CN116679254A - Voltage transformer initial error calculation method - Google Patents
Voltage transformer initial error calculation method Download PDFInfo
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- CN116679254A CN116679254A CN202310927370.9A CN202310927370A CN116679254A CN 116679254 A CN116679254 A CN 116679254A CN 202310927370 A CN202310927370 A CN 202310927370A CN 116679254 A CN116679254 A CN 116679254A
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- 238000004364 calculation method Methods 0.000 title abstract description 6
- 230000002068 genetic effect Effects 0.000 claims abstract description 10
- 238000005259 measurement Methods 0.000 claims description 22
- 238000000034 method Methods 0.000 claims description 21
- 238000012795 verification Methods 0.000 claims description 15
- 238000006243 chemical reaction Methods 0.000 claims description 9
- 238000005457 optimization Methods 0.000 claims description 8
- 230000009466 transformation Effects 0.000 claims description 4
- 230000035772 mutation Effects 0.000 claims description 3
- 238000010187 selection method Methods 0.000 claims description 3
- 238000012549 training Methods 0.000 description 4
- 238000011156 evaluation Methods 0.000 description 2
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R35/00—Testing or calibrating of apparatus covered by the other groups of this subclass
- G01R35/02—Testing or calibrating of apparatus covered by the other groups of this subclass of auxiliary devices, e.g. of instrument transformers according to prescribed transformation ratio, phase angle, or wattage rating
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/12—Computing arrangements based on biological models using genetic models
- G06N3/126—Evolutionary algorithms, e.g. genetic algorithms or genetic programming
Abstract
The invention discloses a voltage transformer initial error calculation method, which comprises the following steps: collecting primary side voltage and secondary side voltage of each voltage transformer, and establishing an in-phase constraint model and a multiphase constraint model of the voltage transformer; obtaining initial error expression of each channel of the voltage transformer according to the in-phase constraint model and the multi-phase constraint model; constructing an objective function of the initial error, and calculating an optimal value of the objective function by adopting a genetic algorithm; and calculating the initial error value of each channel of the voltage transformer based on the optimized value of the objective function and the initial error expression of each channel of the voltage transformer. The invention solves the technical problem of how to accurately and rapidly calculate the initial error of the voltage transformer and output the result.
Description
Technical Field
The invention relates to the technical field of transformers, in particular to a method for calculating initial errors of a voltage transformer.
Background
Capacitive voltage transformers (Capacitor Voltage Transformer, hereinafter CVT) are widely used in high voltage class applications because of their good insulation properties. Compared with the traditional electromagnetic voltage transformer, the capacitive voltage transformer has more complex structure, and is easier to generate out-of-tolerance phenomenon in the operation process, thereby affecting the fair trade of electric energy settlement. The existing verification mode is offline verification of broken wires, the transformer to be verified and the high-precision standard device apply the same voltage signals at the same time, the difference between the output value of the transformer to be detected and the output value of the standard device is the static error of the transformer, the mode cannot reflect the error dynamic change process of the transformer under the actual working condition in real time, and the power failure maintenance of the high-voltage power transmission and transformation line is difficult.
At present, the online evaluation of the voltage transformer at the current stage is as follows: when the monitor is hung on a net and operates, secondary side data of the transformer are collected, the secondary side data are used as training data, an error evaluation model is built, in the error evaluation stage, the calculated error value is based on the training data, and the final metering error of the transformer is equal to the initial error corresponding to the training data and the subsequently monitored error variation. Therefore, the initial error corresponding to the training data when the power-off verification monitor is hung on the net is an indispensable link, but the power-off verification at the present stage is difficult to realize, the latest off-line verification data is usually replaced, and even an initial error is randomly given to an application scene without off-line verification data, so that the final transformer error assessment result has larger difference. Therefore, it is needed to provide a method for calculating the initial error of the voltage transformer, which solves the technical problem of how to accurately and rapidly calculate the initial error of the voltage transformer and output the result.
Disclosure of Invention
The invention mainly aims to provide a method for calculating initial errors of a voltage transformer, which aims to solve the technical problem of how to accurately and rapidly calculate the initial errors of the voltage transformer and output results.
In order to achieve the above object, the present invention provides a method for calculating an initial error of a voltage transformer, wherein the method for calculating the initial error of the voltage transformer comprises the following steps:
s1, collecting primary side voltage and secondary side voltage of each voltage transformer, and establishing an in-phase constraint model and a multiphase constraint model of the voltage transformer;
s2, obtaining initial error expression of each channel of the voltage transformer according to the in-phase constraint model and the multi-phase constraint model;
s3, constructing an objective function of the initial error, and calculating an optimal value of the objective function by adopting a genetic algorithm;
and S4, calculating initial error values of all channels of the voltage transformer based on the optimal value of the objective function and the initial error expression of all channels of the voltage transformer.
In one preferred scheme, in the step S1, an in-phase constraint model of the voltage transformer is built, specifically:
according to the primary side voltage and the secondary side voltage of each voltage transformer, establishing a conversion relation between the primary side voltage and the secondary side voltage of the voltage transformer;
and establishing a constraint relation between the secondary side voltage and the in-phase error of the voltage transformer with the same voltage class based on the conversion relation between the primary side voltage and the secondary side voltage of the voltage transformer.
In one preferred scheme, the conversion relationship between the primary side voltage and the secondary side voltage of the voltage transformer is as follows:
wherein ,is a secondary side voltage measurement value of the voltage transformer,as a primary side voltage measurement of the voltage transformer,as an error of the voltage transformer,is the rated transformation ratio of the voltage transformer.
One of the preferred schemes, the constraint relation between the secondary side voltage and the in-phase error of the voltage transformer is as follows:
wherein ,is a voltage transformerThe error of the A, B, C phase of (c),is a voltage transformerThe error of the A, B, C phase of (c),is a voltage transformerA, B, C phase secondary side voltage measurements of (c),is a voltage transformerA, B, C phase secondary side voltage measurements of (c).
In one preferred scheme, the step S1 is to build a multiphase constraint model of the voltage transformer, specifically:
wherein ,is a voltage transformerThe error of the A, B, C phase of (c),is a voltage transformerThe error of the A, B, C phase of (c),is a voltage transformerA, B, C phase secondary side voltage measurements of (c),is a voltage transformerA, B, C phase secondary side voltage measurements of (c).
In one of the preferred embodiments, the initial error is expressed as:
wherein ,respectively represent voltage transformersInitial errors of phases a, B, C,respectively represent voltage transformersIs a function of the initial error of the A, B, C phase,，，，，，is that。
In one preferred embodiment, the step S3 constructs an objective function of the initial error, specifically:
and constructing an objective function according to the normal distribution of the offline verification error data of the voltage transformer.
In one of the preferred embodiments, the objective function is:
wherein ,as an objective function of the initial error of the voltage transformer,is that，Is a voltage transformerIs used for the phase-C error of (C),is a voltage transformer、Is used to determine the initial error of (1),and (5) verifying expected values of error data normal distribution for the voltage transformer offline.
In one preferred embodiment, the step S3 calculates an optimal value of the objective function by using a genetic algorithm, specifically:
s31, initializing a population, and setting independent variablesFor randomly generated independent variablesBinary coding is carried out, and the initialization of the population is completed;
s32, iterative optimization, and calculating all independent variables in the populationPerforming iterative optimization to form a new population;
s33, decoding and outputting, wherein when the iteration times of the population reach the iteration threshold, the objective function value is the smallestAnd decoding and outputting the value to obtain an optimal value.
In one preferred embodiment, the step S32 of iterative optimization specifically includes:
calculating all independent variables in a populationUsing a tournament selection method to reserve individuals in the father whose objective function value is less than a first threshold;
independent variable according to crossover probability and mutation probabilityGenetic operator manipulation is performed to form new hybrid or variant offspring individuals and, together with the remaining parents, new populations.
In the technical scheme of the invention, the method for calculating the initial error of the voltage transformer comprises the following steps: collecting primary side voltage and secondary side voltage of each voltage transformer, and establishing an in-phase constraint model and a multiphase constraint model of the voltage transformer; obtaining initial error expression of each channel of the voltage transformer according to the in-phase constraint model and the multi-phase constraint model; constructing an objective function of the initial error, and calculating an optimal value of the objective function by adopting a genetic algorithm; and calculating the initial error value of each channel of the voltage transformer based on the optimal value of the objective function and the initial error expression of each channel of the voltage transformer. The invention solves the technical problem of how to accurately and rapidly calculate the initial error of the voltage transformer and output the result.
According to the invention, the initial error is calibrated without power failure, the initial error expression is obtained by establishing the in-phase and multi-phase constraint models of one side and the secondary side of the voltage transformer, and the initial error value of each channel of the voltage transformer is finally calculated by optimizing through a genetic algorithm, so that the calculation of the initial error of each channel of the voltage transformer is realized.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings may be obtained from the structures shown in these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic diagram of a method for calculating an initial error of a voltage transformer according to an embodiment of the present invention.
The achievement of the object, functional features and advantages of the present invention will be further described with reference to the drawings in connection with the embodiments.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention. All other embodiments, based on the embodiments of the invention, which are apparent to those of ordinary skill in the art without inventive faculty, are intended to be within the scope of the invention.
Furthermore, descriptions such as those referred to as "first," "second," and the like, are provided for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implying an order of magnitude of the indicated technical features in the present disclosure. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature.
Moreover, the technical solutions of the embodiments of the present invention may be combined with each other, but it is necessary to be based on the fact that those skilled in the art can implement the embodiments, and when the technical solutions are contradictory or cannot be implemented, it should be considered that the combination of the technical solutions does not exist, and is not within the scope of protection claimed by the present invention.
Referring to fig. 1, according to an aspect of the present invention, the present invention provides a voltage transformer initial error calculation method, wherein the voltage transformer initial error calculation method includes the steps of:
s1, collecting primary side voltage and secondary side voltage of each voltage transformer, and establishing an in-phase constraint model and a multiphase constraint model of the voltage transformer;
s2, obtaining initial error expression of each channel of the voltage transformer according to the in-phase constraint model and the multi-phase constraint model;
s3, constructing an objective function of the initial error, and calculating an optimal value of the objective function by adopting a genetic algorithm;
and S4, calculating initial error values of all channels of the voltage transformer based on the optimal value of the objective function and the initial error expression of all channels of the voltage transformer.
Specifically, in this embodiment, in the step S1, an in-phase constraint model of the voltage transformer is built, and the aunt transformers are grouped according to the voltage level, specifically:
s11, according to the primary side voltage and the secondary side voltage of each voltage transformer, a conversion relation between the primary side voltage and the secondary side voltage of the voltage transformer is established due to a measurement error necessarily existing in the transformer; the conversion relation between the primary side voltage and the secondary side voltage of the voltage transformer is as follows:
wherein ,is a secondary side voltage measurement value of the voltage transformer,as a primary side voltage measurement of the voltage transformer,as an error of the voltage transformer,the rated transformation ratio of the voltage transformer;
s12, establishing a constraint relation between the secondary side voltage and the in-phase error of the voltage transformer with the same voltage class based on the conversion relation between the primary side voltage and the secondary side voltage of the voltage transformer;
taking two channels of phase a as an example for illustration, there are:
wherein ,respectively, voltage transformerA-phase secondary side voltage measurement and primary side voltageThe measured value is used to determine, for each of the measured values,respectively, voltage transformerA phase a secondary side voltage measurement and a primary side voltage measurement,is a voltage transformerIs used for the phase a error of (c),is a voltage transformerAn error of phase a;
because the primary side voltage of the voltage transformer is relatively stable, namely the voltage transformerAnd voltage transformerIs equal, i.eThe method can obtain:
is a voltage transformerThe error of phase a, which is a small number close to 0, is available in taylor's equation:
then there are:
neglecting the 2 nd order small amount, there are:
the same principle is as follows:
the constraint relation between the secondary side voltage and the in-phase error of the voltage transformer is as follows:
wherein ,is a voltage transformerThe error of the A, B, C phase of (c),is a voltage transformerThe error of the A, B, C phase of (c),is a voltage transformerA, B, C phase secondary side voltage measurements of (c),is a voltage transformerA, B, C phase secondary side voltage measurements of (c).
Specifically, in this embodiment, according to the three-phase relationship, the step S1 establishes a multiphase constraint model of the voltage transformer, and the imbalance of the secondary-side-point aunt of the normally operating voltage transformer changes less in a certain time, specifically:
wherein ,is a voltage transformerThe error of the A, B, C phase of (c),is a voltage transformerThe error of the A, B, C phase of (c),is a voltage transformerA, B, C phase secondary side voltage measurements of (c),is a voltage transformerA, B, C phase secondary side voltage measurements of (c).
Specifically, in this embodiment, the initial error is expressed as:
wherein ,respectively represent voltage transformersInitial errors of phases a, B, C,respectively represent voltage transformersIs a function of the initial error of the A, B, C phase,，，，，，is that。
Specifically, in this embodiment, the step S3 constructs an objective function of the initial error, specifically: according to the normal distribution of the off-line verification error data of the voltage transformer, an objective function is constructed, the off-line verification period of the voltage transformer is 4 years according to the verification regulations of the voltage transformer, a large amount of off-line verification error data of the voltage transformer are counted, the error statistics of the off-line verification error data is compliant with the normal distribution,for the expected value of the normal distribution of the off-line verification error data of the voltage transformer, the error value of the voltage transformer to be evaluated should be close to the off-line verification error dataError expectation value of line statistics; the objective function is:
wherein ,as an objective function of the initial error of the voltage transformer,is that，Is a voltage transformerIs used for the phase-C error of (C),is a voltage transformer、Is used to determine the initial error of (1),and (5) verifying expected values of error data normal distribution for the voltage transformer offline.
Specifically, in this embodiment, the step S3 calculates the optimal value of the objective function by using a genetic algorithm, specifically:
s31, initializing a population, and setting independent variablesFor randomly generated independent variablesBinary coding is carried out to finish the initial populationInitializing; wherein, the parameter settings are as follows: independent variableIs of (1)The objective function isThe invention does not limit the above parameters specifically, and can be set as required, with the population size of 50, the crossover probability of 0.7, the variation probability of 0.01 and the iteration threshold of 100;
s32, iterative optimization, and calculating all independent variables in the populationPerforming iterative optimization to form a new population; the method comprises the following steps:
calculating all independent variables in a populationUsing a tournament selection method to reserve individuals in the father whose objective function value is less than a first threshold; independent variable according to crossover probability and mutation probabilityPerforming genetic operator operation to form new hybrid or variant offspring individuals, and forming a new population together with the reserved father, thereby completing one-time iterative evolution;
s33, decoding and outputting, wherein when the iteration times of the population reach an iteration threshold or meet a convergence condition, the objective function value is the smallest in the population evolved by the last iterationAnd decoding and outputting the value, and outputting the minimum value of the objective function at the same time, thereby obtaining the optimal value.
Specifically, in this embodiment, the initial error value of each channel of the voltage transformer may be calculated by combining the obtained optimal value of the objective function with the initial error expression of each channel of the voltage transformer.
The foregoing description of the preferred embodiments of the present invention should not be construed as limiting the scope of the invention, but rather as utilizing equivalent structural changes made in the description of the present invention and the accompanying drawings or directly/indirectly applied to other related technical fields under the inventive concept of the present invention.
Claims (10)
1. The method for calculating the initial error of the voltage transformer is characterized by comprising the following steps of:
s1, collecting primary side voltage and secondary side voltage of each voltage transformer, and establishing an in-phase constraint model and a multiphase constraint model of the voltage transformer;
s2, obtaining initial error expression of each channel of the voltage transformer according to the in-phase constraint model and the multi-phase constraint model;
s3, constructing an objective function of the initial error, and calculating an optimal value of the objective function by adopting a genetic algorithm;
and S4, calculating initial error values of all channels of the voltage transformer based on the optimal value of the objective function and the initial error expression of all channels of the voltage transformer.
2. The method for calculating the initial error of the voltage transformer according to claim 1, wherein the step S1 of establishing the in-phase constraint model of the voltage transformer specifically comprises:
according to the primary side voltage and the secondary side voltage of each voltage transformer, establishing a conversion relation between the primary side voltage and the secondary side voltage of the voltage transformer;
and establishing a constraint relation between the secondary side voltage and the in-phase error of the voltage transformer with the same voltage class based on the conversion relation between the primary side voltage and the secondary side voltage of the voltage transformer.
3. The method for calculating the initial error of the voltage transformer according to claim 2, wherein the conversion relationship between the primary side voltage and the secondary side voltage of the voltage transformer is:
；
wherein ,for the secondary side voltage measurement of the voltage transformer, < >>For primary side voltage measurement of the voltage transformer, +.>Error of voltage transformer->Is the rated transformation ratio of the voltage transformer.
4. The method for calculating the initial error of the voltage transformer according to claim 2, wherein the constraint relation between the secondary side voltage and the in-phase error of the voltage transformer is:
；
wherein ,is a voltage transformer->A, B, C phase error of>Is a voltage transformer->A, B, C phase error of>Is a voltage transformer->A, B, C phase secondary side voltage measurements of (c),is a voltage transformer->A, B, C phase secondary side voltage measurements of (c).
5. The method for calculating the initial error of the voltage transformer according to claim 2, wherein the step S1 is to build a multiphase constraint model of the voltage transformer, specifically:
；
wherein ,is a voltage transformer->A, B, C phase error of>Is a voltage transformer->A, B, C phase error of>Is a voltage transformer->A, B, C phase secondary side voltage measurement，Is a voltage transformer->A, B, C phase secondary side voltage measurements of (c).
6. The method for calculating an initial error of a voltage transformer according to claim 5, wherein the initial error is expressed as:
；
wherein ,respectively represent voltage transformer->Initial errors of phases A, B, C, < >>Respectively represent voltage transformer->A, B, C phase of (a) initial error, +.>，/>，/>，/>，，/>Is->。
7. The method for calculating initial errors of voltage transformers according to any one of claims 1 to 6, wherein said step S3 constructs an objective function of the initial errors, specifically:
and constructing an objective function according to the normal distribution of the offline verification error data of the voltage transformer.
8. The method for calculating the initial error of the voltage transformer according to claim 7, wherein the objective function is:
；
wherein ,is an objective function of the initial error of the voltage transformer, < >>Is->，/>Is a voltage transformer->Error of phase C, +.>Is of voltageMutual inductor->、/>Is>And (5) verifying expected values of error data normal distribution for the voltage transformer offline.
9. The method for calculating the initial error of the voltage transformer according to claim 8, wherein the step S3 calculates the optimal value of the objective function by using a genetic algorithm, specifically:
s31, initializing a population, and setting independent variablesFor the randomly generated argument +.>Binary coding is carried out, and the initialization of the population is completed;
s32, iterative optimization, and calculating all independent variables in the populationPerforming iterative optimization to form a new population;
s33, decoding and outputting, wherein when the iteration times of the population reach the iteration threshold, the objective function value is the smallestAnd decoding and outputting the value to obtain an optimal value.
10. The method for calculating the initial error of the voltage transformer according to claim 9, wherein the iterative optimization in step S32 is specifically:
calculating the speciesAll arguments in a groupUsing a tournament selection method to reserve individuals in the father whose objective function value is less than a first threshold;
independent variable according to crossover probability and mutation probabilityGenetic operator manipulation is performed to form new hybrid or variant offspring individuals and, together with the remaining parents, new populations.
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