obtaining a distribution model of the wind speed and the rainfall; based on the distribution model, obtaining a probability distribution function and a probability density function of wind speed and rainfall, and constructing a joint probability distribution function and a joint probability density function of wind and rain loads of the power line and the tower through a Copula function; and according to the joint probability distribution function and the joint probability density function of the wind and rain loads of the power line and the tower, and the design load of the power line and the design load of the tower, obtaining the probability of power line breakage and tower collapse. According to the method, the correlation between the wind speed and the rainfall in the typhoon disaster is considered, the wind load probability distribution and the rain load probability distribution are connected by using the Copula theory, and the more accurate probability of power line breakage and tower collapse under the typhoon disaster is obtained.

Description

Technical Field

[0001] The present invention relates to the field of risk assessment of power grid failures under extreme weather conditions, and in particular to a method and system for calculating the probability of power line disconnection and tower collapse under typhoon disasters. Background Art

[0002] Affected by factors such as global climate change, the frequency of extreme disasters such as typhoons is increasing year by year. At the same time, with the continuous increase in transmission voltage levels, the height of transmission towers is also increasing. Since overhead transmission lines are exposed to the natural environment for a long time, they are vulnerable to natural disasters such as typhoons, causing transmission line failures and tower damage and collapse, resulting in huge economic losses. The power grid failure risk assessment technology under extreme weather uses the GIS platform to obtain the line, tower location, and meteorological information in the disaster area to evaluate the line failure risk caused by severe weather such as typhoons and wildfires, and provide quantitative failure risk probability or failure risk level warning information to provide decision support for power grid dispatching, maintenance operations, emergency rescue, etc., enhance the power grid's ability to cope with severe weather conditions, and improve the level of safe operation of the power grid.

[0003] The main cause of typhoon disasters is the wind load on poles and power lines caused by high wind speeds. When the load exceeds the design load level of the poles and power lines, there is a probability of power line disconnection and tower collapse. Typhoons are often accompanied by heavy rains, and the rain load caused by heavy rains on power lines and poles is also a disaster factor that must be considered. In order to obtain a more accurate probability of power line disconnection and tower collapse under typhoon disasters, some studies have considered both wind load and helium load, but the correlation between wind speed and rainfall data under typhoon disasters has not been fully considered and utilized. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the above existing problems, the present invention is proposed. Therefore, the present invention provides a method for calculating the probability of power line disconnection and tower collapse under typhoon disasters to solve the problem of inaccurate prediction caused by not fully considering the correlation between wind speed and rainfall data in the probability calculation of power line disconnection and tower collapse under typhoon disasters.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a method for calculating the probability of power line disconnection and tower collapse under typhoon disasters, comprising:

[0008] Obtain wind speed data and rainfall data during typhoon disasters;

[0009] Performing correlation analysis on the wind speed data and rainfall data to obtain correlation results, and based on the correlation results, modeling the wind speed data and rainfall data to obtain a distribution model of wind speed and rainfall;

[0010] Based on the distribution model of wind speed and rainfall, the probability distribution function and probability density function of wind speed and rainfall are obtained, and then the joint probability distribution function and joint probability density function of wind and rain loads of power lines and towers are constructed through Copula function;

[0011] The probability of power line disconnection and tower collapse is obtained according to the joint probability distribution function and joint probability density function of the wind and rain loads of the power line and the tower, as well as the design load of the power line and the design load of the tower.

[0012] As a preferred solution of the method for calculating the probability of power line disconnection and tower collapse under typhoon disasters described in the present invention, wherein: performing correlation analysis on the wind speed data and rainfall data to obtain correlation results includes:

[0013] According to the wind speed data and rainfall data, a scatter plot is drawn to conduct a qualitative analysis of wind speed and rainfall, and then the wind speed and rainfall are quantitatively analyzed through the correlation coefficient to obtain the correlation results between wind speed and rainfall.

[0014] As a preferred solution of the method for calculating the probability of power line disconnection and tower collapse under typhoon disasters described in the present invention, wherein: according to the correlation result, the wind speed data and rainfall data are modeled to obtain the distribution model of wind speed and rainfall, including:

[0015] The thresholds of wind speed and rainfall are determined by using the excess expectation method. Based on the thresholds, the maximum likelihood method is used to estimate the parameters of the generalized Pareto distribution of the excess data, and a generalized Pareto distribution model of wind speed and rainfall is established.

[0016] As a preferred solution of the method for calculating the probability of power line disconnection and tower collapse under typhoon disasters described in the present invention, the joint probability distribution function and joint probability density function of wind and rain loads of power lines are constructed by Copula function, including:

[0017] Based on wind speed data, rainfall data and power line data, establish wind load and rain load models for power lines;

[0018] According to the wind load and rain load model of the power line, combined with the probability distribution function and probability density function of wind speed and rainfall, the probability distribution of wind load and rain load of the power line is obtained;

[0019] The probability distributions of wind load and rain load of power lines are connected by Copula function to obtain the joint probability distribution function and joint probability density function of wind and rain load of power lines. The joint probability distribution function and joint probability density function of wind and rain load of power lines are expressed as follows:

[0020]

[0021]

[0022] Among them, θ l is the connection coefficient between wind and rain loads on power lines, t Lr is the rain load on the power line, t Lv is the wind load on the power line, F(t Lr ) is the probability distribution of rain load on power lines, F(t Lv ) is the probability distribution of wind load on power lines, F(t Lr , t Lv ) is the joint probability distribution function of wind and rain loads on power lines, f(t Lr , t Tv ) is the joint probability density function of wind and rain loads on power lines.

[0023] As a preferred solution of the method for calculating the probability of power line disconnection and tower collapse under typhoon disasters described in the present invention, the joint probability distribution function and joint probability density function of wind and rain loads of the tower are constructed by Copula function, including:

[0024] Based on wind speed data, rainfall data and tower data, establish the wind load and rain load model of the tower;

[0025] According to the wind load and rain load model of the tower, combined with the probability distribution function and probability density function of wind speed and rainfall, the probability distribution of wind load and rain load of the tower is obtained;

[0026] The probability distributions of wind load and rain load of the tower are connected by Copula function to obtain the joint probability distribution function and joint probability density function of wind and rain load of the tower. The joint probability distribution function and joint probability density function of wind and rain load of the tower are expressed as follows:

[0027]

[0028] Among them, θ t is the connection coefficient between wind and rain loads on the tower, t Tr is the rain load on the tower, t Tv is the wind load on the tower, F(t Tr ) is the probability distribution of rain load on the tower, F(t Tv) is the probability distribution of wind load on the tower, F(t Tr , t Tv ) is the joint probability distribution function of wind and rain loads on the tower, f(t Tr , t Tv ) is the joint probability density function of wind and rain loads on the tower.

[0029] As a preferred solution of the method for calculating the probability of power line disconnection and tower collapse under typhoon disasters described in the present invention, obtaining the probability of power line disconnection includes:

[0030] Based on the joint probability distribution function and joint probability density function of the wind and rain loads of the power line and the design load of the power line, a probability calculation model of power outage under typhoon disaster is obtained. The probability calculation model of power outage is expressed as:

[0031]

[0032] Among them, P L is the probability of power line disconnection, F Lmax is the maximum load that the power line can bear, f(t Lr , t Lv ) is the joint probability density function of wind and rain loads on the power line, Lr is the rainfall on the power line, and Lv is the wind speed on the power line.

[0033] As a preferred solution of the method for calculating the probability of power line disconnection and tower collapse under typhoon disasters described in the present invention, obtaining the probability of tower collapse includes:

[0034] Based on the joint probability distribution function and joint probability density function of the wind and rain loads of the tower, as well as the design load of the tower, a probability calculation model of the tower collapse under typhoon disaster is obtained. The probability calculation model of the tower collapse is expressed as:

[0035]

[0036] Among them, P T is the probability of tower collapse, F Tmax is the maximum load that the tower can bear, f(t Tr , t Tv ) is the joint probability density function of wind and rain loads on the tower, Tr is the rainfall on the tower, and Tv is the wind speed on the tower.

[0037] In a second aspect, the present invention provides a system for calculating the probability of power line disconnection and tower collapse under typhoon disasters, comprising:

[0038] Data acquisition module, used to obtain wind speed data and rainfall data under typhoon disasters;

[0039] A data modeling module, used for performing correlation analysis on the wind speed data and rainfall data to obtain correlation results, and based on the correlation results, modeling the wind speed data and rainfall data to obtain a distribution model of wind speed and rainfall;

[0040] A joint probability distribution modeling module is used to obtain the probability distribution function and probability density function of wind speed and rainfall based on the distribution model of wind speed and rainfall, and then construct the joint probability distribution function and joint probability density function of wind and rain loads of power lines and towers through Copula function;

[0041] The risk assessment module is used to obtain the probability of power line disconnection and tower collapse based on the joint probability distribution function and joint probability density function of the wind and rain loads of the power lines and towers, as well as the design loads of the power lines and towers.

[0042] In a third aspect, the present invention provides a computing device, comprising:

[0043] Memory and processor;

[0044] The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the method for calculating the probability of power line disconnection and tower collapse under typhoon disasters are implemented.

[0045] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the method for calculating the probability of power line failure and tower collapse under a typhoon disaster.

[0046] Compared with the prior art, the present invention has the following beneficial effects: the present invention adopts the generalized Pareto distribution to fit the wind speed and rainfall data, and obtains a more accurate and appropriate wind speed and rainfall distribution model; the present invention takes into account the rainstorm disaster-causing factors in typhoon disasters, and at the same time, based on the correlation between wind speed and rainfall, the Copula theory is used to connect the wind load probability distribution and the rain load probability distribution, and obtain a more accurate probability of power line disconnection and tower collapse under typhoon disasters; the present invention can be applied to the risk fault assessment of power grids in typhoon-affected areas, and can also be used to construct an anticipated accident set for the comprehensive defense system of the power system, and has certain theoretical value and engineering value. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0048] Figure 1 It is a schematic diagram of the overall process of a method for calculating the probability of power line disconnection and tower collapse under a typhoon disaster according to an embodiment of the present invention;

[0049] Figure 2 A schematic diagram of a result of selecting a threshold value of rainfall for a method for calculating the probability of power line disconnection and tower collapse under a typhoon disaster according to an embodiment of the present invention;

[0050] Figure 3 A schematic diagram of the results of selecting the wind speed threshold value for a method for calculating the probability of power line disconnection and tower collapse under a typhoon disaster according to an embodiment of the present invention;

[0051] Figure 4 A schematic diagram of a joint probability distribution result of power line disconnection in a method for calculating the probability of power line disconnection and tower collapse under a typhoon disaster according to an embodiment of the present invention;

[0052] Figure 5 This is a schematic diagram of the joint probability distribution results of tower collapses in a method for calculating the probability of power line disconnection and tower collapses during a typhoon disaster described in an embodiment of the present invention. DETAILED DESCRIPTION

[0053] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0054] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0055] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0056] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0057] At the same time, in the description of the present invention, it should be noted that the orientations or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the orientations or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the system or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0058] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0059] Example 1

[0060] Reference Figure 1 , which is an embodiment of the present invention, provides a method for calculating the probability of power line disconnection and tower collapse under typhoon disasters, comprising:

[0061] S100: Obtain wind speed data and rainfall data under typhoon disaster;

[0062] In an embodiment of the present application, after obtaining the wind speed data and rainfall data under the typhoon disaster, the wind speed data and rainfall data are preprocessed, and the data acquisition and preprocessing specifically include: with the help of GIS technology, by querying the historical observation data of meteorological stations in the typhoon occurrence area, selecting two significant disaster-causing factors, namely 6-hour precipitation and the maximum wind speed at a height of 10 meters, and completing the missing data through sorting, calculation and spatial interpolation, to obtain a complete data set of wind speed and rainfall within a certain time scale in the typhoon occurrence area; comprehensively considering the accuracy and complexity of the wind speed data and rainfall data, selecting a spatial resolution of 1km*1km and a time resolution of 12 hours, and screening and simplifying the typhoon wind speed and rainfall intensity data in the typhoon occurrence area.

[0063] S102: performing correlation analysis on the wind speed data and the rainfall data to obtain correlation results, and based on the correlation results, modeling the wind speed data and the rainfall data to obtain a distribution model of the wind speed and rainfall;

[0064] Preferably, according to the wind speed data and rainfall data, a scatter plot is drawn to perform a qualitative analysis on the wind speed and rainfall, and then a correlation coefficient is used to perform a quantitative analysis on the wind speed and rainfall to obtain a correlation result between the wind speed and rainfall;

[0065] Specifically, according to the wind speed and rainfall data selected by the resolution in step 100, the wind speed unit is m / s, and the rainfall unit is mm, a scatter plot of wind speed and rainfall is drawn, and a simple judgment is made on the linear correlation between wind speed and rainfall; after a simple judgment, the Pearson correlation coefficient is used to analyze the correlation between wind speed and rainfall data under typhoon disasters again:

[0066]

[0067] Among them, r represents the correlation coefficient between wind speed and rainfall, x i and i represent samples of wind speed and rainfall respectively, and They represent the mean values ​​of the samples, respectively, and n is the number of samples;

[0068] It has been verified that there is a strong positive correlation between wind speed and rainfall;

[0069] Preferably, the thresholds of wind speed and rainfall are determined by using the excess expectation method, and based on the thresholds, the parameters of the generalized Pareto distribution are estimated for the excess data using the maximum likelihood method to establish a generalized Pareto distribution model of wind speed and rainfall;

[0070] Specifically, taking the rainfall threshold as an example, the threshold of the generalized Pareto distribution of rainfall determined by the excess expectation method is expressed as:

[0071]

[0072] Among them, r t Indicates that the rainfall is distributed in a sequence from small to large, the number is N r ,u r represents the rainfall threshold, k = min{t|r t >u r}, according to the point (u r ,e(u r )) and select the largest possible threshold u r , so that when r ≥ u r When, e(u r ) is an approximate linear function;

[0073] Determining the scale parameter σ of the generalized Pareto distribution of rainfall using the maximum likelihood method r and the shape parameter ξ r , the log-likelihood function is expressed as:

[0074]

[0075] in, is the number of rainfall exceeding limit samples, Nu is the total number of rainfall samples, y i is the rainfall of sample i;

[0076] For σ r and r Find the partial derivative, the KKT condition for the logarithmic maximum likelihood problem is:

[0077]

[0078] in, is the number of rainfall exceeding limit samples, N u is the total number of rainfall samples, y i is the rainfall of sample i;

[0079] By solving the nonlinear algebraic equation, we can obtain the maximum likelihood estimate of the parameter of the generalized Pareto distribution: r and r ;

[0080] It should be noted that the steps for selecting the wind speed threshold and parameter range are consistent with the rainfall threshold and parameter estimation;

[0081] It should also be noted that the present invention conducts a qualitative analysis of wind speed and rainfall by drawing a scatter plot, quickly and intuitively determines the possible linear relationship between the two, and then uses the Pearson correlation coefficient to conduct an accurate quantitative analysis of wind speed and rainfall, and determines that there is a strong positive correlation between the two, which provides a strong basis for subsequent modeling; in the modeling process, the excess expectation method is selected to determine the thresholds of wind speed and rainfall, which can effectively identify extreme values ​​in the data and provide a suitable threshold for subsequent generalized Pareto distribution modeling. After determining the threshold, the maximum likelihood method is used to estimate the parameters of the generalized Pareto distribution, including scale parameters and shape parameters, which not only takes into account the overall distribution of the data, but also makes full use of the information in the excess data, so that the established model is closer to the actual data.

[0082] S104: Based on the distribution model of wind speed and rainfall, the probability distribution function and probability density function of wind speed and rainfall are obtained, and then the joint probability distribution function and joint probability density function of wind and rain loads of power lines and towers are constructed through Copula function;

[0083] It should be noted that the probability distribution of wind and rain loads on power lines and towers presents a lower fat-tail characteristic. Considering Clayton-Copula, that is, the probability scatter points of the Copula function have a lower left fat-tail characteristic, Clayton-Copula is selected to construct the joint distribution function of wind load and rain load on power lines. The probability distribution function and probability density function of the Clayton-Copula function are:

[0084]

[0085] The Copula function can connect the marginal distribution functions u and v with a one-dimensional marginal distribution. F(u,v) is the joint distribution function of u and v, and θ is the connection coefficient of the joint distribution.

[0086] Based on the distribution model of wind speed and rainfall, the probability distribution function and probability density function of wind speed and rainfall are obtained. The probability distribution function and probability density function of rainfall r are:

[0087]

[0088] Among them, N r is the number of rainfall samples, U r is the rainfall threshold, represents the number of rainfall samples exceeding the threshold, σ r and r are the scale parameter and shape parameter of the generalized Pareto distribution of rainfall;

[0089] The probability distribution function and probability density function of wind speed v are:

[0090]

[0091] Among them, N v is the number of wind speed samples, U v is the wind speed threshold, represents the number of wind speed samples exceeding the threshold, σ v and v are the scale parameter and shape parameter of the generalized Pareto distribution of wind speed;

[0092] Preferably, a wind load and rain load model of the power line is established based on the wind speed data, the rainfall data and the power line data;

[0093] In the embodiment of the present application, the rain load calculation model T of the power line Lr for:

[0094] T Lr =kp r v 2 d 3 L

[0095] Among them, p r represents rainfall density, v represents rain velocity, which is assumed to be equal to wind velocity, d represents the diameter of raindrops, L represents the length of power lines, and k represents the correction factor;

[0096] In the embodiment of the present application, the wind load calculation model T of the power line Lv for:

[0097]

[0098] in, represents the wind pressure unevenness coefficient, S represents the shape coefficient of the power line, D represents the power line diameter, L represents the length of the power line, and v represents the wind speed;

[0099] Preferably, according to the wind load and rain load model of the power line, the probability distribution of the wind load and rain load of the power line is obtained by combining the probability distribution function and probability density function of wind speed and rainfall;

[0100] In the embodiment of the present application, the probability distribution of rain load on the power line F(t Lr )for:

[0101]

[0102] Among them, p r represents rainfall density, v represents rain velocity, which is assumed to be equal to wind speed, d represents the diameter of raindrops, L represents the length of power lines, k represents the correction factor, r represents rainfall, and t Lr is the rain load on the power line, is the upper limit of the double integral of the rain load on the power line;

[0103] In the embodiment of the present application, the probability distribution of wind load on the power line F(t Lv )for:

[0104]

[0105] Among them, ε represents the wind pressure unevenness coefficient, S represents the shape coefficient of the power line, D represents the power line diameter, L represents the length of the power line, v represents the wind speed, and t Lv is the wind load on the power line, q is the upper limit of the double integral of the wind load on the power line, and r represents the rainfall;

[0106] Preferably, the probability distributions of wind load and rain load of the power line are connected by using Copula function to obtain the joint probability distribution function and joint probability density function of wind and rain load of the power line. The joint probability distribution function and joint probability density function of wind and rain load of the power line are expressed as:

[0107]

[0108] Among them, θ l is the connection coefficient between wind and rain loads on power lines, t Lr is the rain load on the power line, t Lv is the wind load on the power line, F(t Lr ) is the probability distribution of rain load on power lines, F(t Lv ) is the probability distribution of wind load on power lines, F(t Lr , tLv ) is the joint probability distribution function of wind and rain loads on power lines, f(t L r, t Lv ) is the joint probability density function of wind and rain loads on power lines.

[0109] Preferably, based on the wind speed data, rainfall data and tower data, a wind load and rain load model of the tower is established;

[0110] In the embodiment of the present application, the rain load calculation model T of the tower Tr for:

[0111]

[0112] Among them, A r represents the area of ​​the tower affected by raindrops, ρ r represents rainfall density, v represents rain velocity, which is assumed to be equal to wind speed, d represents the diameter of raindrops, and n represents the number of rainfall samples;

[0113] In the embodiment of the present application, the tower wind load calculation model T Tv for:

[0114]

[0115] Where ρ represents the air density, C d (α) represents the drag coefficient of the tower when the wind load acts at an angle of attack of α. f It represents the effective area of ​​the tower components that bear the wind pressure, and v represents the wind speed;

[0116] Preferably, according to the wind load and rain load model of the tower, the probability distribution of the wind load and rain load of the tower is obtained by combining the probability distribution function and probability density function of wind speed and rainfall;

[0117] In the embodiment of the present application, the probability distribution of rain load on the tower is F(t Tr ):

[0118]

[0119] Among them, A r represents the area of ​​the tower affected by raindrops, ρ r represents rainfall density, v represents rain velocity, which is assumed to be equal to wind velocity, d represents the diameter of raindrops, n represents the number of rainfall samples, and δ is the upper limit of the double integral of rain load on the tower;

[0120] In the embodiment of the present application, the probability distribution of wind load on the tower F(t Tv ):

[0121]

[0122] Where ρ represents the air density, C d (α) represents the drag coefficient of the tower when the wind load acts at an angle of attack of α. f represents the effective area of ​​the tower components bearing wind pressure, v represents the wind speed, and ∈ is the upper limit of the double integral of the wind load on the tower;

[0123] Preferably, the probability distributions of the wind load and rain load of the tower are connected by using a Copula function to obtain the joint probability distribution function and joint probability density function of the wind and rain loads of the tower. The joint probability distribution function and joint probability density function of the wind and rain loads of the tower are expressed as:

[0124]

[0125] Among them, θ t is the connection coefficient between wind and rain loads on the tower, t Tr is the rain load on the tower, t Tv is the wind load on the tower, F(t Tr ) is the probability distribution of rain load on the tower, F(t Tv ) is the probability distribution of wind load on the tower, F(t Tr , t Tv ) is the joint probability distribution function of wind and rain loads on the tower, f(t Tr , t Tv ) is the joint probability density function of wind and rain loads on the tower;

[0126] The joint probability distribution function and joint probability density function of wind and rain loads of power lines and towers are constructed through Copula functions. The connection coefficients of the Copula functions of power line loads and tower loads are solved by the maximum likelihood method. Take the calculation of power line loads as an example:

[0127]

[0128] Among them, C(F(t lr ),F(t lv );θ) represents the probability density function of the Copula function of wind and rain loads on power lines;

[0129]

[0130] Where n is the number of wind and rain load samples, F(t lr,i ) and F(t lv,i ) is the probability value of the i-th sample wind and rain load, θ l is the maximum likelihood estimate;

[0131] It should be noted that the connection coefficient θ of the Copula function of the tower load can be obtained by the same method:t ;

[0132] It should also be noted that the present invention integrates the distribution models of wind speed and rainfall to obtain their respective probability distribution functions and probability density functions. In order to more accurately evaluate the risks of power lines and poles in extreme weather such as typhoons, the probability distribution of wind and rain loads of power lines and poles is considered to have a lower thick tail characteristic, and the Clayton-Copula function is selected, whose lower left thick tail characteristic is consistent with the actual situation. The introduction of the Copula function not only simplifies the calculation process of complex joint distribution, but more importantly, it accurately captures the correlation between wind speed and rainfall, and provides a powerful analysis tool for the joint probability distribution of wind and rain loads of power lines and poles, which can more comprehensively evaluate the stress conditions of power lines and poles in extreme weather.

[0133] S106: Obtain the probability of power line disconnection and tower collapse according to the joint probability distribution function and joint probability density function of wind and rain loads of power lines and towers, as well as the design loads of power lines and towers;

[0134] Preferably, based on the joint probability distribution function and joint probability density function of the wind and rain loads of the power line and the design load of the power line, a probability calculation model of power line disconnection under typhoon disaster is obtained, and the probability calculation model of power line disconnection is expressed as:

[0135]

[0136] Among them, P L is the probability of power line disconnection, F Lma is the maximum load that the power line can bear, f(t Lr , t Lv ) is the joint probability density function of wind and rain loads on the power line, Lr is the rainfall on the power line, Lv is the wind speed on the power line, M L Indicates the load acting on the power line;

[0137] In the embodiment of the present application, the load expression of the power line is:

[0138]

[0139] Among them, T Lr represents rain load, T Lv represents wind load, L represents the length of the power line, ρ l represents the mass density of electric lines, and g represents the gravitational constant;

[0140] Preferably, based on the joint probability distribution function and joint probability density function of the wind and rain loads of the tower, and the design load of the tower, a probability calculation model of the tower collapse under a typhoon disaster is obtained, and the probability calculation model of the tower collapse is expressed as:

[0141]

[0142] Among them, P T is the probability of tower collapse, F Tmax is the maximum load that the tower can bear, f(t Tr , t Tv ) is the joint probability density function of wind and rain loads on the tower, Tr is the rainfall on the tower, Tv is the wind speed on the tower, M T Indicates the load acting on the tower;

[0143] In the embodiment of the present application, the load expression of the tower is:

[0144] M T =T Tr +T Tv

[0145] Among them, T Tr represents rain load, T Lv represents wind load;

[0146] It should be noted that the present invention establishes a probability calculation model for power line breaks and tower collapses by constructing a joint probability distribution function and a joint probability density function of wind and rain loads on power lines and towers, and combining the design loads of power lines and towers, thereby improving the accuracy of safety assessments of power lines and towers under extreme weather conditions such as typhoons; by accurately calculating the probabilities of power line breaks and tower collapses, it can provide an important reference basis for the safe operation of the power grid, thereby helping decision makers to formulate reasonable risk prevention and control measures and emergency plans.

[0147] The above is a schematic scheme of a method for calculating the probability of power line disconnection and tower collapse under typhoon disasters in this embodiment. It should be noted that the technical scheme of the system for calculating the probability of power line disconnection and tower collapse under typhoon disasters and the technical scheme of the method for calculating the probability of power line disconnection and tower collapse under typhoon disasters belong to the same concept. For details not described in detail in the technical scheme of the system for calculating the probability of power line disconnection and tower collapse under typhoon disasters in this embodiment, please refer to the description of the technical scheme of the method for calculating the probability of power line disconnection and tower collapse under typhoon disasters.

[0148] In this embodiment, the power line disconnection and tower collapse probability calculation system under typhoon disaster includes:

[0149] Data acquisition module, used to obtain wind speed data and rainfall data under typhoon disasters;

[0150] A data modeling module is used to perform correlation analysis on wind speed data and rainfall data to obtain correlation results, and based on the correlation results, model the wind speed data and rainfall data to obtain a distribution model of wind speed and rainfall;

[0151] The joint probability distribution modeling module is used to obtain the probability distribution function and probability density function of wind speed and rainfall based on the distribution model of wind speed and rainfall, and then construct the joint probability distribution function and joint probability density function of wind and rain loads of power lines and towers through the Copula function;

[0152] The risk assessment module is used to obtain the probability of power line disconnection and tower collapse based on the joint probability distribution function and joint probability density function of wind and rain loads of power lines and towers, as well as the design loads of power lines and towers.

[0153] This embodiment also provides a computing device, which is applicable to the case of calculating the probability of power line disconnection and tower collapse under typhoon disasters, including:

[0154] Memory and processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the method for calculating the probability of power line disconnection and tower collapse under typhoon disasters as proposed in the above embodiment.

[0155] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for calculating the probability of power line disconnection and tower collapse under typhoon disasters as proposed in the above embodiment is implemented.

[0156] The storage medium proposed in this embodiment and the method for calculating the probability of power line disconnection and tower collapse under typhoon disasters proposed in the above embodiment belong to the same inventive concept. The technical details not described in detail in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0157] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ReadOnly, Memory, ROM), random access memory (RandomAccess Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform the methods of various embodiments of the present invention.

[0158] Example 2

[0159] Reference Figure 2-5Table 1 and Table 2 are an embodiment of the present invention, which provide a method for calculating the probability of power line disconnection and tower collapse under typhoon disasters. In order to verify its beneficial effects, comparison results of two schemes are provided.

[0160] Taking a coastal area severely hit by typhoons as an example, for 220kV transmission lines in the area, based on the present invention, the probability of power line disconnection and tower collapse under typhoon disasters is calculated using Copula theory.

[0161] First, the wind speed and rainfall data are processed using the excess expectation method to select a suitable wind speed threshold U v and rainfall threshold U r ,like Figure 2 and Figure 3 As shown, U r When ≥15mm, e(U r ) approximate linear function, U v ≥20m / s, e(U v ) approximates a linear function, so the wind speed threshold U is selected v =20m / s, rainfall threshold U r =15mm;

[0162] Then, the maximum likelihood method is used to estimate the generalized Pareto distribution parameters of wind speed and rainfall to obtain the probability distribution of wind speed and rainfall. Combined with the wind load and rain load models of power lines and towers, the probability distribution of wind and rain loads on power lines and towers is calculated.

[0163] Finally, using the Copula theory, the probability distribution of wind load and rain load of power lines are connected by Clayton-Copula to obtain the joint probability density of wind and rain load of power lines. Then, the joint probability of power line disconnection under typhoon disaster is calculated by combining the design load and applied load of power lines. Figure 4 Similarly, the joint probability of tower collapse under typhoon disaster can be obtained as Figure 5 .

[0164] In the embodiment of the present invention, the designed wind-rain load of the pole tower is 80kN, and the designed wind-rain load of the power line is 120kN; the probability of line breakage and tower collapse under 8 groups of different wind and rain loads is calculated, and the probability of line breakage and tower collapse obtained without considering the correlation between wind and rain factors is compared with the probability of line breakage and tower collapse, and the results are shown in Table 1;

[0165] Table 1 Comparison of the probability of disconnection and tower collapse obtained by using Copula theory and not using it

[0166]

[0167]

[0168] It can be seen from Table 1 that with the increase of wind load and rain load, the probability of line breakage and tower collapse increases rapidly. Compared with the failure probability results without considering the wind and rain correlation, it is found that the probability estimate without considering the correlation is large and too conservative, which will increase the cost investment of transmission lines and towers in the initial design and cause a waste of defense and repair resources;

[0169] On the other hand, when the wind and rain loads increase, the change in the numerical value of the failure probability is not sensitive enough. In contrast, the method proposed in the present invention has a certain accuracy and sensitivity in calculating the probability of power line disconnection and tower collapse under typhoon disasters.

[0170] It can be seen from the results of the above embodiments that the present invention is a method for calculating the probability of power line disconnection and tower collapse under typhoon disasters based on Copula theory. The generalized Pareto distribution is used to model the wind speed and rainfall under typhoon disasters, and the probability distribution of wind and rain loads is calculated based on the wind and rain load model. The correlation between wind and rain factors is considered, and the probability distribution of wind and rain loads is connected using Copula theory to calculate the probability of power line disconnection and tower collapse. The proposed method can more comprehensively consider the disaster-causing factors of typhoons and obtain a more accurate probability of line disconnection and tower collapse. While ensuring the safe operation of the power grid and saving disaster prevention and repair resources, it has a high sensitivity for calculating the probability of power line disconnection and tower collapse under typhoon disasters.

[0171] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for calculating the probability of power line disconnection and tower collapse under typhoon disasters, characterized in that: include: Obtain wind speed data and rainfall data under typhoon disasters; Performing correlation analysis on the wind speed data and rainfall data to obtain correlation results, and based on the correlation results, modeling the wind speed data and rainfall data to obtain a distribution model of wind speed and rainfall; Based on the distribution model of wind speed and rainfall, the probability distribution function and probability density function of wind speed and rainfall are obtained, and then the joint probability distribution function and joint probability density function of wind and rain loads of power lines and towers are constructed through Copula function; The probability of power line disconnection and tower collapse is obtained according to the joint probability distribution function and joint probability density function of the wind and rain loads of the power line and the tower, as well as the design load of the power line and the design load of the tower.

2. The method for calculating the probability of power line disconnection and tower collapse under typhoon disaster according to claim 1, characterized in that: Performing correlation analysis on the wind speed data and rainfall data to obtain correlation results includes: According to the wind speed data and rainfall data, a scatter plot is drawn to conduct a qualitative analysis of wind speed and rainfall, and then the wind speed and rainfall are quantitatively analyzed through the correlation coefficient to obtain the correlation results between wind speed and rainfall.

3. The method for calculating the probability of power line disconnection and tower collapse under typhoon disaster according to claim 1 or 2, characterized in that: According to the correlation result, modeling the wind speed data and rainfall data to obtain a distribution model of wind speed and rainfall includes: The thresholds of wind speed and rainfall are determined by using the excess expectation method. Based on the thresholds, the maximum likelihood method is used to estimate the parameters of the generalized Pareto distribution of the excess data, and a generalized Pareto distribution model of wind speed and rainfall is established.

4. The method for calculating the probability of power line disconnection and tower collapse under typhoon disaster according to claim 3, characterized in that: The joint probability distribution function and joint probability density function of wind and rain loads of power lines are constructed through Copula functions, including: Based on wind speed data, rainfall data and power line data, establish wind load and rain load models for power lines; According to the wind load and rain load model of the power line, combined with the probability distribution function and probability density function of wind speed and rainfall, the probability distribution of wind load and rain load of the power line is obtained; The probability distributions of wind load and rain load of power lines are connected by Copula function to obtain the joint probability distribution function and joint probability density function of wind and rain load of power lines. The joint probability distribution function and joint probability density function of wind and rain load of power lines are expressed as follows: Among them, θ l is the connection coefficient between wind and rain loads on power lines, t Lr is the rain load on the power line, t Lv is the wind load on the power line, F(t Lr ) is the probability distribution of rain load on power lines, F(t Lv ) is the probability distribution of wind load on power lines, F(t Lr , t Lv ) is the joint probability distribution function of wind and rain loads on power lines, f(t Lr , t Lv ) is the joint probability density function of wind and rain loads on power lines.

5. The method for calculating the probability of power line disconnection and tower collapse under typhoon disaster according to claim 4, characterized in that: The joint probability distribution function and joint probability density function of wind and rain loads of the tower are constructed through Copula function, including: Based on wind speed data, rainfall data and tower data, establish the wind load and rain load model of the tower; According to the wind load and rain load model of the tower, combined with the probability distribution function and probability density function of wind speed and rainfall, the probability distribution of wind load and rain load of the tower is obtained; The probability distributions of wind load and rain load of the tower are connected by Copula function to obtain the joint probability distribution function and joint probability density function of wind and rain load of the tower. The joint probability distribution function and joint probability density function of wind and rain load of the tower are expressed as follows: Among them, θ t is the connection coefficient between wind and rain loads on the tower, t Tr is the rain load on the tower, t Tv is the wind load on the tower, F(t Tr ) is the probability distribution of rain load on the tower, F(t Tv ) is the probability distribution of wind load on the tower, F(t Tr , t Tv ) is the joint probability distribution function of wind and rain loads on the tower, f(t Tr , t Tv ) is the joint probability density function of wind and rain loads on the tower.

6. The method for calculating the probability of power line disconnection and tower collapse under typhoon disaster according to claim 4, characterized in that: Obtaining the probability of power outage includes: Based on the joint probability distribution function and joint probability density function of the wind and rain loads of the power line and the design load of the power line, a probability calculation model of power outage under typhoon disaster is obtained. The probability calculation model of power outage is expressed as: Among them, P L is the probability of power line disconnection, F Lmax is the maximum load that the power line can bear, f(t Lr , t Lv ) is the joint probability density function of wind and rain loads on the power line, Lr is the rainfall on the power line, and Lv is the wind speed on the power line.

7. The method for calculating the probability of power line disconnection and tower collapse under typhoon disaster according to claim 5, characterized in that: Obtaining the probability of tower collapse includes: Based on the joint probability distribution function and joint probability density function of the wind and rain loads of the tower, as well as the design load of the tower, a probability calculation model of the tower collapse under typhoon disaster is obtained. The probability calculation model of the tower collapse is expressed as: Among them, P T is the probability of tower collapse, F Tmax is the maximum load that the tower can bear, f(t Tr , t Tv ) is the joint probability density function of wind and rain loads on the tower, Tr is the rainfall on the tower, and Tv is the wind speed on the tower.

8. A system for calculating the probability of power line disconnection and tower collapse under typhoon disasters, characterized in that: include, Data acquisition module, used to obtain wind speed data and rainfall data under typhoon disasters; A data modeling module, used for performing correlation analysis on the wind speed data and rainfall data to obtain correlation results, and based on the correlation results, modeling the wind speed data and rainfall data to obtain a distribution model of wind speed and rainfall; A joint probability distribution modeling module is used to obtain the probability distribution function and probability density function of wind speed and rainfall based on the distribution model of wind speed and rainfall, and then construct the joint probability distribution function and joint probability density function of wind and rain loads of power lines and towers through Copula function; The risk assessment module is used to obtain the probability of power line disconnection and tower collapse based on the joint probability distribution function and joint probability density function of the wind and rain loads of the power lines and towers, as well as the design loads of the power lines and towers.

9. An electronic device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the method for calculating the probability of power line failure and tower collapse under typhoon disasters described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the method for calculating the probability of power line disconnection and tower collapse under a typhoon disaster as described in any one of claims 1 to 7.

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