Voltage transformer measurement error and uncertainty online evaluation method and system

Abstract

The application discloses a kind of voltage transformer measurement error and uncertainty online evaluation method and system, its method includes: the error correlation model between the two voltage transformers connected by overhead transmission line in transformer substation is constructed;Calibrated mutual inductor error distribution is input to the error correlation model, and the error distribution of uncalibrated voltage transformer is obtained based on Monte Carlo method;The measurement error and uncertainty of uncalibrated voltage transformer are obtained by optimal estimation to the error distribution of uncalibrated voltage transformer based on Bayesian fusion method.Based on the above data processing procedure, the application realizes the modeling and evaluation of mutual inductor measurement error and uncertainty, and is beneficial to the security and stability of power system and the fairness and justice of electric energy trade.

Description

Technical Field

[0001] This invention relates to the field of power transmission equipment condition assessment and online monitoring, and in particular to a method and system for online assessment of measurement errors and uncertainties of voltage transformers. Background Technology

[0002] Voltage transformers are responsible for proportionally transforming primary electrical signals into measurable secondary signals, and are the core components for realizing power metering and state estimation. Due to the influence of factors such as electromagnetic fields, temperature, and humidity, transformers may exhibit measurement errors. On the one hand, limited by the reliability requirements of power systems and engineering constraints, in practical scenarios, only a small number of transformers can be verified using a comparative method with standard transformers under power outage conditions to obtain estimates of their measurement errors and uncertainties. On the other hand, the measurement accuracy of transformers directly affects the safety and stability of the power system and the fairness of power trading; therefore, strict requirements are placed on the accuracy of their measurement error assessment.

[0003] Existing methods primarily focus on online assessment of voltage transformer errors, neglecting the need for uncertainty assessment. Therefore, there is an urgent need for an online assessment method for the measurement errors and uncertainties of voltage transformers in power systems. Summary of the Invention

[0004] This invention provides an online evaluation method and system for measurement errors and uncertainties of voltage transformers, which solves the problems that existing online methods for voltage transformer calibration neglect uncertainty evaluation, and that traditional power outage verification methods are labor-intensive, resource-intensive, and have poor real-time performance.

[0005] Firstly, a method for online evaluation of measurement error and uncertainty of voltage transformers is provided, including:

[0006] Construct an error correlation model between two voltage transformers connected by an overhead transmission line in a substation;

[0007] The calibrated transformer error distribution is input into the error correlation model, and the uncalibrated voltage transformer error distribution is obtained based on the Monte Carlo method.

[0008] The error distribution of the uncalibrated voltage transformer is optimally estimated based on the Bayesian fusion method, and the measurement error and uncertainty of the uncalibrated voltage transformer are obtained.

[0009] In some embodiments, constructing an error correlation model between two voltage transformers connected by an overhead transmission line in a substation includes:

[0010] Based on the symmetric component method, the three-phase transmission network of the substation is equivalent to three independent positive, negative and zero-sequence lumped parameter networks under steady state, and the corresponding positive, negative and zero-sequence network power flow equations are constructed for the positive, negative and zero-sequence lumped parameter networks respectively.

[0011] The least squares algorithm is used to solve the positive-sequence correction coefficient, negative-sequence correction coefficient, and zero-sequence correction coefficient of the uncalibrated voltage transformer in the positive, negative, and zero-sequence network power flow equations after dimension expansion.

[0012] The three-phase electrical quantities of the three-phase transmission network are decoupled into positive and negative zero-sequence components using a decoupling model. The positive and negative zero-sequence components include the positive sequence correction coefficient of the uncalibrated voltage transformer, the negative sequence correction coefficient of the uncalibrated voltage transformer, and the zero sequence correction coefficient of the uncalibrated voltage transformer.

[0013] The decoupling process is solved using the least squares algorithm to obtain the three-phase correction coefficients of the uncalibrated voltage transformer;

[0014] The three-phase phase error and three-phase phase angle error of the uncalibrated voltage transformer are obtained based on the three-phase correction coefficient of the uncalibrated voltage transformer.

[0015] In some embodiments, constructing corresponding positive, negative, and zero-order network power flow equations for the positive, negative, and zero-order lumped parameter networks respectively includes:

[0016] The power flow equations for the orthogonal network are shown below:

[0017]

[0018] In the formula, These are unmarked positive sequence voltage measurements; The current is the positive sequence measurement value without marking. These are the marked positive sequence voltage measurements; The current positive sequence measurement value has been marked; This is the positive-sequence series impedance of the transmission line; Represents the positive-sequence parallel admittance of the transmission line; For unmarked voltage transformers, the positive sequence correction coefficient is used. For unmarked current transformers, the positive sequence correction coefficient is used. For the positive sequence correction coefficient of the marked voltage transformer; For the positive sequence correction coefficient of the marked current transformer;

[0019] The power flow equations for the negative-order network are shown below:

[0020]

[0021] In the formula, These are unmarked negative sequence voltage measurements; The current is an unmarked negative sequence measurement. These are the marked negative sequence voltage measurements; The current negative sequence measurement value has been marked; This is the negative sequence series impedance of the transmission line; Represents the negative-sequence parallel admittance of the transmission line; For unmarked voltage transformers, the negative sequence correction coefficient is used. For unmarked current transformers, the negative sequence correction coefficient is used. For the negative sequence correction coefficient of the marked voltage transformer; For the marked negative sequence correction coefficient of the current transformer;

[0022] The power flow equations for the zero-order network are as follows:

[0023]

[0024] In the formula, This is an unmarked zero-sequence voltage measurement. This is an unmarked zero-sequence current measurement. The zero-sequence voltage measurement value has been marked. The zero-sequence current measurement value has been marked. This is the zero-sequence series impedance of the transmission line; This is the zero-sequence parallel admittance of the transmission line; This refers to the zero-sequence correction coefficient for unmarked voltage transformers. This refers to the zero-sequence correction coefficient for unmarked current transformers. The zero-sequence correction coefficient for the marked voltage transformer; This is the zero-sequence correction coefficient for the marked current transformer.

[0025] In some embodiments, the method for decoupling the three-phase electrical quantities of a three-phase transmission network into positive and negative zero-sequence components using a decoupling model is shown in the following equation:

[0026]

[0027] Among them, the decoupling model is: ;

[0028] In the formula, , , These are the measured values ​​of the uncalibrated three-phase voltages A, B, and C. , , These are the three-phase correction coefficients for uncalibrated voltage transformers A, B, and C, respectively. For unmarked voltage transformers, the positive sequence correction coefficient is used. These are unmarked positive sequence voltage measurements; For unmarked voltage transformers, the negative sequence correction coefficient is used. These are unmarked negative sequence voltage measurements; This refers to the zero-sequence correction coefficient for unmarked voltage transformers. These are unmarked zero-sequence voltage measurements.

[0029] In some embodiments, the method for obtaining the three-phase phase value error and three-phase phase angle error of the uncalibrated voltage transformer based on the three-phase correction coefficient of the uncalibrated voltage transformer is shown in the following formula:

[0030]

[0031] In the formula, The error is due to the A-component ratio of the uncalibrated voltage transformer. The error is due to the ratio of the uncalibrated voltage transformer B. This refers to the C-component ratio error of the uncalibrated voltage transformer; The phase angle error of phase A of the uncalibrated voltage transformer; The phase angle error of phase B of the uncalibrated voltage transformer; This refers to the phase angle error of the C-phase of an uncalibrated voltage transformer. To determine the phase angle.

[0032] In some embodiments, the step of inputting the calibrated transformer error distribution into the error correlation model and obtaining the uncalibrated voltage transformer error distribution based on the Monte Carlo method includes:

[0033] Error distribution of calibrated current transformers A set of sample values ​​is extracted from the model and input into the error correlation model. A set of error estimates for uncalibrated voltage transformers is output. The set of error estimates for uncalibrated voltage transformers includes a set of three-phase phase value errors and three-phase phase angle errors.

[0034] Repeat the input-output operation on the error correlation model M times, and fit any set of ratio errors or any set of phase angle errors in the M sets of uncalibrated voltage transformer error estimates to obtain... Error distribution of uncalibrated voltage transformers corresponding to calibrated voltage transformers ;

[0035] In the formula, This represents the average error of the calibrated current transformers. The standard deviation of the calibrated current transformer error; For the first i The average error of an uncalibrated voltage transformer corresponding to a calibrated voltage transformer; For the first iThe standard deviation of the error of an uncalibrated voltage transformer corresponding to a calibrated voltage transformer.

[0036] In some embodiments, the method for optimally estimating the error distribution of the uncalibrated voltage transformer based on the Bayesian fusion method to obtain the measurement error and uncertainty of the uncalibrated voltage transformer is shown in the following formula:

[0037]

[0038] In the formula, For measurement error of uncalibrated voltage transformers; 2 times This represents the uncertainty of an uncalibrated voltage transformer.

[0039] Secondly, an online evaluation system for measurement error and uncertainty of voltage transformers is provided, including:

[0040] The error correlation model construction module is used to construct an error correlation model between two voltage transformers connected by an overhead transmission line in a substation.

[0041] The uncalibrated error distribution calculation module is communicatively connected to the error correlation model construction module. It is used to input the calibrated transformer error distribution into the error correlation model and obtain the uncalibrated voltage transformer error distribution based on the Monte Carlo method; and...

[0042] The error and uncertainty calculation module is communicatively connected to the uncalibrated error distribution calculation module. It is used to perform optimal estimation of the error distribution of the uncalibrated voltage transformer based on the Bayesian fusion method, so as to obtain the measurement error and uncertainty of the uncalibrated voltage transformer.

[0043] Thirdly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the online evaluation method for voltage transformer measurement error and uncertainty as described above.

[0044] Fourthly, embodiments of the present invention provide an electronic device, including a storage medium, a processor, and a computer program stored in the storage medium and executable on the processor, characterized in that, when the processor runs the computer program, it implements the online evaluation method for voltage transformer measurement error and uncertainty as described above.

[0045] Compared with existing technologies, the advantages of this invention are as follows: It constructs an error correlation model to describe the error correlation between voltage transformers in two substations connected by transmission lines; it proposes a measurement error distribution propagation method, calculating the error distribution of uncalibrated voltage transformers based on the error distribution of calibrated transformers and combined with the Monte Carlo method; and it utilizes a Bayesian fusion method to optimally estimate the error distribution of uncalibrated voltage transformers. This solves the problem of online assessment of measurement errors and uncertainties of voltage transformers, not only reducing the consumption of manpower and resources under power outage verification mode, but also realizing real-time online sensing of the metering performance of voltage transformers, effectively ensuring the safe and reliable operation of the power system. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the substation topology of the present invention;

[0047] Figure 2 This is a flowchart illustrating an online evaluation method for measurement error and uncertainty of a voltage transformer according to the present invention.

[0048] Figure 3 This is a schematic diagram of the structure of an online evaluation system for measurement error and uncertainty of a voltage transformer according to the present invention. Detailed Implementation

[0049] Referring now to specific embodiments of the invention, examples of which are illustrated in the accompanying drawings. Although the invention will be described in conjunction with specific embodiments, it will be understood that it is not intended to limit the invention to the described embodiments. Rather, it is intended to cover variations, modifications, and equivalents included within the spirit and scope of the invention as defined by the appended claims. It should be noted that the method steps described herein can be implemented by any functional block or functional arrangement, and any functional block or functional arrangement can be implemented as a physical entity or a logical entity, or a combination of both.

[0050] To enable those skilled in the art to better understand the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0051] Note: The examples described below are merely specific examples and are not intended to limit the embodiments of the present invention to the specific steps, values, conditions, data, order, etc. Those skilled in the art can utilize the concept of the present invention to construct more embodiments not mentioned herein by reading this specification.

[0052] Please see Figure 1In this embodiment of the invention, the voltage transformers are installed on the busbar within the substation. Multiple sites with calibrated voltage transformers are connected to one site with an uncalibrated voltage transformer via an overhead transmission line, with current transformers deployed at both ends of the overhead transmission line. The overhead transmission line is connected to the busbar.

[0053] Please see Figure 2 The present invention provides a flowchart illustrating an online evaluation method for measurement errors and uncertainties of voltage transformers. The method includes:

[0054] Step S100: Construct an error correlation model between two voltage transformers connected by an overhead transmission line in a substation, including:

[0055] Step S110: Based on the symmetric component method, the three-phase transmission network of the substation is equivalent to three independent positive, negative and zero-sequence lumped parameter networks in steady state, and the corresponding positive, negative and zero-sequence network power flow equations are constructed for the positive, negative and zero-sequence lumped parameter networks respectively.

[0056] Step S120: Solve the positive-sequence correction coefficient, negative-sequence correction coefficient, and zero-sequence correction coefficient of the uncalibrated voltage transformer in the positive, negative, and zero-sequence network power flow equations after dimension expansion based on the least squares algorithm.

[0057] Specifically, in this embodiment, assuming the error parameters of the labeled current transformer are known, the current transformer error can be described by the correction coefficient or the ratio difference and angle difference, and their relationship is as follows:

[0058] Equation (1)

[0059] In the formula, For mutual inductor correction coefficients, For the ratio difference of the mutual inductor, This refers to the angle difference of the mutual inductors. The deviation between the measured value and the relative true value of the current transformer can be described as follows:

[0060] Equation (2)

[0061] in, Represents the true value of voltage or current. This represents the measured value of a voltage or current transformer.

[0062] First, based on the symmetrical component method, the three-phase transmission network can be equivalent to the superposition of positive, negative, and zero-sequence lumped parameter networks that do not affect each other under steady state.

[0063] In a positive-order network, the power flow equations for the positive-order network to be solved can be constructed based on the power flow equations, as shown below:

[0064] Equation (3)

[0065] In the formula, These are unmarked positive sequence voltage measurements; The current is the positive sequence measurement value without marking. These are the marked positive sequence voltage measurements; The current positive sequence measurement value has been marked; This is the positive-sequence series impedance of the transmission line; Represents the positive-sequence parallel admittance of the transmission line; For unmarked voltage transformers, the positive sequence correction coefficient is used. For unmarked current transformers, the positive sequence correction coefficient is used. For the positive sequence correction coefficient of the marked voltage transformer; The positive sequence correction coefficient for the marked current transformer is given; all variables in the formula are phasors.

[0066] Equation (3) is In the form of, , A matrix consisting of known quantities. A matrix consisting of unknowns. For... Data collected at each moment, The dimension is expanded to , The dimension is expanded to The extended (3) can be solved using least squares to obtain the solution. .

[0067] Correspondingly,

[0068] Equation (4)

[0069] In negative-order networks, the power flow equations for the negative-order network to be solved can be constructed based on the power flow equations, as shown below:

[0070] Equation (5)

[0071] In the formula, These are unmarked negative sequence voltage measurements; The current is an unmarked negative sequence measurement. These are the marked negative sequence voltage measurements; The current negative sequence measurement value has been marked; This is the negative sequence series impedance of the transmission line; Represents the negative-sequence parallel admittance of the transmission line; For unmarked voltage transformers, the negative sequence correction coefficient is used. For unmarked current transformers, the negative sequence correction coefficient is used. For the negative sequence correction coefficient of the marked voltage transformer; The negative sequence correction coefficient for the marked current transformer is given; all variables in the formula are phasors.

[0072] Equation (5) is In the form of, , A matrix consisting of known quantities. A matrix consisting of unknowns. For... Data collected at each moment, The dimension is expanded to , The dimension is expanded to The extended (5) can be solved using least squares to obtain the solution. .

[0073] Correspondingly,

[0074] Equation (6)

[0075] In zero-order networks, the power flow equations to be solved can be constructed based on the power flow equations, as shown below:

[0076] Equation (7)

[0077] In the formula, This is an unmarked zero-sequence voltage measurement. This is an unmarked zero-sequence current measurement. The zero-sequence voltage measurement value has been marked. The zero-sequence current measurement value has been marked. This is the zero-sequence series impedance of the transmission line; This is the zero-sequence parallel admittance of the transmission line; This refers to the zero-sequence correction coefficient for unmarked voltage transformers. This refers to the zero-sequence correction coefficient for unmarked current transformers. The zero-sequence correction coefficient for the marked voltage transformer; The zero-sequence correction coefficient for the marked current transformer is given; all variables in the formula are phasors.

[0078] Equation (7) is In the form of, , A matrix consisting of known quantities. A matrix consisting of unknowns. For... Data collected at each moment, The dimension is expanded to , The dimension is expanded to The extended (7) can be solved using least squares to obtain the solution. .

[0079] Correspondingly,

[0080] Equation (8)

[0081] Step S130: The three-phase electrical quantities of the three-phase transmission network are decoupled into positive and negative zero-sequence components using a decoupling model. The positive and negative zero-sequence components include the positive sequence correction coefficient of the uncalibrated voltage transformer, the negative sequence correction coefficient of the uncalibrated voltage transformer, and the zero sequence correction coefficient of the uncalibrated voltage transformer.

[0082] Specifically, in this embodiment, the decoupling model is defined as follows:

[0083] Equation (9)

[0084] The purpose of the decoupling model is to decouple three-phase electrical quantities into positive and negative zero-sequence components. Therefore:

[0085] Equation (10)

[0086] In the formula, , , These are the measured values ​​of the uncalibrated three-phase voltages A, B, and C. , , These are the three-phase correction coefficients for uncalibrated voltage transformers A, B, and C, respectively. For unmarked voltage transformers, the positive sequence correction coefficient is used. These are unmarked positive sequence voltage measurements; For unmarked voltage transformers, the negative sequence correction coefficient is used. These are unmarked negative sequence voltage measurements; This refers to the zero-sequence correction coefficient for unmarked voltage transformers. These are unmarked zero-sequence voltage measurements.

[0087] against Data collected at each moment, The dimension is expanded to , The dimension is expanded to .

[0088] Step S140: Solve the decoupling process, i.e., equation (10), based on the least squares algorithm to obtain the three-phase correction coefficients of the uncalibrated voltage transformer;

[0089] Step S150, the method for obtaining the three-phase phase value error and three-phase phase angle error of the uncalibrated voltage transformer according to the three-phase correction coefficient of the uncalibrated voltage transformer and formula (1) is as follows:

[0090] Equation (11)

[0091] In the formula, The error is due to the A-component ratio of the uncalibrated voltage transformer. The error is due to the ratio of the uncalibrated voltage transformer B. This refers to the C-component ratio error of the uncalibrated voltage transformer; The phase angle error of phase A of the uncalibrated voltage transformer; The phase angle error of phase B of the uncalibrated voltage transformer; This refers to the phase angle error of the C-phase of an uncalibrated voltage transformer. To determine the phase angle.

[0092] In summary, the error correlation between voltage transformers in two substations connected by a transmission line can be expressed as follows:

[0093] Equation (12)

[0094] in, This indicates the error of an uncalibrated voltage transformer. H represents the error of the calibrated voltage transformer, and H represents the error correlation model between the two, namely the modeling and solution process of the above equations (3)-(11).

[0095] Step S200 involves inputting the calibrated transformer error distribution into the error correlation model and obtaining the uncalibrated voltage transformer error distribution based on the Monte Carlo method, including:

[0096] Its known parameters are the current transformer measurement dataset, its input is the error sample values ​​of the calibrated current transformer, and its output is the error estimate of the uncalibrated current transformer. Combining the Monte Carlo method, the error distribution of the uncalibrated sensing device can be obtained. The specific process is as follows:

[0097] Error distribution of calibrated current transformers Extract a set of sample values The extracted set of sample values ​​is input into the error correlation model, and a set of uncalibrated voltage transformer error estimates is output. The set of uncalibrated voltage transformer error estimates includes a set of three-phase phase value errors and three-phase phase angle errors.

[0098] Repeat the input-output operation on the error correlation model M times, with the sample size M being 10000. Analyze the resulting M sets of error estimates for uncalibrated voltage transformers. Any set of ratio error or any set of phase angle error in the data is fitted to a normal distribution, as follows:

[0099] Equation (13)

[0100] Obtain the error distribution of the uncalibrated voltage transformer .

[0101] Following the above process, we obtain Error distribution of uncalibrated voltage transformers corresponding to calibrated voltage transformers ;

[0102] In the formula, This represents the average error of the calibrated current transformers. The standard deviation of the calibrated current transformer error; For the first i The average error of an uncalibrated voltage transformer corresponding to a calibrated voltage transformer; For the first i The standard deviation of the error of an uncalibrated voltage transformer corresponding to a calibrated voltage transformer.

[0103] In other words, the error distribution of the uncalibrated voltage transformer is... The estimated fitted value of the error of any one of the following uncalibrated voltage transformers: phase ratio error of uncalibrated voltage transformer A, phase ratio error of uncalibrated voltage transformer B, phase ratio error of uncalibrated voltage transformer C, phase angle error of uncalibrated voltage transformer A, phase angle error of uncalibrated voltage transformer B, and phase angle error of uncalibrated voltage transformer C.

[0104] Step S300: Based on the Bayesian fusion method, the error distribution of the uncalibrated voltage transformer is optimally estimated to obtain the measurement error and uncertainty of the uncalibrated voltage transformer.

[0105] Specifically, in this embodiment, for all Error distribution of uncalibrated voltage transformers corresponding to calibrated voltage transformers The calculation results are considered as multiple observation sources of the error distribution of uncalibrated voltage transformers. A Bayesian fusion method is then used to analyze the error distribution of the uncalibrated transformers. To perform the optimal estimation, the specific parameters are as follows:

[0106] Equation (14)

[0107] Equation (14) is the optimal estimate of the error distribution of the uncalibrated voltage transformer. The error of the uncalibrated transformer is... The uncertainty is (Corresponding to half the width of the 95% confidence interval).

[0108] See also Figure 3 This invention also provides an online evaluation system for measurement errors and uncertainties of voltage transformers, comprising:

[0109] The error correlation model construction module is used to construct an error correlation model between two voltage transformers connected by an overhead transmission line in a substation.

[0110] The uncalibrated error distribution calculation module is communicatively connected to the error correlation model construction module. It is used to input the calibrated transformer error distribution into the error correlation model and obtain the uncalibrated voltage transformer error distribution based on the Monte Carlo method; and...

[0111] The error and uncertainty calculation module is communicatively connected to the uncalibrated error distribution calculation module. It is used to perform optimal estimation of the error distribution of the uncalibrated voltage transformer based on the Bayesian fusion method, so as to obtain the measurement error and uncertainty of the uncalibrated voltage transformer.

[0112] In summary, the main advantages of this invention are as follows: It constructs an error correlation model to describe the error correlation between voltage transformers in two substations connected by transmission lines; it proposes a measurement error distribution propagation method, calculating the error distribution of uncalibrated voltage transformers based on the error distribution of calibrated transformers and combined with the Monte Carlo method; and it utilizes a Bayesian fusion method to optimally estimate the error distribution of uncalibrated voltage transformers. This solves the problem of online assessment of measurement errors and uncertainties of voltage transformers, not only reducing the consumption of manpower and resources under power outage verification mode but also realizing real-time online sensing of voltage transformer metering performance, effectively ensuring the safe and reliable operation of the power system.

[0113] Specifically, this embodiment corresponds one-to-one with the above method embodiments. The functions of each module have been described in detail in the corresponding method embodiments, so they will not be repeated here.

[0114] Based on the same inventive concept, embodiments of this application also provide a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements all or part of the method steps of the above method.

[0115] The present invention can implement all or part of the processes in the above methods, or it can be accomplished by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content contained in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0116] Based on the same inventive concept, embodiments of this application also provide an electronic device, including a memory and a processor. The memory stores a computer program that runs on the processor. When the processor executes the computer program, it implements all or part of the method steps described above.

[0117] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the computer device, connecting all parts of the computer device through various interfaces and lines.

[0118] Memory can be used to store computer programs and / or modules. The processor performs various functions of the computer device by running or executing the computer programs and / or modules stored in the memory, and by accessing data stored in the memory. Memory can primarily include a program storage area and a data storage area. The program storage area can store the operating system and at least one application program required for a function (e.g., sound playback, image playback, etc.); the data storage area can store data created based on the use of the mobile phone (e.g., audio data, video data, etc.). Furthermore, memory can include high-speed random access memory, and can also include non-volatile memory, such as hard disks, RAM, plug-in hard disks, SmartMedia Cards (SMC), Secure Digital (SD) cards, Flash Cards, at least one disk storage device, flash memory device, or other volatile solid-state storage devices.

[0119] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, servers, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0120] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), servers, and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0121] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0122] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0123] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for on-line evaluation of measurement error and uncertainty of a voltage transformer, characterized in that, The application comprises the following steps: An error correlation model between two voltage transformers connected by overhead transmission lines in a substation is constructed; A calibrated transformer error distribution is input into the error correlation model, and an uncalibrated voltage transformer error distribution is obtained based on a Monte Carlo method; An optimal estimation of the uncalibrated voltage transformer error distribution is performed based on a Bayesian fusion method to obtain measurement error and uncertainty of the uncalibrated voltage transformer; The error correlation model between two voltage transformers connected by overhead transmission lines in a substation is constructed, comprising the following steps: Three independent positive, negative and zero sequence lumped parameter networks are equivalent to a three-phase transmission network in a substation under steady state based on a symmetrical component method, and corresponding positive, negative and zero sequence network flow equations are constructed for the positive, negative and zero sequence lumped parameter networks respectively; Uncalibrated voltage transformer positive sequence correction coefficients, uncalibrated voltage transformer negative sequence correction coefficients and uncalibrated voltage transformer zero sequence correction coefficients are respectively solved in the dimensionally expanded positive, negative and zero sequence network flow equations based on a least square algorithm; Three-phase electrical quantities of the three-phase transmission network are decoupled into positive, negative and zero sequence components by using a decoupling model, wherein the positive, negative and zero sequence components include the uncalibrated voltage transformer positive sequence correction coefficients, the uncalibrated voltage transformer negative sequence correction coefficients and the uncalibrated voltage transformer zero sequence correction coefficients; Uncalibrated voltage transformer three-phase correction coefficients are obtained by solving the decoupling process based on a least square algorithm; Uncalibrated voltage transformer three-phase ratio errors and three-phase phase angle errors are obtained according to the uncalibrated voltage transformer three-phase correction coefficients.

2. The on-line evaluation method of voltage transformer measurement error and uncertainty according to claim 1, characterized in that, The corresponding positive, negative and zero sequence network flow equations are constructed for the positive, negative and zero sequence lumped parameter networks respectively, comprising the following steps: The positive sequence network flow equation is as follows: wherein is the unmarked voltage positive sequence measurement; is the unmarked current positive sequence measurement; is the marked voltage positive sequence measurement; is the marked current positive sequence measurement; is the transmission line positive sequence series impedance; represents the transmission line positive sequence shunt admittance; is the unmarked voltage transformer positive sequence correction factor; is the unmarked current transformer positive sequence correction factor; is the marked voltage transformer positive sequence correction factor; is the marked current transformer positive sequence correction factor; The negative sequence network flow equation is as follows: wherein is the unmarked voltage negative sequence measurement; is the unmarked current negative sequence measurement; is the marked voltage negative sequence measurement; is the marked current negative sequence measurement; is the transmission line negative sequence series impedance; represents the transmission line negative sequence shunt admittance; is the unmarked voltage transformer negative sequence correction factor; is the unmarked current transformer negative sequence correction factor; is the marked voltage transformer negative sequence correction factor; is the marked current transformer negative sequence correction factor; The zero sequence network flow equation is as follows: wherein is the unmarked voltage zero sequence measurement; is the unmarked current zero sequence measurement; is the marked voltage zero sequence measurement; is the marked current zero sequence measurement; is the transmission line zero sequence series impedance; is the transmission line zero sequence shunt admittance; is the unmarked voltage transformer zero sequence correction factor; is the unmarked current transformer zero sequence correction factor; is the marked voltage transformer zero sequence correction factor; is the marked current transformer zero sequence correction factor.

3. The on-line evaluation method of voltage transformer measurement error and uncertainty according to claim 1, characterized in that, The method for decoupling three-phase electrical quantities of the three-phase transmission network into positive, negative and zero sequence components by using a decoupling model is as follows: wherein the decoupling model is: ; wherein, , , are the uncalibrated voltage A, B, C three-phase measurement values, respectively, , , are the uncalibrated voltage transformer A, B, C three-phase correction factors, respectively; is the uncalibrated voltage transformer positive sequence correction factor; is the uncalibrated voltage positive sequence measurement value; is the uncalibrated voltage transformer negative sequence correction factor; is the uncalibrated voltage negative sequence measurement value; is the uncalibrated voltage transformer zero sequence correction factor; is the uncalibrated voltage zero sequence measurement value.

4. The on-line evaluation method of voltage transformer measurement error and uncertainty according to claim 1, characterized in that, The method for obtaining uncalibrated voltage transformer three-phase ratio errors and three-phase phase angle errors according to the uncalibrated voltage transformer three-phase correction coefficients is as follows: wherein, is the uncalibrated voltage transformer A phase ratio error; is the uncalibrated voltage transformer B phase ratio error; is the uncalibrated voltage transformer C phase ratio error; is the uncalibrated voltage transformer A phase angle error; is the uncalibrated voltage transformer B phase angle error; is the uncalibrated voltage transformer C phase angle error; is the phase angle taken.

5. The on-line evaluation method of voltage transformer measurement error and uncertainty according to claim 1, characterized in that, The calibrated transformer error distribution is input into the error correlation model, and an uncalibrated voltage transformer error distribution is obtained based on a Monte Carlo method, comprising the following steps: extracting a set of sample values from the calibrated transformer error distribution inputting the extracted set of sample values to the error correlation model, and outputting a set of uncalibrated voltage transformer error estimates, the set of uncalibrated voltage transformer error estimates including a set of three-phase ratio errors and three-phase phase angle errors; Repeating the input-output operation of the error correlation model M times, fitting any phase comparison error set or any phase phase angle error set in the M sets of error estimation values of the uncalibrated voltage transformer respectively to obtain an error distribution of the uncalibrated voltage transformer corresponding to the calibrated voltage transformer ; wherein, is the calibrated transformer error mean; is the calibrated transformer error standard deviation; is the uncalibrated transformer error mean corresponding to the i th calibrated voltage transformer; is the uncalibrated transformer error standard deviation corresponding to the i th calibrated voltage transformer.

6. The on-line evaluation method of voltage transformer measurement error and uncertainty according to claim 1, characterized in that, The method for performing optimal estimation of the uncalibrated voltage transformer error distribution based on a Bayesian fusion method to obtain measurement error and uncertainty of the uncalibrated voltage transformer is as follows: wherein is the measurement error of the uncalibrated voltage transformer; 2 times is the uncertainty of the uncalibrated voltage transformer.

7. A system for on-line evaluation of measurement error and uncertainty of a voltage transformer, characterized by The application comprises the following steps: An error correlation model between two voltage transformers connected by overhead transmission lines in a substation is constructed by an error correlation model construction module; A calibrated transformer error distribution is input into the error correlation model, and an uncalibrated voltage transformer error distribution is obtained based on a Monte Carlo method by an uncalibrated error distribution calculation module in communication connection with the error correlation model construction module; and An error and uncertainty calculation module, in communication with the uncalibrated error distribution calculation module, configured to perform optimal estimation on the uncalibrated error distribution of the uncalibrated voltage transformer based on a Bayesian fusion method, to obtain measurement error and uncertainty of the uncalibrated voltage transformer; The error correlation model between the two voltage transformers connected by overhead transmission lines in the substation comprises: The three-phase transmission network of the substation is equivalent to three independent positive, negative and zero sequence lumped parameter networks under steady state based on the symmetrical component method, and corresponding positive, negative and zero sequence network flow equations are constructed for the positive, negative and zero sequence lumped parameter networks respectively; The positive, negative and zero sequence network flow equations with extended dimensions are solved based on the least square algorithm to obtain corresponding uncalibrated voltage transformer positive sequence correction coefficients, uncalibrated voltage transformer negative sequence correction coefficients and uncalibrated voltage transformer zero sequence correction coefficients respectively; Three-phase electrical quantities of the three-phase transmission network are decoupled into positive, negative and zero sequence components using a decoupling model, wherein the positive, negative and zero sequence components include the uncalibrated voltage transformer positive sequence correction coefficients, the uncalibrated voltage transformer negative sequence correction coefficients and the uncalibrated voltage transformer zero sequence correction coefficients; The decoupling process is solved based on the least square algorithm to obtain uncalibrated voltage transformer three-phase correction coefficients; Three-phase ratio error and three-phase phase angle error of the uncalibrated voltage transformer are obtained based on the uncalibrated voltage transformer three-phase correction coefficients.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program, when executed by a processor, implements the online evaluation method of measurement error and uncertainty of a voltage transformer according to any one of claims 1 to 6.

9. An electronic device comprising a storage medium, a processor, and a computer program stored in the storage medium and operable on the processor, characterized in that, The processor, when running the computer program, implements the online evaluation method of measurement error and uncertainty of a voltage transformer according to any one of claims 1 to 6.

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