CN116739399A - High-voltage cable running state evaluation method - Google Patents
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Abstract
The invention discloses a high-voltage cable running state evaluation method, which mainly comprises the following steps: establishing a high-voltage cable operation state evaluation index system, which comprises the following steps: determining a factor set of a three-layer structure with a target layer, a project layer and an index layer from operation parameters of the high-voltage cable according to enterprise standards; and establishing a state set; collecting index data corresponding to the factor set of the high-voltage cable to be evaluated; normalizing the collected index data; the gray fuzzy theory is utilized to realize the first-level evaluation from the index layer to the item layer, and the evaluation result of each item is obtained; and (3) realizing the second-level evaluation from the project layer to the target layer by using the D-S evidence theory, and obtaining the running state of the high-voltage cable. The invention evaluates the running state of the high-voltage cable based on the gray fuzzy theory and the D-S evidence theory, and can fully consider the gray, the fuzzy and the randomness of each state quantity representing the current running state, thereby obtaining an evaluation result which is more close to the actual state of the equipment.
Description
Technical Field
The invention relates to a high-voltage cable operation system, in particular to a high-voltage cable operation state evaluation method.
Background
In recent years, as the ground-entering rate of overhead lines increases year by year, the importance of high-voltage cables in urban power supply systems is becoming more and more prominent. In the long-term operation process, the high-voltage cable can generate the phenomena of insulation aging and damage, if the phenomena of insulation aging and damage are not found in time and remedial measures are taken, the insulation degradation can be deepened continuously along with time, finally, the power supply line is caused to fail, the daily life electricity consumption of people and the production operation electricity consumption of enterprises are influenced slightly, and the casualties can be caused. Therefore, the method has extremely important significance for evaluating the running state of the high-voltage cable in the power grid.
At present, the evaluation of the running state of the high-voltage cable is mostly based on state evaluation guidelines issued by power enterprises such as national grid company, namely, the cable is scored according to the weight and defect degree of the single characteristic quantity of the cable, and the scores are accumulated to determine which state the cable is in. However, the weight and the deduction standard of the method are determined by experts, so that the method has strong subjectivity, complex changes of different characteristic quantities of different equipment cannot be fully considered, and some potential faults cannot be effectively mined.
Disclosure of Invention
Aiming at the prior art, the invention provides a high-voltage cable running state evaluation method, which is used for evaluating the running state of a high-voltage cable based on a gray fuzzy theory and a D-S evidence theory, and can fully consider the gray, fuzzy and randomness of various state quantities representing the current running state so as to obtain an evaluation result which is closer to the actual state of equipment.
In order to solve the technical problems, the invention provides a high-voltage cable running state evaluation method, which mainly comprises the following steps:
step 1, establishing a high-voltage cable running state evaluation index system, which comprises the following steps: determining a factor set of a three-layer structure with a target layer, a project layer and an index layer from operation parameters of the high-voltage cable according to enterprise standards; and establishing a state set;
step 2, collecting index data corresponding to the high-voltage cable to be evaluated and the factor set, wherein all the index data are derived from original materials, operation records, preventive tests, electrified detection and online monitoring systems;
step 3, normalizing the index data collected in the step 2, including: dividing the high-voltage cable running state evaluation index into a quantized index, a descriptive index and a qualitative evaluation index; the quantitative index is obtained by an online monitoring system or field measurement, the quantitative index is normalized by referring to the concept of relative degradation degree, the normalization result is [0,1], and the closer to 1, the better the cable running state; the described index is an index which can be described by language only by state degree dividing standard, and the described index is normalized by adopting expert scoring method, wherein the scoring range is [0,1], and the closer the score is 1, the better the cable running state is represented; the expert scoring basis is Q/GDW 456-2010 cable line state evaluation guideline issued by national grid Limited; the qualitative evaluation type index is characterized in that the state of the cable component has two definite division standards, the normalization result is 0 or 1,1 is in a normal state, and 0 is in a serious state according to the two division standards;
Step 4, realizing first-level evaluation from an index layer to a project layer by utilizing a gray fuzzy theory, so as to obtain an evaluation result of each project;
and 5, realizing secondary evaluation from the project layer to the target layer by using a D-S evidence theory, and finally obtaining the running state of the high-voltage cable.
Further, the method for evaluating the operation state of the high-voltage cable disclosed by the invention comprises the following steps of:
in step 1, the target layer is in a high-voltage cable running state, and is composed of five item layers, wherein the five item layers comprise a cable body Z 1 Line termination Z 2 Intermediate joint Z 3 Accessory device Z 4 And line channel Z 5 The method comprises the steps of carrying out a first treatment on the surface of the Each project layer comprises a plurality of index layers, wherein the cable body Z 1 Pressure test results Z of the cable body including index layer 11 Insulation resistor Z of outer sheath 12 Partial discharge amount Z 13 Line load Z 14 Appearance Z 15 Familial defect Z 16 Maintenance record Z 17 Operational years Z 18 The method comprises the steps of carrying out a first treatment on the surface of the The line terminal Z 2 Metal junction temperature Z including line termination 21 Sleeve temperature Z 22 Partial discharge Z 23 Appearance Z 24 Familial defect Z 25 Maintenance record Z 26 And operating years Z 27 The method comprises the steps of carrying out a first treatment on the surface of the The middle joint Z 3 Results of pressure test Z including an intermediate connector 31 Partial discharge amount Z 32 Intermediate joint temperature Z 33 Appearance Z 34 Familial defect Z 35 Maintenance record Z 36 And operating years Z 37 The method comprises the steps of carrying out a first treatment on the surface of the The accessory device Z 4 Pressure test results Z including ancillary facilities 41 Ground current Z 42 Temperature Z at the junction of the devices 43 And appearance Z 44 The method comprises the steps of carrying out a first treatment on the surface of the The line channel Z 5 Channel body construction case Z comprising a line channel 51 Channel external environmental conditions Z5 2 Channel marker Z 53 Frame internal facility Z 54 Leakage and ponding conditions Z 55 Fireproof and antitheft system condition Z 56 And harmful gases and foreign substances Z 57 ；
The method comprises the steps of combining enterprise standards for evaluating the states of the cable lines and selecting state quantities of actual working states of high-voltage cables running by the high-voltage cables, wherein the selected state quantities are as follows: taking the selected state quantity as a judging factor:
U＝{U 1 ,U 2 ,…,U m } (1)
in the formula (1), U i (i=1, 2, …, 5) represents five project layer cable bodies Z characterizing the cable running state 1 Line termination Z 2 Intermediate joint Z 3 Accessory device Z 4 And line channel Z 5 ；
In the formula (2), u ij (j=1, 2, …, n) represents a j-th index in an i-th item layer representing the cable operation state;
establishing a state set:
V＝{v 1 ,v 2 ,v 3 ,v 4 } (3)
dividing the operation state of the high-voltage cable into four state grades including a normal state, an attention state, an abnormal state and a serious state, respectively using v in turn 1 ,v 2 ,v 3 ,v 4 A representation;
the normal state is: the indexes of the index layer in the factor set are all within the attention value specified by the enterprise standard for evaluating the cable line state;
the attention state is that one or more indexes in the factor concentration index layer are intermediate values of attention values and abnormal values specified by enterprise standards of cable line state evaluation;
the abnormal state is that one or more indexes in the index layer in the factor set exceed the warning value, but do not reach the abnormal value;
the severity state is when one or more indicators in the indicators layer in the factor set exceed a specified outlier.
In step 2, the sources of all index layer data are:
said cable body Z 1 In the voltage withstand test result Z of the cable body 11 Insulation resistance value Z of outer sheath 12 Derived from preventive tests, local discharge Z 13 From live detection, line load Z 14 From an on-line monitoring system, appearance Z 15 Maintenance record Z 17 From the record of operation, familial defect Z 16 Operational years Z 18 Derived from the original material. The line terminal Z 2 In the metal junction temperature Z of the line terminal 21 Sleeve temperature Z 22 Partial discharge amount Z 23 From live detection, appearance Z 24 Maintenance record Z 26 From the record of operation, familial defect Z 25 Operational years Z 27 Derived from the original material. The middle joint Z 3 Results of pressure test of intermediate connector Z 31 Derived from preventive tests, local discharge Z 32 IntermediateJoint temperature Z 33 From live detection, appearance Z 34 Maintenance record Z 36 From the record of operation, familial defect Z 35 Operational years Z 37 Derived from the original material. The accessory device Z 4 Pressure test results Z of auxiliary facilities 41 From preventive tests, the ground current Z 42 Temperature Z at the junction of the devices 43 From live detection, appearance Z 44 From the operational record. The line channel Z 5 In the main structure case Z of the line channel 51 Channel external environmental conditions Z 52 Channel identification Z 53 Frame internal facility Z 54 Fireproof and antitheft system condition Z 56 From the running record, the water leakage and ponding situation Z 55 Harmful gas and foreign matter Z 57 Derived from an on-line monitoring system.
And 4, realizing the first-level evaluation from the index layer to the item layer by using a gray fuzzy theory, thereby obtaining the evaluation result of each item, wherein the contents comprise:
step 4-1) determining a gray fuzzy weight matrix: the gray fuzzy weight matrix consists of a model part and a gray part;
the model part of the gray fuzzy weight matrix refers to the weight corresponding to the evaluation index, determining the model part of the gray fuzzy weight matrix comprises determining subjective weight through a hierarchical analysis method, determining objective weight through an entropy weight method, and obtaining combined weight according to the subjective weight and the objective weight through a game theory; the gray part of the gray fuzzy weight matrix is determined by an expert scoring method according to the reliability of the weight; the gray part of the gray fuzzy weight matrix refers to the point gray corresponding to the weight;
Step 4-2) determining a gray fuzzy discriminant matrix: the gray fuzzy judgment matrix consists of a mould part and a gray part; the model part of the gray fuzzy judgment matrix represents fuzzy membership of the evaluation indexes to each evaluation state by fuzzy membership, and the membership is determined by adopting a cloud model theory; the gray part of the gray fuzzy judgment matrix represents the credibility of determining the fuzzy membership degree of the evaluation index in the form of point gray points;
and 4-3) synthesizing gray fuzzy comprehensive judgment, and converting the gray fuzzy comprehensive judgment matrix into a system result set according to the maximum membership degree and the minimum gray degree principle, wherein the system result set is the evaluation result of each item.
And 5, realizing the second-level evaluation from the project layer to the target layer by using the D-S evidence theory, and finally obtaining the running state of the high-voltage cable, wherein the content comprises the following steps:
step 5-1) determination of identification framework Θ: identifying the four state classes v of the frame Θ from the normal, attentive, abnormal and severe states of the operating state of the high-voltage cable 1 、v 2 、v 3 、v 4 And uncertainty θ specified by D-S evidence theory, namely:
Θ＝{v 1 ,v 2 ,v 3 ,v 4 ,θ}
step 5-2) determining a basic assignment function for each independent proof: according to the established high-voltage cable running state evaluation index system, the cable body Z of the project layer is evaluated 1 Line termination Z 2 Intermediate joint Z 3 Accessory facility Z 4 And line channel Z 5 Five items are used as independent evidences, the evaluation result of each item obtained in the step 4 is used as a basic assignment function of each independent evidence, and m is used i (A) The expression is satisfied:
introducing a confidence parameter α to said basic assignment function m i (A) Performing correction to represent the relative importance of different items; alpha is derived from the formula:
where λ is a finite confidence coefficient, λ=0.9; omega i Is the weight of the ith item in the weight vector of five independent evidences, omega max Is the maximum value in the weight vector;
the basic assignment function after the reliability correction is defined as:
step 5-3) evidence fusion: the evidence fusion is performed according to the following formula,
wherein m (A) is a basic assignment function corresponding to each state level after evidence fusion; a is that i To identify a subset of the frames Θ;
step 5-4) evaluation decision: judging the basic assignment function result of each state level by adopting the maximum membership rule, wherein the condition formula is that
Wherein m (v) 0 ) Representing the maximum value of the rating base assignment function, namely:
representing the next largest value of the rating base assignment function, i.eIf the difference exceeds a predetermined value epsilon 1 ，ε 1 ＝0.15；
If the formula (36) is satisfied, the evaluation result of the final operation state of the high-voltage cable is v 0 A corresponding grade;
if the formula (36) is not satisfied, adopting a credibility criterion to judge the basic assignment function result of each state level, wherein the formula is
In the formula (37), ε 2 For confidence level, ε 2 =0.5; if the formula (37) is satisfied, the evaluation result of the final operation state of the high-voltage cable is v 0 A corresponding grade;
if the expression (37) is not satisfied, the method returns to the step 4 to adjust the cloud model, subjective weight and gray part of the gray fuzzy weight matrix and gray part of the gray fuzzy judgment matrix until the expression (36) or the expression (37) is satisfied.
In the present invention, the enterprise criteria include: Q/GDW 456-2010 cable line state evaluation guidelines issued by national grid company, and Q/GDW 11316-2014 Power Cable line test Specification.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, factors influencing the running state of the high-voltage cable are fully analyzed based on enterprise standards and actual work of the high-voltage cable, a high-voltage cable running state evaluation index system is established, comprehensive evaluation on the running state of the high-voltage cable is realized by utilizing a gray fuzzy theory and a D-S evidence theory, the problems of fuzziness, randomness and gray of evaluation factors are effectively solved, an evaluation result is more comprehensive and accurate, a basis is provided for state maintenance of the high-voltage cable, occurrence of a power failure event caused by equipment failure is reduced, and the power supply reliability of the cable is improved.
Drawings
FIG. 1 is a flow chart of a method for evaluating the operation state of a high-voltage cable according to the invention;
FIG. 2 is an index system of the method for evaluating the operation state of the high-voltage cable;
FIG. 3 is a first-level evaluation flow from an index layer to a project layer by using a gray fuzzy theory in the evaluation method of the invention;
FIG. 4 is a flow chart of a second level evaluation from the project layer to the target layer by using the D-S evidence theory in the evaluation method of the invention.
Detailed Description
The invention will now be further described with reference to the accompanying drawings and specific examples, which are in no way limiting.
As shown in fig. 1, the method for evaluating the running state of the high-voltage cable provided by the invention mainly comprises the following steps:
step 1, establishing a high-voltage cable running state evaluation index system;
step 2, collecting index data corresponding to the factor set of the high-voltage cable to be evaluated;
step 3, normalizing the index data collected in the step 2;
step 4, realizing first-level evaluation from the index layer to the project layer by utilizing a gray fuzzy theory, and obtaining an evaluation result of the project layer;
and 5, realizing secondary evaluation from the project layer to the target layer by using a D-S evidence theory, and obtaining the running state of the evaluated high-voltage cable.
The step 1 comprises the following steps: determining a factor set of a three-layer structure with a target layer, a project layer and an index layer from operation parameters of the high-voltage cable according to enterprise standards; and establishing a state set;
1.1 determining an evaluation index System
When a researcher establishes an evaluation index system of a high-voltage cable, the research staff generally performs longitudinal division from four dimensions of original data, operation data, maintenance data and other data. However, because the high-voltage cable line is generally longer, the index system is not beneficial to the fault location, identification and subsequent state maintenance work of the equipment; meanwhile, the components of the cable line are relatively independent, and the functions and the reasons for causing faults are obviously different, so that the performance requirements in the aspects of electric, mechanical and the like are also different. The method fully considers the relative independence and different points among the components of the high-voltage cable, transversely divides the high-voltage cable into five units of a cable body, a line terminal, an intermediate joint, an accessory facility and a line channel, analyzes the index of the characterization state of each unit, and finally obtains the current operation state evaluation result. The system structure can adopt different evaluation methods for different components, and has the characteristics of clear structure, clear level and easy understanding.
The high-voltage cable running state evaluation index system is shown in fig. 2, wherein the target layer is a high-voltage cable running state and consists of five project layers, and the five project layers comprise a cable body Z 1 Line termination Z 2 Intermediate joint Z 3 Accessory device Z 4 And line channel Z 5 ；
Each item layer comprises a plurality of index layers, wherein,
the cable body Z 1 Pressure test results Z of the cable body including index layer 11 Insulation resistor Z of outer sheath 12 Partial discharge amount Z 13 Line load Z 14 Appearance Z 15 Familial defect Z 16 Maintenance record Z 17 Operational years Z 18 ；。
The line terminal Z 2 Metal junction temperature Z including line termination 21 Sleeve temperature Z 22 Partial discharge Z 23 Appearance Z 24 Familial defect Z 25 Maintenance record Z 26 And operating years Z 27 。
The middle joint Z 3 Results of pressure test Z including an intermediate connector 31 Partial discharge amount Z 32 Intermediate joint temperature Z 33 Appearance Z 34 Familial defect Z 35 Maintenance record Z 36 And operating years Z 37 。
The accessory device Z 4 Pressure test results Z including ancillary facilities 41 Ground current Z 42 Temperature Z at the junction of the devices 43 And appearance Z 44 。
The line channel Z 5 Channel body construction case Z comprising a line channel 51 Channel external environmental conditions Z 52 Channel marker Z 53 Frame internal facility Z 54 Leakage and ponding conditions Z 55 Fireproof and antitheft system condition Z 56 And harmful gases and foreign substances Z 57 。
1.2 determining the factor set and the State set
The enterprise standard (generally comprising Q/GDW456-2010 cable line state evaluation guidelines issued by the national power grid company, Q/GDW 11316-2014 power cable line test procedure) and the selected state quantity of the actual working state of the high-voltage cable operated by the high-voltage cable are combined, wherein the selected state quantity comprises the following steps:
according to the high-voltage cable running state evaluation index system, the selected state index quantity is used as a judgment factor:
U＝{U 1 ,U 2 ,…,U m } (1)
in the formula (1), U i (i=1, 2, …, 5) represents five project layer cable bodies Z characterizing the cable running state 1 Line termination Z 2 Intermediate joint Z 3 Accessory device Z 4 And line channel Z 5 ；
U i ＝{u i1 ，u i2 ，…，u in } (2)
In the formula (2), u ij (j=1, 2, …, n) represents a j-th index in an i-th item layer representing the operation state of the cable, representing an i-th influencing factor of each unit of the cable. Take the cable body as an example, where m=1, n= 8,u 11 To u 18 Respectively representing withstand voltage test, insulation resistance of the outer sheath, partial discharge amount, line load, appearance, familial defect, maintenance record and operation life.
Establishing a state set:
V＝{v 1 ,v 2 ,v 3 ,v 4 } (3)
in the invention, the running state of the high-voltage cable is divided into four state grades comprising a normal state, an attention state, an abnormal state and a serious state, and v is respectively used in sequence 1 ,v 2 ,v 3 ,v 4 A representation;
the normal state is: the indexes of the index layer in the factor set are all within the attention value specified by the enterprise standard for evaluating the cable line state. When the cable state is in a normal state, the whole operation state of the cable meets the requirement. All indexes are within a specified attention value and a specified warning value, and the normal operation of the indexes is realized.
The attention state is that one or more indicators in the factor concentration indicator layer are intermediate values of attention values and outliers specified by the enterprise standard for the evaluation of the cable line state. When the cable state is in the attention state, the cable is indicated that one or more indexes of the cable are developed towards the direction approaching the standard limit value, and the cable can still operate because the standard limit value is not exceeded or part of indexes with less influence on the performance and the safe operation of the equipment exceed the standard limit value. Monitoring the operation should be enhanced.
An abnormal state is when one or more indicators in the indicator layer in the factor set exceeds the warning value, but does not reach the abnormal value. When the cable state is in an abnormal state, the cable state indicates that a certain index has larger change amplitude and is close to or slightly exceeds the standard, the operation process of the cable is monitored, and maintenance is arranged in a certain period.
The severity state is when one or more indicators in the indicators layer in the factor set exceed a specified outlier. When the cable state is in a serious state, the cable state indicates that a certain index is seriously out of standard or a plurality of indexes which have great influence on the performance and the safe operation of the equipment are close to or exceed the standard limit value, and the overhaul should be arranged in time.
2. And collecting index data corresponding to the factor set of the high-voltage cable to be evaluated, wherein all the index data are derived from original data, operation records, preventive tests, electrified detection and an online monitoring system. The sources of all index layer data are:
said cable body Z 1 In the voltage withstand test result Z of the cable body 11 Insulation resistance value Z of outer sheath 12 Derived from preventive tests, local discharge Z 13 From live detection, line load Z 14 From an on-line monitoring system, appearance Z 15 Maintenance record Z 17 From the record of operation, familial defect Z 16 Operational years Z 18 Derived from the original material.
The line terminal Z 2 In the metal junction temperature Z of the line terminal 21 Sleeve temperature Z 22 Partial discharge amount Z 23 Derived fromElectrified detection, appearance Z 24 Maintenance record Z 26 From the record of operation, familial defect Z 25 Operational years Z 27 Derived from the original material.
The middle joint Z 3 Results of pressure test of intermediate connector Z 31 Derived from preventive tests, local discharge Z 32 Intermediate joint temperature Z 33 From live detection, appearance Z 34 Maintenance record Z 36 From the record of operation, familial defect Z 35 Operational years Z 37 Derived from the original material.
The accessory device Z 4 Pressure test results Z of auxiliary facilities 41 From preventive tests, the ground current Z 42 Temperature Z at the junction of the devices 43 From live detection, appearance Z 44 From the operational record.
The line channel Z 5 In the main structure case Z of the line channel 51 Channel external environmental conditions Z 52 Channel identification Z 53 Frame internal facility Z 54 Fireproof and antitheft system condition Z 56 From the running record, the water leakage and ponding situation Z 55 Harmful gas and foreign matter Z 57 Derived from an on-line monitoring system.
3. Evaluation index normalization
Because various indexes generally have different dimensions and magnitude orders, if the indexes are directly used for calculation, the problem of mismatch of evaluation state grades is caused, and the operation state of the high-voltage cable cannot be reflected correctly. Therefore, normalization processing is required for each index. The invention divides the high-voltage cable running state evaluation index into a quantized index, a descriptive index and a qualitative evaluation index. The normalization of each index is analyzed below.
(1) Quantitative index:
the quantitative index is obtained by an on-line monitoring system or on-site measurement, has definite measurement data and a numerical scale, and can directly reflect the current running state of the equipment. And (3) carrying out normalization processing on the concept of the relative degradation degree of the quantized index reference, wherein the normalization result is [0,1], and the closer to 1, the better the cable operation state is. In the normalization processing of the concept of the relative degradation degree of the quantized index reference, the relative degradation degree L represents the deviation degree of each index of the high-voltage cable and the normal condition, and the numerical interval of L is [0,1]; when the value of L is 1, the index is characterized as an optimal state; when the value of L is 0, the index is characterized as the worst state.
a) For the larger and more optimal index, the actual measured data is normalized according to the following formula:
b) For smaller and more optimal indexes, the actual measured data is normalized according to the following formula:
c) For the moderate index, the actual measured data is normalized as follows:
in the formulas (4), (5) and (6), L represents the relative degradation degree of the index, X represents the original value of the index, and X max 、X min Respectively representing the upper limit and the lower limit of the index safe operation, X m Indicating the index optimum value.
(2) Description type index:
for indexes such as the appearance of each part of the cable, the state degree dividing standard can only be described by language, and the subjective judgment of an evaluator is greatly influenced. For the descriptive index, adopting an expert scoring method, wherein the expert scoring basis is Q/GDW 456-2010 cable line state evaluation guideline issued by the national grid Limited company; the scoring range is [0,1] to correspond to the relative degradation, and the score is closer to 1 as the index reflects the better the cable running state.
(3) The qualitative evaluation index: the index has clear dividing standard among the state grades, for example, the pressure test only passes and fails the two results, and the two states respectively correspond to normal and serious states. Namely, the qualitative evaluation type index is characterized in that the state of the cable component has two definite division standards, and the normalization result is 0 or 1,1 is in a normal state and 0 is in a serious state according to the two division standards;
4. the first level evaluation from the index layer to the project layer was achieved using the gray fuzzy theory, as shown in fig. 3.
4.1, determining a gray fuzzy weight matrix:
the gray fuzzy weight matrix consists of a model part and a gray part; the model part of the gray fuzzy weight matrix refers to the weight corresponding to the evaluation index, and the gray part of the gray fuzzy weight matrix is determined by an expert scoring method according to the reliability of the weight; the gray part of the gray fuzzy weight matrix refers to the point gray corresponding to the weight.
4.1.1 modulo part of the gray fuzzy weight matrix
The model part is obtained by combining an analytic hierarchy process and an entropy weight process.
Subjective weights are first determined by analytic hierarchy process.
1) Calculating hierarchical weights
The establishment of the index system determines the membership between the layers. For an element of a certain layer, a 1-9 scale method is adopted to represent the importance degree of the element compared with other elements by taking the related element of the upper layer as a reference. When the elements of the same layer are compared with each other every two, the obtained ratio number is put into a matrix, and the judgment matrix of the layer is obtained. Judgment matrix a= (a) ij ) n×m The values and the corresponding degrees of the values are shown in Table 1.
Table 1 scale method
The expression of the judgment matrix a is as follows:
in the formula (7), n is the order of the matrix A, a ij Represents the x < th i The third factor and the x j The ratio of the weights of the individual elements relative to a.
2) Consistency verification
For the maximum eigenvalue lambda corresponding to the judgment matrix A max The result obtained after the normalization processing is carried out on the feature vectors of the above layers, namely the weight ranking of the importance of a certain factor of the same layer to the corresponding factor of the previous layer, is called layer single ranking. When the system evaluation factors are more, the judgment matrix is often complex, the situation of contradiction between the front and back can possibly occur, and the consistency condition is difficult to completely meet, so that the judgment matrix needs to be checked according to a consistency check formula. The method comprises the following steps of
(1) Calculating the product M of each row of elements of the judgment matrix A i ：
(2) Calculate each row M i N times root W:
(3) pair vector w= (W 1 ,W 2 ,…,W n ) T Normalization processing is carried out to obtain a weight coefficient value w which is the index i ：
(4) And (3) performing consistency verification:
wherein CI is a consistency index, CR is a test coefficient, RI is an average random consistency index, n is the order of the judgment matrix, lambda max Is the maximum eigenvalue of the decision matrix a.
The RI values of the average random consistency index are shown in table 2.
Table 2 1-13 order average random uniformity index
When CR <0.1, the consistency check is considered to be qualified; when CR >0.1, the consistency check is not satisfied, and the mutual importance among the indexes needs to be reassigned until the consistency check of the judgment matrix is passed.
(2) And determining objective weights by using an entropy weight method.
1) Constructing an original evaluation matrix
If the m objects are evaluated by n indexes, the original evaluation matrix is
2) Normalization processing of judgment matrix
Due to the difference of the properties and the magnitude between the evaluation indexes, the matrix R is normalized by adopting a critical value method, so that a dimensionless index matrix R ' = (R ') ' ij ) m×n 。
3) Determining information entropy of each index
And calculating the specific gravity of the j index of the i object, namely the variation size of the index.
Entropy value b of jth index of sample j The method comprises the following steps:
entropy weight w 'of the j-th index' j The method comprises the following steps:
finally, the weight vector of the obtained index is obtained as follows:
W'＝(w' 1 ,w' 2 ,…,w' n ) T (17)
(3) Obtaining a combined weight according to the subjective weight and the objective weight by using the game theory;
the comprehensive weight calculation process based on game theory comprises the following steps:
1) Calculating n weights according to n different methods, and then establishing a basic weight vector set W= { W 1 ,w 2 ,…,w n One possible weight vector w is combined by n vectors in arbitrary linear combinations, expressed as follows:
wherein w is a weight vector, alpha k Is a weight coefficient.
2) The combined weight method based on game theory is to calculate the optimal balance weight vector w in a centralized way among possible weight vectors, which indicates that n weight calculation methods reach a compromise. This compromise can be considered as a linear combination of weight coefficients α k W and w are made using the following formula k The deviation between them is minimized:
according to the differentiation characteristics of the matrix, the conditions of the optimal first derivative in the above formula are as follows:
/>
the corresponding linear equation is:
3) Weight coefficient (alpha) is calculated by using the above method 1 ，α 2 ，…，α n ) The weight coefficients are then normalized using the following equation
4) Calculating final comprehensive weight
4.1.2 gray portions of the gray fuzzy weight matrix
The gray part of the gray fuzzy weight matrix is determined by adopting a method of solving an average value by an expert scoring method. The gray scale scoring criteria are shown in table 3.
TABLE 3 Standard reference Table for gray scale scoring
N evaluation indexes a1, a2, …, a are provided n Inviting m experts to comprehensively score the two experts, wherein the corresponding scores are b respectively 1 ,b 2 ,…,b m . In order to lighten subjective prejudices of experts, most of the expert opinions are fully considered, and a method of averaging after removing the highest score and the lowest score is adopted in specific implementation to obtain a final scoring value. The calculation formula is as follows:
thus, to the same layerThe n evaluation indexes a below 1 ,a 2 ,…,a n Constructing a weight matrix with a model part of [ w ] 1 ,w* 2 ,…,w* n ]The gray part is [ v ] 1 ,v 2 ,…,v n ]. The gray fuzzy weight matrix is represented as follows:
4.2 determining the Gray fuzzy discriminant matrix
The gray fuzzy discriminant matrix is also composed of a model part and a gray part. The model part represents the fuzzy membership of the evaluation index to each evaluation state in a fuzzy membership degree, and the gray part represents the credibility of the determination of the fuzzy membership degree of the evaluation index in a point gray point form.
For the quantitative and descriptive indexes, the invention adopts the cloud model theory to determine the membership degree (the qualitative index directly adopts the normalization result) state quantity for normalization post-treatment, and then classifies the grades according to the reference and expert experience, namely V 1 (c,d](d,∞]，V 2 (b 2 ,c 1 ]，V 3 (a 1 ,b 1 ]，V 4 (0,a]. And finally, three digital characteristic values of the cloud model are determined, and the determination method is shown in table 4.
Table 4 cloud model eigenvalue determination method
Reading index z i The corresponding value l of the processed original data 0 ，z i ＝l 0 Respectively cross with four clouds at M i Cloud drop, M i The membership mean value of each cloud drop is an index z i Membership μ with respect to State classes ij I.e.
Wherein x is 0 As index value relative deterioration degree E x For the expected value E ni Is based on E x Is the expected value, H e Is a normal random number of standard deviation.
For the qualitative index, the index has clear dividing standard among the state grades, so the index can only be completely under one state. If the pressure test is passed and failed, the two states of normal and serious are respectively corresponding to the two results, and the membership degrees are expressed by (1, 0) and (0.0.0.1).
The gray part calculation method of the gray fuzzy discriminant matrix is the same as that of the gray fuzzy weight matrix.
Therefore, n evaluation indexes a at the same level 1 ,a 2 ,…,a n Form gray fuzzy discriminant matrix and membership mu ij Represents the fuzzy membership between the evaluation index and the evaluation state, and the point gray scale v ij Corresponding membership mu ij The determined reliability is shown as follows:
4.3 comprehensive gray fuzzy evaluation
The high-voltage cable running state evaluation is analysis on the dynamic change of the running state of the equipment, and the actual state of each evaluation index cannot be accurately grasped in the evaluation process. In order to keep as much information as possible, the comprehensive evaluation module operation adopts M (·, +) operators, the gray part adopts M (+, +) operators, and the synthesized gray fuzzy comprehensive evaluation formula is as follows:
In the method, in the process of the invention,representing a weight matrix, +.>Representation and->Corresponding grey fuzzy discriminant matrix, w i And v i The weight and the corresponding point gray scale are used for evaluating the index; mu (mu) kj And v kj The membership value and the corresponding point gray level of the corresponding index are obtained.
Comprehensively considering the ambiguity and the graying of state evaluation, and according to the principles of maximum membership and minimum graying degreeAnd converting into a system result set. Suppose b ij Is->Is the j-th vector of (u) j Representing membership degree, v j Representing gray scale, the system result set is:
the system result set is the evaluation result of each item.
5. The D-S evidence theory is used to achieve a second level of evaluation from the project layer to the target layer, as shown in fig. 4.
(1) Determination of identification framework Θ
The invention divides the operation state of the high-voltage cable into 4 grades of normal, attention, abnormal and serious, and identifies the frame theta from the four grades v of the normal, attention, abnormal and serious operation state of the high-voltage cable 1 、v 2 、v 3 、v 4 And uncertainty θ specified by D-S evidence theory, namely:
Θ＝{v 1 ,v 2 ,v 3 ,v 4 ,θ} (30)
(2) Determining basic assignment functions for independent evidence
According to the established high-voltage cable operation state evaluation index system, in the invention, cables of a project layer are subjected to Body Z 1 Line termination Z 2 Intermediate joint Z 3 Accessory facility Z 4 And line channel Z 5 Five items are used as independent evidences, and the evaluation result of each item obtained by adopting the gray fuzzy theory is used as the basic assignment function of each independent evidence, and m is used i (A) The expression is satisfied:
considering the factors such as different importance degrees of each item layer as evidence, different precision in the data acquisition process of parameters, and the like, the credibility of each item layer evidence is also different, so that the basic assignment function of each item layer needs to be corrected before evidence synthesis. The confidence parameter alpha is introduced here k To indicate the relative importance between the different items. Alpha k The following equation is used to obtain:
where λ is a finite confidence coefficient, and a lot of practices have found that λ=0.9 is most effective, where λ=0.9; omega i Is the weight of the ith item in the weight vector of five independent evidences, omega max Is the maximum value in the weight vector;
the basic assignment function after the reliability correction is defined as:
(3) Evidence fusion
The evidence fusion is performed according to the following formula,
wherein m (A) is a basic assignment function corresponding to each state level after evidence fusion; a is that i To identify the frameA subset of the frames Θ;
(4) Evaluation decision
In the D-S evidence theory, two evaluation decision methods of a maximum membership rule and a confidence rule are generally selected. In practical application, the maximum membership rule requires a certain gap between membership degrees of all state levels, and when the gap is smaller than a preset value, an accurate result cannot be given; the confidence criterion may incorrectly determine the result as a previous result when the processing state level approaches the confidence level. Therefore, the invention organically fuses the two, and adopts a combined evaluation decision method. The specific method is as follows.
Judging the basic assignment function result of each state level by adopting the maximum membership rule, wherein the condition formula is that
Wherein m (v) 0 ) Representing the maximum value of the rating base assignment function, namely:
representing the next largest value of the rating base assignment function, i.eIf the difference exceeds a predetermined value epsilon 1 ，ε 1 ＝0.15；
If the formula (36) is satisfied, the evaluation result of the final operation state of the high-voltage cable is v 0 A corresponding grade;
if the formula (36) is not satisfied, if the maximum membership rule cannot be used, it is indicated that the evaluation level basic assignment function value has a smaller difference, and at this time, the reliability rule is adopted to judge the basic assignment function result of each state level, and the formula is that
In the formula (37), ε 2 For confidence level, ε 2 =0.5; if the formula (37) is satisfied, the evaluation result of the final operation state of the high-voltage cable is v 0 A corresponding grade;
if the expression (37) is not satisfied, the method returns to the step 4 to adjust the cloud model, subjective weight and gray part of the gray fuzzy weight matrix and gray part of the gray fuzzy judgment matrix until the expression (36) or the expression (37) is satisfied.
Study calculation example:
taking a 110kV line as an example, the state quantity and the normalization result are shown in table 5:
TABLE 5
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The subjective weight of the cable body is W1= [0.1455 0.0442 0.2724 0.3585 0.0573 0.0753 0.0202 0.0266],
objective weight is w2= [0.0600 0.1161 0.1369 0.1056 0.0600 0.0600 0.3229]
The combination weight is W= [0.1116 0.0726 0.2193 0.2707 0.0764 0.0693 0.03359 0.1442]
The gray fuzzy weight of the cable body is as follows:
the membership was calculated using a cloud model, and the results are shown in table 6.
TABLE 6
And according to the adequacy degree of the cable body information, adopting an expert scoring method to calculate the mean value to determine the corresponding credibility of the membership degree of each state grade corresponding to each evaluation index, and obtaining the gray fuzzy judgment matrix.
Finally, the color-to-color fuzzy evaluation result of the cable body is obtained
The gray fuzzy evaluation results of other 4 items such as line terminals, intermediate connectors, auxiliary facilities, line channels and the like are respectively obtained by the same method
After gray fuzzy evaluation results of the cable body, the line terminal, the intermediate connector, the auxiliary facilities and the line channel are obtained, a system result set is obtained through calculation:
and finally judging the states of the cable body, the auxiliary facilities and the line channels to be evaluated as normal, and the states of the line terminals and the intermediate connectors to be evaluated as attention.
And then, the evaluation of the overall state of the high-voltage cable, namely, the evaluation from the project layer to the target layer is completed by utilizing the D-S evidence theory, gray fuzzy evaluation results of all the project layers are fused as evidence, and finally, the evaluation result of the running state of the high-voltage cable is obtained.
The gray fuzzy evaluation results of the five items of the item layer calculated previously are used as the initial basic assignment function of the comprehensive evaluation, as shown in table 7.
TABLE 7
The weight of each item layer is calculated by using a combined weight method:
W＝[0.23，0.281，0.298，0.099，0.092]
calculating the credibility parameter alpha by a formula k The uncertainty m (theta) = [0.305,0.151,0.1,0.701,0.722 ] is calculated by the formula = [0.695,0.849,0.9,0.299,0.278 ]]The corrected basic probability distribution results are shown in table 8.
TABLE 8
And carrying out fusion operation on the basic probability distribution result according to a formula, and obtaining a result shown in a table 9.
TABLE 9
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Judging the evaluation result by adopting the judging method, firstly verifying the uncertainty, and indicating that the uncertainty of the evaluation meets the requirement, wherein m (theta) = 0.0460.05; then the maximum membership criterion is verified, and the maximum membership criterion is obtained by a formula0.189 > 0.15, meets the maximum membership criterion requirement, and thereby judges that the high-voltage cable is in an 'attention' state.
Although the invention has been described above with reference to the accompanying drawings, the invention is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and many modifications may be made by those of ordinary skill in the art without departing from the spirit of the invention, which fall within the protection of the invention.
Claims (6)
1. The method for evaluating the running state of the high-voltage cable is characterized by comprising the following steps of:
step 1, establishing a high-voltage cable running state evaluation index system, which comprises the following steps: determining a factor set of a three-layer structure with a target layer, a project layer and an index layer from operation parameters of the high-voltage cable according to enterprise standards; and establishing a state set;
step 2, collecting index data corresponding to the high-voltage cable to be evaluated and the factor set, wherein all the index data are derived from original materials, operation records, preventive tests, electrified detection and online monitoring systems;
Step 3, normalizing the index data collected in the step 2, including:
dividing the high-voltage cable running state evaluation index into a quantized index, a descriptive index and a qualitative evaluation index;
the quantitative index is obtained by an online monitoring system or field measurement, the quantitative index is normalized by referring to the concept of relative degradation degree, the normalization result is [0,1], and the closer to 1, the better the cable running state;
the described index is an index which can be described by language only by state degree dividing standard, and the described index is normalized by adopting expert scoring method, wherein the scoring range is [0,1], and the closer the score is 1, the better the cable running state is represented; the expert scoring basis is Q/GDW 456-2010 cable line state evaluation guideline issued by national grid Limited;
the qualitative evaluation type index is characterized in that the state of the cable component has two definite division standards, the normalization result is 0 or 1,1 is in a normal state, and 0 is in a serious state according to the two division standards;
step 4, realizing first-level evaluation from an index layer to a project layer by utilizing a gray fuzzy theory, so as to obtain an evaluation result of each project;
And 5, realizing secondary evaluation from the project layer to the target layer by using a D-S evidence theory, and finally obtaining the running state of the high-voltage cable.
2. The method for evaluating an operating state of a high-voltage cable according to claim 1, wherein in step 1,
the target layer is in a high-voltage cable running state and consists of five project layers, wherein the five project layers comprise a cable body Z 1 Line termination Z 2 Intermediate joint Z 3 Accessory device Z 4 And line channel Z 5 ；
Each project layer comprises a plurality of index layers, wherein the cable body Z 1 Pressure test results Z of the cable body including index layer 11 Insulation resistor Z of outer sheath 12 Partial discharge amount Z 13 Line load Z 14 Appearance Z 15 Familial defect Z 16 Maintenance record Z 17 Operational years Z 18 The method comprises the steps of carrying out a first treatment on the surface of the The line terminal Z 2 Metal junction temperature Z including line termination 21 Sleeve temperature Z 22 Partial discharge Z 23 Appearance Z 24 Familial defect Z 25 Maintenance record Z 26 And operating years Z 27 The method comprises the steps of carrying out a first treatment on the surface of the The middle joint Z 3 Results of pressure test Z including an intermediate connector 31 Partial discharge amount Z 32 Intermediate joint temperature Z 33 Appearance Z 34 Familial defect Z 35 Maintenance record Z 36 And operating years Z 37 The method comprises the steps of carrying out a first treatment on the surface of the The accessory device Z 4 Pressure test results Z including ancillary facilities 41 Ground current Z 42 Temperature Z at the junction of the devices 43 And appearance Z 44 The method comprises the steps of carrying out a first treatment on the surface of the The line channel Z 5 Including a line channelChannel body structure case Z of (2) 51 Channel external environmental conditions Z 52 Channel marker Z 53 Frame internal facility Z 54 Leakage and ponding conditions Z 55 Fireproof and antitheft system condition Z 56 And harmful gases and foreign substances Z 57 ；
The method comprises the steps of combining enterprise standards for evaluating the states of the cable lines and selecting state quantities of actual working states of high-voltage cables running by the high-voltage cables, wherein the selected state quantities are as follows:
taking the selected state quantity as a judging factor:
U＝{U 1 ,U 2 ,…,U m } (1)
in the formula (1), U i (i=1, 2, …, 5) represents five project layer cable bodies Z characterizing the cable running state 1 Line termination Z 2 Intermediate joint Z 3 Accessory device Z 4 And line channel Z 5 ；
U i ＝{u i1 ,u i2 ,…,u in } (2)
In the formula (2), u ij (j=1, 2, …, n) represents a j-th index in an i-th item layer representing the cable operation state;
establishing a state set:
V＝{v 1 ,v 2 ,v 3 ,v 4 } (3)
dividing the operation state of the high-voltage cable into four state grades including a normal state, an attention state, an abnormal state and a serious state, respectively using v in turn 1 ,v 2 ,v 3 ,v 4 A representation;
the normal state is: the indexes of the index layer in the factor set are all within the attention value specified by the enterprise standard for evaluating the cable line state;
The attention state is that one or more indexes in the factor concentration index layer are intermediate values of attention values and abnormal values specified by enterprise standards of cable line state evaluation;
the abnormal state is that one or more indexes in the index layer in the factor set exceed the warning value, but do not reach the abnormal value;
the severity state is when one or more indicators in the indicators layer in the factor set exceed a specified outlier.
3. The method for evaluating the operation state of a high-voltage cable according to claim 2, wherein the enterprise standard comprises: Q/GDW 456-2010 cable line state evaluation guidelines issued by national grid company, and Q/GDW11316-2014 Power Cable line test Specification.
4. The method for evaluating the operation state of a high-voltage cable according to claim 2, wherein in step 2, the sources of all index layer data are:
said cable body Z 1 In the voltage withstand test result Z of the cable body 11 Insulation resistance value Z of outer sheath 12 Derived from preventive tests, local discharge Z 13 From live detection, line load Z 14 From an on-line monitoring system, appearance Z 15 Maintenance record Z 17 From the record of operation, familial defect Z 16 Operational years Z 18 Derived from the original material;
the line terminal Z 2 In the metal junction temperature Z of the line terminal 21 Sleeve temperature Z 22 Partial discharge amount Z 23 From live detection, appearance Z 24 Maintenance record Z 26 From the record of operation, familial defect Z 25 Operational years Z 27 Derived from the original material;
the middle joint Z 3 Results of pressure test of intermediate connector Z 31 Derived from preventive tests, local discharge Z 32 Intermediate joint temperature Z 33 From live detection, appearance Z 34 Maintenance record Z 36 From the record of operation, familial defect Z 35 Operational years Z 37 Derived from the original material;
the accessory device Z 4 Pressure test results Z of auxiliary facilities 41 From preventive tests, the ground current Z 42 Temperature Z at the junction of the devices 43 From live detection, appearance Z 44 Derived from the operational record;
the line channel Z 5 In the main structure case Z of the line channel 51 Channel external environmental conditions Z 52 Channel identification Z 53 Frame internal facility Z 54 Fireproof and antitheft system condition Z 56 From the running record, the water leakage and ponding situation Z 55 Harmful gas and foreign matter Z 57 Derived from an on-line monitoring system.
5. The method for evaluating the operation state of the high-voltage cable according to claim 1, wherein the step 4 is implemented by using a gray fuzzy theory from an index layer to a project layer, so as to obtain the evaluation result of each project, and the content comprises:
Step 4-1) determining a gray fuzzy weight matrix: the gray fuzzy weight matrix consists of a model part and a gray part;
the model part of the gray fuzzy weight matrix refers to the weight corresponding to the evaluation index, determining the model part of the gray fuzzy weight matrix comprises determining subjective weight through a hierarchical analysis method, determining objective weight through an entropy weight method, and obtaining combined weight according to the subjective weight and the objective weight through a game theory; the gray part of the gray fuzzy weight matrix is determined by an expert scoring method according to the reliability of the weight; the gray part of the gray fuzzy weight matrix refers to the point gray corresponding to the weight;
step 4-2) determining a gray fuzzy discriminant matrix: the gray fuzzy judgment matrix consists of a mould part and a gray part; the model part of the gray fuzzy judgment matrix represents fuzzy membership of the evaluation indexes to each evaluation state by fuzzy membership, and the membership is determined by adopting a cloud model theory; the gray part of the gray fuzzy judgment matrix represents the credibility of determining the fuzzy membership degree of the evaluation index in the form of point gray points;
and 4-3) synthesizing gray fuzzy comprehensive judgment, and converting the gray fuzzy comprehensive judgment matrix into a system result set according to the maximum membership degree and the minimum gray degree principle, wherein the system result set is the evaluation result of each item.
6. The method for evaluating the operation state of the high-voltage cable according to claim 5, wherein the step 5 of using the D-S evidence theory to realize the second-level evaluation from the project layer to the target layer, and finally obtaining the operation state of the high-voltage cable comprises the following steps:
step 5-1) determination of identification framework Θ: identifying the four state classes v of the frame Θ from the normal, attentive, abnormal and severe states of the operating state of the high-voltage cable 1 、v 2 、v 3 、v 4 And uncertainty θ specified by D-S evidence theory, namely:
Θ＝{v 1 ,v 2 ,v 3 ,v 4 ,θ}
step 5-2) determining a basic assignment function for each independent proof: according to the established high-voltage cable running state evaluation index system, the cable body Z of the project layer is evaluated 1 Line termination Z 2 Intermediate joint Z 3 Accessory facility Z 4 And line channel Z 5 Five items are used as independent evidences, the evaluation result of each item obtained in the step 4 is used as a basic assignment function of each independent evidence, and m is used i (A) The expression is satisfied:
introducing a confidence parameter α to said basic assignment function m i (A) Performing correction to represent the relative importance of different items; alpha is derived from the formula:
where λ is a finite confidence coefficient, λ=0.9; omega i Weights for five independent evidence Weight, ω, of the ith term in the vector max Is the maximum value in the weight vector;
the basic assignment function after the reliability correction is defined as:
step 5-3) evidence fusion: the evidence fusion is performed according to the following formula,
wherein m (A) is a basic assignment function corresponding to each state level after evidence fusion; a is that i To identify a subset of the frames Θ;
step 5-4) evaluation decision: judging the basic assignment function result of each state level by adopting the maximum membership rule, wherein the condition formula is that
Wherein m (v) 0 ) Representing the maximum value of the rating base assignment function, namely:
representing the next largest value of the rating base assignment function, i.eIf the difference exceeds a predetermined value epsilon 1 ，ε 1 ＝0.15；
If the formula (36) is satisfied, the evaluation result of the final operation state of the high-voltage cable is v 0 A corresponding grade;
if the formula (36) is not satisfied, adopting a credibility criterion to judge the basic assignment function result of each state level, wherein the formula is
In the formula (37), ε 2 For confidence level, ε 2 =0.5; if the formula (37) is satisfied, the evaluation result of the final operation state of the high-voltage cable is v 0 A corresponding grade;
if the expression (37) is not satisfied, the method returns to the step 4 to adjust the cloud model, subjective weight and gray part of the gray fuzzy weight matrix and gray part of the gray fuzzy judgment matrix until the expression (36) or the expression (37) is satisfied.
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