CN104123468A - Distribution transformer state assessment method based on kernel state quantity set - Google Patents

Abstract

A state evaluation method for distribution transformers based on a collection of core state quantities. Through the analysis of the maximum eigenvalue of the state quantity judgment matrix, the core state quantity set required for state evaluation is obtained, so as to achieve the purpose of dimensionality reduction. On the basis of re-distributing the weights of the core state variables, the initial results of distribution transformer state evaluation are obtained. The sensitivity of non-core state quantities to the evaluation results is further obtained, and the initial evaluation results are corrected by using the sensitivity, so that a more accurate final result of distribution transformer state evaluation is obtained. Considering the core state quantities and changing non-core state quantities in the evaluation process not only reduces the demand for data, but also ensures the accuracy of the evaluation results.

Description

Distribution Transformer State Evaluation Method Based on Core State Quantity Collection

technical field

The invention relates to a method for accurately evaluating the state of electrical equipment in a distribution network with a small amount of data, and belongs to the technical field of data processing.

Background technique

The distribution network is one of the main components of the power system, and its operation is closely related to the national economy and people's lives. The reliability of the distribution equipment in the distribution network is the basis for ensuring the reliable operation of the distribution network. Therefore, the evaluation of the status of the distribution equipment is one of the effective measures to improve the reliability of the distribution equipment. As the key equipment of distribution network, distribution transformer is the first step to carry out condition assessment of distribution equipment.

One of the key issues in distribution transformer state assessment is the acquisition of transformer state quantity data. The more complete and accurate the obtained transformer state quantity data is, the more accurate the state evaluation result will be. However, due to the importance of power distribution equipment and the scope of influence after outage is smaller than that of power transmission equipment, and the number is large, and the degree of attention is not enough, there are almost no online monitoring devices, resulting in the status of distribution network equipment that can be obtained The lack of data greatly restricts the development of distribution network equipment status assessment.

Contents of the invention

The purpose of the present invention is to provide a distribution transformer state evaluation method based on the set of core state quantities in order to further improve the efficiency and accuracy of distribution network equipment state evaluation.

Problem described in the present invention is realized with following technical scheme:

A distribution transformer state assessment method based on a set of core state quantities, the method first analyzes and screens each state quantity that affects the state of the distribution transformer through the maximum eigenvalue method, and obtains a set of core state quantities for evaluating the distribution transformer; Then use the core state quantities to calculate the initial results of the distribution transformer evaluation; finally calculate the sensitivity of the non-core state quantities to the evaluation results, and according to the sensitivity, consider the changed non-core state quantities to correct the initial results to obtain the final evaluation results result.

The above-mentioned distribution transformer state evaluation method based on the set of core state quantities, the method is carried out according to the following steps:

a. Through the maximum eigenvalue method to analyze and screen the various state quantities that affect the state of the distribution transformer, and obtain the core state quantity set for evaluating the distribution transformer, the specific method is as follows:

① Construct a judgment matrix

Establish a hierarchical structure model of the distribution transformer status evaluation index system, assuming that the element R _k in the R layer is related to A ₁ , A ₂ ,...A _m in the next layer, relative to R _k , A ₁ , A ₂ ,...A The weights of _m are respectively w ₁ , w ₂ , ... w _m , and the sum of the weights is 1, then the judgment matrix A can be expressed as:

,

In the formula, a _ij represents the numerical representation of the relative importance of A _i to A _j for R _k ;

② Make a scoring table, use the expert scoring method, compare the status evaluation indicators of distribution transformers in pairs, determine the value of a _ij , and obtain the judgment matrix after comparison, and then solve the maximum eigenvalue of the judgment matrix and its corresponding eigenvector , each component of the feature vector is the weight of each index relative to a certain target;

③Sort by weight

According to the weight of each index obtained by solving, set a threshold value, select the index whose weight is greater than the threshold value, form the core index, and the state quantity set composed of the core index is the core state quantity set;

b. Utilize the core state quantity and use the fuzzy analytic hierarchy process to evaluate the state of the distribution transformer, and obtain the initial result P ₀ of the evaluation;

c. Find the sensitivity of the non-core state quantity to the evaluation result:

Set a given increment k, change a non-core state quantity by k%, use the fuzzy analytic hierarchy process to obtain the evaluation result of the changed distribution transformer, set it as P, then the sensitivity is S=(PP ₀ )/k; for Obtain more accurate data, calculate different S values corresponding to different k values, and take the average value of these S as the final sensitivity of the non-core state quantity to the evaluation result; where the final sensitivity is the average value of non-zero S; k When it is a positive value, it means that a certain state quantity increases, and when it is negative, it means a decrease;

d. Considering the change of the non-core state quantity, the initial result is corrected according to the sensitivity of the changed non-core state quantity to the evaluation result, and the final result of the evaluation is obtained:

Assuming that the actual change of the non-core state quantity i is k _i %, and the initial evaluation result P ₀ obtained from the core state quantity is known, the final result after correction is P=P ₀ +∑(S _i *k _i ), S _i is the sensitivity of the non-core state quantity i.

The above-mentioned distribution transformer state evaluation method based on the collection of core state quantities uses the fuzzy analytic hierarchy process to evaluate the state of the distribution transformer. The specific steps are as follows:

①Establish the evaluation factor set

The selected state parameters are used as evaluation factors to establish a set of evaluation factors for the operating state of power distribution equipment, represented by U _j , U _j = (u ₁ , u ₂ , u ₃ ,… u _n );

②Establish a judgment level set

Divide the operating status of the distribution network equipment into five situations: "good", "normal", "suspicious", "abnormal", and "dangerous", that is, the evaluation level set is: V={good, normal, suspicious, abnormal, dangerous }={v ₁ , v ₂ , v ₃ , v ₄ , v ₅ };

③Establish the weight set of evaluation factors

Each evaluation factor u _i is assigned a corresponding weight coefficient w _i (i=1, 2, 3,…,n), then the weight set of evaluation factors is W=(w ₁ , w ₂ ,…,w _n ), and the weight coefficient Normalization conditions must be met: ;

④ Construct fuzzy judgment matrix

The evaluation object is judged according to the i-th factor u _i in the evaluation factor set, and the membership degree of the j-th element v _j in the corresponding evaluation grade set is r _ij , then the evaluation result of the i-th element u _i can be obtained from the fuzzy set R _i =( r _i1 ,, r _i2 ,, r _i3 ,…,, r _in ) means that the fuzzy evaluation matrix R is composed of the membership degree of each factor evaluation set as the row;

⑤Fuzzy comprehensive evaluation

The evaluation result is B=A·R=(b ₁ , , b ₂ ,,…, , b _n ), where “·” is a fuzzy operator, and B _j is called the first-level fuzzy comprehensive evaluation result, which means that according to the factors in U When comprehensive evaluation is carried out for all grades, the evaluation object's membership degree to the jth grade in the evaluation grade is determined according to the principle of the maximum membership degree to determine the evaluation grade to which the evaluated object belongs.

The above distribution transformer state evaluation method based on the set of core state quantities, the element a _ij in the judgment matrix indicates the relative importance of the state quantity A _i to A _j for the state of the distribution transformer; a _ij adopts 1-9 levels Scaling method, its scaling value and corresponding meaning are as follows:

Scale value 1: indicates that A _i and A _j have the same importance;

Scale value 3: indicates that A _i is slightly more important than A _j ;

Scale value 5: indicates that A _i is significantly more important than A _j ;

Scale value 7: Indicates that A _i is more important than A _j ;

Scale value 9: indicates that A _i is extremely important than A _j ;

Scale values 2, 4, 6, 8: represent the median value of the above two adjacent judgments;

According to this, it can be obtained: a _ii =1, a _ij =1/a _ji (i, j=1, 2...m); that is, the relative importance of state quantity A _j to A _i a _ji is the comparison between A _i and A _j The reciprocal of the scale a _ij .

The present invention only considers the core state quantity and the changed non-core state quantity in the process of evaluating the state of the distribution transformer, which not only reduces the demand for data volume, improves the evaluation efficiency, but also ensures the accuracy of the evaluation result through correction sex. The effectiveness of the proposed method is verified by analyzing an evaluation example of an oil-immersed distribution transformer.

Description of drawings

The present invention will be described in further detail below in conjunction with the accompanying drawings.

Figure 1 shows the evaluation index system of oil-immersed distribution transformers;

Figure 2 shows the core evaluation index system of oil-immersed distribution transformers.

The list of symbols in this paper is: A is the judgment matrix; a _ij is the numerical expression of the relative importance of A _i to A _j for R _k ; U _j is the set of evaluation factors for the operation status of power distribution equipment; w _i is the evaluation factor u _i W is the weight set of evaluation factors; B is the evaluation result.

Detailed ways

The present invention provides a distribution transformer state evaluation method based on a set of core state quantities, so as to better carry out the state evaluation work of the distribution network equipment and improve the efficiency of the state evaluation work of the distribution network equipment. The state quantity described in the present invention refers to the general term of various technical indicators, performance and operating conditions that directly or indirectly characterize the status of the equipment; The obtained state quantities have a relatively large impact on the evaluation results; non-core state quantities refer to state quantities other than the core state quantities.

The core state quantity set of the distribution transformer described in the present invention is shown in Figure 2, which includes two layers: a first-level index set and a second-level index set. The first-level indicators include winding and bushing, oil tank, non-electrical protection, grounding and insulating oil; the second-level indicators include DC resistance, insulation resistance, joint temperature, integrity of winding and bushing, sound, sealing, oil level, oil 13 items including temperature, insulation of non-electrical protection devices, grounding resistance, grounding down-conductor, color of insulating oil, and withstand voltage test of insulating oil.

The non-core state quantity in the present invention includes two layers: a first-level index set and a second-level index set. The first-level indicators include two items of tap changer and identification; the second-level indicators include three-phase unbalance rate, load rate, pollution level, tap-changer performance, distribution transformer bench-to-ground distance, respirator silicone color, rust, and complete identification Wait for 8 items.

In order to reflect the operating state of distribution transformers as accurately as possible, through the research on the formation mechanism of various transformer faults, and considering the operability of distribution transformer state evaluation, a state quantity including test information, operation information, and inspection information is formed. Collectively, a distribution transformer status evaluation index system is established. Taking oil-immersed distribution transformer as an example, the first-level indicators of the evaluation index system include: winding and bushing, tap changer, oil tank, non-electrical protection, grounding, insulating oil, and identification; each first-level indicator includes several The hierarchical structure of the second-level indicators is shown in Figure 1 (the second column in Figure 1 is the first-level indicators, and the third column is the second-level indicators).

According to the scale size between the elements in the indicators at all levels, the judgment matrix of the first-level indicators can be established, as shown in Table 1. Taking the last column as an example, the element 7 in the first row indicates that the winding bushing is much more important than the identification for the status of the distribution transformer; the element 2 in the second row indicates that the status of the tap changer is slightly more important than the identification for the status of the distribution transformer. Important; element 3 in the third row indicates that the status of the fuel tank is slightly more important than the identification for the status of the distribution transformer; and so on. By calculating the maximum eigenvalue of the judgment matrix and its corresponding eigenvector, the weight vector can be obtained after normalizing the eigenvector.

Table 1 Judgment matrix and weight vector of primary index of oil-immersed distribution transformer

In the same way, after establishing the secondary index judgment matrix of winding, bushing and fuel tank, the weight of each index can be obtained according to the maximum eigenvalue method. The following table shows the judgment matrix and weight of the winding and bushing, and the judgment matrix and weight of the fuel tank.

Table 2 Judgment matrix and weight vector of oil-immersed distribution transformer winding bushing index

Table 3 Oil-immersed distribution transformer oil tank index judgment matrix and weight vector

Considering that the number of secondary state quantity indicators of various components such as tap changer, non-electrical protection, grounding, insulating oil, and identification is small, dimensionality reduction is no longer considered here.

According to the maximum eigenvalue method to analyze the weight size, it is considered that the feature quantities with smaller weights have less influence on the final evaluation results, so these feature quantities are eliminated. Considering the actual situation, the present invention sets the threshold value to 0.1, and eliminates the state quantities whose weights are less than or close to 0.1 or whose weights are significantly different from other state quantities in actual operation. Therefore, tap-changers and signs are excluded from the first-level indicators, and three-phase unbalance rate, load rate and pollution level are excluded from the second-level indicators of windings and bushings. The secondary index of the oil tank excludes the color of the silica gel of the respirator, the distance from the distribution transformer stand to the ground and the rust. The final evaluation index system of the core state quantity is shown in Figure 2 (the second column in Figure 2 is the first-level indicator, and the third column is the second-level indicator). The core state quantity evaluation indicators are re-weighted according to the maximum eigenvalue method, and the results are shown in Table 4-Table 8.

Table 4 Weight of primary index of oil-immersed distribution transformer

Table 5 Weights of core state quantities of windings and bushings of oil-immersed distribution transformers

Table 6 Weight of core state quantity of oil-immersed distribution transformer oil tank

Table 7 Weight of core state variables for grounding of oil-immersed distribution transformers

state quantity Appearance of grounding down conductor Ground resistance Weights 0.2 0.8

Table 8 The weight of the core state quantities of insulating oil in oil-immersed distribution transformers

Based on the distribution transformer state evaluation method based on the set of core state quantities, the method of calculating the sensitivity of non-core state quantities to the evaluation results is as follows:

Taking the test and inspection data of a 10kV oil-immersed distribution transformer as an example, the sensitivity of non-core state quantities is calculated. Transformer capacity 315kVA, voltage 10±5%/0.4kV, model S11-M-315, wiring group Yy _no . The line-to-line DC resistance AB/BC/CA of the winding and bushing is 3.285/3.290/3.281 Ω, the phase-to-phase DC resistance Ao/Bo/Co is 0.002527/0.002552/0.002547 Ω, the insulation resistance is 2100MΩ, and the joint temperature/temperature difference is 58°C /11K, the load rate is 82%, the three-phase unbalance rate is 15%, the pollution level is no pollution, complete and no damage; the tapping performance of the tap changer is normal; the sound of the fuel tank is normal, and the distance between the stand and the ground meets the requirements Requirements, no oil leakage in the seal, no abnormality in the oil level, no discoloration of the silica gel of the respirator, normal oil temperature, and no rust; the insulation resistance of the non-electrical protection device is 1.36MΩ; the grounding resistance is 3.3Ω, and the appearance of the grounding down conductor is normal; The color of the insulating oil is normal, and the withstand voltage test is qualified; the markings are complete. Based on this data, the sensitivity of the non-core state quantity is analyzed.

Under the condition that all state variables participate in the evaluation, the result of transformer state evaluation is value=92.29.

Set the variation of the three-phase unbalance rate Δ=5%. When the three-phase unbalance rate changes and other state quantities remain unchanged, the results of transformer state evaluation and the sensitivity of the three-phase unbalance rate are shown in the table below. The final value of the sensitivity of the three-phase unbalance rate: S _av =-(0.02+0.017+0.018+0.016)/4=-0.01775

Table 9 Sensitivity of three-phase unbalance rate

Set the variation of load rate Δ=5%. When the load rate changes and other state quantities remain unchanged, the results of transformer state evaluation and the sensitivity of the load rate are shown in the table below. The final value of the load rate sensitivity (since the change is negative, the sensitivity is 0, that is, the evaluation result does not change, so only the sensitivity with a positive change is considered when calculating the average value of the sensitivity): S _av =-(0.012+0.03 )/2=-0.021

Table 10 Sensitivity of Load Rate

Similarly, the sensitivities of other state quantities are shown in the table below.

Table 11 Sensitivity of other state variables

The distribution transformer state evaluation method based on the core state quantity set, the final result is obtained by the following method: the initial result of the distribution transformer evaluation is obtained through the calculation of the core state quantity set, and if the non-core state quantity does not change at this time, the result is The final result of the transformer state evaluation; if the non-core state quantity data has changed compared with the previous evaluation, then the impact of the non-core state quantity on the initial evaluation result must be considered. According to the sensitivity of the obtained non-core state quantity to the evaluation result, the initial result is corrected to obtain the final evaluation result.

Case Analysis

Taking the above-mentioned transformer as an example, fuzzy tomographic analysis method is used for state evaluation, and the method is verified by programming in VS2010 environment.

The state quantity data of the transformer during a certain state evaluation is as follows: the line-to-line DC resistance AB/BC/CA of the winding and bushing is 3.371/3.378/3.367 , the phase-to-phase DC resistance Ao/Bo/Co is 0.002719/0.002725/0.002735 , the insulation resistance is 0.002719/0.002725/0.002735 M , the joint temperature/temperature difference is 70°C/15K, the load rate is 85%, the three-phase unbalance rate is 20%, the pollution level is no pollution, complete and no damage; the tapping performance of the tap changer is normal; the sound of the fuel tank is no Abnormal, the distance between the bench and the ground meets the requirements, the seal has no oil leakage, the oil level is normal, the color of the silicone respirator has not changed, the oil temperature is normal, and the corrosion is moderate corrosion; the insulation resistance of the non-electrical protection device is 1.33 MΩ; the grounding resistance is 3.4 Ω, the appearance of the grounding down-conductor is normal; the color of the insulating oil is normal, the withstand voltage test is qualified; the marks are complete.

The initial evaluation results obtained by state evaluation based on the core state quantities in Figure 2 are shown in the table below.

Table 12 Evaluation results of distribution transformer core state quantities

Since the non-core state quantity data has changed, the evaluation result should be corrected according to the sensitivity of the non-core state quantity.

Correction results of winding and bushing three-phase unbalance rate:

Δvalue1=-0.01775×5=-0.08875;

Correction results of winding and bushing load rate:

Δvalue2=-0.021×3=-0.063;

Correction results for fuel tank corrosion:

Δvalue3=-0.62;

The evaluation results of the final transformer are:

value=90.20-0.08875-0.063-0.62=89.428;

It can be seen that the state evaluation result of the distribution transformer obtained by this method is 89.428, and the state of the transformer is normal.

At the same time, it can be evaluated according to all the state quantities in Figure 1, and the obtained evaluation result is 89.85, and the state of the transformer is also normal. Compared with the two results, the deviation is not large, so this example verifies the effectiveness of the proposed method.

Claims (4)

1. the substation transformer state evaluating method based on kernel state duration set, it is characterized in that, first described method is analyzed and is screened the each quantity of state that affects substation transformer state by algorithm based on the largest eigenvalue, obtains assessing the kernel state duration set of substation transformer; Then utilize kernel state amount to calculate the initial result of substation transformer assessment; Finally ask for the sensitivity of non-core quantity of state to assessment result, and according to sensitivity, consider that vicissitudinous non-core quantity of state revises initial result, obtain the net result of assessment.

2. the substation transformer state evaluating method based on kernel state duration set according to claim 1, is characterized in that, described method is carried out according to following steps:

A. by algorithm based on the largest eigenvalue, the each quantity of state that affects substation transformer state is analyzed and screened, obtain assessing the kernel state duration set of substation transformer, concrete grammar is as follows:

1. Judgement Matricies

Set up the hierarchy Model of substation transformer State Assessment Index System, suppose element R in R layer _kwith A in lower one deck ₁, A ₂... A _mbe related, with respect to R _k, A ₁, A ₂... A _mweight be respectively w ₁, w ₂... w _m, weight sum is 1, judgment matrix A can be expressed as:

In formula, a _ijrepresent for R _k, A _ito A _jthe numerical value performance of relative importance;

2. make marking form, adopt the mode of expert's marking, substation transformer state estimation index is compared between two, determine a _ijvalue, the judgment matrix after drawing relatively, then solves maximum characteristic root and its characteristic of correspondence vector of judgment matrix, each component of proper vector is the weight of the relatively a certain target of each index;

3. weight sequence

According to the weight that solves the each index obtaining, a threshold value is set, weight selection is greater than the index of threshold value, forms core index, and the quantity of state set being made up of core index is kernel state duration set;

B. utilize kernel state amount, adopt Fuzzy AHP to assess the state of substation transformer, obtain the initial result P of assessment ₀;

C. ask for the sensitivity of non-core quantity of state to assessment result:

If given increment k, changes k% by certain non-core quantity of state, adopt Fuzzy AHP to ask for the substation transformer assessment result after variation, be made as P, sensitivity is S=(P-P ₀)/k; Calculate different S values corresponding when different value of K, and the mean value of getting these S is the ultimate sensitivity of this non-core quantity of state to assessment result; Wherein, ultimate sensitivity is the mean value of the S of non-zero; K on the occasion of time represent that certain quantity of state increases, when negative value, represent to reduce;

D. consider the variation of non-core quantity of state, according to vicissitudinous non-core quantity of state, the sensitivity of assessment result revised initial result, obtain the net result of assessment:

If non-core quantity of state i actual change is k _i%, the known initial assessment result P measuring according to kernel state ₀, revised net result is P=P ₀+ ∑ (S _i* k _i), S _ifor the sensitivity of non-core quantity of state i.

3. the substation transformer state evaluating method based on kernel state duration set according to claim 2, is characterized in that, the concrete steps that adopt Fuzzy AHP to assess the state of substation transformer are as follows:

1. set up evaluation factor collection

Using selected state parameter as evaluation factor, set up controller switching equipment running status evaluation factor collection, use U _jrepresent U _j=(u ₁, u ₂, u ₃... u _n);

2. set up evaluation rank collection

The running status of distribution net equipment is divided into " well ", " normally ", " suspicious ", " extremely ", " danger " five kinds of situations, and evaluation rank collection is: V={ is good, normal, suspicious, abnormal, danger }={ v ₁, v ₂, v ₃, v ₄, v ₅;

3. set up evaluation factor weight sets

To each evaluation factor u _igive corresponding weight coefficient w _i(i=1,2,3 ..., n), evaluation factor weight sets is W=(w ₁, w ₂..., w _n), weight coefficient must meet normalizing condition: ;

4. construct fuzzy evaluation matrix

Press concentrated i the factor u of evaluation factor to passing judgment on object _ienter to pass judgment on, corresponding opinion rating is concentrated j element v _jsubjection degree be r _ij, i element u _ievaluation result can use fuzzy set R _i=(r _i1,, r _i2,, r _i3...,, r _in) represent, form fuzzy evaluation matrix R taking the degree of membership of each factor evaluation collection as going;

5. fuzzy comprehensive evoluation

Evaluation result is B=AR=(b ₁,, b ₂, ...,, b _n), wherein " " is fuzzy operator, B _jbe called one-level Result of Fuzzy Comprehensive Evaluation, while representing to carry out comprehensive evaluation by all grades of factor in U, the degree of membership of evaluation object to j grade in opinion rating, according to maximum membership grade principle, determines and is evaluated the affiliated evaluation rank of object.

4. the substation transformer state evaluating method based on kernel state duration set according to claim 3, is characterized in that, the element a in judgment matrix _ijrepresent for the state of substation transformer quantity of state A _ito A _jrelative importance; a _ijadopt 1～9 grade of Scale Method, its scale value and corresponding implication are as follows:

Scale value 1: represent A _iwith A _jthere is no less important;

Scale value 3: represent A _icompare A _jimportant a little;

Scale value 5: represent A _icompare A _jobviously important;

Scale value 7: represent A _icompare A _jvery important;

Scale value 9: represent A _icompare A _jof crucial importance;

Scale value 2,4,6,8: the intermediate value that represents above-mentioned two adjacent judgements;

Can obtain accordingly: a _ii=1, a _ij=1/a _ji(i, j=1,2 ... m), i.e. quantity of state A _jto A _irelative importance a _jia _iwith A _jrelatively scale a _ijinverse.