CN113609756A - Method for evaluating operation failure of drainage wire of island distribution line - Google Patents

Method for evaluating operation failure of drainage wire of island distribution line Download PDF

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CN113609756A
CN113609756A CN202110787658.1A CN202110787658A CN113609756A CN 113609756 A CN113609756 A CN 113609756A CN 202110787658 A CN202110787658 A CN 202110787658A CN 113609756 A CN113609756 A CN 113609756A
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汤波
郑宇鹏
余光正
林静涛
杨鹏
蒋向兵
李健强
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Shanghai University of Electric Power
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Abstract

The invention relates to an island distribution line drainage wire operation failure evaluation method, which comprises the steps of counting a historical fault data set formed by fault frequency, fault duration and power loss load of a island distribution line fault drainage wire sample and carrying out clustering treatment to obtain a fault partition; taking a fault drainage wire with the highest fault frequency value in each fault partition as a typical representative; collecting wind speed, wind direction along the line, temperature of the drainage wire, solar radiation intensity, ambient temperature, salt haze and relative humidity of a typical fault drainage wire sample set to form a historical environment data set, and solving wind load operation failure probability and temperature rise failure probability of the drainage wire to further obtain operation failure probability; and solving the failure correction coefficient by an entropy weight method, correcting the operation failure probability of the drainage wire, and further obtaining a comprehensive operation failure index for evaluation. Compared with the prior art, the method has the advantages of improving the accuracy of the operation failure evaluation, reducing the evaluation workload and the like.

Description

Method for evaluating operation failure of drainage wire of island distribution line
Technical Field
The invention relates to the technical field of monitoring of states of distribution line drainage wires in an island environment, in particular to an evaluation method for operation failure of the distribution line drainage wires in the island.
Background
Compared with inland regions, islands have special geographical meteorological environments, and mainly show environmental characteristics such as strong wind speed, heavy salt fog, high humidity and the like. Particularly, because the salt fog content in the air of the island is high, the insulation aging and the performance degradation degree of the island power distribution network equipment are remarkably increased due to salt fog corrosion and strong wind attack every year. Therefore, the reliable state detection is carried out on the island distribution line equipment, the health management of the equipment can be effectively realized, and the running stability of the island distribution network is further improved.
The drain wire, which is a member of the distribution equipment, plays an important role in the distribution line. The drainage wire runs in a strong wind speed and strong corrosion environment of the island, the mechanical property and the electrical property of the drainage wire are seriously damaged, and the main failure modes are as follows: heating of the drainage wire, wire breakage and swinging of the drainage wire after wire breakage cause interphase short circuit faults. According to statistics, more than 300 power distribution network electrical equipment faults occur in the Zhejiang navishan power distribution network from 2016 to 2019, and the power failure caused by the drainage line fault accounts for more than 60% of the total number of faults. Therefore, the failure evaluation of the distribution line drainage wire in the typical environment of the island is particularly important.
The existing fault research on the drainage wire mainly focuses on: the drainage wire fault early warning method comprises three aspects of oscillation strand breakage, drainage wire corrosion aging and galloping wire breakage faults, and drainage wire fault early warning considering meteorological disaster influence, wherein the drainage wire is subjected to long-term action of wind load force. The fatigue fracture characteristic generated when the drainage wire is subjected to wind loading force is researched and analyzed by building a drainage wire swinging fatigue test platform, but if the fatigue fracture characteristic is only started from the wind loading test angle of the drainage wire, the fatigue fracture characteristic is not combined with the actual operation environment, especially the influence of the special strong wind speed and strong corrosion environment of the island is not considered, and the fatigue fracture characteristic has great limitation. The influence of wind load on the drainage wire in an inland environment is analyzed by a meteorological coefficient method, and the operation failure of the drainage wire in a strong wind environment is predicted by a data driving mode. However, these studies lack the consideration of multi-environment scenes and the detection and analysis of the operating state of the drainage wire in the sea island environment.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a method for evaluating the operation failure of the jumper of the island distribution line.
The purpose of the invention can be realized by the following technical scheme:
a method for evaluating the operation failure of a drainage wire of an island distribution line comprises the following steps:
s1: and acquiring the fault frequency, the fault duration and the power loss load of the fault drainage wire sample of the island distribution line, and forming a historical fault data set by the three.
S2: and performing dimension reduction processing on the historical fault data set to obtain a two-dimensional matrix of the historical fault data set.
Further, a KPCA-Kmeans method is adopted to perform dimension reduction processing on the historical fault data set. The method comprises the following specific steps:
21) wall calendarThe history fault data set { Y } forms a high-dimensional matrix Y ═ Y1，y2，y3]，y1，y2，y3Respectively obtaining the fault frequency, the fault duration time and the power loss load of the fault drainage wire sample of the island distribution line, and obtaining a high-dimensional characteristic image l by mapping phii，i＝1，2，3；
22) To liThe new target is solved as follows:
Figure BDA0003159681780000021
in the formula, wiIs a projected hyperplane;
Figure BDA0003159681780000022
λiis composed of
Figure BDA0003159681780000023
A characteristic value of (d); and m is 3.
23) And (3) realizing mapping phi by adopting a kernel function sigmoid function:
Figure BDA0003159681780000024
wherein, tanh is a hyperbolic tangent function; j is i in the hyperplane wiCorresponding values, j ═ i ═ 1, 2, 3; beta and mu are constants, and beta is 3, mu is 11.16;
24) the new target is simplified by sigmoid function 22):
Kαij＝λjαij
wherein K is a kernel matrix corresponding to the sigmoid function, Kij＝sigmoid(yi,yj)，αijα for the hyperplane j corresponding to plane i, which is numerically equal to αiEqual, λjIn a number corresponding to λiEqual;
25) the original data matrix Y is equal to [ Y ═ Y1，y2，y3]Reduced to two dimensions to obtain a matrix z]The coordinate of the nth (n is 1, 2) dimensionComprises the following steps:
Figure BDA0003159681780000025
s3: clustering a two-dimensional matrix of a historical fault data set, preliminarily dividing fault drainage wire samples to obtain three types of fault areas, and taking the sum of the fault frequency, the fault duration and the power loss load of each area as a criterion to obtain three types of fault partitions with sequentially decreasing fault degrees. The concrete contents are as follows:
31) setting the number of clustering clusters as 3, and randomly selecting an initial mean vector c (c belongs to [ z ]);
32) by the distance calculation formula: d | | | z '-c | |, the distance of each group of vectors z' and c of other groups in the matrix [ z ] is calculated;
33) setting iteration times, continuously selecting a new mean value vector c from the matrix [ z ] for iteration updating, and obtaining three primarily-divided fault partitions according to a final fault drainage line sample clustering partition result after the iteration times are finished;
34) at the moment, according to the fault frequency y of all the fault drainage wire sample sets in each fault partition1And duration of failure y2To which it is numerically summed y1+y2And obtaining three types of fault partitions with sequentially decreasing fault degrees according to numerical value sorting: s1、S2、S3。
S4: and selecting the fault drainage wire with the highest fault frequency value in each fault partition as a typical representative, and if the fault drainage wire samples with the same fault frequency exist, sequentially comparing the fault duration and the power loss load value to select.
S5: the wind speed, the wind direction along the line, the temperature of the drainage wire, the solar radiation intensity, the environmental temperature, the salt fog degree and the relative humidity of a typical fault drainage wire sample are collected through an SCADA (supervisory control and data acquisition) system of the island distribution line, and a historical environmental data set is formed.
S6: based on a historical environment data set, the wind speed and the wind direction along the line of a typical fault drainage wire sample are combined, and the wind load failure probability of the island distribution line drainage wire is obtained through an island drainage wire wind load failure calculation formula and an extreme value I-type probability distribution function. The concrete contents are as follows:
61) according to the actual operation condition of the island drainage line, the calculation formula of the standard value of the wind load of the overhead conductor of the power distribution network is improved, and the calculation formula is associated with the wind speed and the wind direction along the line, so that the calculation formula of the wind load of the island distribution line drainage line is obtained:
Wx＝αμsμzdLwv2 sin2θ/1600
in the formula, alpha is a wind load span coefficient; v is the wind speed; theta is the wind direction along the line, and the corresponding numerical value is in the historical environment data set; mu.szIs the wind pressure height variation coefficient; l iswIs a wind span; mu.ssIs the wind load body type coefficient;
62) setting specific parameters of the improved formula in the step 61) according to the actual situation of the island to obtain a final calculation formula of the wind load of the diversion line of the island distribution line;
63) obtaining the wind load value W of the drainage wire in the sea island environmentxThen, the probability p of drainage wire wind load failure is determined by using extreme value I type probability distributionfAnd (3) calculating:
Figure BDA0003159681780000041
in the formula, σxWind load standard deviation; a is a scale parameter of extreme value I type distribution; w is axIs wind load; u. ofxDesigning wind load; u is the location parameter of the extreme type I distribution.
S7: and (4) solving the temperature rise failure probability of the drainage wire of the island distribution line by combining the drainage wire temperature of the drainage wire sample with the collection of the typical fault.
Further, the temperature rise failure probability of the drainage wire of the island distribution line is obtained through an Arrhenius drainage wire service life-temperature rise calculation method and a Weibull probability distribution function. The method comprises the following specific steps:
71) based on an Arrhenius drainage wire service life-temperature rise calculation method, the formula is as follows:
Figure BDA0003159681780000042
wherein L (θ) is a quantifiable average lifetime; thetayFor the drain wire temperature, the corresponding value is in the historical environmental data set { in; a and B are empirical constants;
72) according to the solution method of L (theta) in the step 71), the temperature rise failure probability p of the island distribution line drainage wire is determined by adopting Weibull probability distributionwAnd (3) solving:
Figure BDA0003159681780000043
in the formula, t is the running time of the drainage wire; beta is asIs a shape parameter.
S8: and carrying out weighted summation on the wind load failure probability of the island distribution line drainage line and the temperature rise failure probability of the island distribution line drainage line to obtain the operation failure probability of the drainage line.
Wind load failure probability p of island distribution line drainage linefAnd temperature rise failure probability pwCarrying out weighted addition, calculating to obtain the operation failure probability p of the drainage wire, taking twice standard wind load as a destruction basis, and when the wind load exceeds twice standard wind load, the drainage wire is damaged due to strong instantaneous destruction; the calculation formula of the operation failure probability p of the diversion line of the island distribution line is as follows:
Figure BDA0003159681780000044
in the formula, wxThe actual wind load is obtained; w is adIs a standard wind load; k is a radical off、kwRespectively, wind load and temperature rise weight coefficients.
S9: the method comprises the steps of obtaining weights of solar radiation intensity, ambient temperature, salt haze and relative humidity of a typical fault drainage wire sample through an entropy weight method, solving a failure correction coefficient through a correction coefficient calculation method, correcting the operation failure probability of the drainage wire in a mode of multiplying the failure correction coefficient by the operation failure probability of the drainage wire, and further obtaining the comprehensive operation failure index of the island distribution line drainage wire. The method comprises the following specific steps:
91) calculating the intensity x of sunlight radiation by entropy weight method4Ambient temperature x5Salt haze x6And relative humidity x7Total weight omega of four environment variablesj，j＝1，2，3，4：
Figure BDA0003159681780000051
In the formula, ωjIs the entropy weight; e.g. of the typejIs the information entropy; m is 4;
92) intensity x of solar radiation4Ambient temperature x5Salt haze x6And relative humidity x7The values in the historical environment data set { X } form a matrix X ═ X1,x2,x3,x4]And constructing a corresponding weight matrix omega ═ omega1,ω2,ω3,ω4]The composite score criterion was calculated as follows:
Figure BDA0003159681780000052
Figure BDA0003159681780000053
in the formula, Wmax、WminRespectively as a reference comprehensive score maximum value and a reference comprehensive score minimum value; x is the number ofmax,i、xmin,iRespectively the upper and lower bounds of the variable value; m is 4;
93) calculating a comprehensive fault score value:
Figure BDA0003159681780000054
94) calculating a failure correction coefficient delta:
Figure BDA0003159681780000055
95) and correcting the island distribution line drainage wire operation failure model by multiplying the failure correction coefficient delta by the island distribution line drainage wire operation failure probability p to obtain U:
Figure BDA0003159681780000056
in the formula, wxThe actual wind load is obtained; w is adIs a standard wind load; p is a radical offThe probability of wind load failure of the drainage line of the island distribution line is determined; p is a radical ofwThe probability of the temperature rise failure of the drainage wire of the island distribution line is shown.
S10: and evaluating the running state of the drainage wire by taking the comprehensive running failure index of the drainage wire of the island distribution line as a running failure evaluation basis of the drainage wire of the island distribution line. Specifically, the method comprises the following steps:
judging according to the obtained comprehensive operation failure index U of the island distribution line drainage line, if U is less than 30%, judging that the drainage line has good operation condition and cannot fail under the normal operation condition; if U is more than or equal to 30% and less than 60%, the operation condition of the drainage wire is judged to be general, and the drainage wire is not easy to lose efficacy under the normal operation condition; if the number of the drainage wires is more than 60 percent and less than U, the drainage wires are judged to have poor running conditions and are easy to have running failure conditions.
Compared with the prior art, the method for evaluating the operation failure of the drainage wire of the island distribution line, provided by the invention, at least has the following beneficial effects:
firstly, the invention fully considers the fault influence of island microclimate environment on the operation failure of the distribution line drainage wire to different degrees, uses a KPCA-Kmeans method to perform clustering processing on a historical fault data set, and uses the sum of the fault frequency, the fault duration and the power loss load of each area as a criterion to obtain three fault partitions with sequentially decreasing fault degrees; and the representative fault drainage wire in each subarea is obtained by taking the fault frequency as the basis, so that the workload of calculation and evaluation is reduced, and the typical and accurate evaluation is ensured.
According to the actual running condition of the distribution line drainage wire in the island environment, the running failure probability of the island drainage wire is obtained by combining the wind load failure probability and the temperature rise failure probability of the island distribution line drainage wire; the method is the embodiment of the running condition of the drainage wire in the sea island environment, and has a good evaluation effect.
Solving failure coefficients of sunlight radiation intensity, environment temperature, salt haze and relative humidity, and correcting the operation failure probability of the drainage wire in a mode of multiplying the failure coefficients by the operation failure probability of the island drainage wire so as to obtain a comprehensive operation failure index of the island distribution line drainage wire; by taking the index as an evaluation basis, the accuracy of evaluation can be effectively improved, and better benefits can be obtained.
Drawings
FIG. 1 is a schematic flow chart of a method for evaluating operation failure of a drainage wire of an island distribution line in an embodiment;
FIG. 2 is a schematic diagram of evaluation of the integrated operation failure indicator U of the drainage wire in the embodiment.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, shall fall within the scope of protection of the present invention.
Examples
The invention relates to an evaluation method for the operation failure of a drainage wire of an island distribution line, which is implemented by counting the failure frequency y of a failure drainage wire sample of the island distribution line1Fault duration y2Power-off load y3Forming a historical fault data set { Y }, clustering the { Y } by using a KPCA-Kmeans method, primarily dividing to obtain 3 types of fault areas, and using each area Y to obtain a plurality of fault areas1+y2+y3The numerical value of the three-level fault is taken as a criterion to obtain the fault partitions S with the 3 types of fault degrees decreasing in sequence1、S2、S3(ii) a Get y in each fault partition1The highest value of faulty jumper is typically represented (if y is present)1Equal faulty drainage wire samples, then y is compared in order2、y3The value of the drainage line sample set is selected), the wind speed x of the typical fault drainage line sample set is acquired through an island distribution line data acquisition system SCADA (supervisory control and data acquisition)1Wind direction x along the line2Temperature x of the drainage wire3Intensity of solar radiation x4Ambient temperature x5Salt haze x6Relative humidity x7Forming a historical environment data set { X }; based on the historical environment data set { X }, incorporating X1、x2Solving the wind load operation failure probability p of the drainage wire through the wind load failure calculation formula of the sea island drainage wire and the extreme value I type probability distribution functionf(ii) a Binding of x3The temperature rise failure probability p of the drainage wire is obtained through an Arrhenius drainage wire life-temperature rise calculation formula and a Weibull probability distribution functionw(ii) a P is to befAnd pwCarrying out weighted summation to obtain the operation failure probability p of the drainage wire; for x by entropy weight method4、x5、x6、x7Solving a weight value, and solving a failure correction coefficient delta by using a correction coefficient calculation method; correcting the operation failure probability of the drainage wire in a mode of multiplying delta by p so as to obtain the comprehensive operation failure index U of the drainage wire of the island distribution line; the U is used as the evaluation basis for the operation failure of the drainage wire of the island distribution line, if the U is less than 30 percent, the operation condition of the drainage wire is good, and the drainage wire cannot fail under the normal operation condition; if U is more than or equal to 30% and less than 60%, the operation condition of the drainage wire is general, and the drainage wire is not easy to lose efficacy under the normal operation condition; if the ratio of 60 percent to U is less than U, the operation condition of the drainage wire is poor, and the operation failure condition is easy to occur.
The main principle of the method for evaluating the operation failure of the drainage wire of the island distribution line is as follows: firstly, clustering is carried out by using a KPCA-Kmeans clustering method on the basis of a historical fault data set { Y } formed by fault frequency Y1, fault duration Y2 and power loss load Y3 of a fault drainage wire, and each region Y is used for clustering1+y2+y3Dividing the numerical value of the data into 3 types of fault partitions with sequentially decreasing fault degrees by taking the numerical value of the data as a criterionS1、S2、S3The calculation range is reduced, and the drainage wire failure evaluation is made to be typical. Starting from the wind stress mechanical damage and corrosion temperature rise electrical damage angles of the typical strong wind speed and strong corrosion scene of the island to the drainage wire, the wind load operation failure probability p of the drainage wire is obtainedfAnd temperature rise failure probability pwAnd weighting and adding to obtain the drainage wire failure probability p. Thirdly, in finding out the island x4、x5、x6、x7On the basis of the weight value, the comprehensive operation failure index U of the island distribution line drainage wire is obtained by solving a correction coefficient delta and correcting the operation failure probability of the drainage wire in a mode of multiplying delta by p. And fourthly, taking the comprehensive operation failure index U as an evaluation standard: if U is less than 30%, the drainage wire has good running condition and cannot lose efficacy under the normal running condition; if U is more than or equal to 30% and less than 60%, the operation condition of the drainage wire is general, and the drainage wire is not easy to lose efficacy under the normal operation condition; if the number of the U is less than 60 percent, the operation condition of the drainage wire is poor, the operation failure condition is easy to occur, and important attention is needed.
The method for evaluating the operation failure of the drainage wire of the island distribution line comprises the following steps:
step one, counting the fault frequency y of the fault drainage wire sample of the island distribution line1Fault duration y2Power-off load y3Constitute the historical failure data set Y.
Step two, using a KPCA-Kmeans method, setting the number of principal components in KPCA as 2, and carrying out dimension reduction processing on { Y }, and carrying out three-dimensional variable matrix [ Y ]1、y2、y3]Dimension reduction to obtain a two-dimensional matrix [ z ]]. At this time, there are 2 variables in the two-dimensional matrix, named: principal component 1, principal component 2. The specific realization of the KPCA dimension reduction comprises the following steps:
21) and forming a high-dimensional matrix Y (Y) by the historical fault data set (Y)1，y2，y3]And obtaining a high-dimensional characteristic image l by mapping phii，i＝1，2，3。
22) To liSolving a new target:
Figure BDA0003159681780000081
in the formula, wiIs a projected hyperplane;
Figure BDA0003159681780000082
λiis composed of
Figure BDA0003159681780000083
A characteristic value of (d); and m is 3.
23) And (3) realizing mapping phi by adopting a kernel function sigmoid function:
Figure BDA0003159681780000084
wherein, tanh is a hyperbolic tangent function; j is i in the hyperplane wiCorresponding values, j ═ i ═ 1, 2, 3; β and μ are constants, β is 3, and μ is 11.16.
24) The new target is simplified by sigmoid function 22):
Kαij＝λjαij
wherein K is a kernel matrix corresponding to the sigmoid function, Kij＝sigmoid(yi,yj)，αijα for the hyperplane j corresponding to plane i, which is numerically equal to αiEqual, λjIn a number corresponding to λiAre equal.
25) The original data matrix Y is equal to [ Y ═ Y1，y2，y3]Reduced to two dimensions to obtain a matrix z]And the coordinate of the nth (n is 1, 2) dimension is:
Figure BDA0003159681780000085
step three, obtaining a two-dimensional matrix [ z ] in dimensionality reduction]Then, the two-dimensional matrix [ z ] is mapped by Kmeans]And clustering is carried out, and the fault drainage wire sample set is preliminarily divided into 3 types of fault partitions. Further, with each region y1+y2+y3The numerical value of the three-level fault is taken as a criterion to obtain the fault partitions S with the 3 types of fault degrees decreasing in sequence1、S2、S3. The specific clustering content comprises:
31) setting the number of clustering clusters to be 3, and randomly selecting an initial mean vector c (c belongs to [ z ]).
32) By the distance calculation formula: and d | | z '-c | |, and the distance between each group of vectors z' of other groups in the matrix [ z ] and c is obtained.
33) And setting the iteration times as 100 times, and continuously selecting a new mean vector c from the matrix [ z ] for iterative updating (namely selecting a division result with the shortest calculation distance in each iteration). And after the iteration times are finished, obtaining the preliminarily divided 3 types of fault partitions according to the final fault drainage line sample clustering partition result.
34) At the moment, according to the fault frequency y of all the fault drainage wire sample sets in each partition1Fault duration y2To which it is numerically summed y1+y2And sequencing according to the numerical value to obtain 3 types of fault partitions with sequentially decreasing fault degrees: s1、S2、S3。
Step four, obtaining the fault partitions S with 3 types of fault degrees sequentially decreasing in clustering division1、S2、S3And then, selecting the fault drainage wire with the highest fault frequency in each fault partition as a typical representative, and if the fault drainage wire samples with the same fault frequency exist, sequentially comparing and selecting according to the fault duration and the magnitude of the power loss load, and finally obtaining 3 typical fault drainage wires in 3 types of fault partitions.
Step five, collecting the wind speed x of a typical fault drainage wire sample through an SCADA (supervisory control and data acquisition) system of the island distribution line1Wind direction x along the line2Temperature x of the drainage wire3Intensity of solar radiation x4Ambient temperature x5Salt haze x6Relative humidity x7A historical environment data set X is constructed.
And step six, taking the influence of the strong wind speed environment of the island on the drainage wire into consideration on the basis of the historical environment data set { X }, and taking the fault drainage wire thereinThe wind speed x1 of the streamline sample and the wind direction x2 along the streamline sample are used for calculating the wind load failure probability p of the diversion line of the island distribution line through the wind load failure calculation formula of the island diversion line and the extreme value I-shaped probability distribution functionfThe method comprises the following specific steps:
61) the calculation formula of the standard value of the wind load of the overhead conductor of the power distribution network is as follows:
Wx＝αμsdLwWo
in the formula, WxThe standard value of the wind load of the wire is set; alpha is the wind load span coefficient; d is the calculated diameter of the wire; l iswIs a wind span; mu.ssIs the wind load body type coefficient; woThe standard value of the wind pressure is used as a benchmark.
62) According to the operation condition of the island drainage wire, improving the calculation formula 61), and associating the calculation formula with the wind speed and the wind direction along the line to obtain the wind load calculation formula of the island distribution line drainage wire:
Wx＝αμsμzdLwv2 sin2θ/1600
wherein v is the wind speed, theta is the wind direction along the line, and the corresponding numerical value is in the historical environment data set { X }; mu.szIs the wind pressure height variation coefficient.
63) According to the actual condition of the island, setting 62) concrete parameters of an improved formula: taking alpha as 0.85, d as 9.5mm, Lw＝0.6，μs＝1.2，μz1.38. Obtaining a final calculation formula of the wind load of the drainage line of the island distribution line:
Wx＝4.982904×10-3v2sin2θ
64) obtaining the wind load value W of the drainage wire in the sea island environmentxThen, the probability p of drainage wire wind load failure is determined by using extreme value I type probability distributionfAnd (3) calculating:
Figure BDA0003159681780000101
in the formula, σxFor the standard deviation of wind load, take sigmax1 is ═ 1; a is an electrodeTaking a as 2 as a scale parameter of the I-type distribution; w is axIs wind load; u. ofxTo design wind load, take ux3.114; and u is a position parameter of the extreme value type I distribution, and is 0.5.
Step seven, considering the influence of the sea island strong corrosion environment on the heating operation of the drainage wire, and taking the temperature X of the drainage wire in the historical environment data set { X }, wherein3Data, calculating the temperature rise failure probability p of the drainage wire of the island distribution line by using an Arrhenius drainage wire life-temperature rise calculation method and a Weibull probability distribution functionwThe method comprises the following specific steps:
71) the service life-temperature rise calculation method of the Arrhenius drainage wire is used, and the formula is as follows:
Figure BDA0003159681780000102
wherein L (θ) is a quantifiable average lifetime; thetayFor drainage wire temperatures, the corresponding values are in the historical environmental dataset { X }; a and B are empirical constants, and take A-50 and B-23.
72) According to 71) solution method for L (theta), using Weibull probability distribution for pwAnd (3) solving:
Figure BDA0003159681780000103
in the formula, t is the running time of the drainage wire; beta is asTaking beta as a shape parameters＝1.25。
Step eight, carrying out wind load failure probability p on the island distribution line drainage linefAnd temperature rise failure probability pwAnd performing weighted addition, and calculating to obtain the operation failure probability p of the drainage wire. And 2 times of standard wind load is taken as a destruction basis, and when the wind load exceeds 2 times of standard wind load, the drainage wire is damaged due to strong instantaneous destruction. The operation failure probability p of the drainage wire of the island distribution line is calculated as follows:
Figure BDA0003159681780000104
in the formula, wxThe actual wind load is obtained; w is adIs a standard wind load; k is a radical off、kwRespectively are wind load and temperature rise weight coefficients; taking k according to the operation condition of the sea island drainage linef＝0.65，kw＝0.35。
Ninth, the intensity x of the sunlight radiation is measured by an entropy weight method4Ambient temperature x5Salt haze x6Relative humidity x7The method comprises the following steps of calculating a weight, solving a failure correction coefficient delta by using a correction coefficient calculation method, correcting the operation failure probability of the drainage wire in a mode of multiplying delta by p, and further obtaining a comprehensive operation failure index U of the drainage wire of the island distribution line, wherein the specific steps are as follows:
91) method for calculating solar radiation intensity x by using entropy weight method4Ambient temperature x5Salt haze x6Relative humidity x7Total weight omega of 4 environment variablesj(j＝1，2，3，4)：
Figure BDA0003159681780000111
In the formula, ωjIs the entropy weight; e.g. of the typejIs the information entropy; and m is 4.
92) The values of the sunlight radiation intensity, the ambient temperature, the salt fog degree and the relative humidity in the historical environment data set { X } form a matrix X ═ X1,x2,x3,x4]And constructing a corresponding weight matrix omega ═ omega1,ω2,ω3,ω4]. Calculating a comprehensive scoring benchmark:
Figure BDA0003159681780000112
Figure BDA0003159681780000113
in the formula, Wmax、WminRespectively as a reference comprehensive score maximum value and a reference comprehensive score minimum value; x is the number ofmax,i、xmin,iRespectively the upper and lower bounds of the variable value; and m is 4.
93) Calculating a comprehensive fault score value:
Figure BDA0003159681780000114
94) calculating a failure correction coefficient delta:
Figure BDA0003159681780000115
95) correcting the operation failure model of the island distribution line drainage wire by delta x p to obtain U:
Figure BDA0003159681780000116
tenthly, evaluating the running state of the drainage wire by taking the U as a running failure evaluation basis of the drainage wire of the island distribution line: if U is less than 30%, the drainage wire has good running condition and cannot lose efficacy under the normal running condition; if U is more than or equal to 30% and less than 60%, the operation condition of the drainage wire is general, and the drainage wire is not easy to lose efficacy under the normal operation condition; if the ratio of 60 percent to U is less than U, the operation condition of the drainage wire is poor, and the operation failure condition is easy to occur.
The invention fully considers the fault influence of island microclimate environment on the operation failure of the distribution line drainage wire in different degrees, uses KPCA-Kmeans method to cluster the historical fault data set { Y }, and uses each region Y to cluster1+y2+y3The numerical value of the three-level fault is taken as a criterion to obtain the fault partitions S with the 3 types of fault degrees decreasing in sequence1、S2、S3(ii) a And the representative fault drainage wire in each subarea is obtained by taking the fault frequency y1 as a basis, so that the workload of calculation and evaluation is reduced, and the typical and accurate evaluation is ensured.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and those skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (10)

1. A method for evaluating the operation failure of a drainage wire of an island distribution line is characterized by comprising the following steps:
1) acquiring the fault frequency, the fault duration and the power loss load of the island distribution line fault drainage wire sample, and forming a historical fault data set by the three;
2) performing dimension reduction processing on the historical fault data set to obtain a two-dimensional matrix of the historical fault data set;
3) clustering a two-dimensional matrix of a historical fault data set, preliminarily dividing a fault drainage wire sample to obtain three types of fault areas, and taking the sum of the fault frequency, the fault duration and the power loss load of each area as a criterion to obtain three types of fault partitions with sequentially reduced fault degrees;
4) selecting a fault drainage wire with the highest fault frequency value in each fault partition as a typical representative, and if a fault drainage wire sample with the same fault frequency exists, sequentially comparing the fault duration and the power-off load value to select;
5) collecting the wind speed, the wind direction along the line, the temperature of the drainage wire, the solar radiation intensity, the environmental temperature, the salt fog degree and the relative humidity of a typical fault drainage wire sample by using an SCADA (supervisory control and data acquisition) system of an island distribution line to form a historical environmental data set;
6) based on a historical environment data set, combining the wind speed and the wind direction along the line of a typical fault drainage wire sample, and solving the wind load failure probability of the drainage wire of the island distribution line through an island drainage wire wind load failure calculation formula and an extreme value I-shaped probability distribution function;
7) the temperature rise failure probability of the drainage wire of the island distribution line is obtained by combining the drainage wire temperature of a drainage wire sample with a typical fault;
8) weighting and summing the wind load failure probability of the island distribution line drainage line and the temperature rise failure probability of the island distribution line drainage line to obtain the operation failure probability of the drainage line;
9) solving weights of solar radiation intensity, ambient temperature, salt haze and relative humidity of a typical fault drainage wire sample by an entropy weight method, solving a failure correction coefficient by using a correction coefficient calculation method, correcting the operation failure probability of the drainage wire in a mode of multiplying the failure correction coefficient by the operation failure probability of the drainage wire, and further obtaining the comprehensive operation failure index of the island distribution line drainage wire;
10) and evaluating the running state of the drainage wire by taking the comprehensive running failure index of the drainage wire of the island distribution line as a running failure evaluation basis of the drainage wire of the island distribution line.
2. The method for evaluating the operation failure of the drainage wire of the island distribution line of claim 1, wherein in the step 2), a KPCA-Kmeans method is adopted to perform dimension reduction processing on the historical fault data set.
3. The method for evaluating the operation failure of the drainage wire of the island distribution line of claim 2, wherein the step of performing the dimensionality reduction on the historical fault data set by adopting a KPCA-Kmeans method comprises the following steps:
21) and forming a high-dimensional matrix Y (Y) by the historical fault data set (Y)1，y2，y3]，y1，y2，y3Respectively obtaining the fault frequency, the fault duration time and the power loss load of the fault drainage wire sample of the island distribution line, and obtaining a high-dimensional characteristic image l by mapping phii，i＝1，2，3；
22) To liThe new target is solved as follows:
Figure FDA0003159681770000021
in the formula, wiIs a projected hyperplane;
Figure FDA0003159681770000022
λiis composed of
Figure FDA0003159681770000023
A characteristic value of (d); m is 3;
23) and (3) realizing mapping phi by adopting a kernel function sigmoid function:
Figure FDA0003159681770000024
wherein, tanh is a hyperbolic tangent function; j is i in the hyperplane wiCorresponding values, j ═ i ═ 1, 2, 3; beta and mu are constants, and beta is 3, mu is 11.16;
24) the new target is simplified by sigmoid function 22):
Kαij＝λjαij
wherein K is a kernel matrix corresponding to the sigmoid function, Kij＝sigmoid(yi,yj)，αijα for the hyperplane j corresponding to plane i, which is numerically equal to αiEqual, λjIn a number corresponding to λiEqual;
25) the original data matrix Y is equal to [ Y ═ Y1，y2，y3]Reduced to two dimensions to obtain a matrix z]And the coordinate of the nth (n is 1, 2) dimension is:
Figure FDA0003159681770000025
4. the method for evaluating the operation failure of the drainage wire of the island distribution line of claim 3, wherein the specific content of the step 3) is as follows:
31) setting the number of clustering clusters as 3, and randomly selecting an initial mean vector c (c belongs to [ z ]);
32) by the distance calculation formula: d | | | z '-c | |, the distance of each group of vectors z' and c of other groups in the matrix [ z ] is solved;
33) setting iteration times, continuously selecting a new mean value vector c from the matrix [ z ] for iteration updating, and obtaining three primarily-divided fault partitions according to a final fault drainage line sample clustering partition result after the iteration times are finished;
34) at the moment, according to the fault frequency y of all the fault drainage wire sample sets in each fault partition1And duration of failure y2To which it is numerically summed y1+y2And obtaining three types of fault partitions with sequentially decreasing fault degrees according to numerical value sorting: s1、S2、S3。
5. The method for evaluating the operation failure of the drainage wire of the island distribution line according to claim 1, wherein the specific content of the step 6) is as follows:
61) according to the actual operation condition of the island drainage line, the calculation formula of the standard value of the wind load of the overhead conductor of the power distribution network is improved, and the calculation formula is associated with the wind speed and the wind direction along the line, so that the calculation formula of the wind load of the island distribution line drainage line is obtained:
Wx＝αμsμzdLwv2sin2θ/1600
in the formula, alpha is a wind load span coefficient; v is the wind speed; theta is the wind direction along the line, and the corresponding numerical value is in the historical environment data set; mu.szIs the wind pressure height variation coefficient; l iswIs a wind span; mu.ssIs the wind load body type coefficient;
62) setting specific parameters of the improved formula in the step 61) according to the actual situation of the island to obtain a final calculation formula of the wind load of the diversion line of the island distribution line;
63) obtaining the wind load value W of the drainage wire in the sea island environmentxThen, the probability p of drainage wire wind load failure is determined by using extreme value I type probability distributionfAnd (3) calculating:
Figure FDA0003159681770000031
in the formula, σxWind load standard deviation; a is a scale parameter of extreme value I type distribution; w is axIs wind load; u. ofxDesigning wind load; u is the location parameter of the extreme type I distribution.
6. The method for evaluating the operation failure of the drainage wire of the island power distribution line of claim 1, wherein in the step 7), the temperature rise failure probability of the drainage wire of the island power distribution line is obtained through an Arrhenius drainage wire life-temperature rise calculation method and a Weibull probability distribution function.
7. The method for evaluating the operation failure of the drainage wire of the island power distribution line of claim 6, wherein the specific content of the probability of the temperature rise failure of the drainage wire of the island power distribution line obtained by the Arrhenius drainage wire life-temperature rise calculation method and the weibull probability distribution function is as follows:
71) based on an Arrhenius drainage wire service life-temperature rise calculation method, the formula is as follows:
Figure FDA0003159681770000032
wherein L (θ) is a quantifiable average lifetime; thetayFor the drain wire temperature, the corresponding value is in the historical environmental data set { in; a and B are empirical constants;
72) according to the solution method of L (theta) in the step 71), the temperature rise failure probability p of the island distribution line drainage wire is determined by adopting Weibull probability distributionwAnd (3) solving:
Figure FDA0003159681770000041
in the formula, t is the running time of the drainage wire; beta is asIs a shape parameter.
8. The method for evaluating the operation failure of the drainage wire of the island distribution line according to claim 1, wherein the specific content of the step 8) is as follows:
wind load failure probability p of island distribution line drainage linefAnd temperature rise failure probability pwCarrying out weighted addition, calculating to obtain the operation failure probability p of the drainage wire, taking twice standard wind load as a destruction basis, and when the wind load exceeds twice standard wind load, the drainage wire is damaged due to strong instantaneous destruction; the calculation formula of the operation failure probability p of the diversion line of the island distribution line is as follows:
Figure FDA0003159681770000042
in the formula, wxThe actual wind load is obtained; w is adIs a standard wind load; k is a radical off、kwRespectively, wind load and temperature rise weight coefficients.
9. The method for evaluating the operation failure of the drainage wire of the island distribution line of claim 1, wherein the step 9) of obtaining the comprehensive operation failure index of the drainage wire of the island distribution line comprises the following specific steps:
91) calculating the intensity x of sunlight radiation by entropy weight method4Ambient temperature x5Salt haze x6And relative humidity x7Total weight omega of four environment variablesj，j＝1，2，3，4：
Figure FDA0003159681770000043
In the formula, ωjIs the entropy weight; e.g. of the typejIs the information entropy; m is 4;
92) intensity x of solar radiation4Ambient temperature x5Salt haze x6And relative humidity x7The values in the historical environment data set { X } form a matrix X ═ X1,x2,x3,x4]And constructing a corresponding weight matrix omega ═ omega1,ω2,ω3,ω4]Is calculated according to the following formulaAnd (3) comprehensive scoring benchmark:
Figure FDA0003159681770000044
Figure FDA0003159681770000045
in the formula, Wmax、WminRespectively as a reference comprehensive score maximum value and a reference comprehensive score minimum value; x is the number ofmax,i、xmin,iRespectively the upper and lower bounds of the variable value; m is 4;
93) calculating a comprehensive fault score value:
Figure FDA0003159681770000051
94) calculating a failure correction coefficient delta:
Figure FDA0003159681770000052
95) and correcting the island distribution line drainage wire operation failure model by multiplying the failure correction coefficient delta by the island distribution line drainage wire operation failure probability p to obtain U:
Figure FDA0003159681770000053
in the formula, wxThe actual wind load is obtained; w is adIs a standard wind load; p is a radical offThe probability of wind load failure of the drainage line of the island distribution line is determined; p is a radical ofwThe probability of the temperature rise failure of the drainage wire of the island distribution line is shown.
10. The method for evaluating the operation failure of the drainage wire of the island distribution line of claim 1, wherein the specific content of the step 10) is as follows:
judging according to the obtained comprehensive operation failure index U of the island distribution line drainage line, if U is less than 30%, judging that the drainage line has good operation condition and cannot fail under the normal operation condition; if U is more than or equal to 30% and less than 60%, the operation condition of the drainage wire is judged to be general, and the drainage wire is not easy to lose efficacy under the normal operation condition; if the number of the drainage wires is more than 60 percent and less than U, the drainage wires are judged to have poor running conditions and are easy to have running failure conditions.
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2016026355A1 (en) * 2014-08-18 2016-02-25 国家电网公司 Voltage sag simulation and evaluation method of active power distribution grid
CN112488208A (en) * 2020-12-03 2021-03-12 上海电力大学 Method for acquiring remaining life of island pillar insulator
CN112668821A (en) * 2019-12-24 2021-04-16 国网新疆电力有限公司伊犁供电公司 Distribution line risk analysis method based on insulator fault probability of sand blown region
KR20210045753A (en) * 2019-10-17 2021-04-27 한국전력공사 System and Method for managing Power Distribution Facility

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2016026355A1 (en) * 2014-08-18 2016-02-25 国家电网公司 Voltage sag simulation and evaluation method of active power distribution grid
KR20210045753A (en) * 2019-10-17 2021-04-27 한국전력공사 System and Method for managing Power Distribution Facility
CN112668821A (en) * 2019-12-24 2021-04-16 国网新疆电力有限公司伊犁供电公司 Distribution line risk analysis method based on insulator fault probability of sand blown region
CN112488208A (en) * 2020-12-03 2021-03-12 上海电力大学 Method for acquiring remaining life of island pillar insulator

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
何迪;章禹;郭创新;陈玉峰;张金江;刘辉: "一种面向风险评估的输电线路故障概率模型", 电力系统保护与控制, vol. 45, no. 7 *

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