CN112163331A - Distribution network line vulnerability calculation method and related device - Google Patents
Distribution network line vulnerability calculation method and related device Download PDFInfo
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Abstract
The application discloses a distribution network line vulnerability calculation method and a related device, wherein the method comprises the following steps: according to the structural characteristic and the distribution law of pole in the distribution network system obtain the pole parameter, the pole parameter includes: rod body characteristic parameters, foundation characteristics, soil property parameters, wind field parameters and lead span; sampling the electric pole parameters by adopting a preset Latin hypercube sampling algorithm to obtain uniform sample parameters; inputting the sample parameters into a preset Kriging agent model for calculation to obtain the structural resistance of the electric pole under different electric pole failure modes; when the structural resistance of the electric pole is smaller than the preset structural load effect, calculating the vulnerability of the electric pole of the distribution network line according to a preset electric pole reliability theory to obtain an electric pole vulnerability curve, and calculating the preset structural load effect according to a preset cantilever beam force balance basic principle. The method and the device can solve the technical problems that the existing calculation method is limited and the time cost is high.
Description
Technical Field
The application relates to the technical field of power grid disaster prevention, in particular to a distribution network line vulnerability calculation method and a related device.
Background
The main failure modes of the distribution network line in typhoon weather are large-scale reversing, diagonal rods, broken lines and the like, and the typhoon wind speed exceeding the design standard is the main reason of the large-scale reversing and broken lines of the distribution network line. Distribution network line destructive faults caused by typhoons are large in influence range and long in duration, and huge economic losses are brought to the society.
In the prior art, a method for constructing a model is mostly adopted to solve the reliability or vulnerability of a power transmission line in a distribution network system in typhoon weather, but the existing model considers fewer factors when calculating the vulnerability and lacks theoretical basis, so that the model has low applicability and limitation on calculation results of distribution network lines in different regions; in addition, the wire span area of the distribution network system is too large, the types of electric poles are various, and the calculation is very time-consuming.
Disclosure of Invention
The application provides a distribution network line vulnerability calculation method and a related device, which are used for solving the technical problems that the existing calculation method is limited and the time cost is high.
In view of this, a first aspect of the present application provides a distribution network line vulnerability calculating method, including:
the method comprises the following steps of obtaining electric pole parameters according to structural characteristics and distribution rules of electric poles in a distribution network system, wherein the electric pole parameters comprise: rod body characteristic parameters, foundation characteristics, soil property parameters, wind field parameters and lead span;
sampling the electric pole parameters by adopting a preset Latin hypercube sampling algorithm to obtain uniform sample parameters;
inputting the sample parameters into a preset Kriging agent model for calculation to obtain the structural resistance of the electric pole under different electric pole failure modes;
and when the structural resistance of the electric pole is smaller than the preset structural load effect, calculating the electric pole vulnerability of the distribution network line according to a preset electric pole reliability theory to obtain an electric pole vulnerability curve, wherein the preset structural load effect is obtained according to a preset cantilever beam force balance basic principle.
Optionally, the preset Kriging agent model is expressed by a first preset formula as follows:
y(x)＝f(x)Tβ+z(x)；
wherein f (x) is a regression function set, beta is a regression coefficient vector, z (x) is a zero-mean Gaussian process, and the standard deviation corresponding to the zero-mean Gaussian process is sigmayThe covariance matrix is E (z).
Optionally, when the structural resistance of the electric pole is smaller than the preset structural load effect, calculating the electric pole vulnerability of the distribution network line according to a preset electric pole reliability theory to obtain an electric pole vulnerability curve, including:
when the structural resistance of the electric pole is smaller than the preset structural load effect, a second preset formula is obtained according to a preset electric pole reliability theory, wherein the second preset formula is as follows:
wherein, PfFor the failure probability of the electric pole, R is the structural resistance of the electric pole, S is the load effect of the preset structure, fZ(z) is a probability density function corresponding to the structural function of the electric pole;
and calculating the electric pole vulnerability of the distribution network line according to the second preset formula to obtain an electric pole vulnerability curve.
Optionally, calculate the pole vulnerability of joining in marriage the net twine way according to preset pole reliability theory, obtain pole vulnerability curve, later still include:
and carrying out vulnerability assessment on the distribution network line of the distribution network system according to the pole vulnerability curve to obtain an assessment result.
A second aspect of the present application provides a distribution network line vulnerability calculating apparatus, including:
the acquisition module is used for acquiring the electric pole parameters according to the structural characteristics and the distribution rules of the electric pole in the distribution network system, and the electric pole parameters comprise: rod body characteristic parameters, foundation characteristics, soil property parameters, wind field parameters and lead span;
the sampling module is used for sampling the electric pole parameters by adopting a preset Latin hypercube sampling algorithm to obtain uniform sample parameters;
the first calculation module is used for inputting the sample parameters into a preset Kriging agent model for calculation to obtain the structural resistance of the electric pole under different electric pole failure modes;
and the second calculation module is used for calculating the electric pole vulnerability of the distribution network line according to a preset electric pole reliability theory to obtain an electric pole vulnerability curve when the structural resistance of the electric pole is smaller than a preset structural load effect, and the preset structural load effect is obtained according to a preset cantilever beam force balance basic principle.
Optionally, the preset Kriging agent model is expressed by a first preset formula as follows:
y(x)＝f(x)Tβ+z(x)；
wherein f (x) is a regression function set, beta is a regression coefficient vector, z (x) is a zero-mean Gaussian process, and the standard deviation corresponding to the zero-mean Gaussian process is sigmayThe covariance matrix is E (z).
Optionally, the second calculating module is specifically configured to:
when the structural resistance of the electric pole is smaller than the preset structural load effect, a second preset formula is obtained according to a preset electric pole reliability theory, wherein the second preset formula is as follows:
wherein, PfFor the failure probability of the electric pole, R is the structural resistance of the electric pole, S is the load effect of the preset structure, fZ(z) is a probability density function corresponding to the structural function of the electric pole;
and calculating the electric pole vulnerability of the distribution network line according to the second preset formula to obtain an electric pole vulnerability curve.
Optionally, the method further includes:
and the evaluation module is used for evaluating the vulnerability of the distribution network line of the distribution network system according to the electric pole vulnerability curve to obtain an evaluation result.
A third aspect of the application provides a distribution network line vulnerability computing device, the device comprising a processor and a memory:
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is used for executing the distribution network line vulnerability calculation method in the above method embodiment according to the instructions in the program code.
A fourth aspect of the present application provides a computer-readable storage medium for storing program codes, where the program codes are used to execute the distribution network line vulnerability calculation method in the above method embodiments.
According to the technical scheme, the embodiment of the application has the following advantages:
the application provides a distribution network line vulnerability calculation method, which comprises the following steps: according to the structural characteristic and the distribution law of pole in the distribution network system obtain the pole parameter, the pole parameter includes: rod body characteristic parameters, foundation characteristics, soil property parameters, wind field parameters and lead span; sampling the electric pole parameters by adopting a preset Latin hypercube sampling algorithm to obtain uniform sample parameters; inputting the sample parameters into a preset Kriging agent model for calculation to obtain the structural resistance of the electric pole under different electric pole failure modes; when the structural resistance of the electric pole is smaller than the preset structural load effect, calculating the vulnerability of the electric pole of the distribution network line according to a preset electric pole reliability theory to obtain an electric pole vulnerability curve, and calculating the preset structural load effect according to a preset cantilever beam force balance basic principle.
According to the distribution network line vulnerability calculation method, in order to enable the calculation method to be more universal, parameter selection is carried out by integrating characteristics of an electric pole and a wire in a distribution network system, the wire span in the electric pole parameter is an important influence element for describing the wire to the electric pole, the rod body characteristic parameter of the electric pole directly concerns the wind resistance of the electric pole, the foundation characteristic and the soil property parameter are used for describing the influence of environmental factors on the collapse of the electric pole, and the wind field parameter is used for describing the destructive influence caused by typhoon; through comprehensive analysis, a plurality of influence factors of different levels are selected, so that the calculated vulnerability reliability is higher; and the preset Latin hypercube sampling algorithm is adopted to sample to obtain research sample parameters, so that the calculation process can be effectively accelerated, the time cost is saved, and the time consumption is reduced. Therefore, the method and the device can solve the technical problems that the existing calculation method is limited and the time cost is high.
Drawings
Fig. 1 is a schematic flowchart of a distribution network line vulnerability calculation method provided in an embodiment of the present application;
fig. 2 is a schematic structural diagram of a distribution network line vulnerability calculating apparatus provided in an embodiment of the present application.
Detailed Description
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
For convenience of understanding, referring to fig. 1, a first embodiment of a distribution network line vulnerability calculation method provided by the present application includes:
It should be noted that the failure probability of the wires in the distribution network system is much smaller than that of the electric poles, the probability of the wires being directly blown off by wind is very low, and the failure probability of the electric poles is high when the wind speed is high, so that the failure probability of the distribution network system is controlled by the failure probability of the electric pole structure, but the wires can also bring influence to the electric poles and are mainly described through wire spans. Most of towers adopted in the existing distribution lines are annular concrete poles, and the bending strength of the annular concrete poles presents certain discreteness mainly due to uncertainty in aspects such as manufacturing processes and measurement errors. The cracking test bending moment of the concrete pole is obtained through the cracking test, and the bearing capacity test bending moment of the pole can be calculated according to the cracking test bending moment:
Mu＝βuMk；
wherein M iskTesting bending moment for cracking, betauThe value of the comprehensive checking coefficient of the bearing capacity can be 2.0. Through a large number of concrete pole destructive tests, the mean value of the bending strength of the pole is found to be more than the bearing capacity to check the bending moment MuSlightly larger and the bending strength approximately satisfies the normal distribution. Besides the above electric pole parameters, the wind direction angle under the typhoon condition can be obtained.
And 102, sampling the electric pole parameters by adopting a preset Latin hypercube sampling algorithm to obtain uniform sample parameters.
It should be noted that the latin hypercube sampling algorithm (LHS) is a method of approximate random sampling from multivariate parameter distribution, belongs to a hierarchical sampling technique, also called a hierarchical extraction method, is a statistical global sampling method, and can generate random samples satisfying a specified distribution. In the embodiment, a large number of electric pole parameters are obtained, in order to reduce the calculation pressure and compress the calculation time, the obtained electric pole parameters need to be sampled through a Latin hypercube sampling algorithm to obtain uniform sample parameters, and the sampling process belongs to the data preparation and arrangement process. The specific sampling process is as follows: for k random variables (x)1,x2,...,xk) NS random numbers can be generated for each random variable by LHS, where S is the number of samples and is the number of segments, i.e., each random variableThe cumulative probability distribution function is divided into N equal parts, N random numbers can be obtained by randomly sampling once from each equal part, k-dimensional random samples of k-dimensional random variables can be obtained by combining with sampling results of other random variables, and different from the traditional sampling method, the method can ensure that the generated random numbers can cover the whole probability distribution range by maximally segmenting the edge distribution function of each random variable.
And 103, inputting the sample parameters into a preset Kriging agent model for calculation to obtain the structural resistance of the electric pole under different electric pole failure modes.
It should be noted that the failure modes of the electric pole mainly include: insufficient bottom shear bearing capacity failure, insufficient bottom bending bearing capacity failure, insufficient support strength failure and the like. The Kriging agent model is an unbiased estimation model with minimum estimation variance and has the characteristic of local estimation; the resistance models of all structures in the distribution network system under different failure modes are established by adopting the preset Kriging agent model, so that the vulnerability models in the whole distribution network do not need to be established, and the calculation amount is reduced. The preset Kriging agent model comprises a regression part and a nonparametric part, and specifically, the preset Kriging agent model is expressed by adopting a first preset formula as follows:
y(x)＝f(x)Tβ+z(x)；
wherein f (x) is a regression function set, beta is a regression coefficient vector, z (x) is a zero-mean Gaussian process, and the standard deviation corresponding to the zero-mean Gaussian process is sigmayThe covariance matrix is E (z).
The covariance matrix is E (z) can be expressed as:
wherein R (theta, x)j,xk) Sample parameters z (x) expressed for any two sets of Gaussian process functionsj)、z(xk) The spatial correlation function of (a) plays a role in determining the accuracy of the simulation process, and theta is a correlation function parameter. R (theta, x)j,xk) Can adopt fingersNumber, gaussian, linear and spherical function descriptions, the present embodiment selects the expression mode of the gaussian function:
wherein i is the ith element of the input parameter vector, j and k are the jth and k input variables, n is the number of the input variables, thetaiIs a correlation function parameter. The process of calculating the structural resistance of the electric pole under different electric pole failure modes is to process the input sample parameters through a finite element analysis module to obtain the resistance under various failure modes. The construction process of the preset Kriging agent model is constructed by the method, but the used parameter libraries are different. The structural resistance of the electric pole under different electric pole failure modes is calculated by adopting different electric pole parameters through a preset model, so that the calculation result is more representative, and the model is also constructed according to the type of data, therefore, the model has better applicability and can describe the vulnerability of the distribution network line of the distribution network under larger coverage area.
And 104, when the structural resistance of the electric pole is smaller than the preset structural load effect, calculating the electric pole vulnerability of the distribution network line according to a preset electric pole reliability theory to obtain an electric pole vulnerability curve.
The preset structural load effect is obtained according to a preset cantilever beam force balance basic principle, S can be used as the preset structural load effect, and R can be used as the structural resistance of the electric pole; when the structural resistance of the electric pole is smaller than the preset structural load effect, a second preset formula is obtained according to the preset electric pole reliability theory, and the second preset formula is as follows:
wherein, PfFor the failure probability of the electric pole, R is the structural resistance of the electric pole, S is the load effect of the preset structure, fZ(z) is a probability density function corresponding to the structural function of the electric pole; according to the second presetAnd calculating the vulnerability of the electric pole of the distribution network line to obtain an electric pole vulnerability curve.
Specifically, the obtaining process of the second preset formula is as follows:
firstly, the bending moment M is checked according to the bearing capacityuThe probability density function corresponding to the bending strength of the electric pole can be obtained by the calculation formula:
wherein, mup＝βMuIs the mean value of the bending strength of the electric pole, the unit is N.m, beta is an amplification factor,p＝νMuthe standard deviation of the bending strength of the electric pole is shown, and v is a coefficient of variation.
Secondly, after the strength and the load effect of the overhead distribution line component are determined, according to the structure reliability theory, the reliability of the electric pole component under the action of external load can be calculated through a function, and the state description of the overhead distribution line component is as follows:
Z＝g(x)＝g(X1,X2,......,Xn)；
wherein Z is a basic variable of the state of the member, XiThe conditions of the overhead distribution line component in this embodiment are classified into failure conditions, limit conditions and reliable conditions according to the value of Z. In addition, the function can be expressed as two types, one type is resistance and the other type is load effect, namely the electric pole structure resistance and the preset structure load effect in the embodiment of the application, so that the function can also be expressed as Z ═ R-S.
Then, according to the definition of the structure reliability, the probability that the structure completes the predetermined function within the specified time and under the specified condition is the reliability of the structure; from this, the reliability probability of the overhead distribution line member:
Pr＝P{Z＝g(X)＝g(X1,X2,......,Xn)＞0}；
in general, the function is a continuous function, the limit state is a point in the probability density function, but not a section, and therefore, the probability that a member such as an electric pole is in the limit state is 0, and the failure probability and the reliability probability of the member satisfy the following relationship:
Pr+Pf＝1；
wherein, PrFor reliable probability, PfIs the probability of failure of the pole.
And finally, combining the above formulas, and analyzing the condition of the electric pole failure to obtain a second preset formula.
And further, carrying out vulnerability assessment on the distribution network lines of the distribution network system according to the pole vulnerability curve to obtain an assessment result.
According to the distribution network line vulnerability calculation method, in order to enable the calculation method to be more universal, parameter selection is carried out by integrating characteristics of an electric pole and a wire in a distribution network system, the wire span in the electric pole parameter is an important influence element for describing the wire to the electric pole, the rod body characteristic parameter of the electric pole directly concerns the wind resistance of the electric pole, the foundation characteristic and the soil property parameter are used for describing the influence of environmental factors on the collapse of the electric pole, and the wind field parameter is used for describing the destructive influence caused by typhoon; through comprehensive analysis, a plurality of influence factors of different levels are selected, so that the calculated vulnerability reliability is higher; and the preset Latin hypercube sampling algorithm is adopted to sample to obtain research sample parameters, so that the calculation process can be effectively accelerated, the time cost is saved, and the time consumption is reduced. Therefore, the method and the device can solve the technical problems that the existing calculation method is limited and the time cost is high.
To facilitate understanding, referring to fig. 2, the present application provides an embodiment of a distribution network line vulnerability calculation apparatus, comprising:
the obtaining module 201 is configured to obtain a parameter of the electric pole according to a structural characteristic and a distribution rule of the electric pole in the distribution network system, where the parameter of the electric pole includes: rod body characteristic parameters, foundation characteristics, soil property parameters, wind field parameters and lead span;
the sampling module 202 is used for sampling the electric pole parameters by adopting a preset Latin hypercube sampling algorithm to obtain uniform sample parameters;
the first calculation module 203 is used for inputting the sample parameters into a preset Kriging agent model for calculation to obtain the structural resistance of the electric pole under different electric pole failure modes;
and the second calculating module 204 is configured to calculate the vulnerability of the electric pole of the distribution network line according to a preset electric pole reliability theory when the structural resistance of the electric pole is smaller than a preset structural load effect, so as to obtain an electric pole vulnerability curve, and the preset structural load effect is obtained according to a preset cantilever beam force balance basic principle.
Further, the preset Kriging agent model is expressed by adopting a first preset formula as follows:
y(x)＝f(x)Tβ+z(x)；
wherein f (x) is a regression function set, beta is a regression coefficient vector, z (x) is a zero-mean Gaussian process, and the standard deviation corresponding to the zero-mean Gaussian process is sigmayThe covariance matrix is E (z).
Further, the second calculating module 204 is specifically configured to:
when the structural resistance of the electric pole is smaller than the preset structural load effect, a second preset formula is obtained according to the preset electric pole reliability theory, and the second preset formula is as follows:
wherein, PfFor the failure probability of the electric pole, R is the structural resistance of the electric pole, S is the load effect of the preset structure, fZ(z) is a probability density function corresponding to the structural function of the electric pole;
and calculating the electric pole vulnerability of the distribution network line according to a second preset formula to obtain an electric pole vulnerability curve.
Further, still include:
and the evaluation module 205 is used for evaluating the vulnerability of the distribution network line of the distribution network system according to the pole vulnerability curve to obtain an evaluation result.
The application also provides distribution network line vulnerability computing equipment, which comprises a processor and a memory:
the memory is used for storing the program codes and transmitting the program codes to the processor;
the processor is used for executing the distribution network line vulnerability calculation method in the above method embodiment according to the instructions in the program code.
The application also provides a computer-readable storage medium for storing program codes, wherein the program codes are used for executing the distribution network line vulnerability calculation method in the method embodiment.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for executing all or part of the steps of the method described in the embodiments of the present application through a computer device (which may be a personal computer, a server, or a network device). And the aforementioned storage medium includes: a U disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (10)
1. A distribution network line vulnerability calculation method is characterized by comprising the following steps:
the method comprises the following steps of obtaining electric pole parameters according to structural characteristics and distribution rules of electric poles in a distribution network system, wherein the electric pole parameters comprise: rod body characteristic parameters, foundation characteristics, soil property parameters, wind field parameters and lead span;
sampling the electric pole parameters by adopting a preset Latin hypercube sampling algorithm to obtain uniform sample parameters;
inputting the sample parameters into a preset Kriging agent model for calculation to obtain the structural resistance of the electric pole under different electric pole failure modes;
and when the structural resistance of the electric pole is smaller than the preset structural load effect, calculating the electric pole vulnerability of the distribution network line according to a preset electric pole reliability theory to obtain an electric pole vulnerability curve, wherein the preset structural load effect is obtained according to a preset cantilever beam force balance basic principle.
2. The distribution network line vulnerability calculation method of claim 1, wherein the preset Kriging agent model is expressed as follows by adopting a first preset formula:
y(x)＝f(x)Tβ+z(x)；
wherein f (x) is a regression function set, beta is a regression coefficient vector, z (x) is a zero-mean Gaussian process, and the standard deviation corresponding to the zero-mean Gaussian process is sigmayThe covariance matrix is E (z).
3. The distribution network line vulnerability calculation method of claim 1, wherein when the pole structural resistance is less than a preset structural load effect, calculating the pole vulnerability of the distribution network line according to a preset pole reliability theory to obtain a pole vulnerability curve, comprises:
when the structural resistance of the electric pole is smaller than the preset structural load effect, a second preset formula is obtained according to a preset electric pole reliability theory, wherein the second preset formula is as follows:
wherein, PfFor the failure probability of the electric pole, R is the structural resistance of the electric pole, S is the load effect of the preset structure, fZ(z) is a probability density function corresponding to the structural function of the electric pole;
and calculating the electric pole vulnerability of the distribution network line according to the second preset formula to obtain an electric pole vulnerability curve.
4. The distribution network line vulnerability calculation method according to claim 1, wherein the pole vulnerability of the distribution network line is calculated according to a preset pole reliability theory to obtain a pole vulnerability curve, and then further comprising:
and carrying out vulnerability assessment on the distribution network line of the distribution network system according to the pole vulnerability curve to obtain an assessment result.
5. A distribution network line vulnerability calculation apparatus, comprising:
the acquisition module is used for acquiring the electric pole parameters according to the structural characteristics and the distribution rules of the electric pole in the distribution network system, and the electric pole parameters comprise: rod body characteristic parameters, foundation characteristics, soil property parameters, wind field parameters and lead span;
the sampling module is used for sampling the electric pole parameters by adopting a preset Latin hypercube sampling algorithm to obtain uniform sample parameters;
the first calculation module is used for inputting the sample parameters into a preset Kriging agent model for calculation to obtain the structural resistance of the electric pole under different electric pole failure modes;
and the second calculation module is used for calculating the electric pole vulnerability of the distribution network line according to a preset electric pole reliability theory to obtain an electric pole vulnerability curve when the structural resistance of the electric pole is smaller than a preset structural load effect, and the preset structural load effect is obtained according to a preset cantilever beam force balance basic principle.
6. The distribution network line vulnerability calculation apparatus of claim 5, wherein the preset Kriging agent model is expressed as:
y(x)＝f(x)Tβ+z(x)；
wherein f (x) is a regression function set, beta is a regression coefficient vector, z (x) is a zero-mean Gaussian process, and the standard deviation corresponding to the zero-mean Gaussian process is sigmayThe covariance matrix is E (z).
7. The distribution network line vulnerability calculation apparatus of claim 5, wherein the second calculation module is specifically configured to:
when the structural resistance of the electric pole is smaller than the preset structural load effect, a second preset formula is obtained according to a preset electric pole reliability theory, wherein the second preset formula is as follows:
wherein, PfFor the failure probability of the electric pole, R is the structural resistance of the electric pole, S is the load effect of the preset structure, fZ(z) is a probability density function corresponding to the structural function of the electric pole;
and calculating the electric pole vulnerability of the distribution network line according to the second preset formula to obtain an electric pole vulnerability curve.
8. The distribution network line vulnerability calculation apparatus of claim 5, further comprising:
and the evaluation module is used for evaluating the vulnerability of the distribution network line of the distribution network system according to the electric pole vulnerability curve to obtain an evaluation result.
9. A distribution network line vulnerability computing device, the device comprising a processor and a memory:
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to execute the method of calculating vulnerability of a distribution network line of any of claims 1-4 according to instructions in the program code.
10. A computer readable storage medium, characterized in that the computer readable storage medium is configured to store program code for performing the distribution network line vulnerability calculation method of any of claims 1-4.
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| CN115099066A (en) * | 2022-07-26 | 2022-09-23 | 南京工业大学 | Kriging-based power transmission tower structure wind disaster vulnerability modeling method |
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