CN102759670A - Method for evaluating operation state of dry type transformer - Google Patents

Method for evaluating operation state of dry type transformer Download PDF

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CN102759670A
CN102759670A CN2011104598218A CN201110459821A CN102759670A CN 102759670 A CN102759670 A CN 102759670A CN 2011104598218 A CN2011104598218 A CN 2011104598218A CN 201110459821 A CN201110459821 A CN 201110459821A CN 102759670 A CN102759670 A CN 102759670A
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type transformer
parameter
dry
index
running status
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熊兰
赵艳龙
杨子康
宋道军
徐敏捷
周健瑶
何为
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Chongqing University
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Abstract

The invention relates to the technical field for evaluating the operation state of a transformer, in particular to a method for evaluating the operation state of a dry type transformer. Influences of parameters to the operation state of the dry type transformer are integrated, reliable level analysis is carried out on the operation state of the dry type transformer, and the convenience is brought for operators to hold the operation condition of the dry type transformer in real time and immediately make condition based maintenance. The method comprises the following steps of: 1) detecting parameter data of the operation state and an operation environment of the dry type transformer, and obtaining inherent characteristics of the dry type transformer and parameter data of the operation history; 2) normalizing parameter data of the operation states, the operation environment, the inherent characteristics and the operation history of the dry type transformer; 3) obtaining each parameter membership corresponding to a comment through a membership function of each parameter and the comment, and obtaining a single factor judge matrix; 4) obtaining a comprehensive judge matrix by combining weights of the parameters; and 5) obtaining a comprehensive evaluation value the operation state of the dry type transformer. The operation state of the dry type transformer can be reflected through the evaluation value.

Description

The dry-type transformer running status detects appraisal procedure
Technical field
The present invention relates to the transformer running status and detect the assessment technology field, be specifically related to a kind of dry-type transformer running status comprehensive estimation method.
Background technology
In recent years, along with the continuous increase of network load, dry-type transformer is owing to its outstanding advantage is widely used.But dry-type transformer is in operation and happens occasionally owing to insulation breakdown causes accident on fire from explosion, and not only the personal safety to the field operator threatens, and also influences safety, the even running of electrical network simultaneously.
At present, the judgement to the dry-type transformer operation conditions mainly realizes through monitoring parameters such as its temperature, humidity, voltage, electric current and power.Wherein, winding temperature can reflect dry-type transformer built-in electrical insulation situation to a certain extent, when temperature value or temperature rise value surpass threshold value, carries out operations such as interruption maintenance.But these methods all are the state analysis method based on a certain parameter, can not scientifically assess out the operation conditions and the state development trend of dry-type transformer.
The dry-type transformer running status receives influence of various factors, and its running status also is in the dynamic development and change, and this just need set up dry-type transformer running status comprehensive assessment model.Through real-time analysis to data, the operation conditions of comprehensive assessment dry-type transformer and possible development of defects trend, thereby the time and the localization of faults that come the suggestion dry-type transformer to overhaul.
Summary of the invention
Given this; In order to address the above problem; The invention discloses and a kind ofly judge that through the comprehensive assessment model dry-type transformer running status of dry-type transformer running status detects appraisal procedure, comprehensively each parameter is made reliable grade analysis to the influence of dry-type transformer operation conditions to the dry-type transformer running status; So that the operations staff can grasp dry-type transformer ruuning situation in real time, in time make repair based on condition of component.
The objective of the invention is to realize like this: the dry-type transformer running status detects appraisal procedure, comprises the steps:
1) detects the operating condition of dry-type transformer and the parametric data of running environment, and obtain the inherent characteristic of dry-type transformer and the parametric data of history run;
2) parametric data of operating condition, running environment, inherent characteristic and the history run of dry-type transformer being carried out normalization handles;
3) through the membership function of each parameter and comment, obtain the degree of membership of the corresponding comment of each parameter, and obtain single factor judge matrix R:
The running status comment collection of dry-type transformer comprises well, general, attention, serious 4 grades, representes with V1, V2, V3, V4 respectively; r IjRepresent that i parameter belongs to grade V jDegree; I=1,2,3 ..., m; J=1,2,3,4; M is an index parameter number;
4) combine the weights of each parameter, obtain comprehensive evaluation matrix B;
Figure BDA0000128373110000022
W is the index weight sets; w i(i=1,2 ..., m) be the variable weight of each evaluation factor; b j(j=1,2,3,4) are the fuzzy overall evaluation index;
5) obtain dry-type transformer running status comprehensive assessment value V;
Figure BDA0000128373110000023
h jFor four kinds of pairing score values of state of V1～V4, be respectively 1～4; b jBe the evaluation index that obtains through fuzzy comprehensive evoluation.
In the said step 1), inherent characteristic X1 comprises class of insulation X11, dielectric level X12, cooling structure X13, these four index parameters of types of housings X14; Operating condition X2 comprises load level X21, medial temperature X22, temperature rise horizontal X 23, these four index parameters of noise level X24; Running environment X3 comprises environment temperature X31, ambient humidity X32, THD value X33, these four index parameters of voltage deviation X34; History run X4 comprises X41 tenure of use, maintenance record X42, alarm logging X43, these four index parameters of protection action X44.
Further, said step 2) in, the qualitative index parameter adopts expert's methods of marking to obtain, and the scoring interval is [0,1], and score value is big more, and the index performance is excellent more; Quantitatively property index parameter carries out the following method of normalization processing employing;
Figure BDA0000128373110000031
x iIt is the normalized value of i parameter; C 0Permissible value for this parameter; C MaxUltimate value for this index; C iMeasured value for this index; K is that parameter quantitative index parameter comprises load level X21, medial temperature X22, temperature rise horizontal X 23, noise level X24, environment temperature X31, ambient humidity X32, THD value X33, voltage deviation X34, tenure of use X41, and the qualitative index parameter comprises class of insulation X11, dielectric level X12, cooling structure X13, types of housings X14, maintenance record X42, alarm logging X43, protection action X44; All the other are the qualitative index parameter.
Further, in the step 4), the weights of each parameter obtain through following method:
41) according to the relative importance between each factor, confirm precedence relationship matrix F 1, matrix F 1 adopts 0.1～0.9 scaling law structure;
42) convert precedence relationship matrix F 1 into Fuzzy consistent matrix F2:
At first with precedence relationship matrix F 1=(f Ij) N * nBy the row summation, be designated as
Figure BDA0000128373110000032
Carry out following mathematic(al) manipulation: r then Ij=(r i-r j)/2 (n-1)+0.5, then the matrix after the conversion is Fuzzy consistent matrix F2;
43) confirm the normal weight w of each parameter according to the factor relation method i
The expression formula of factor relation method is:
Figure BDA0000128373110000041
β representes the poor of weight, and β is more little, and the difference of weight is big more;
44), obtain the change weights of each parameter factor by following formula according to each parameter normalized value:
Figure BDA0000128373110000042
x iBe i the value of passing judgment on parameter, m is for passing judgment on parameter number, w iBe the variable weight of i kind parameter, w i 0Be the Chang Quanchong of i kind parameter, α is a balance factor.
Further, in the step 4), the normal weights of each parameter are following:
X1, X2, X3, the normal weights of X4 are respectively 0.1833,0.3167,0.2278,0.2722;
X11, X12, X13, the normal weights of X14 are respectively 0.1945,0.1833,0.3278,0.2944;
X21, X22, X23, the normal weights of X24 are respectively 0.2167,0.3166,0.3389,0.1278;
X31, X32, X33, the normal weights of X34 are respectively 0.15,0.1944,0.35,0.3056;
X41, X42, X43, the normal weights of X44 are respectively 0.2389,0.3167,0.2611,0.183
Further, in the step 3), the quantitative target parameter adopts half distribution function trapezoidal and that half mountain range shape combines to confirm its degree of membership; The qualitative index parameter adopts the half trapezoidal distribution function that combines with triangle to confirm its degree of membership.
Further; In the step 5); Assessed value V and dry-type transformer running status mapping table are following: 0＜V≤1 expression dry-type transformer running status is good; 1＜V≤2 expression dry-type transformer running statuses are general, and 2＜V≤3 expression dry-type transformer running statuses are for noticing that 3＜V≤4 expression dry-type transformer running statuses are serious.
Beneficial effect of the present invention is following: dry-type transformer running status comprehensive estimation method disclosed by the invention; Through of the influence of each parameter such as comprehensive inherent characteristic, operating condition, running environment, maintenance history to the dry-type transformer operation conditions; Utilize Fuzzy AHP to confirm the weight of each index parameter; Theoretical according to the change of balance function power then, according to passing judgment on the level that parameter departs from normal value, the fixedly Chang Quan of each index parameter is revised; Can analyze the operation conditions of dry-type transformer effectively; The dry-type transformer running status is carried out objective quantitative evaluation,, in time make repair based on condition of component so that the operations staff can grasp dry-type transformer ruuning situation in real time.The present invention has stronger operability, and can be dry-type transformer state evaluation and definite repair time provides effective theoretical foundation, and is significant to safety, the stable operation of electrical network.
Description of drawings
In order to make the object of the invention, technical scheme and advantage clearer, will combine accompanying drawing that the present invention is made further detailed description below:
Fig. 1 is a schematic flow sheet of the present invention;
Fig. 2 is the dry-type transformer running status judging quota system that the present invention sets up;
Fig. 3 is a membership function distribution plan partly trapezoidal and that half mountain range shape combines;
Fig. 4 is the half trapezoidal membership function distribution plan that combines with triangle.
Embodiment
Below will carry out detailed description to the preferred embodiment of invention.
Referring to Fig. 1, the dry-type transformer running status detects appraisal procedure, comprises the steps:
1) detects the operating condition of dry-type transformer and the parametric data of running environment, and obtain the inherent characteristic of dry-type transformer and the parametric data of history run; Set up three layers of dry-type transformer running status judging quota system; Referring to Fig. 2; Three layers of dry-type transformer running status judging quota system comprise destination layer, item layer, indicator layer; Destination layer is the dry-type transformer running status, and item layer comprises inherent characteristic X1, operating condition X2, running environment X3, history run X4;
In the indicator layer, inherent characteristic X1 comprises class of insulation X11, dielectric level X12, cooling structure X13, these four index parameters of types of housings X14; Operating condition X2 comprises load level X21, medial temperature X22, temperature rise horizontal X 23, these four index parameters of noise level X24; Running environment X3 comprises environment temperature X31, ambient humidity X32, THD value X33, these four index parameters of voltage deviation X34; History run X4 comprises X41 tenure of use, maintenance record X42, alarm logging X43, these four index parameters of protection action X44.
Inherent characteristic X1 comprises class of insulation X11, dielectric level X12, cooling structure X13, these four index parameters of types of housings X14; Operating condition X2 comprises load level X21, medial temperature X22, temperature rise horizontal X 23, these four index parameters of noise level X24; Running environment X3 comprises environment temperature X31, ambient humidity X32, THD value X33, these four index parameters of voltage deviation X34; History run X4 comprises X41 tenure of use, maintenance record X42, alarm logging X43, these four index parameters of protection action X44.The quantitative target parameter comprises load level X21, medial temperature X22, temperature rise horizontal X 23, noise level X24, environment temperature X31, ambient humidity X32, THD value X33, voltage deviation X34, tenure of use X41, and the qualitative index parameter comprises class of insulation X11, dielectric level X12, cooling structure X13, types of housings X14, maintenance record X42, alarm logging X43, protection action X44; All the other are the qualitative index parameter.
2) parametric data of operating condition, running environment, inherent characteristic and the history run of dry-type transformer being carried out normalization handles; The qualitative index parameter adopts expert's methods of marking to obtain, and the scoring interval is [0,1], and score value is big more, and the index performance is excellent more; Quantitatively property index parameter carries out the following method of normalization processing employing;
x iIt is the normalized value of i parameter; C 0Permissible value for this parameter; C MaxUltimate value for this index; C iMeasured value for this index; K is that parameter changes the influence degree to equipment state;
3) through the membership function of each parameter and comment, obtain the degree of membership of the corresponding comment of each parameter, and obtain single factor judge matrix R:
Figure BDA0000128373110000071
The running status comment collection of dry-type transformer comprises well, general, attention, serious 4 grades, representes with V1, V2, V3, V4 respectively; r IjRepresent that i parameter belongs to grade V jDegree; I=1,2,3 ..., m; J=1,2,3,4; M is an index parameter number;
4) combine the weights of each parameter, obtain comprehensive evaluation matrix B;
Figure BDA0000128373110000072
W is the index weight sets; w i(i=1,2 ..., m) be the variable weight of each evaluation factor; b j(j=1,2,3,4) are the fuzzy overall evaluation index;
In the step 4), the weights of each parameter obtain through following method:
41) according to the relative importance between each factor, confirm precedence relationship matrix F 1, matrix F 1 adopts 0.1～0.9 scaling law structure;
The definition of table 10.1～0.9 scale
Figure BDA0000128373110000081
For example the precedence relationship matrix F 1 of item layer is expressed as:
42) convert precedence relationship matrix F 1 into Fuzzy consistent matrix F2:
At first with precedence relationship matrix F 1=(f Ij) N * nBy the row summation, be designated as
Figure BDA0000128373110000083
Carry out following mathematic(al) manipulation: r then Ij=(r i-r j)/2 (n-1)+0.5, then the matrix after the conversion is Fuzzy consistent matrix F2; For example the precedence relationship matrixing of item layer is that Fuzzy consistent matrix is:
43) confirm the normal weight w of each parameter according to the factor relation method i
The expression formula of factor relation method is:
β representes the poor of weight, and β is more little, and the difference of weight is big more; When β=(n-1)/2, the difference of weight reaches maximal value.In order to pay attention to significance level difference between element, get β=(n-1)/2 in this method.
The normal weights of each parameter are following:
Figure BDA0000128373110000091
44), obtain the change weights of each parameter factor by following formula according to each parameter normalized value:
Figure BDA0000128373110000092
x iBe i the value of passing judgment on parameter, m is for passing judgment on parameter number, w iBe the variable weight of i kind parameter, w i 0Be the Chang Quanchong of i kind parameter, α is a balance factor;
45) obtain the membership function of each quantitative target parameter and qualitative index parameter.Referring to Fig. 3, the quantitative target parameter adopts half distribution function trapezoidal and that half mountain range shape combines to confirm its degree of membership; For example the membership function table of load level X21 and running temperature X22 is as shown in table 3;
The membership function table of table 3 load level X21 and running temperature X22
Figure BDA0000128373110000093
Figure BDA0000128373110000101
Referring to Fig. 4, the qualitative index parameter adopts the half trapezoidal distribution function that combines with triangle to confirm its degree of membership.For example the membership function table of alarm logging X43 and protection action X44 such as table 4 are not;
The membership function table of table 4 alarm logging X43 and protection action X44
Figure BDA0000128373110000102
5) obtain dry-type transformer running status comprehensive assessment value V through following formula, assessed value V promptly representes the dry-type transformer running status:
Figure BDA0000128373110000103
h jFor four kinds of pairing score values of state of V1～V4, be respectively 1～4; b jBe the evaluation index that obtains through fuzzy comprehensive evoluation.Assessed value and dry-type transformer running status mapping table are following:
Assessed value V The dry-type transformer running status
0＜V≤1 Grade good (V1)
1＜V≤2 Grade general (V2)
2＜V≤3 Note (V3)
3＜V≤4 Seriously (V4)
Grade good (V1) expression dry-type transformer overall performance is good, and running status is stable; Grade general (V2) expression dry-type transformer overall performance descends to some extent, and operation conditions can satisfy the demands basically, and the possibility that breaks down is smaller, needs multi-track to observe during operation; It is bigger that grade notices that (V3) expression dry-type transformer overall performance descends, and existence possibly damage the risk of transformer, and operation can be carried out, but the possibility that breaks down is bigger, should overhaul under the situation of having ready conditions; Grade seriously (V4) expression dry-type transformer overall performance descends seriously, and some position possibly damaged, and it is seriously undesired to move, and needs interruption maintenance or replacing transformer immediately.
The above is merely the present invention that preferably is not limited to of the present invention, and obviously, those skilled in the art can carry out various changes and modification and not break away from the spirit and scope of the present invention the present invention.Like this, belong within the scope of claim of the present invention and equivalent technologies thereof if of the present invention these are revised with modification, then the present invention also is intended to comprise these changes and modification interior.

Claims (8)

1. the dry-type transformer running status detects appraisal procedure, it is characterized in that: comprise the steps:
1) detects the operating condition of dry-type transformer and the parametric data of running environment, and obtain the inherent characteristic of dry-type transformer and the parametric data of history run;
2) parametric data of operating condition, running environment, inherent characteristic and the history run of dry-type transformer being carried out normalization handles;
3) through the membership function of each parameter and comment, obtain the degree of membership of the corresponding comment of each parameter, and obtain single factor judge matrix R:
R = ( r ij ) m × 4 r 11 r 12 r 13 r 14 r 21 r 22 r 23 r 24 . . . . r m 1 r m 2 r m 3 r m 4
The running status comment collection of dry-type transformer comprises well, general, attention, serious 4 grades, representes with V1, V2, V3, V4 respectively; r IjRepresent that i parameter belongs to grade V jDegree; I=1,2,3 ..., m; J=1,2,3,4; M is an index parameter number;
4) combine the weights of each parameter, obtain comprehensive evaluation matrix B;
B = W · R = ( w 1 , w 2 , . , w m ) · r 11 r 12 r 13 r 14 r 21 r 22 r 23 r 24 . . . . r m 1 r m 2 r m 3 r m 4 = ( b 1 , b 2 , b 3 , b 4 )
W is the index weight sets; w i(i=1,2 ..., m) be the variable weight of each evaluation factor; b j(j=1,2,3,4) are the fuzzy overall evaluation index;
5) obtain dry-type transformer running status comprehensive assessment value V;
V = Σ j = 1 4 b j h j / Σ j = 1 4 b j
h jFor four kinds of pairing score values of state of V1～V4, be respectively 1～4; b jBe the evaluation index that obtains through fuzzy comprehensive evoluation.
2. dry-type transformer running status as claimed in claim 1 detects appraisal procedure, and it is characterized in that: in the said step 1), inherent characteristic X1 comprises class of insulation X11, dielectric level X12, cooling structure X13, these four index parameters of types of housings X14; Operating condition X2 comprises load level X21, medial temperature X22, temperature rise horizontal X 23, these four index parameters of noise level X24; Running environment X3 comprises environment temperature X31, ambient humidity X32, THD value X33, these four index parameters of voltage deviation X34; History run X4 comprises X41 tenure of use, maintenance record X42, alarm logging X43, these four index parameters of protection action X44.
3. dry-type transformer running status as claimed in claim 2 detects appraisal procedure, it is characterized in that: said step 2), the qualitative index parameter adopts expert's methods of marking to obtain, and the scoring interval is [0,1], and score value is big more, and the index performance is excellent more; Quantitatively property index parameter carries out the following method of normalization processing employing;
x i = ( C i - C 0 C max - C 0 ) k
x iIt is the normalized value of i parameter; C 0Permissible value for this parameter; C MaxUltimate value for this index; C iMeasured value for this index; K is that parameter changes the influence degree to equipment state; The quantitative target parameter comprises load level X21, medial temperature X22, temperature rise horizontal X 23, noise level X24, environment temperature X31, ambient humidity X32, THD value X33, voltage deviation X34, tenure of use X41, and the qualitative index parameter comprises class of insulation X11, dielectric level X12, cooling structure X13, types of housings X14, maintenance record X42, alarm logging X43, protection action X44; All the other are the qualitative index parameter.
4. the dry-type transformer running status described in claim 3 detects appraisal procedure, and it is characterized in that: in the step 4), the weights of each parameter obtain through following method:
41) according to the relative importance between each factor, confirm precedence relationship matrix F 1, matrix F 1 adopts 0.1～0.9 scaling law structure;
42) convert precedence relationship matrix F 1 into Fuzzy consistent matrix F2:
At first with precedence relationship matrix F 1=(f Ij) N * nBy the row summation, be designated as
r i = Σ k = 1 n f ik ( i = 1,2 , . , n )
Carry out following mathematic(al) manipulation: r then Ij=(r i-r j)/2 (n-1)+0.5, then the matrix after the conversion is Fuzzy consistent matrix F2;
43) confirm the normal weight w of each parameter according to the factor relation method i
The expression formula of factor relation method is:
w i = 1 n - 1 2 β + 1 nβ Σ k = 1 n r ik β ≥ n - 1 2 , i = 1,2 , . , n
β representes the poor of weight, and β is more little, and the difference of weight is big more;
44), obtain the change weights of each parameter factor by following formula according to each parameter normalized value:
w i ( x 1 , x 2 , . , x m ) = w i 0 x i α - 1 / Σ k = 1 m w k 0 x k α - 1
x iBe i the value of passing judgment on parameter, m is for passing judgment on parameter number, w iBe the variable weight of i kind parameter, w i 0Be the Chang Quanchong of i kind parameter, α is a balance factor.
5. dry-type transformer running status as claimed in claim 4 detects appraisal procedure, it is characterized in that: step 43) in, β=(n-1)/2.
6. dry-type transformer running status as claimed in claim 5 detects appraisal procedure, and it is characterized in that: in the step 4), the normal weights of each parameter are following:
X1, X2, X3, the normal weights of X4 are respectively 0.1833,0.3167,0.2278,0.2722;
X11, X12, X13, the normal weights of X14 are respectively 0.1945,0.1833,0.3278,0.2944;
X21, X22, X23, the normal weights of X24 are respectively 0.2167,0.3166,0.3389,0.1278;
X31, X32, X33, the normal weights of X34 are respectively 0.15,0.1944,0.35,0.3056;
X41, X42, X43, the normal weights of X44 are respectively 0.2389,0.3167,0.2611,0.1833.
7. detect appraisal procedure like each described dry-type transformer running status in the claim 1 to 6, it is characterized in that: in the step 3), the quantitative target parameter adopts half distribution function trapezoidal and that half mountain range shape combines to confirm its degree of membership; The qualitative index parameter adopts the half trapezoidal distribution function that combines with triangle to confirm its degree of membership.
8. detect appraisal procedure like each described dry-type transformer running status among the claim 1-7; It is characterized in that: in the step 5); Assessed value V and dry-type transformer running status mapping table are following: 0＜V≤1 expression dry-type transformer running status is good; 1＜V≤2 expression dry-type transformer running statuses are general, and 2＜V≤3 expression dry-type transformer running statuses are for noticing that 3＜V≤4 expression dry-type transformer running statuses are serious.
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