Evaluation method for uneven aging state distribution of oil-immersed transformer

Abstract

The invention discloses a method for evaluating non-uniform aging state distribution of an oil-immersed transformer, which belongs to the technical field of power transformer operation and maintenance, and comprises the following steps of: establishing an axial segmentation evaluation model, setting a dynamic degradation interval, and comparing an actual measurement curve with a calculation data set on the basis of a genetic algorithm, and traversing and optimizing; performing loop iteration in a set degradation interval, and determining an actual axial segmentation proportion; the positioning of axial aging and the quantitative evaluation of the non-uniform aging state distribution of the transformer are realized; the probability of data combination is increased, multi-parameter optimization is carried out on laboratory data based on actually measured data, the insulation state of each insulation layer is inversely solved, and errors possibly generated by temperature, environment and man-made factors of the laboratory data are eliminated.

Description

Technical Field

[0001] The invention belongs to the technical field of power transformer operation and maintenance, and in particular relates to an evaluation method for uneven aging state distribution of an oil-immersed transformer. Background Art

[0002] Oil-immersed transformers play many important roles in the actual operation of power systems, including voltage conversion, isolation protection, harmonic suppression, and long-distance and efficient power transmission. Therefore, they are indispensable key equipment in modern power grids and are crucial to achieving efficient, safe, and reliable power transportation.

[0003] During the operation of oil-immersed transformers, the flow pattern of transformer oil may cause uneven aging of the internal main insulation. Since the flow path of transformer oil may be uneven, there will be a certain area where the oil flow rate is slow or almost stagnant, causing the temperature in this area to be too high compared to other temperatures, forming a hot spot. Under rated operating conditions, the hot spot temperature can reach up to 156°C. High temperature will accelerate the aging of the oil-paper insulation structure and reduce its insulation performance. The hot spot area is the weakest place for the insulation of the oil-immersed transformer, and the insulation state of the hot spot area can represent the overall insulation state of the oil-immersed transformer. Therefore, it is crucial to evaluate the uneven aging insulation state of the oil-immersed transformer.

[0004] Traditional insulation condition assessment methods all assess the transformer as a whole, without considering the uneven aging of the transformer's oil-paper insulation structure, or failing to detect the uneven distribution of the transformer's aging condition, so that the measured data cannot represent the true insulation condition of the transformer.

[0005] Therefore, a new technical solution is urgently needed in the prior art to solve this problem. Summary of the invention

[0006] In order to overcome the deficiencies in the prior art, the present invention provides a method for evaluating the uneven aging state distribution of an oil-immersed transformer, which is used to solve the problem of accurately evaluating the uneven aging state distribution of the transformer.

[0007] In order to achieve the above object, the technical solution adopted by the present invention is: a method for evaluating the uneven aging state distribution of an oil-immersed transformer, comprising the following steps:

[0008] S1. Perform frequency domain dielectric response tests on insulating paperboard samples with different polymerization degrees at different temperatures; perform frequency domain dielectric response tests on insulating oil samples with different aging days at different temperatures;

[0009] S2. Constructing a database of complex relative dielectric constants of insulating paperboards with different polymerization degrees; constructing a database of complex relative dielectric constants of insulating oils with different aging days;

[0010] S3. According to the main insulation structure of the transformer, the capacitance expression of the composite multi-oil channel column main insulation structure as a whole is obtained by using the relationship between capacitance and complex relative dielectric constant;

[0011] S4. According to the structural dimensions and radial insulation layer number of the actual transformer, substitute into the database of S2, and use the permutations function to generate all possible combinations, each of which corresponds to the complex relative dielectric constant of one type of oil and the complex relative dielectric constant of each insulation layer; substitute all the above combinations into the capacitance expression of the composite multi-oil channel column type main insulation structure of S3 as a whole, and obtain the basic database of the equivalent capacitance of the overall transformer; each value in the basic database corresponds to a group of capacitances; the group of capacitances corresponds to the complex relative dielectric constant of one type of oil and the complex relative dielectric constant of each insulation layer;

[0012] S5. measuring the actual transformer loss factor at different frequencies to obtain a database of complex capacitance test values ​​of the actual transformer;

[0013] S6. Set the percentage of the height of the starting point below the actual transformer axial degradation interval to T, the percentage of the degradation interval to S, and the actual transformer complex capacitance test value of S5 to the basic database of transformer equivalent capacitance of S4 based on the genetic algorithm according to the structural size of the transformer and the number of radial insulation layers. Perform traversal optimization, inverse iteratively obtain the average complex relative dielectric constant and average degree of polymerization of each insulation layer, and determine the values ​​of T and S according to the gradient change of the degree of polymerization;

[0014] S7, based on the data of S2 and the values ​​of T and S determined by S6, a database of complex relative dielectric constants considering axial non-uniform aging is established, thereby establishing a capacitance expression considering axial non-uniform aging;

[0015] S8, input the specific geometric parameters and the number of insulation layers of the actual transformer, substitute the database of complex relative dielectric constant of S7 into the basic database of equivalent capacitance of the overall transformer in S4, and construct an extended database of equivalent capacitance of the overall transformer considering axial non-uniform aging;

[0016] S9. According to the complex capacitance test value of the actual transformer of S5, the extended database of the overall transformer equivalent capacitance of S8 is traversed and optimized, and the complex relative dielectric constant distribution matrix at different frequency points is obtained by iterative inversion calculation combined with the genetic algorithm. The distribution matrix is ​​substituted into the database of S2 to obtain the aggregation degree distribution matrix at different frequency points; the arithmetic mean of the elements at the same position of the aggregation degree distribution matrix at different frequency points is calculated to form an aggregation degree distribution matrix.

[0017] The preferred databases of complex relative dielectric constants of S2 are all databases that have undergone frequency-temperature shift processing.

[0018] Each capacitance in the basic database of transformer equivalent capacitance of the preferred S4 is normalized.

[0019] Preferably, the insulating layer described in S4 includes one or more partition-oil gap-strut structural units.

[0020] The specific steps for determining the values ​​of T and S in the preferred S6 are as follows:

[0021] S601, setting a threshold interval of T, when the value of T is at the lower limit of the threshold interval, iterating between samples in the degradation interval S according to the first iteration step length, obtaining a data set of each sample, comparing the data set of each sample with the complex relative dielectric constant of each insulating layer obtained by inversion, traversing and optimizing, taking a group of numbers with the smallest value function value, and obtaining the average degree of polymerization of the corresponding axial segment of each sample;

[0022] S602, calculate the relative error between the degree of aggregation of each sample and the degree of aggregation of the previous sample, and continue the iterative calculation until the maximum threshold of the degradation interval is reached. If the relative error exceeds 6%±0.8%, output the degradation interval value corresponding to the previous sample to determine the actual axial segmentation ratio under the T value;

[0023] S603, T iterates according to the second iteration step within the threshold range set in S601, and iterates from S601 to S602 for each T value; compares the value function value corresponding to each T value, takes the group with the smallest value function value, and finally determines the values ​​of T and S of the measured transformer.

[0024] Through the above design scheme, the present invention can bring the following beneficial effects:

[0025] 1. The inversion method based on genetic algorithm increases the possibility of data combination, and optimizes the laboratory data with multiple parameters based on the measured data, and inversely solves the insulation state of each insulation layer, eliminating the errors that may be caused by temperature, environment and human factors in the laboratory data;

[0026] 2. Establish an axial segmentation evaluation model, set a dynamic degradation interval, and compare the measured curve with the calculated data set based on the genetic algorithm to traverse and find the best solution; iterate within the set degradation interval to determine the actual axial segmentation ratio; realize the positioning of axial aging and the quantitative evaluation of the distribution of uneven aging status of transformers;

[0027] 3. Normalize the data in big data to maximize data expansion and save storage space;

[0028] 4. Construct an equivalent capacitor parallel model of the composite multi-oil channel column main insulation structure, which is different from the evaluation model of the traditional XY model and is more in line with the model of the actual transformer insulation structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 The present invention is a flow chart of a method for evaluating the uneven aging state distribution of an oil-immersed transformer.

[0030] Figure 2 It is a schematic diagram of the axial segmented model structure in an embodiment of a method for evaluating the uneven aging state distribution of an oil-immersed transformer of the present invention.

[0031] Figure 3 This is a comparison diagram of the measurement curve and calculation curve of the loss factor of a 220 kV oil-immersed transformer in an embodiment of a method for evaluating the uneven aging state distribution of an oil-immersed transformer of the present invention. DETAILED DESCRIPTION

[0032] The following is a detailed description of the specific implementation of the present invention in conjunction with the accompanying drawings.

[0033] In order to more clearly illustrate the present invention, the present invention is further described below in conjunction with the preferred embodiments. It should be understood by those skilled in the art. The content described in detail below is illustrative rather than restrictive, and the user may make various changes to the following parameters without departing from the inventive mechanism and scope set forth in the claims. In order to avoid confusing the essence of the present invention, known methods and processes are not described in detail.

[0034] By the attached Figures 1 to 3 As shown: A method for evaluating the uneven aging state distribution of an oil-immersed transformer comprises the following steps:

[0035] S1. Perform frequency domain dielectric response tests on insulating paperboard samples with different polymerization degrees at different temperatures; perform frequency domain dielectric response tests on insulating oil samples with different aging days at different temperatures;

[0036] S2. Constructing a database of complex relative dielectric constants of insulating paperboards with different polymerization degrees; constructing a database of complex relative dielectric constants of insulating oils with different aging days;

[0037] S3. According to the main insulation structure of the transformer, the capacitance expression of the composite multi-oil channel column main insulation structure as a whole is obtained by using the relationship between capacitance and complex relative dielectric constant; the specific derivation is as follows:

[0038] The capacitance expressions and required parameters of the partitions, stays and oil gaps under the composite multi-oil channel column main insulation structure are:

[0039]

[0040] Where r is the inner radius of the high-voltage winding, unit: meter, r0 is the outer radius of the low-voltage winding, unit: meter, and M is the ratio of the difference between the inner radius r of the high-voltage winding and the outer radius r0 of the low-voltage winding to the outer radius r0 of the low-voltage winding.

[0041]

[0042] Where C paper (i) represents the capacitance of the i-th layer of the partition, n is the number of layers of the transformer main insulation structure, ε0 is the vacuum dielectric constant, ε0 = 8.854 × 10 -12 Farad / m, ε b is the relative dielectric constant of the oil-immersed paperboard, unit: Farad / meter, h is the height of the transformer main insulation structure, unit: meter, X is the ratio of the thickness of the brace to the thickness of the partition, M is the ratio of the difference between the inner radius r of the high-voltage winding and the outer radius r0 of the low-voltage winding to the outer radius r0 of the low-voltage winding,

[0043]

[0044] Where W is the length of the brace, unit: meter, r0 is the outer radius of the low-voltage winding, unit: meter, k is the ratio of the brace length W to the outer radius of the low-voltage winding r0,

[0045]

[0046] Where k is the ratio of the length of the brace W to the outer radius r0 of the low-voltage winding, M is the ratio of the difference between the inner radius r of the high-voltage winding and the outer radius r0 of the low-voltage winding to the outer radius r0 of the low-voltage winding, n is the number of layers of the transformer main insulation structure, Y(i) is the ratio of the total length of all braces in the i-th layer to the perimeter of the i-1th layer of the partition,

[0047]

[0048] Where: C ba (i) C oil (i) represents the capacitance of the i-th layer of the stay and the oil gap, respectively; k is the ratio of the stay length W to the outer radius r0 of the low-voltage winding; Y(i) is the ratio of the total length of all stays in the i-th layer to the perimeter of the i-th layer of the partition; n is the number of layers of the transformer main insulation structure; ε0 is the vacuum dielectric constant, ε0 = 8.854 × 10 -12 Farad / m, ε b is the relative dielectric constant of oil-impregnated paperboard, unit: Farad / meter, ε oil is the relative dielectric constant of the oil, unit: Farad / meter, h is the height of the transformer main insulation structure, unit: meter, X is the ratio of the thickness of the brace to the thickness of the partition, M is the ratio of the difference between the inner radius r of the high-voltage winding and the outer radius r0 of the low-voltage winding to the outer radius r0 of the low-voltage winding,

[0049] The equivalent parallel model constructed is to connect the capacitances of each layer of partitions and stays, partitions and oil gaps in series, and then connect the series capacitances in parallel to obtain the parallel equivalent capacitance of each layer. The expression of the equivalent capacitance of each layer is:

[0050]

[0051] Where C paper (i) C ba (i) C oil (i) represents the capacitance of the i-th layer of partition, stay and oil gap, ε b (i) is the relative dielectric constant of the i-th layer of oil-impregnated paperboard, unit: Farad / meter, ε oil (i) is the relative dielectric constant of the i-th layer of oil, unit: Farad / m, h is the height of the transformer main insulation structure, unit: meter, Y(i) is the ratio of the total length of all the struts in the i-th layer to the perimeter of the i-1-th layer of partition, and the expressions of the i-th layer parameters b(i) and d(i) are:

[0052]

[0053] Where X is the ratio of the thickness of the brace to the thickness of the partition, M is the ratio of the difference between the inner radius r of the high-voltage winding and the outer radius r0 of the low-voltage winding to the outer radius r0 of the low-voltage winding, Y(i) is the ratio of the total length of all braces in the i-th layer to the circumference of the i-1-th layer of partition, n is the number of layers of the transformer main insulation structure, ε b (i) is the relative dielectric constant of the i-th layer of oil-impregnated paperboard, unit: Farad / meter, ε oil (i) is the relative dielectric constant of the i-th layer of oil, unit: Farad / meter,

[0054] The equivalent parallel capacitance of each layer is connected in parallel to obtain the equivalent parallel capacitance C of the overall oil-immersed transformer. all :

[0055]

[0056] Where X is the ratio of the thickness of the brace to the thickness of the partition, Y(i) is the ratio of the total length of all the braces in the i-th layer to the perimeter of the i-1-th layer of the partition, n is the number of layers of the transformer main insulation structure, and ε b (i) is the relative dielectric constant of the i-th layer of oil-impregnated paperboard, unit: Farad / meter, ε oil (i) is the relative dielectric constant of the i-th layer of oil, unit: Farad / m, h is the height of the transformer main insulation structure, unit: meter, b(i) and d(i) are two parameters of the i-th layer,

[0057] S4. According to the structural dimensions and radial insulation layer number of the actual transformer, substitute into the database of S2, and use the permutations function to generate all possible combinations, each of which corresponds to the complex relative dielectric constant of one type of oil and the complex relative dielectric constant of each insulation layer; substitute all the above combinations into the capacitance expression of the composite multi-oil channel column type main insulation structure of S3 as a whole, and obtain the basic database of the equivalent capacitance of the overall transformer; each value in the basic database corresponds to a group of capacitances; the group of capacitances corresponds to the complex relative dielectric constant of one type of oil and the complex relative dielectric constant of each insulation layer;

[0058] S5. measuring the actual transformer loss factor at different frequencies to obtain a database of complex capacitance test values ​​of the actual transformer;

[0059] S6. Set the percentage of the height of the starting point below the actual transformer axial degradation interval to T, the percentage of the degradation interval to S, and the actual transformer complex capacitance test value of S5 to the basic database of transformer equivalent capacitance of S4 based on the genetic algorithm according to the structural size of the transformer and the number of radial insulation layers. Perform traversal optimization, inverse iteratively obtain the average complex relative dielectric constant and average degree of polymerization of each insulation layer, and determine the values ​​of T and S according to the gradient change of the degree of polymerization;

[0060] S7, based on the data of S2 and the values ​​of T and S determined by S6, a database of complex relative dielectric constants considering axial non-uniform aging is established, thereby establishing a capacitance expression considering axial non-uniform aging;

[0061] S8, input the specific geometric parameters and the number of insulation layers of the actual transformer, substitute the database of complex relative dielectric constant of S7 into the basic database of equivalent capacitance of the overall transformer in S4, and construct an extended database of equivalent capacitance of the overall transformer considering axial non-uniform aging;

[0062] S9. According to the complex capacitance test value of the actual transformer of S5, the extended database of the overall transformer equivalent capacitance of S8 is traversed and optimized, and the complex relative dielectric constant distribution matrix at different frequency points is obtained by iterative inversion calculation combined with the genetic algorithm. The distribution matrix is ​​substituted into the database of S2 to obtain the aggregation degree distribution matrix at different frequency points; the arithmetic mean of the elements at the same position of the aggregation degree distribution matrix at different frequency points is calculated to form an aggregation degree distribution matrix.

[0063] Furthermore, the databases of complex relative dielectric constants of S2 are all databases that have undergone frequency-temperature shift processing.

[0064] In order to further expand the data to the greatest extent and save storage space, each capacitor in the basic database of S4's transformer equivalent capacitance is normalized. The specific formula is as follows:

[0065]

[0066] In the formula, C all is the equivalent parallel capacitance of the overall oil-immersed transformer, unit: Farad; C0 is the equivalent parallel capacitance of the overall oil-immersed transformer under vacuum conditions, unit: Farad; ε0 is the vacuum dielectric constant, ε0 = 8.854 × 10 -12 Farad / meter, h is the height of the transformer main insulation structure, unit: meter,

[0067] Further, the insulating layer described in S4 includes one or more partition-oil gap-support bar structural units.

[0068] Further, the specific steps of determining the values ​​of T and S in S6 are as follows:

[0069] S601, setting a threshold interval of T, when the value of T is at the lower limit of the threshold interval, iterating between samples in the degradation interval S according to the first iteration step length, obtaining a data set of each sample, comparing the data set of each sample with the complex relative dielectric constant of each insulating layer obtained by inversion, traversing and optimizing, taking a group of numbers with the smallest value function value, and obtaining the average degree of polymerization of the corresponding axial segment of each sample;

[0070] S602, calculate the relative error between the degree of aggregation of each sample and the degree of aggregation of the previous sample, and continue the iterative calculation until the maximum threshold of the degradation interval is reached. If the relative error exceeds 6%±0.8%, output the degradation interval value corresponding to the previous sample to determine the actual axial segmentation ratio under the T value;

[0071] S603, T iterates according to the second iteration step within the threshold range set in S601, and iterates from S601 to S602 for each T value; compares the value function value corresponding to each T value, takes the group with the smallest value function value, and finally determines the values ​​of T and S of the measured transformer.

[0072] In the specific implementation, multiple oil-paper insulation samples and oil samples were thermally aged under laboratory conditions to obtain oil-paper insulation samples and oil samples with different aging degrees; the selected test temperatures were: -30°C, -10°C, 10°C, 30°C, 60°C, 90°C, and different aging degrees were selected with a polymerization degree range of 1002-342, an interval of 5, and oil samples with the same aging days. The measured transformer is a 220kV oil-immersed transformer, and its internal main insulation structure has 9 partition-oil gap-strut structure units. The transformer geometric parameters are: main insulation height 400mm, main insulation low-voltage winding outer radius 350mm, main insulation high-voltage winding outer radius 422mm, and strut thickness 8mm. In order to simplify the calculation process and make the calculation faster, in this embodiment, every 3 partition-oil gap-strut structure units are made into one layer, and are divided into three layers in the radial direction, so the whole is divided into a 3*3 distribution matrix for evaluation.

[0073] The dielectric loss factor curve of a 220 kV oil-immersed transformer was measured. The actual temperature was 26 degrees Celsius. The measured curve, the curve calculated by the patent and the curve calculated by the traditional evaluation method are as follows: Figure 3 The frequency range of the curve is: 1000, 470, 220, 110, 70, 40, 20, 10, 4.6, 2.2, 1, 0.46, 0.22, 0.1, 0.046, 0.022, 0.01, 0.0046, 0.0022, 0.001.

[0074] Input the number of insulation layers and geometric parameters of the transformer. Submit the oil-paper insulation samples and oil samples of different aging degrees into the permutations function to generate 20 lines of 17689 30 Column combination, bring all combinations into the S3 composite multi-oil channel column type main insulation structure equivalent capacitance parallel model, obtain the data set of equivalent capacitance of the whole transformer, normalize each capacitance of the data set, and build a large database of the overall capacitance of the transformer; read the measured transformer curve, compare all capacitance values ​​of the curve with the database, and continuously select the global optimal solution through the genetic algorithm to invert a set of numbers with the minimum value function value. The value function expression is:

[0075] F=min{(y 实际 -y 计算 )}

[0076] In the formula, F is the cost function, which represents the minimum error between the calculated curve and the measured curve after N traversals. The smaller the cost function value, the closer it is to the measured curve. The closer the calculated degree of polymerization and moisture content are to the measured ones, the better the data match. 实际 Indicates the measured value at a certain frequency point. 计算 Indicates the calculated value at a certain frequency point.

[0077] Set the percentage of the height of the starting point below the actual transformer axial degradation interval to T, the threshold interval of T to 80% to 90%, the second iteration step to 1%, the range of the degradation interval S corresponding to each T is between 1% and 4%, the first iteration step is 0.5%, and the iteration cycle is seven times; bring the data of S2 into the axial segmented model expression, and repeat the above iterations; the data set obtained by each sample is compared with the complex dielectric constant of each layer inverted to traverse and optimize, and take the set of numbers with the smallest value function value. The relative error of the degree of aggregation calculated for all samples does not exceed 6% ± 0.8%, and the dynamic degradation percentage of the transformer is determined to be T = 88%, and the actual degradation range is S = 4%;

[0078] The complex relative permittivity expression of the axial segmented model is determined as:

[0079] ε b =8%ε r (a)+4ε r (b) +88%ε r (c)

[0080] Substitute the data of S2 into the above expression, and then substitute the capacitance expression of the composite multi-oil channel column main insulation structure in S3, and normalize the obtained capacitance to build a 3*3 capacitance database; then compare the measured curve with this capacitance database with a matrix dimension of 3*3, and continuously select the global optimal solution through the genetic algorithm to invert a set of numbers with the smallest value function value, which are the complex relative dielectric constant and polymerization degree values ​​of the three layers and three segments of each layer at each frequency point;

[0081] To simplify the calculation, take 5 frequency points as an example:

[0082] The calculation results of the distribution matrix of complex relative dielectric constant at different frequency points are as follows:

[0083] 220Hz:

[0084]

[0085] 110Hz:

[0086]

[0087] 40Hz:

[0088]

[0089] 0.22Hz:

[0090]

[0091] 0.01Hz:

[0092]

[0093] According to the data of S2, the aggregation degree distribution matrix of different frequency points is obtained as follows:

[0094] 220Hz:

[0095]

[0096] 110Hz:

[0097]

[0098] 40Hz:

[0099]

[0100] 0.22Hz:

[0101]

[0102] 0.01Hz:

[0103]

[0104] The arithmetic mean of the elements at the same position of the aggregation degree distribution matrix at different frequency points is calculated to form an aggregation degree distribution matrix as follows:

[0105]

[0106] The minimum aggregation degree was screened out to be 763, which is the aggregation degree value of the most seriously aged part of the transformer, and can be used to evaluate the actual aging insulation state of the transformer and the quantitative evaluation of the distribution of the uneven aging state of the transformer.

[0107] The traditional evaluation method that does not consider the specific inversion process of the axial segmentation evaluation model is to grid the transformer segmentation. The evaluation process is based on the iterative calculation of the XY model, and does not consider the impact of the axial segmentation ratio on uneven aging, and cannot locate the location where the actual aging is the most serious. The minimum degree of aggregation obtained by the traditional evaluation method is 831. The comparison between the calculated curve and the measured curve is shown in the figure below. Figure 3 In comparison, the inversion positioning segmentation method proposed in the present invention is more accurate in evaluation.

[0108] Obviously, the above described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0109] The above mainly introduces the solution of the embodiment of the present application from the perspective of the execution process of the method side. It can be understood that in order to implement the above functions, the network device includes a hardware structure and / or software module corresponding to each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiment provided in this article,

[0110] The present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is performed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present application.

[0111] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or all or part of the technical solution, can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or TRP, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

Claims

1. A method for evaluating the uneven aging state distribution of an oil-immersed transformer, characterized in that: The steps include: S1. Perform frequency domain dielectric response tests on insulating paperboard samples with different polymerization degrees at different temperatures; perform frequency domain dielectric response tests on insulating oil samples with different aging days at different temperatures; S2. Constructing a database of complex relative dielectric constants of insulating paperboards with different polymerization degrees; constructing a database of complex relative dielectric constants of insulating oils with different aging days; S3. According to the main insulation structure of the transformer, the capacitance expression of the composite multi-oil channel column main insulation structure as a whole is obtained by using the relationship between capacitance and complex relative dielectric constant; S4. According to the structural dimensions and radial insulation layer number of the actual transformer, substitute into the database of S2, and use the permutations function to generate all possible combinations, each of which corresponds to the complex relative dielectric constant of one type of oil and the complex relative dielectric constant of each insulation layer; substitute all the above combinations into the capacitance expression of the composite multi-oil channel column type main insulation structure of S3 as a whole, and obtain the basic database of the equivalent capacitance of the overall transformer; each value in the basic database corresponds to a group of capacitances; the group of capacitances corresponds to the complex relative dielectric constant of one type of oil and the complex relative dielectric constant of each insulation layer; S5. measuring the actual transformer loss factor at different frequencies to obtain a database of complex capacitance test values ​​of the actual transformer; S6. Set the percentage of the height of the starting point below the actual transformer axial degradation interval to T, the percentage of the degradation interval to S, and the actual transformer complex capacitance test value of S5 to the basic database of transformer equivalent capacitance of S4 based on the genetic algorithm according to the structural size of the transformer and the number of radial insulation layers. Perform traversal optimization, inverse iteratively obtain the average complex relative dielectric constant and average degree of polymerization of each insulation layer, and determine the values ​​of T and S according to the gradient change of the degree of polymerization; S7, based on the data of S2 and the values ​​of T and S determined by S6, a database of complex relative dielectric constants considering axial non-uniform aging is established, thereby establishing a capacitance expression considering axial non-uniform aging; S8, input the specific geometric parameters and the number of insulation layers of the actual transformer, substitute the database of complex relative dielectric constant of S7 into the basic database of equivalent capacitance of the overall transformer in S4, and construct an extended database of equivalent capacitance of the overall transformer considering axial non-uniform aging; S9. According to the complex capacitance test value of the actual transformer of S5, the extended database of the overall transformer equivalent capacitance of S8 is traversed and optimized, and the complex relative dielectric constant distribution matrix at different frequency points is obtained by iterative inversion calculation combined with the genetic algorithm. The distribution matrix is ​​substituted into the database of S2 to obtain the aggregation degree distribution matrix at different frequency points; the arithmetic mean of the elements at the same position of the aggregation degree distribution matrix at different frequency points is calculated to form an aggregation degree distribution matrix.

2. The method for evaluating the uneven aging state distribution of an oil-immersed transformer according to claim 1, characterized in that: The databases of complex relative dielectric constants of S2 are all processed by frequency-temperature translation.

3. The method for evaluating the uneven aging state distribution of an oil-immersed transformer according to claim 1, characterized in that: Each capacitance in the basic database of S4's transformer equivalent capacitance is normalized.

4. The method for evaluating the uneven aging state distribution of an oil-immersed transformer according to claim 1, characterized in that: The insulating layer described in S4 includes one or more partition-oil gap-support bar structural units.

5. The method for evaluating the uneven aging state distribution of an oil-immersed transformer according to claim 1, characterized in that: The specific steps of determining the values ​​of T and S in S6 are as follows: S601, setting a threshold interval of T, when the value of T is at the lower limit of the threshold interval, iterating between samples in the degradation interval S according to the first iteration step length, obtaining a data set of each sample, comparing the data set of each sample with the complex relative dielectric constant of each insulating layer obtained by inversion, traversing and optimizing, taking a group of numbers with the smallest value function value, and obtaining the average degree of polymerization of the corresponding axial segment of each sample; S602, calculate the relative error between the degree of aggregation of each sample and the degree of aggregation of the previous sample, and continue the iterative calculation until the maximum threshold of the degradation interval is reached. If the relative error exceeds 6%±0.8%, output the degradation interval value corresponding to the previous sample to determine the actual axial segmentation ratio under the T value; S603, T iterates according to the second iteration step within the threshold range set in S601, and iterates from S601 to S602 for each T value; compares the value function value corresponding to each T value, takes the group with the smallest value function value, and finally determines the values ​​of T and S of the measured transformer.

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