JP2009168571A - Degradation diagnosis method for oil-filled transformers - Google Patents

Abstract

An object of the present invention is to estimate the average degree of polymerization of insulating paper in an oil-filled transformer with sufficiently high accuracy and reduce the amount of work and cost required to estimate the average degree of polymerization of insulating paper.
In the degradation diagnosis method, measured data of gas in oil, total acid number and withstand voltage in the insulating oil OL are set as a first input factor group, respectively, at the start of use and at the end of use of the oil-filled transformer 20. The average polymerization degree estimation model is constructed by learning the model using the measured average polymerization degree measurement data as the second input factor group and the average polymerization degree estimated value of the insulating paper as the output factor. The most recent measurement data of a plurality of types of oil-in-gas, total acid number, and withstand voltage in the oil-filled transformer 20 is input to the average polymerization degree estimation model, and the insulation in the oil-filled transformer 20 is determined by this average polymerization degree estimation model. Estimate the average degree of polymerization of the paper.
[Selection] Figure 1

Description

  The present invention relates to an oil-filled transformer deterioration diagnosis method for estimating an average degree of polymerization of insulating paper in an oil-filled transformer.

In general, the following materials are used for oil-filled transformers.
(1) Conductive materials such as copper and aluminum (2) Insulating materials such as insulating oil, insulating paper and press board (3) Iron core materials such as silicon steel strips (4) Metal container materials such as iron and stainless steel Among the materials, it is considered that insulating materials such as insulating oil and insulating paper are subject to deterioration over time in the oil-filled transformer. Insulating oil has a function of oil deterioration prevention device (open type, air-sealed type, nitrogen-sealed type, etc.), so the deterioration is very slow, and the breakdown voltage, which is an important characteristic, is low. .

On the other hand, for insulating paper, the degree of decrease in dielectric breakdown voltage due to deterioration over time is small, but the degree of decrease in mechanical strength is large (that is, the paper becomes shabby). As the deterioration of the insulating paper proceeds, the insulating paper is cracked or broken by mechanical stress due to inrush current or electromagnetic force generated at the time of external short circuit, and the risk of dielectric breakdown increases.
Therefore, the life of the oil-filled transformer is strongly influenced by the mechanical strength of the insulating paper, particularly the deterioration state of the winding conductor insulating paper. In other words, the remaining life of the oil-filled transformer is conventionally considered to be determined by the dielectric breakdown of the winding conductor insulating paper, that is, the state of deterioration of the insulating paper (decrease in average polymerization degree).

Below, the average degree of polymerization of the insulating paper, the remaining life of the oil-filled transformer, and the deterioration diagnosis method will be discussed.
(1) Average degree of polymerization of insulating paper Insulating paper is a polymer obtained by polymerizing a large number of cellulose molecules, and the number of basic molecules constituting this cellulose is called the degree of polymerization. The average degree of polymerization in the case of new kraft paper as insulating paper is about 1000. As for this average polymerization degree, when the insulating paper is oxidized and deteriorated, the chain of cellulose molecules is cut and the molecular weight of the cellulose molecules is lowered, that is, the average polymerization degree is lowered. For example, in a transformer used for 30 years, the average polymerization degree of insulating paper is said to decrease to about 40 to 60% of the initial value (polymerization degree 400 to 600).
(2) Life of oil-filled transformer The Japan Electrical Manufacturers' Association standard JEM1463-1993 defines an evaluation standard for oil-filled transformers exceeding 1000 [kVA]. Generally, according to this standard, the average degree of polymerization is The point at which it is supposed to be 450 is defined as the life of the oil-filled transformer.

(3) Degradation diagnosis method for current oil-filled transformer In the remaining life diagnosis of a transformer, if it is intended to follow the standard of (2) above, it is necessary to measure or estimate the average degree of polymerization of coil insulating paper . However, it is difficult to measure the coil insulation paper of the oil-filled transformer in operation because it cannot be easily collected. Therefore, the average polymerization degree of the insulating material (press board, lead insulating paper) that can be collected inside the transformer, and the amount of furfural and CO ₂ + CO, which are products of the decomposition process of the insulating paper, were measured, and the results were used. Remaining life diagnosis is performed. These deterioration diagnosis methods are described in Non-Patent Document 1 and Non-Patent Document 2, for example.

Hereinafter, various deterioration diagnosis methods will be outlined.
(A) Degree of polymerization method During inspections such as when the operation is stopped, a method of diagnosing the degree of insulation paper deterioration by collecting the press board or lead insulation paper from the inside of the transformer that does not affect insulation is used. The law. This degree of polymerization method is a method for estimating the remaining life by estimating the degree of deterioration of the coil insulating paper at the hottest portion (hot spot portion) of the winding coil from the average degree of polymerization of the collected insulating paper.

(B) CO ₂ + CO method Insulating paper generates various organic components such as water, CO ₂ , and CO due to deterioration. As effective deterioration index components, there are CO ₂ + CO having a correlation with the average degree of polymerization, and further furfural. Among these, in the CO ₂ + CO method, gas analysis in oil is performed, and deterioration diagnosis is performed by estimating the average degree of polymerization from the amount of CO ₂ + CO that is the final deterioration product of the insulating paper.

(C) Furfural method The furfural aldehyde component is produced during the decomposition process of cellulose. Even when the insulating oil is deaerated, 85% of the furfural remains in the oil and does not diffuse into the gas. For this reason, if the history of the deaeration process is known, this method can be used even if the deaeration process is performed.
In this furfural method, the average degree of polymerization is obtained from the measured amount of furfural according to the correlation obtained in advance. However, the degree of deterioration (remaining life diagnosis) of the average degree of polymerization is considerably wide with respect to the amount of furfural. The diagnosis results also have a wide range, and it is very difficult to estimate the remaining life with high accuracy.

Also, by measuring the temperature of the transformer oil predicts CO 2 ₊ CO concentration, the oil-filled electrical apparatus to detect the insulation deterioration when the difference between the actual value and the predicted value is a certain value or more An insulation diagnostic apparatus is described in Patent Document 1.
Also, measure the amount of gas in the insulation medium (insulating oil) of the static induction device, and detect abnormalities such as local overheating and arc discharge from changes in the type, generation amount, and generation ratio of decomposition products. In the diagnosis method, Patent Document 2 discloses a method of diagnosing abnormality of a static induction appliance using a neural network in which an amount of generation of acetylene as a decomposition product is input data and an abnormal phenomenon such as arc discharge is learned as teacher data. It is described in.

  In addition, as a general maintenance work for oil-filled transformers, in order to grasp the degree of deterioration of the insulation oil itself, periodic sampling of the insulation oil from the oil-filled transformer is performed. Gas measurement, withstand voltage measurement and total acid value measurement are performed. At the time of gas measurement, for example, hydrogen, oxygen, nitrogen, carbon dioxide, carbon monoxide, methane, ethane, ethylene, and acetylene are measured, or two or more kinds of gas in oil selected from this gas group are measured. .

By the way, when trying to accurately estimate the remaining life of the oil-filled transformer, for example, when measuring the average polymerization degree of the insulating paper by the polymerization degree method at the time when the equipment is stopped for a certain period or more, Periodically measure the amount of furfural in insulating oil. When determining the remaining life of the oil-filled transformer, the estimated average polymerization degree of the insulating paper obtained from the most recent furfural amount measurement value is corrected by the average polymerization degree measurement value obtained by the polymerization degree method. The remaining life of the oil-filled transformer is determined based on the corrected average polymerization degree estimate.
“Current Status and Trends of Aging Transformer Reliability Maintenance Technology”, Aging Transformer Reliability Maintenance Technology Investigation Technical Committee, Institute of Electrical Engineers of Japan, March 10, 2003, No. 922, p. 22-27 "Part IV Oil-immersed Transformer Degradation Diagnosis", Electric Cooperative Research, Electric Cooperative Research Society, February 25, 1999, Vol. 54, No. 5 (Part 1), p. 158-168 JP-A-63-52071 (page 2, lower left column, line 14 to page 3, upper right column, line 13, line 5, etc.) JP-A-6-82405 (paragraphs [0025] to [0036], FIG. 1, FIG. 2, etc.)

However, the average degree of polymerization of insulating paper cannot be measured by the polymerization degree method unless the equipment (oil-filled transformer) is not in operation, and the oil-filled transformer is used to measure the furfural amount of insulating oil. A certain amount of insulating oil must be extracted from the tank. For this reason, in order to continue to estimate the average degree of polymerization of insulating paper with high accuracy over a long period from the start of use of the oil-filled transformer to the end of use (disposal), the amount of work and The cost will be cumulative. On the other hand, in facilities such as large-scale steelworks where a large number of oil-filled transformers are installed, it is strongly required to efficiently estimate the average degree of polymerization of insulating paper.
The object of the present invention is to take into account the above facts, and to estimate the average degree of polymerization of insulating paper in an oil-filled transformer with sufficiently high accuracy, and to reduce the amount of work and cost required to estimate the average degree of polymerization of insulating paper. An object of the present invention is to provide a method for diagnosing deterioration of an oil-filled transformer that can be reduced.

  In order to solve the above-mentioned problem, a deterioration diagnosis method for an oil-filled transformer according to claim 1 of the present invention is an oil-filled transformer having a container and a coil immersed in insulating oil stored in the container. A degradation diagnosis method, in which measured values of gas in oil, total acid number and withstand voltage for insulating oil measured at predetermined inspection intervals are set as a first input factor group, and at least when an oil-filled transformer is used And measuring or measuring the average degree of polymerization of the insulating paper of the coil measured at the completion of use as a second input factor group and using the average degree of polymerization of the insulating paper as an output factor Establish an average polymerization degree estimation model of insulating paper, and estimate the average polymerization degree of measured values of gas in oil, total acid value and withstand voltage for insulating oil measured from insulating oil in oil-filled transformer as diagnosis target Enter the model and the average weight Characterized in that the degree estimation model obtain an estimate of the average polymerization degree.

The deterioration diagnosis method for an oil-filled transformer according to claim 2 of the present invention is the deterioration diagnosis method for an oil-filled transformer according to claim 1, wherein when measuring the gas in oil relative to the insulating oil, hydrogen, oxygen, nitrogen, Two or more kinds of oil-in-gas selected from the group consisting of carbon dioxide, carbon monoxide, methane, ethane, ethylene and acetylene are measured.
According to a third aspect of the present invention, there is provided a method for diagnosing deterioration of an oil-filled transformer, wherein the average polymerization degree estimation model is constructed using a neural network. It is characterized by doing.
According to a fourth aspect of the present invention, there is provided a method for diagnosing deterioration of an oil-filled transformer according to the first or second aspect of the present invention, wherein the average polymerization degree estimation model is determined using a multiple regression equation. It is characterized by building.

  According to the deterioration diagnosis method for an oil-filled transformer of the present invention configured as described above, the average degree of polymerization of insulating paper in the oil-filled transformer can be estimated with sufficiently high accuracy, and the average degree of polymerization of insulating paper can be calculated. The amount of work and cost required for estimation can be reduced.

Hereinafter, an oil-filled transformer deterioration diagnosis method according to an embodiment of the present invention will be described with reference to the drawings.
FIG. 1 shows an example of an oil-filled transformer to which the deterioration diagnosis method according to the embodiment of the present invention can be applied, and FIG. 2 shows a deterioration diagnosis method of the oil-filled transformer according to the embodiment of the present invention. It is shown as a flowchart.
As shown in FIG. 1, the oil-filled transformer 20 is disposed in the substantially cylindrical metal container 22 storing the insulating oil OL therein, and immersed in the insulating oil OL. A coil 24 and a tap changer 26 are provided. A circular inspection window 30 is opened in the top plate portion 23 of the metal container 22, and the inspection window 30 is closed by a lid 28. Here, the metal container 22 and the lid 28 are made of a metal material such as stainless steel or carbon steel, and surface treatment such as rust prevention treatment is performed on the surface portion as necessary.

A primary side bushing 32 and a secondary side bushing 34 are fixed to the outer peripheral side of the inspection window 30 on the top plate portion 23 of the metal container 22. The bushings 32 and 34 are each formed in a cylindrical shape by an insulating material such as ceramic, and are fixed in a state where the lower end side penetrates the top plate portion 23. Terminal members 36 and 38 made of conductive metal pass through the central portions of the bushings 32 and 34. The primary side terminal member 36 is connected to an input terminal (not shown) of the coil 24 through the connection cable 40 and the tap changer 26 in the metal container 22. Further, the secondary side terminal member 38 is connected to an output terminal (not shown) of the coil 24 via a connection cable 42 in the middle of the metal container 22.
Here, the coil 24 includes an iron core made of a silicon steel strip or the like, and insulating paper that insulates the band between the cores (not shown). A tap board (not shown) made of insulating paper is disposed in the tap changer 26, and this tap board insulates a plurality of taps.

  In the metal container 22, a buffer tank 44 storing unused insulating oil OL is disposed on the upper side of the top plate portion 23, and this buffer tank 44 communicates with the inside of the metal container 22 through an oil supply pipe 46. In the oil-filled transformer 20, when the insulating oil OL in the metal container 22 decreases for some reason, the insulating oil OL equal to the decrease amount is replenished from the buffer tank 44 into the metal container 22. Further, a sampling valve 50 is connected to the peripheral wall portion of the metal container 22 through an oil collection pipe 48 on the lower end side thereof. In the oil-filled transformer 20, the insulating oil OL in the metal container 22 is removed by opening the sampling valve 50. Can be collected.

Next, a deterioration diagnosis method according to this embodiment for the oil-filled transformer 20 configured as described above will be described.
The deterioration diagnosis method according to the present embodiment includes a past measurement data input step (S1) relating to the gas in oil in the insulating oil OL, the total acid value, and the withstand voltage, at least when the use of the oil-filled transformer 20 is started and when the use is completed. Measurement data input step (S2) of each measured average polymerization degree, insulation paper polymerization degree (average polymerization degree) estimation model construction step (S3), measurement data input step of oil-filled transformer 20 to be diagnosed (S4) and an average polymerization degree estimation step (S5).

Hereinafter, the contents of the above steps will be described sequentially.
(1) Past measurement data input step concerning oil-in-oil gas, total acid value and withstand voltage in insulating oil OL (S1)
In order to construct a model for estimating the average degree of polymerization of insulating paper of the oil-filled transformer 20 by a neural network, measurement is performed at a predetermined inspection cycle in the past as first learning data (first input factor group) of the estimation model. The measurement data of the gas in the oil of the insulating oil OL, the measurement data of the total acid number, and the measurement data of the withstand voltage are respectively input to a neural network (actually, an arithmetic device or the like programmed with the neural network).

Here, when measuring the gas in oil, the amounts of hydrogen, oxygen, nitrogen, carbon dioxide, carbon monoxide, methane, ethane, ethylene, and acetylene in the insulating oil OL are basically measured. However, it is not always necessary to measure all types of gas in oil listed here, depending on the accuracy required for the estimated value of the average degree of polymerization, appropriately select two or more types of gas from the above gas group, Only two or more selected gases in oil may be measured.
In addition, as a method for measuring the total acid value of the insulating oil OL, for example, a method using a two-layer test solution in which hexane is added to a lower alcohol solution containing methyl red or neutral red and whose pH is constantly adjusted with an alkali, etc. Can be used. The withstand voltage of the insulating oil OL is measured by a known withstand voltage test method for the insulating oil.

(2) Step of inputting measurement data of average polymerization degree measured at least at the start of use and at the end of use of oil-filled transformer 20 (S2)
In order to construct an average polymerization degree estimation model of insulating paper of the oil-filled transformer 20 using a neural network, at least the oil-filled transformer 20 is used as second learning data (second input factor group) of the estimation model. Measurement data of the average degree of polymerization measured at the time of use and when the use is completed is input to the neural network.
Here, in order to increase the accuracy of the estimated value based on the average polymerization degree estimation model, the average polymerization degree of the insulating paper is not only when the oil-filled transformer 20 starts to be used and when the use is completed (generally, when discarded), The measurement is preferably performed once to several times between the start of use and the end of use. However, since the average degree of polymerization of the insulating paper can be measured only when the oil-filled transformer 20 is stopped, if such an opportunity does not exist, at least when the oil-filled transformer 20 is used. If the average degree of polymerization of the insulating paper is measured only when the use is completed, the required accuracy can be basically secured for the estimated value based on the average degree of polymerization estimation model.

(3) Average polymerization degree estimation model construction step (S3)
Each measurement data input in the past measurement data input step (S1) regarding the gas in oil in the insulating oil OL, the total acid value and the withstand voltage and the input step (S2) of the measurement data of the average degree of polymerization of the insulating paper The average polymerization degree estimation model is constructed using a neural network. In this neural network, the average degree of polymerization is used as an output factor among the measurement data described above.

(4) Step of inputting measurement data of oil-filled transformer 20 to be diagnosed (S4)
Next, the first input factor group is input to the average polymerization degree estimation model (learned neural network) for the oil-filled transformer 20 to be diagnosed. Specifically, the latest measurement data relating to various gases in oil, total acid number, and withstand voltage obtained by analyzing the insulating oil OL are respectively input to the average polymerization degree estimation model.
(5) Average polymerization degree estimation step (S5)
The average degree of polymerization corresponding to the measurement data input in the input step (S4) is calculated using an average degree of polymerization estimation model.

Next, the degradation diagnosis method using the neural network according to the present embodiment will be specifically described with reference to FIG.
As an average polymerization degree estimation model, a three-layer neural network was used, and an average polymerization degree estimation model was constructed (first to third layers) by appropriately setting initial values of weight coupling. In the degradation diagnosis method according to the present embodiment, each of a plurality of types of oil-in-gas (in this embodiment, hydrogen, oxygen, nitrogen, carbon dioxide, carbon monoxide, methane, ethane, ethylene, and acetylene) in the insulating oil OL. The measurement data, the measurement data of the total acid value of the insulation oil OL, and the measurement data of the withstand voltage of the insulation oil OL are set as the first input factor group, and are measured at least when the oil-filled transformer 20 is used and when the use is completed. The average polymerization degree estimation model is constructed by learning the model using the measured data of the average polymerization degree as the second input factor group and the average polymerization degree estimated value of the insulating paper in the coil 24 as the output factor. In this average polymerization degree estimation model, the latest measurement data of a plurality of types of oil-in-gas, total acid number and withstand voltage in the oil-filled transformer 20 to be diagnosed are input to the average polymerization degree estimation model. The estimated average polymerization degree of insulating paper in the oil-filled transformer 20 is estimated by the estimation model.

Accordingly, the average polymerization degree of the insulating paper can be sufficiently high enough to input the measurement data of the in-oil gas of the insulating oil OL and the withstand voltage of the total acid value in the oil-filled transformer 20 to the average polymerization degree estimation model. Therefore, the remaining life of the oil-filled transformer 20 can be predicted with sufficient accuracy based on the estimated value of the average degree of polymerization.
According to the deterioration diagnosis method according to the present embodiment described above, the measurement data of the withstand voltage of the in-oil gas and the total acid value of the insulating oil OL, which are periodically measured as part of the maintenance work for the oil-filled transformer 20, are obtained. If each is input to the average polymerization degree estimation model, the average polymerization degree of the insulating paper can be estimated with sufficiently high accuracy, so the measurement of the average polymerization degree of the insulating paper by the polymerization method and the insulation oil OL of the furfural method can be estimated. Compared with the conventional degradation diagnosis method that measures the amount of furfural, the amount of work and cost required to estimate the average degree of polymerization of the insulating paper can be effectively reduced.

  In the degradation diagnosis method of the present embodiment, the amount of furfural of the insulating oil OL measured by the furfural method is not used as an input factor to the neural network, but the first input factor and the second input factor described above are used. In addition, the measurement data of furfural as a third input factor may be input to the neural network to construct an average polymerization degree estimation model. Thereby, it is possible to further improve the estimation accuracy for the average degree of polymerization of the insulating paper.

  In the deterioration diagnosis method of the present embodiment, an average polymerization degree estimation model is constructed using a neural network technique. However, each measurement data of a plurality of types of oil-in-gas in the insulating oil OL, the total acid value of the insulating oil OL. Of the insulation oil OL and the withstand voltage of the insulating oil OL, and at least the average polymerization degree measurement data measured at the start of use and at the end of use of the oil-filled transformer 20, respectively, are processed by multivariate multiple regression analysis and averaged. It goes without saying that the result approximated to the case of using the neural network can be obtained by constructing the polymerization degree estimation model.

It is side surface sectional drawing which shows an example of the oil-filled transformer which can apply the degradation diagnostic method which concerns on embodiment of this invention. It is a flowchart which shows the deterioration diagnostic method which concerns on embodiment of this invention. It is explanatory drawing of the input factor and output factor in the case of constructing an average polymerization degree estimation model by a neural network.

Explanation of symbols

20 Oil-filled transformer 22 Metal container 23 Top plate portion 24 Coil 26 Tap changer 28 Lid 30 Inspection window 32, 34 Bushing 36, 38 Terminal member 40, 42 Connection cable 44 Buffer tank 46 Oil supply pipe 48 Oil sampling piping 50 Sampling valve OL Insulating oil

Claims (4)

A deterioration diagnosis method for an oil-filled transformer having a container and a coil immersed in insulating oil stored in the container,
The measured values of the oil-in-gas, total acid number and withstand voltage for the insulating oil measured at each predetermined inspection cycle are set as the first input factor group,
The measured value of the average degree of polymerization of the insulating paper of the coil measured at the start of use and at the end of use of at least the oil-filled transformer as a second input factor group,
By using the average polymerization degree of the insulating paper as an output factor, identifying or learning the model, a model for estimating the average polymerization degree of the insulating paper is constructed,
The measured values of gas in oil, total acid value and withstand voltage for insulating oil measured from insulating oil in oil-filled transformer to be diagnosed are input to the average polymerization degree estimation model, and averaged by the average polymerization degree estimation model A method for diagnosing deterioration of an oil-filled transformer, wherein an estimated value of a degree of polymerization is obtained.   When measuring gas in oil for insulating oil, it is characterized by measuring two or more kinds of gas in oil selected from the group consisting of hydrogen, oxygen, nitrogen, carbon dioxide, carbon monoxide, methane, ethane, ethylene and acetylene. The deterioration diagnosis method for an oil-filled transformer according to claim 1.   The deterioration diagnosis method for an oil-filled transformer according to claim 1, wherein the average polymerization degree estimation model is constructed using a neural network.   The deterioration diagnosis method for an oil-filled transformer according to claim 1, wherein the average polymerization degree estimation model is constructed using multiple regression analysis.

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