CN109146249B - Power distribution network reliability estimation method, device and equipment - Google Patents

Power distribution network reliability estimation method, device and equipment Download PDF

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CN109146249B
CN109146249B CN201810813503.9A CN201810813503A CN109146249B CN 109146249 B CN109146249 B CN 109146249B CN 201810813503 A CN201810813503 A CN 201810813503A CN 109146249 B CN109146249 B CN 109146249B
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CN109146249A (en
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孙大雁
韦永忠
卜荣
张恒
魏刚
苏伟伟
王东
张宇
赵凤展
杜松怀
苏娟
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China Agricultural University
State Grid Jiangsu Electric Power Co Ltd
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State Grid Jiangsu Electric Power Co Ltd
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Abstract

The embodiment of the invention provides a method, a device and equipment for estimating reliability of a power distribution network. According to the method, the device and the equipment, various estimated parameters in the estimation of the reliability of the power distribution network are expressed and calculated through blind numbers, so that the estimation of the reliability of the power distribution network is as close as possible to the actual situation, and the accuracy of the estimation of the reliability of the power distribution network is improved.

Description

Power distribution network reliability estimation method, device and equipment
Technical Field
The embodiment of the invention relates to the technical field of power distribution networks, in particular to a method, a device and equipment for estimating reliability of a power distribution network.
Background
The reliability of the power distribution network is the capability of the power distribution system for continuously supplying power, is an important index for checking the power quality of the power distribution network, reflects the satisfaction degree of the power industry on national economic power demand, and the estimation of the reliability of the power distribution network has important significance for the reconstruction of the power distribution network.
At present, point values, namely specific values, are selected for various estimated parameters (such as line fault rate, repair rate and other parameters between areas) in power distribution network reliability estimation, however, the estimated parameters are related to actually used lines and elements in a power distribution network, line and element manufacturers, even different production batches may cause different parameters corresponding to the lines and elements, and completely consistent lines and elements cannot be selected in the power distribution network, so that the estimation of the power distribution network reliability at present has a large deviation from the actual situation, and an accurate estimation result cannot be obtained.
Disclosure of Invention
In order to overcome the problems or at least partially solve the problems, embodiments of the present invention provide a method, an apparatus, and a device for estimating reliability of a power distribution network.
The embodiment of the invention provides a method for estimating the reliability of a power distribution network, which comprises the following steps: acquiring a blind number of a first outage rate of each area and a blind number of a first outage duration of each area according to a reliability parameter of each element in each area of the power distribution network, wherein the reliability parameter comprises an element failure rate, a planned overhaul rate, an average failure repair duration and an average planned overhaul duration; acquiring the blind number of the second outage rate of each area and the blind number of the second outage duration of each area according to the blind number of the line fault rate of the lines among the areas, the blind number of the first outage rate of each area and the blind number of the first outage duration of each area; acquiring the blind number of the average power failure times of the first user and the blind number of the average power failure time of the first user according to the blind number of the second power failure rate of each area and the blind number of the second power failure time of each area, and acquiring the blind number of the first power supply reliability rate according to the blind number of the average power failure times of the first user; the method comprises the steps of determining the average value of the average power failure times of a first user according to the blind number of the average power failure times of the first user, determining the average value of the average power failure time of the first user according to the blind number of the average power failure time of the first user, determining the average value of the first power supply reliability according to the blind number of the first power supply reliability, and taking the average value of the average power failure times of the first user, the average value of the average power failure time of the first user and the average value of the first power supply reliability as estimation parameters to estimate the reliability of the power distribution network.
The embodiment of the invention provides a power distribution network reliability pre-estimating device, which comprises: the first acquisition module is used for acquiring the blind number of the first outage rate of each area and the blind number of the first outage duration of each area according to the reliability parameters of each element in each area of the power distribution network, wherein the reliability parameters comprise the element failure rate, the planned overhaul rate, the average fault repair duration and the average planned overhaul duration; the second obtaining module is used for obtaining the blind number of the second outage rate of each area and the blind number of the second outage duration of each area according to the blind number of the line fault rate of the lines among the areas, the blind number of the first outage rate of each area and the blind number of the first outage duration of each area; the third obtaining module is used for obtaining the blind number of the average power failure times of the first user and the blind number of the average power failure time of the first user according to the blind number of the second power failure rate of each area and the blind number of the second power failure time of each area, and obtaining the blind number of the first power supply reliability according to the blind number of the average power failure times of the first user; the estimation module is used for determining the average value of the average power failure times of the first user according to the blind number of the average power failure times of the first user, determining the average value of the average power failure time of the first user according to the blind number of the average power failure time of the first user, determining the average value of the first power supply reliability according to the blind number of the first power supply reliability, and taking the average value of the average power failure times of the first user, the average value of the average power failure time of the first user and the average value of the first power supply reliability as estimation parameters to estimate the reliability of the power distribution network.
The embodiment of the invention provides a power distribution network reliability pre-estimating device, which comprises: at least one processor, at least one memory, and a data bus; wherein: the processor and the memory complete mutual communication through a data bus; the memory stores program instructions executable by the processor, which invokes the program instructions to perform the methods described above.
Embodiments of the present invention provide a non-transitory computer-readable storage medium storing a computer program that causes a computer to perform the above-described method.
According to the method, the device and the equipment for estimating the reliability of the power distribution network, the blind number of the first outage rate of the area and the blind number of the first outage duration of the area are obtained through the reliability parameters of the elements in the area, the blind number of the second outage rate of the area and the blind number of the second outage duration of the area are obtained by combining the blind numbers of the line fault rates of lines among the areas, the blind number of the average outage times of the first user, the blind number of the average outage duration of the first user and the blind number of the first power supply reliability are obtained according to the blind numbers of the second outage rate of each area and the blind number of the second outage duration of the area, and the blind numbers of the average outage times of the first user, the blind number of the average outage duration of the first user and the blind number of the first power supply reliability are further averaged respectively, so that the estimated parameters for estimating the reliability of the power distribution network are obtained. According to the method, the device and the equipment, various estimated parameters in the estimation of the reliability of the power distribution network are expressed and calculated through blind numbers, and the selection condition of the power distribution network on elements and lines in practice is simulated as much as possible, so that the estimation of the reliability of the power distribution network is as close as possible to the practical condition, and the accuracy of the estimation of the reliability of the power distribution network is improved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a flowchart of a method for estimating reliability of a power distribution network according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a power distribution network configuration according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a power distribution network reliability estimation device according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a power distribution network reliability estimation device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. 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 invention.
The embodiment of the invention provides a method for estimating the reliability of a power distribution network, which refers to fig. 1 and comprises the following steps: s11, acquiring the blind number of the first outage rate of each area and the blind number of the first outage duration of each area according to the reliability parameters of each element in each area of the power distribution network, wherein the reliability parameters comprise element failure rate, planned overhaul rate, average fault repair duration and average planned overhaul duration; s12, acquiring the blind number of the second outage rate of each area and the blind number of the second outage duration of each area according to the blind number of the line fault rate of the lines among the areas, the blind number of the first outage rate of each area and the blind number of the first outage duration of each area; s13, acquiring the blind number of the average power failure times of the first user and the blind number of the average power failure time of the first user according to the blind number of the second power failure rate of each area and the blind number of the second power failure time of each area, and acquiring the blind number of the first power supply reliability rate according to the blind number of the average power failure times of the first user; s14, determining the average value of the average power failure times of the first user according to the blind number of the average power failure times of the first user, determining the average value of the average power failure time of the first user according to the blind number of the average power failure time of the first user, determining the average value of the first power supply reliability according to the blind number of the first power supply reliability, and taking the average value of the average power failure times of the first user, the average value of the average power failure time of the first user and the average value of the first power supply reliability as estimation parameters to estimate the reliability of the power distribution network.
Specifically, the power distribution network is divided into a plurality of areas, each area includes a plurality of components (including lines), the types of the components are various, and even if the components are the same, there are differences among a plurality of the same components, in the process of estimating the reliability of the power distribution network, the number of the components is huge, and it is difficult to determine specific parameters of each component one by one, so that most of the parameters in the power distribution network have uncertainty, and in the embodiment, the uncertainty of the parameters is represented by blind numbers.
The essence of the blind number is a gray function with a domain of G and a function value of [0,1 ]. There are two important values in the blind number, one is a possible value and one is a confidence level, each possible value corresponds to a confidence level, and the meaning of the confidence level is the probability that the corresponding parameter takes the corresponding possible value. The expression for the blind number is:
Figure GDA0002760683900000051
due to the uncertainty of the parameters of all elements in the area, the outage rate and the outage duration of the area also have uncertainty, and the outage rate and the outage duration of the area can be represented by blind numbers. In this embodiment, according to the reliability parameter of each element in each area of the power distribution network, the blind number of the first outage rate of each area and the blind number of the first outage duration of each area are obtained, where the reliability parameter includes an element failure rate, a planned overhaul rate, an average fault repair duration, and an average planned overhaul duration.
The first outage rate and the first outage duration of the area are only influence factors of elements in the area, and various lines between the areas also have influence on the outage rate and the outage duration of the area, so that the second outage rate and the second outage duration of the area are acquired by combining the line fault rates of the lines between the areas, and similarly, the line fault rates of the lines between the areas also have uncertainty and can also be represented by blind numbers; in this embodiment, the blind number of the second outage rate of each area and the blind number of the second outage duration of each area are obtained according to the blind number of the line fault rate of the inter-area line, the blind number of the first outage rate of each area and the blind number of the first outage duration of each area.
The blind number of the second outage rate of the area and the blind number of the second outage duration are obtained in relation to the line connection relationship between the distribution network areas, for example, as shown in fig. 2, the power distribution network structure, the power supply system, and the lines among the 5 areas are l1, l2, l3, l4, and l5, respectively, and the obtaining of the blind number of the second outage rate of the area can be expressed by the following formula:
Figure GDA0002760683900000061
wherein,
Figure GDA0002760683900000062
is a blind number of the second outage rate for the ith zone,
Figure GDA0002760683900000063
Figure GDA0002760683900000064
is a blind number of the first outage rate for the ith zone,
Figure GDA0002760683900000065
is a blind number of line failure rates for the ith line.
The acquisition of the blind number of the second blackout period of the area can be represented by the following formula:
Figure GDA0002760683900000066
wherein,
Figure GDA0002760683900000067
a blind number of the second blackout duration for the ith zone,
Figure GDA0002760683900000068
Figure GDA0002760683900000069
is a blind number of the first blackout duration of the ith zone,
Figure GDA00027606839000000610
is a blind number of line failure rates for the ith line.
The four-rule operation between the blind numbers can be completed by a blind number four-rule algorithm, and specifically, for the blind numbers A and B, the expression of A and B is as follows:
Figure GDA00027606839000000611
Figure GDA00027606839000000612
the result after the four arithmetic operations between a and B can be obtained by the following possible value matrix and confidence matrix:
Figure GDA0002760683900000071
Figure GDA0002760683900000072
where denotes an addition, subtraction, multiplication, or division by four operator, and denotes a multiplication operator.
Taking the elements with the same value in the possible value matrix of the operation of A and B as one value and obtaining the possible value sequence after the operation of A and B:
Figure GDA0002760683900000073
will be provided with
Figure GDA0002760683900000074
The corresponding reliability product is recorded as
Figure GDA0002760683900000075
The function phi (z) of the operation of the blind numbers a and B is noted as:
Figure GDA0002760683900000076
acquiring the blind number of the average power failure times of the first user and the blind number of the average power failure time of the first user according to the blind number of the second power failure rate of each area and the blind number of the second power failure time of each area, and acquiring the blind number of the first power supply reliability rate according to the blind number of the average power failure times of the first user; expressions of the blind number of the average power failure times of the first user, the blind number of the average power failure duration of the first user and the blind number of the first power supply reliability are respectively as follows:
Figure GDA0002760683900000077
Figure GDA0002760683900000078
Figure GDA0002760683900000081
wherein, AITC0Blind number, AIHC, for average number of blackouts of first user0Is the blind number of the average power-off time of the first user, RS0Blind number, N, for first power supply reliabilityi( i 1, 2.. said., m) is the number of users of the ith area,
Figure GDA0002760683900000082
is a blind number of the second outage rate for the ith zone,
Figure GDA0002760683900000083
and T is the blind number of the second power failure time length of the ith area, and is the statistical time.
Determining the average value of the average power failure times of the first user according to the blind number of the average power failure times of the first user, determining the average value of the average power failure time of the first user according to the blind number of the average power failure time of the first user, determining the average value of the first power supply reliability according to the blind number of the first power supply reliability, and performing reliability estimation on the power distribution network by taking the average value of the average power failure times of the first user, the average value of the average power failure time of the first user and the average value of the first power supply reliability as estimation parameters; the mean value of the average power failure times of the first user, the mean value of the average power failure duration of the first user and the mean value of the first power supply reliability indicate that the corresponding blind number is converted into a determined value through a preset calculation rule, the determined value obtained through conversion is called the mean value of the corresponding parameter, the blind number is converted into the mean value through the preset calculation rule, and the mean value is the determined value, so that reliability estimation on the power distribution network is more visual.
According to the power distribution network reliability estimation method, various estimation parameters in power distribution network reliability estimation are expressed and calculated through blind numbers, the selection condition of the power distribution network on elements and lines in practice is simulated as much as possible, the estimation of the power distribution network reliability is close to the practical condition as much as possible, and the accuracy of the power distribution network reliability estimation is improved.
Based on the above embodiment, obtaining the blind number of the first outage rate of each area and the blind number of the first outage duration of each area according to the reliability parameter of each element in each area of the power distribution network includes: for any area of the power distribution network, acquiring a parameter value of each parameter in a plurality of production batches of the reliability parameter of each element in the any area, taking the parameter value of each parameter in the plurality of production batches as a plurality of possible values of the blind number of the corresponding parameter, and determining the reliability corresponding to the plurality of possible values of the blind number of each parameter respectively, wherein the parameter values of the planned overhaul rate in the reliability parameter in the plurality of production batches are the same; and determining the blind number of the first outage rate of any area and the blind number of the first outage duration of any area according to the planned overhaul rate of each element, the blind number of the element failure rate of each element, the blind number of the average fault repair duration of each element and the blind number of the average planned overhaul duration of each element in any area on the basis of the series or parallel connection relation between the elements in any area and a four-rule pre-algorithm of the blind numbers.
Specifically, for four parameters, namely the element failure rate, the planned overhaul rate, the mean fault repair time length and the mean planned overhaul time length, among the reliability parameters, the possible values of the blind numbers of the four parameters may be determined by the parameter values of the corresponding parameters provided by the manufacturer in each production batch, and the reliability corresponding to each possible value may be determined according to the use probability of each production batch in the actual use process, or may be determined in other manners. The scheduled maintenance rate provided by a manufacturer is a determined value and is not represented by a blind number, the average fault repair time length of the element fault rate and the average scheduled maintenance time length are represented by the blind number, and then the blind number of the first outage rate of any area and the blind number of the first outage time length of any area are determined according to the scheduled maintenance rate of each element, the blind number of the element fault rate of each element, the blind number of the average fault repair time length of each element and the blind number of the average scheduled maintenance time length of each element in any area based on four pre-calculation rules of the blind number. Wherein the two series-connected elements are parametrically combined by the following calculation:
Figure GDA0002760683900000091
λ'＝λ1'+λ2'；
Figure GDA0002760683900000092
Figure GDA0002760683900000093
wherein,
Figure GDA0002760683900000094
a blind number of component failure rates after parametric consolidation for two series-connected components,
Figure GDA0002760683900000095
is a blind number of component failure rates of one of the two series-connected components,
Figure GDA0002760683900000096
for a blind number of failure rates of the other of the two series-connected elements, lambda' is the planned maintenance rate of the two series-connected elements after parameter combination, lambda1' planned maintenance, λ, for one of two series-connected elements2' is the planned maintenance rate of the other of the two series-connected elements,
Figure GDA0002760683900000101
a blind number of mean-time-to-fail repairs after parameter consolidation for two series-connected elements,
Figure GDA0002760683900000102
a blind number of mean-time-to-fail repairs of one of the two series-connected elements,
Figure GDA0002760683900000103
a blind number of mean-time-to-fail repairs of the other of the two series-connected elements,
Figure GDA0002760683900000104
blind number of average planned overhaul duration after parameter combination for two series-connected elements,
Figure GDA0002760683900000105
a blind number of average planned service hours for one of the two series-connected elements,
Figure GDA0002760683900000106
a blind number of average planned service hours for the other of two series-connected elements.
The two parallel-connected elements are combined by the following calculation:
Figure GDA0002760683900000107
Figure GDA0002760683900000108
Figure GDA0002760683900000109
Figure GDA00027606839000001010
wherein,
Figure GDA00027606839000001011
a blind number of component failure rates after parametric consolidation for two parallel connected components,
Figure GDA00027606839000001012
is a blind number of component failure rates of one of the two parallel-connected components,
Figure GDA00027606839000001013
for a blind number of component failure rates of the other of the two parallel-connected components, lambda' is the planned maintenance rate after parameter combination of the two parallel-connected components, lambda1' planned maintenance, lambda, for one of two elements connected in parallel2' is the planned maintenance rate of the other of the two elements connected in parallel,
Figure GDA00027606839000001014
a blind number of mean-time-to-fail repairs after parameter consolidation for two parallel-connected elements,
Figure GDA00027606839000001015
a blind number of mean-time-to-fail repairs of one of the two parallel-connected elements,
Figure GDA00027606839000001016
a blind number of mean time to failure repair of the other of the two parallel connected elements,
Figure GDA00027606839000001017
blind numbers of average planned overhaul duration after parameter combination for two parallel connected elements,
Figure GDA00027606839000001018
a blind number of average planned service hours for one of two elements connected in parallel,
Figure GDA00027606839000001019
a blind number of average planned service hours for the other of two elements connected in parallel.
And combining the parameters pairwise through the calculation formula to finally obtain the blind number of the fault rate, the scheduled maintenance rate, the blind number of the average fault repair time length and the blind number of the average scheduled maintenance time length of the region.
The blind number of the first outage rate of the zone and the blind number of the first outage duration of the zone are obtained by:
Figure GDA0002760683900000111
Figure GDA0002760683900000112
wherein,
Figure GDA0002760683900000113
is a blind number of the first outage rate for the ith zone,
Figure GDA0002760683900000114
is a blind number of failure rate of the i-th area, lambda'iIs the planned maintenance rate for the i-th zone,
Figure GDA0002760683900000115
is a blind number of the first blackout duration of the ith zone,
Figure GDA0002760683900000116
is a blind number of mean-time-to-fail repair times for the ith zone,
Figure GDA0002760683900000117
blind numbers for the average planned length of service for zone i.
Based on the above embodiments, determining the confidence levels corresponding to the plurality of possible values in the blind number of each parameter respectively includes: for any parameter, determining the relative possibility degree between any two possible values in all possible values in the blind number of the parameter; constructing a judgment matrix according to the relative possibility between any two possible values in all the possible values, wherein the judgment matrix comprises a characteristic root parameter; determining a maximum characteristic root of the judgment matrix, and taking the maximum characteristic root as a value of a characteristic root parameter; constructing a homogeneous equation by using the judgment matrix as a coefficient matrix of the equation; and performing normalization processing on the feature vectors formed by solving the homogeneous equation, and taking each vector value in the feature vectors after the normalization processing as the corresponding credibility of the corresponding possible value.
Wherein, the expression of the judgment matrix is:
Figure GDA0002760683900000118
in the above formula, bij(i-1, 2, …, m, j-1, 2, …, m) is the ratio of the relative likelihood of the ith possible value to the relative likelihood of the jth possible value, λ being the characteristic root parameter.
Specifically, all possible values in the blind number of any parameter are taken as a possible value set X ═ (X)1,x2,…,xm) For a pair of possible values x of the set of possible valuesiAnd xjTo xiAnd xjIs compared with the possible degree of
Figure GDA0002760683900000121
Represents a possible value xjRelative possible value xiThe relative degree of likelihood of (c) is,
Figure GDA0002760683900000122
represents a possible value xiRelative possible value xjRelative degree of probability of (c), definition of bijSatisfies the following formula:
Figure GDA0002760683900000123
and defining a judgment matrix as:
Figure GDA0002760683900000124
wherein, bij(i-1, 2, …, m, j-1, 2, …, m) is the ratio of the relative likelihood of the ith possible value to the relative likelihood of the jth possible value, λ being the characteristic root parameter.
The relative likelihood represents a ratio between the probabilities of two possible values occurring, and the relative likelihood of the ith possible value with respect to the jth possible value is the ratio of the probability of the ith possible value occurring to the probability of the jth possible value occurring. For example, the parameter value of each parameter in multiple production batches is used as multiple possible values in the blind number of the corresponding parameter, when a user uses a certain element, according to the actual use condition and the historical use condition, the element of the ith production batch is determined to be k times of the use amount of the element of the jth production batch, the probability of the ith possible value of the parameter representing the element is k times of the probability of the ith possible value, and the relative possibility of the ith possible value to the jth possible value is k; or determining the relative likelihood according to the production capacity of each production batch provided by the manufacturer, wherein the production capacity of different production batches can represent the use amount of the elements of different production batches in the actual use process, and the production capacity of the ith production batch is k times of the production capacity of the jth production batch, so that the relative likelihood of the ith possible value relative to the jth possible value can be considered to be k.
And (c) solving a solution obtained by solving the homogeneous equation as a characteristic vector xi ═ c (c ═ 0), wherein the solution is obtained by solving the homogeneous equation by taking a B matrix corresponding to the maximum value of the lambda as a coefficient matrix of the homogeneous equation1,c2,…,cm) And normalizing the feature vector xi:
Figure GDA0002760683900000131
and taking each vector value in the feature vector after the normalization processing as the corresponding credibility of the corresponding possible value.
Based on the above embodiment, determining the average value of the average power failure times of the first user according to the blind number of the average power failure times of the first user, determining the average value of the average power failure time of the first user according to the blind number of the average power failure time of the first user, and determining the average value of the first power supply reliability according to the blind number of the first power supply reliability includes: taking the sum of products obtained by multiplying each possible value in the blind number of the first user average power failure times by the credibility corresponding to each possible value as the average value of the first user average power failure times, taking the sum of products obtained by multiplying each possible value in the blind number of the first user average power failure time length by the credibility corresponding to each possible value as the average value of the first user average power failure time length, and taking the sum of products obtained by multiplying each possible value in the blind number of the first power supply reliability by the credibility corresponding to each possible value as the average value of the first power supply reliability.
Specifically, the present embodiment may determine the mean value of each parameter through the blind number of each parameter, and for any parameter, take the sum of products obtained by multiplying each possible value in the blind number of the parameter by the corresponding confidence level of each possible value as the mean value of the parameter; the mean value of the parameters can be obtained by:
Figure GDA0002760683900000132
wherein x ispIs the p-th possible value of the blind number of the parameter, alphapIs xpCorresponding confidence, m is the total number of possible values in the blind number of parameters.
Based on the above embodiment, after determining the average value of the average power failure times of the first user according to the blind number of the average power failure times of the first user, determining the average value of the average power failure time of the first user according to the blind number of the average power failure time of the first user, and determining the average value of the first power supply reliability according to the blind number of the first power supply reliability, the method further includes: determining an access line of the distributed power supply to the power distribution network; based on a blind number four rule algorithm, acquiring a blind number of the average power failure times of a second user according to the blind number of the line fault rate of the access line and the blind number of the average power failure times of the first user, acquiring a blind number of the average power failure times of the second user according to the blind number of the line fault rate of the access line and the blind number of the average power failure time of the first user, and acquiring a blind number of the second power supply reliability according to the blind number of the line fault rate of the access line and the blind number of the first power supply reliability; determining the average value of the average power failure times of the second user according to the blind number of the average power failure times of the second user, determining the average value of the average power failure time of the second user according to the blind number of the average power failure time of the second user, determining the average value of the second power supply reliability rate according to the blind number of the second power supply reliability rate, and taking the average value of the average power failure times of the second user, the average value of the average power failure time of the second user and the average value of the second power supply reliability rate as estimation parameters to carry out reliability estimation on the power distribution network accessed to the distributed power supply.
Specifically, the reliability of the power distribution network accessed to the distributed power supply can be estimated, an access line of the distributed power supply accessed to the power distribution network is determined first, the blind number of the line fault rate of the access line is obtained, the blind number of the average power failure times of the second user is obtained according to the blind number of the line fault rate of the access line and the blind number of the average power failure times of the first user, the blind number of the average power failure times of the second user is obtained according to the blind number of the line fault rate of the access line and the blind number of the average power failure time of the first user, and the blind number of the second power supply reliability is obtained according to the blind number of the line fault rate of the access line and the blind number of the first power supply reliability; then, the average power failure times of the second user, the average power failure duration of the second user and the average value of the second power supply reliability are respectively determined, and the method for determining the average values of the three parameters can also adopt the method for determining the average value in the embodiment, which is not described herein again; and then taking the average value of the average power failure times of the second user, the average value of the average power failure duration of the second user and the average value of the second power supply reliability rate as estimation parameters to estimate the reliability of the power distribution network accessed to the distributed power supply.
For example, as shown in fig. 2, a distribution network structure is connected to a distributed power supply DG, an access line of the DG connected to the distribution network is l6, and the blind number of the line fault rate of the access line is
Figure GDA0002760683900000141
The method for acquiring the blind number of the line fault rate can also adopt the method for acquiring the blind number in the embodiment, and the calculation formulas of the average power failure times of the second user, the average power failure duration of the second user and the blind number of the second power supply reliability rate are as follows:
Figure GDA0002760683900000151
Figure GDA0002760683900000152
Figure GDA0002760683900000153
wherein, AITC1Blind number, AITC, for average number of blackouts of second subscriber0Is a blind number of average blackout times of the first user,
Figure GDA0002760683900000154
for line fault rate of access lineBlind number, AIHC1For blind number of average power-off duration of second user, AIHC0Is the blind number of the average power-off time of the first user, RS1Blind number, RS, for second power reliability0Blind number, P, for first power supply reliabilityDGFor the power supply of a distributed power supply, Pload,iAnd m is the total number of the areas of the power distribution network.
Based on the above embodiment, after the reliability of the power distribution network accessing the distributed power supply is estimated by using the average value of the average power failure times of the second user, the average value of the average power failure duration of the second user, and the average value of the second power supply reliability as estimation parameters, the method further includes: acquiring a first influence coefficient of the access of the distributed power supply on the average power failure times of users of the power distribution network according to the average value of the average power failure times of the first user and the average value of the average power failure times of the second user, acquiring a second influence coefficient of the access of the distributed power supply on the average power failure times of users of the power distribution network according to the average value of the average power failure times of the first user and the average value of the average power failure times of the second user, and acquiring a third influence coefficient of the access of the distributed power supply on the power supply reliability of the power distribution network according to the average value of the first power supply reliability and the average value of the second power supply reliability; and taking the first influence coefficient, the second influence coefficient and the third influence coefficient as the improvement effect parameters of the reliability of the distributed power supply access to the power distribution network.
Specifically, in this embodiment, a first influence coefficient of the access of the distributed power source on the average power failure frequency of the users of the power distribution network may also be obtained according to the average value of the average power failure frequency of the first user and the average value of the average power failure frequency of the second user, a second influence coefficient of the access of the distributed power source on the average power failure frequency of the users of the power distribution network may be obtained according to the average value of the average power failure time of the first user and the average value of the average power failure time of the second user, and a third influence coefficient of the access of the distributed power source on the power supply reliability of the power distribution network may be obtained according to the average value of the first power supply reliability and the average value of the second power supply reliability.
Wherein the first, second and third influence coefficients are calculated as follows:
Figure GDA0002760683900000161
Figure GDA0002760683900000162
Figure GDA0002760683900000163
in the above formula, the first and second carbon atoms are,
Figure GDA0002760683900000164
as a first influence coefficient, is selected,
Figure GDA0002760683900000165
is the average value of the average power failure times of the first user,
Figure GDA0002760683900000166
is the average value of the average power failure times of the second user,
Figure GDA0002760683900000167
as a result of the second influence coefficient,
Figure GDA0002760683900000168
is the average value of the average power failure time of the first user,
Figure GDA0002760683900000169
is the average value of the average power failure time of the second user,
Figure GDA00027606839000001610
as a third influence coefficient, is determined,
Figure GDA00027606839000001611
is the average of the first power reliability,
Figure GDA00027606839000001612
mean value of second power supply reliability, PDGThe power supply power of the distributed power supply.
The embodiment of the present invention further provides a device for estimating reliability of a power distribution network, referring to fig. 3, including: a first obtaining module 31, a second obtaining module 32, a third obtaining module 33, and a pre-estimating module 34, wherein:
the first obtaining module 31 is configured to obtain a blind number of a first outage rate of each area and a blind number of a first outage duration of each area according to a reliability parameter of each element in each area of the power distribution network, where the reliability parameter includes an element failure rate, a planned overhaul rate, an average fault repair duration, and an average planned overhaul duration;
the second obtaining module 32 is configured to obtain the blind number of the second outage rate of each area and the blind number of the second outage duration of each area according to the blind number of the line fault rate of the line between the areas, the blind number of the first outage rate of each area, and the blind number of the first outage duration of each area;
the third obtaining module 33 is configured to obtain the blind number of the average power outage times of the first user and the blind number of the average power outage time of the first user according to the blind number of the second power outage rate of each area and the blind number of the second power outage time of each area, and obtain the blind number of the first power supply reliability according to the blind number of the average power outage times of the first user;
the estimation module 34 is configured to determine an average value of the average power failure times of the first user according to the blind number of the average power failure times of the first user, determine an average value of the average power failure time of the first user according to the blind number of the average power failure time of the first user, determine an average value of the first power supply reliability according to the blind number of the first power supply reliability, and estimate the reliability of the power distribution network by using the average value of the average power failure times of the first user, the average value of the average power failure time of the first user, and the average value of the first power supply reliability as estimation parameters.
The device of the embodiment of the invention can be used for executing the technical scheme of the power distribution network reliability estimation method embodiment shown in fig. 1, and the implementation principle and the technical effect are similar, and are not described herein again.
An embodiment of the present invention further provides a device for estimating reliability of a power distribution network, which, with reference to fig. 4, includes: at least one processor 41, at least one memory 42, and a data bus 43; wherein: the processor 41 and the memory 42 communicate with each other through a data bus 43; the memory 42 stores program instructions executable by the processor 41, and the processor 41 calls the program instructions to execute the methods provided by the above method embodiments, for example, the method includes: acquiring a blind number of a first outage rate of each area and a blind number of a first outage duration of each area according to a reliability parameter of each element in each area of the power distribution network, wherein the reliability parameter comprises an element failure rate, a planned overhaul rate, an average failure repair duration and an average planned overhaul duration; acquiring the blind number of the second outage rate of each area and the blind number of the second outage duration of each area according to the blind number of the line fault rate of the lines among the areas, the blind number of the first outage rate of each area and the blind number of the first outage duration of each area; acquiring the blind number of the average power failure times of the first user and the blind number of the average power failure time of the first user according to the blind number of the second power failure rate of each area and the blind number of the second power failure time of each area, and acquiring the blind number of the first power supply reliability rate according to the blind number of the average power failure times of the first user; the method comprises the steps of determining the average value of the average power failure times of a first user according to the blind number of the average power failure times of the first user, determining the average value of the average power failure time of the first user according to the blind number of the average power failure time of the first user, determining the average value of the first power supply reliability according to the blind number of the first power supply reliability, and taking the average value of the average power failure times of the first user, the average value of the average power failure time of the first user and the average value of the first power supply reliability as estimation parameters to estimate the reliability of the power distribution network.
Embodiments of the present invention further provide a non-transitory computer-readable storage medium, where the non-transitory computer-readable storage medium stores a computer program, and the computer program enables the computer to execute the method provided by the foregoing method embodiments, for example, the method includes: acquiring a blind number of a first outage rate of each area and a blind number of a first outage duration of each area according to a reliability parameter of each element in each area of the power distribution network, wherein the reliability parameter comprises an element failure rate, a planned overhaul rate, an average failure repair duration and an average planned overhaul duration; acquiring the blind number of the second outage rate of each area and the blind number of the second outage duration of each area according to the blind number of the line fault rate of the lines among the areas, the blind number of the first outage rate of each area and the blind number of the first outage duration of each area; acquiring the blind number of the average power failure times of the first user and the blind number of the average power failure time of the first user according to the blind number of the second power failure rate of each area and the blind number of the second power failure time of each area, and acquiring the blind number of the first power supply reliability rate according to the blind number of the average power failure times of the first user; the method comprises the steps of determining the average value of the average power failure times of a first user according to the blind number of the average power failure times of the first user, determining the average value of the average power failure time of the first user according to the blind number of the average power failure time of the first user, determining the average value of the first power supply reliability according to the blind number of the first power supply reliability, and taking the average value of the average power failure times of the first user, the average value of the average power failure time of the first user and the average value of the first power supply reliability as estimation parameters to estimate the reliability of the power distribution network.
Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to computer program instructions, where the computer program may be stored in a computer readable storage medium, and when executed, the computer program performs the steps including the method embodiments; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, the description is as follows: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will 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 of the embodiments of the present invention.

Claims (10)

1. A power distribution network reliability prediction method is characterized by comprising the following steps:
acquiring a blind number of a first outage rate of each area and a blind number of a first outage duration of each area according to a reliability parameter of each element in each area of the power distribution network, wherein the reliability parameter comprises an element failure rate, a planned overhaul rate, an average failure repair duration and an average planned overhaul duration;
acquiring the blind number of the second outage rate of each area and the blind number of the second outage duration of each area according to the blind number of the line fault rate of the lines among the areas, the blind number of the first outage rate of each area and the blind number of the first outage duration of each area;
acquiring the blind number of the average power failure times of the first user and the blind number of the average power failure time of the first user according to the blind number of the second power failure rate of each area and the blind number of the second power failure time of each area, and acquiring the blind number of the first power supply reliability rate according to the blind number of the average power failure times of the first user;
determining the average value of the average power failure times of the first user according to the blind number of the average power failure times of the first user, determining the average value of the average power failure time of the first user according to the blind number of the average power failure time of the first user, determining the average value of the first power supply reliability according to the blind number of the first power supply reliability, and taking the average value of the average power failure times of the first user, the average value of the average power failure time of the first user and the average value of the first power supply reliability as estimation parameters to estimate the reliability of the power distribution network.
2. The method of claim 1, wherein obtaining the blind number of the first outage rate for each area and the blind number of the first outage duration for each area based on the reliability parameters of each element in each area of the power distribution network comprises:
for any area of the power distribution network, acquiring a parameter value of each parameter in a plurality of production batches of the reliability parameter of each element in the any area, taking the parameter value of each parameter in the plurality of production batches as a plurality of possible values of the blind number of the corresponding parameter, and determining the corresponding reliability of the plurality of possible values of the blind number of each parameter, wherein the parameter values of the planned overhaul rate in the reliability parameter in the plurality of production batches are the same;
and determining the blind number of the first outage rate of any area and the blind number of the first outage duration of any area according to the planned overhaul rate of each element, the blind number of the element failure rate of each element, the blind number of the average fault repair duration of each element and the blind number of the average planned overhaul duration of each element in any area on the basis of the series or parallel connection relation between the elements in any area and a four-rule pre-algorithm of the blind numbers.
3. The method of claim 2, wherein determining the confidence level corresponding to each of the plurality of possible values of the blind number for each parameter comprises:
for any parameter, determining the relative possibility degree between any two possible values in all possible values in the blind number of the parameter;
constructing a judgment matrix according to the relative possibility between any two possible values in all the possible values, wherein the judgment matrix comprises a characteristic root parameter;
determining a maximum characteristic root of the judgment matrix, and taking the maximum characteristic root as a value of the characteristic root parameter;
constructing a homogeneous equation by using the judgment matrix as a coefficient matrix of the equation;
and normalizing the feature vectors formed by solving the homogeneous equation, and taking each vector value in the normalized feature vectors as the corresponding credibility of the corresponding possible value.
4. The method of claim 1, wherein the determining the average of the average blackout times of the first user according to the blind number of the average blackout times of the first user, the determining the average of the average blackout time of the first user according to the blind number of the average blackout time of the first user, and the determining the average of the first power supply reliability according to the blind number of the first power supply reliability comprises:
taking the sum of products obtained by multiplying each possible value in the blind number of the first user average power failure times by the corresponding credibility of each possible value as the average value of the first user average power failure times, taking the sum of products obtained by multiplying each possible value in the blind number of the first user average power failure time length by the corresponding credibility of each possible value as the average value of the first user average power failure time length, and taking the sum of products obtained by multiplying each possible value in the blind number of the first power supply reliability by the corresponding credibility of each possible value as the average value of the first power supply reliability.
5. The method of claim 3, wherein the decision matrix is expressed as:
Figure FDA0001739764550000031
wherein, bij(i-1, 2, …, m, j-1, 2, …, m) is the ratio of the relative likelihood of the ith possible value to the relative likelihood of the jth possible value, λ being the characteristic root parameter.
6. The method of claim 1, wherein after determining the average of the average blackout times of the first user according to the blind number of the average blackout times of the first user, determining the average of the average blackout time of the first user according to the blind number of the average blackout time of the first user, and determining the average of the first power supply reliability according to the blind number of the first power supply reliability, further comprising:
determining an access line of a distributed power supply to the power distribution network;
acquiring the blind number of the average power failure times of a second user according to the blind number of the line failure rate of the access line and the blind number of the average power failure times of the first user based on a blind number four rule algorithm, acquiring the blind number of the average power failure time of the second user according to the blind number of the line failure rate of the access line and the blind number of the average power failure time of the first user, and acquiring the blind number of the second power supply reliability rate according to the blind number of the line failure rate of the access line and the blind number of the first power supply reliability rate;
determining the average value of the average power failure times of the second user according to the blind number of the average power failure times of the second user, determining the average value of the average power failure time of the second user according to the blind number of the average power failure time of the second user, determining the average value of the second power supply reliability rate according to the blind number of the second power supply reliability rate, and taking the average value of the average power failure times of the second user, the average value of the average power failure time of the second user and the average value of the second power supply reliability rate as estimation parameters to carry out reliability estimation on the power distribution network accessed to the distributed power supply.
7. The method according to claim 6, wherein after estimating the reliability of the power distribution network accessing the distributed power supply by using the average value of the average number of times of power outage of the second user, the average value of the average length of time of power outage of the second user, and the average value of the second power supply reliability as estimation parameters, the method further comprises:
acquiring a first influence coefficient of the access of the distributed power supply on the average power failure times of users of the power distribution network according to the average value of the average power failure times of the first user and the average value of the average power failure times of the second user, acquiring a second influence coefficient of the access of the distributed power supply on the average power failure times of users of the power distribution network according to the average value of the average power failure times of the first user and the average value of the average power failure times of the second user, and acquiring a third influence coefficient of the access of the distributed power supply on the power supply reliability of the power distribution network according to the average value of the first power supply reliability and the average value of the second power supply reliability;
and taking the first influence coefficient, the second influence coefficient and the third influence coefficient as the improvement effect parameters of the reliability of the distributed power supply on the power distribution network.
8. The utility model provides a distribution network reliability pre-estimation device which characterized in that includes:
the first obtaining module is used for obtaining the blind number of the first outage rate of each area and the blind number of the first outage duration of each area according to the reliability parameters of each element in each area of the power distribution network, wherein the reliability parameters comprise the element failure rate, the planned overhaul rate, the average fault repair duration and the average planned overhaul duration;
the second obtaining module is used for obtaining the blind number of the second outage rate of each area and the blind number of the second outage duration of each area according to the blind number of the line fault rate of the lines among the areas, the blind number of the first outage rate of each area and the blind number of the first outage duration of each area;
the third obtaining module is used for obtaining the blind number of the average power failure times of the first user and the blind number of the average power failure time of the first user according to the blind number of the second power failure rate of each area and the blind number of the second power failure time of each area, and obtaining the blind number of the first power supply reliability according to the blind number of the average power failure times of the first user;
the estimation module is used for determining the average value of the average power failure times of the first user according to the blind number of the average power failure times of the first user, determining the average value of the average power failure time of the first user according to the blind number of the average power failure time of the first user, determining the average value of the first power supply reliability according to the blind number of the first power supply reliability, and taking the average value of the average power failure times of the first user, the average value of the average power failure time of the first user and the average value of the first power supply reliability as estimation parameters to estimate the reliability of the power distribution network.
9. The utility model provides a distribution network reliability prediction equipment which characterized in that includes:
at least one processor, at least one memory, and a data bus; wherein:
the processor and the memory complete mutual communication through the data bus; the memory stores program instructions executable by the processor, the processor calling the program instructions to perform the method of any of claims 1 to 7.
10. A non-transitory computer-readable storage medium storing a computer program that causes a computer to perform the method according to any one of claims 1 to 7.
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