CN109507517A - The distribution transformer running state analysis method compared based on two-sided power big data - Google Patents
The distribution transformer running state analysis method compared based on two-sided power big data Download PDFInfo
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- CN109507517A CN109507517A CN201811491185.5A CN201811491185A CN109507517A CN 109507517 A CN109507517 A CN 109507517A CN 201811491185 A CN201811491185 A CN 201811491185A CN 109507517 A CN109507517 A CN 109507517A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
- G01R31/62—Testing of transformers
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Abstract
The present invention provides a kind of distribution transformer running state analysis method compared based on two-sided power big data, acquires transformer two-sided power including transformer factory power experiment and the foundation of filing data, on-line testing and is recorded and form input data library file.The data file of acquisition is made of two-sided power data, bilateral voltage value and bilateral computing impedance curve, by on-line testing transformer two-sided power parameter, voltage parameter and above-mentioned transformer dispatch from the factory power ratio archives are compared and with it is weekly, monthly, annual parameter big data compares to obtain running state of transformer at this stage and the following operating status.Using transformer two-sided power symmetry principle, existing distribution transformer status assessment inaccuracy is efficiently solved the problems, such as.The detectable degree for improving distribution transformer operation reduces the probability of generation problem after distribution transformer failure.
Description
Technical field
The present invention relates to transformer state analysis and operating condition electric powder predictions, in particular to a kind of to be based on bilateral function
The distribution transformer running state analysis method that rate big data compares.
Background technique
The stable operation of distribution transformer is to be related to the essential condition of power supply reliability and power supply safety.All the time,
It is installed and is dispersed due to distribution transformer, single transformer value is low, and reasons constrain transformer stable operation not in time etc. for inspection,
Although having developed a large amount of transformer detection device for many years, for distribution transformer, lack a kind of simple and reliable
Judgment method and decision logic.The present invention is directed to provide one kind by detection to transformer two-sided power and analysis and can analyze
The analysis method of power transformer interior fault and future malfunction outline.
Summary of the invention
In order to solve the problems, such as described in background technique, the present invention provides a kind of distribution compared based on two-sided power big data
Running state of transformer analysis method has invented a kind of simple possible using transformer two-sided power symmetry principle, can examine in real time
The power transformer interior fault of analysis and the analysis method of future malfunction probability are surveyed, existing distribution transformer state is efficiently solved and comments
Estimate the problem of inaccuracy.The detectable degree for improving distribution transformer operation, occurs problem after reducing distribution transformer failure
Probability.
In order to achieve the above object, the present invention is implemented with the following technical solutions:
A kind of distribution transformer running state analysis method compared based on two-sided power big data, including transformer factory
Power experiment and the foundation of filing data, on-line testing acquire transformer two-sided power and are recorded and form input database
File.The foundation and experiment of transformer factory power data filing are to carry out in transformer factory experiment to a group power test.
The data file of acquisition is made of two-sided power data, bilateral voltage value and bilateral computing impedance curve, is become by on-line testing
Depressor two-sided power parameter, voltage parameter and above-mentioned transformer factory power ratio archives are compared and with it is weekly, it is monthly, year ginseng
Number big data compares the method for obtaining running state of transformer at this stage and the following operating status.
Specifically comprise the following steps:
Step 1: carrying out factory power test, test process is as follows in distribution transformer factory:
1) n power within the scope of transformer efficiency is taken to carry out the given experiment of input power；The choosing of load side input power factor
N numerical value between 0.7-0.98 is taken to be tested, power P 1 of experimental record, secondary power P2, load power factor C, one
Secondary voltage effective value U1, secondary voltage virtual value U2；
2) parameter recorded is formed into following rectangular arrays Ac, Ap, and calculates the product Acp of two matrixes；
Wherein: power factor matrixPower voltage matrix
Calculating matrix product Acp, obtain a result matrix and stores together with above-mentioned two matrix；
Step 2: carrying out online distribution transformer power parameter measurement when transformer actual motion, measurement obtains matrix
Acc,
{ C1 } { P1 P2 U1 U2 }=Acc
It is stored in memory；
Decision conclusions are calculated and obtained Step 3: matrix A cc is compared with matrix A cp；
Calculation method are as follows: calculating matrix Acc is overlapped probability Gb with matrix A cp's, obtains certain in matrix A cc and Acp matrix
One row element probability peak Ga；Running state of transformer is evaluated according to the value of Ga and Gb；
Step 4: by the test data set composite matrix at m time point in the period T for storing transformer station high-voltage side bus
Acpt, combined method are as follows:
Step 5: Acpt and Acp is carried out poor bit arithmetic, equal position deviation matrix Acpp is obtained.Calculate removing for Acp and Accp
Method operation obtains COEFFICIENT K, K=Accp/Acp；
Step 6: estimating the failure rate of the operating status in transformer future according to the value of COEFFICIENT K.
The value according to Ga and Gb in the step three evaluates running state of transformer, specific as follows:
1) work as Ga > a% or multiple coincidence probability Gb > b%, be then judged as that the running state of transformer is outstanding；
2) work as Ga > c% or multiple coincidence probability Gb > d%, be then judged as that the running state of transformer is good；
3) work as Ga > e% or multiple coincidence probability Gb > f%, then it is assumed that the transformer station high-voltage side bus shape is passed；
4) remaining situation then thinks that the transformer station high-voltage side bus is failed；
Wherein, a, b, c, d, e, f be percentage specific ray constant, a, b value range: (100,85], c, d value range: (85,
70], e, f value range: (70,60].
The data of on-line testing in the step three and step 4 can be weekly, monthly or annual time section more
The test data at a time point.
Compared with prior art, the beneficial effects of the present invention are:
A kind of big data based on the online two-sided power test record of distribution transformer of the invention compares operating status point
Analysis and future malfunction rate prediction technique are by on-line testing transformer two-sided power parameter, voltage parameter and above-mentioned transformer
Power ratio of dispatching from the factory archives are compared and with it is weekly, monthly, annual parameter big data compares to obtain transformer station high-voltage side bus at this stage
The method of state and the following operating status.
The present invention using transformer two-sided power symmetry principle provide a kind of simple possible, can real-time detection analysis change
The analysis method of depressor internal fault and future malfunction probability efficiently solves existing distribution transformer status assessment inaccuracy
Problem.The detectable degree for improving distribution transformer operation reduces the probability of generation problem after distribution transformer failure.
Detailed description of the invention
Fig. 1 is a kind of distribution transformer running state analysis method stream compared based on two-sided power big data of the invention
Cheng Tu.
Specific embodiment
Specific embodiment provided by the invention is described in detail below.
As shown in Figure 1, a kind of distribution transformer running state analysis method compared based on two-sided power big data, including
Transformer factory power experiment and the foundation of filing data, on-line testing acquire transformer two-sided power and are recorded and formed
Input data library file.The foundation and experiment of transformer factory power data filing are to carry out in transformer factory experiment to group
Power test.The data file of acquisition is made of two-sided power data, bilateral voltage value and bilateral computing impedance curve.
Specifically comprise the following steps:
Step 1: carrying out factory power test, test process is as follows in distribution transformer factory:
1) n power within the scope of transformer efficiency is taken to carry out the given experiment of input power；The choosing of load side input power factor
N numerical value between 0.7-0.98 is taken to be tested, power P 1 of experimental record, secondary power P2, load power factor C, one
Secondary voltage effective value U1, secondary voltage virtual value U2；
2) parameter recorded is formed into following rectangular arrays Ac, Ap, and calculates the product Acp of two matrixes；
Wherein: power factor matrixPower voltage matrix
Calculating matrix product Acp, obtain a result matrix and stores together with above-mentioned two matrix；
Step 2: carrying out online distribution transformer power parameter measurement when transformer actual motion, measurement obtains matrix
Acc,
{ C1 } { P1 P2 U1 U2 }=Acc
It is stored in memory；
Decision conclusions are calculated and obtained Step 3: matrix A cc is compared with matrix A cp；
Calculation method are as follows: calculating matrix Acc is overlapped probability Gb with matrix A cp's, obtains certain in matrix A cc and Acp matrix
One row element probability peak Ga；Running state of transformer is evaluated according to the value of Ga and Gb；
Step 4: by the test data set composite matrix at m time point in the period T for storing transformer station high-voltage side bus
Acpt, combined method are as follows:
Step 5: Acpt and Acp is carried out poor bit arithmetic, equal position deviation matrix Acpp is obtained.Calculate removing for Acp and Accp
Method operation obtains COEFFICIENT K, K=Accp/Acp；
Step 6: estimating the failure rate of the operating status in transformer future according to the value of COEFFICIENT K.
The data of on-line testing in the step three and step 4 can be weekly, monthly or annual time section more
The test data at a time point.
The value according to Ga and Gb in the step three evaluates running state of transformer, specific as follows:
1) work as Ga > a% or multiple coincidence probability Gb > b%, be then judged as that the running state of transformer is outstanding；
2) work as Ga > c% or multiple coincidence probability Gb > d%, be then judged as that the running state of transformer is good；
3) work as Ga > e% or multiple coincidence probability Gb > f%, then it is assumed that the transformer station high-voltage side bus shape is passed；
4) remaining situation then thinks that the transformer station high-voltage side bus is failed；
Wherein, a, b, c, d, e, f be percentage specific ray constant, a, b value range: (100,85], c, d value range: (85,
70], e, f value range: (70,60].
In the step six, the failure rate for estimating the operating status in transformer future according to the value of COEFFICIENT K is specific as follows:
As COEFFICIENT K≤m%, then it is assumed that transformer future operating status is outstanding；M%≤K≤n%, then it is assumed that transformer is not
It is good to carry out operating status；N%≤K≤p%, then it is assumed that the operation of transformer future is bad.
Wherein, m, n, p be percentage specific ray constant, m value range: (0,10], n value range: (10,20], f value range:
(20,60].
Above embodiments are implemented under the premise of the technical scheme of the present invention, give detailed embodiment and tool
The operating process of body, but protection scope of the present invention is not limited to the above embodiments.Method therefor is such as without spy in above-described embodiment
Not mentionleting alone bright is conventional method.
Claims (2)
1. a kind of distribution transformer running state analysis method compared based on two-sided power big data, which is characterized in that including
Following steps:
Step 1: carrying out factory power test, test process is as follows in distribution transformer factory:
1) n power within the scope of transformer efficiency is taken to carry out the given experiment of input power；Load side input power factor is chosen
N numerical value is tested between 0.7-0.98, power P 1 of experimental record, secondary power P2, load power factor C, once
Voltage effective value U1, secondary voltage virtual value U2；
2) parameter recorded is formed into following rectangular arrays Ac, Ap, and calculates the product Acp of two matrixes；
Wherein: power factor matrixPower voltage matrixCalculating matrix
Product Acp, obtain a result matrix and stores together with above-mentioned two matrix；
Step 2: carrying out online distribution transformer power parameter measurement when transformer actual motion, measurement obtains matrix A cc,
{ C1 } { P1 P2 U1 U2 }=Acc
It is stored in memory；
Decision conclusions are calculated and obtained Step 3: matrix A cc is compared with matrix A cp；
Calculation method are as follows: calculating matrix Acc is overlapped probability Gb with matrix A cp's, obtains certain a line in matrix A cc and Acp matrix
Element probability peak Ga；Running state of transformer is evaluated according to the value of Ga and Gb；
Step 4: by the test data set composite matrix Acpt at m time point in the period T for storing transformer station high-voltage side bus, group
Conjunction method is as follows:
Step 5: Acpt and Acp is carried out poor bit arithmetic, equal position deviation matrix Acpp is obtained.Calculate the division fortune of Acp and Accp
It calculates, obtains COEFFICIENT K, K=Accp/Acp；
Step 6: estimating the failure rate of the operating status in transformer future according to the value of COEFFICIENT K.
2. a kind of distribution transformer running state analysis side compared based on two-sided power big data according to claim 1
Method, which is characterized in that the value according to Ga and Gb in the step three evaluates running state of transformer, specifically such as
Under:
1) work as Ga > a% or multiple coincidence probability Gb > b%, be then judged as that the running state of transformer is outstanding；
2) work as Ga > c% or multiple coincidence probability Gb > d%, be then judged as that the running state of transformer is good；
3) work as Ga > e% or multiple coincidence probability Gb > f%, then it is assumed that the transformer station high-voltage side bus shape is passed；
4) remaining situation then thinks that the transformer station high-voltage side bus is failed；
Wherein, a, b, c, d, e, f be percentage specific ray constant, a, b value range: (100,85], c, d value range: (85,70], e, f
Value range: (70,60].
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110824289A (en) * | 2019-12-16 | 2020-02-21 | 国网辽宁省电力有限公司鞍山供电公司 | Detection and analysis method for running state of power distribution ring main unit |
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