CN115248906B - State error identification method and system for double current transformers on outgoing line of generator - Google Patents
State error identification method and system for double current transformers on outgoing line of generator Download PDFInfo
- Publication number
- CN115248906B CN115248906B CN202211158911.8A CN202211158911A CN115248906B CN 115248906 B CN115248906 B CN 115248906B CN 202211158911 A CN202211158911 A CN 202211158911A CN 115248906 B CN115248906 B CN 115248906B
- Authority
- CN
- China
- Prior art keywords
- phase
- sequence
- current
- abnormal
- data set
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- 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
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
- G01R31/62—Testing of transformers
-
- 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
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/50—Arrangements for eliminating or reducing asymmetry in polyphase networks
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Power Engineering (AREA)
- Theoretical Computer Science (AREA)
- Mathematical Physics (AREA)
- Mathematical Analysis (AREA)
- Computational Mathematics (AREA)
- Operations Research (AREA)
- Probability & Statistics with Applications (AREA)
- Life Sciences & Earth Sciences (AREA)
- Algebra (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Evolutionary Biology (AREA)
- Bioinformatics & Computational Biology (AREA)
- Testing Of Short-Circuits, Discontinuities, Leakage, Or Incorrect Line Connections (AREA)
Abstract
The invention provides a method and a system for identifying state errors of a generator outgoing line double-current transformer, wherein the method comprises the following steps: acquiring a historical three-phase current measurement value of the double current transformers in a normal state; constructing a three-phase relation characteristic quantity data set based on three-phase zero-sequence imbalance and three-phase negative-sequence imbalance, constructing a nuclear density function of the three-phase zero-sequence imbalance and the three-phase negative-sequence imbalance through nuclear density estimation, setting a preset boundary condition, setting a confidence interval, and obtaining a corresponding abnormal boundary threshold value based on the nuclear density function and the confidence interval; and acquiring a three-phase current measured value in online operation, and judging whether each phase current transformer is abnormal or not based on an abnormal boundary threshold value and three-phase statistic parameters. Through the scheme, the online detection of the abnormal state of the current transformer can be realized, the detection result is accurate and reliable, and the long-time monitoring requirement can be met.
Description
Technical Field
The invention belongs to the field of power equipment performance evaluation, and particularly relates to a state error identification method and system for a generator outgoing line double-current transformer.
Background
Current Transformers (CTs) are important metering devices in electrical power systems. The primary winding is connected in series in a main transmission and transformation loop, and the secondary winding is respectively connected with equipment such as a measuring instrument, a relay protection or an automatic device and the like according to different requirements and is used for changing the large current of the primary loop into the small current of the secondary side so as to be convenient for the measurement and control protection metering equipment to safely collect. The accuracy and the reliability of the current transformer have great significance for the safe operation, the control protection, the electric energy metering and the trade settlement of an electric power system.
In a power station, a generator outlet current transformer mainly measures the output current of a generator, and in some generator line structures, the generator is not connected to a bus, but directly supplies power. And in the inspection of the outlet current transformer, because the outlet current of the generator is larger, a larger current experiment power supply is needed. Compared with other bus current transformers, the field wiring of the large-current transformer is more difficult. Therefore, in some generator outlet structures, two current transformers are connected in series on the generator outlet for ensuring the accuracy of the current transformers at the outlet of the generator, ensuring accurate and fair metering power generation and ensuring the safe operation of the generator set. The two groups of current transformers are connected in series on the outgoing line of the same generator to measure the three-phase current on the same line, namely the current flowing through any in-phase current transformer in the two groups of current transformers is kept consistent, and the current of the current transformer on each group of outgoing lines is kept in dynamic balance.
The method has the advantages that the abnormality of the current transformer is found in time, the out-of-limit running time of the error of the current transformer is reduced, and the method has important significance for ensuring the accuracy and the reliability of electric energy metering. Currently, for the state detection of these current transformers, the commonly used error detection methods are mainly divided into off-line detection and on-line detection: the process of off-line detection needs long-time power failure of the detected mutual inductor and peripheral equipment, which causes great influence on the normal operation of a power grid, and the dynamic change of the operation error of the detected mutual inductor cannot be reflected because the working condition during off-line detection is different from the working condition during on-line operation; in the on-line detection process, although the consistency of relevant working condition conditions during operation is met, and the error of the CT to be detected can be calculated more accurately, the standard mutual inductor needs to be connected in a current state, so that potential safety hazards easily exist, and long-time detection is not suitable.
Disclosure of Invention
In view of this, the embodiment of the invention provides a method and a system for identifying state errors of double current transformers on a generator outgoing line, which are used for solving the problems that the normal operation of a power grid is influenced by the error detection of the existing current transformers offline and long-time monitoring cannot be performed online.
In a first aspect of the embodiments of the present invention, a method for identifying a state error of a generator outgoing line dual current transformer is provided, including:
acquiring historical three-phase current measurement values of the double current transformers in a normal state;
constructing a three-phase relation characteristic quantity data set based on three-phase zero-sequence imbalance and three-phase negative-sequence imbalance, constructing a nuclear density function of the three-phase zero-sequence imbalance and the three-phase negative-sequence imbalance through nuclear density estimation, setting a preset boundary condition, setting a confidence interval, and obtaining a corresponding abnormal boundary threshold value based on the nuclear density function and the confidence interval;
and acquiring a three-phase current measured value running on line, and judging whether each phase current transformer is abnormal or not based on an abnormal boundary threshold value and three-phase statistic parameters.
In a second aspect of an embodiment of the present invention, there is provided a system for identifying a state error of a generator outgoing line dual current transformer, including:
the historical data acquisition module is used for acquiring a historical three-phase current measurement value of the double current transformers in a normal state;
the boundary threshold value calculation module is used for constructing a three-phase relation characteristic quantity data set based on three-phase zero-sequence unbalance and three-phase negative-sequence unbalance, constructing a nuclear density function of the three-phase zero-sequence unbalance and the three-phase negative-sequence unbalance through nuclear density estimation, setting a preset boundary condition, setting a confidence interval, and obtaining a corresponding abnormal boundary threshold value based on the nuclear density function and the confidence interval;
and the identification and judgment module is used for acquiring a three-phase current measurement value running on line and judging whether each phase current transformer is abnormal or not based on the abnormal boundary threshold and the three-phase statistic parameters.
In a third aspect of the embodiments of the present invention, there is provided an electronic device, including a memory, a processor, and a computer program stored in the memory and executable by the processor, where the processor executes the computer program to implement the steps of the method according to the first aspect of the embodiments of the present invention.
In a fourth aspect of the embodiments of the present invention, a computer-readable storage medium is provided, which stores a computer program, which when executed by a processor implements the steps of the method provided by the first aspect of the embodiments of the present invention.
In the embodiment of the invention, historical three-phase current data are obtained, a probability density function of three-phase current unbalance is constructed based on kernel density estimation, the running states of two groups of CT are judged by setting a threshold value and comparing the unbalance degree of the three-phase current with the set threshold value, the maximum value of the statistic parameter of each phase in the group is obtained according to the judged running states of the two groups of CT, and the abnormal phase in the current transformer group with abnormality is judged. Therefore, the error state detection of the current transformer connected in series with the outgoing line of the generator on line is realized, the detection result is accurate and reliable, and long-time on-line monitoring can be realized.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a schematic flowchart of a state error identification method for a generator outgoing line dual current transformer according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a state error identification system of a generator outgoing line double current transformer according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be understood that the term "comprises" and its derivatives, as used in the description or claims of the present invention and in the appended drawings, are intended to cover non-exclusive inclusions, such that a process, method or system, or apparatus that comprises a list of steps or elements is not limited to the listed steps or elements. In addition, "first" and "second" are used to distinguish different objects, and are not used to describe a specific order.
Referring to fig. 1, a schematic flow chart of a method for identifying a state error of a generator outgoing line dual current transformer according to an embodiment of the present invention includes:
s101, obtaining historical three-phase current measurement values of the double current transformers in a normal state;
the current transformers are installed on the power generator outgoing line, two current transformers are connected to the power generator outgoing line in series, and the two current transformers measure three-phase currents on the same line.
Specifically, three-phase current historical data measured by two groups of current transformers in a normal operation state of the double current transformers on the outgoing line of the generator are counted, and a three-phase current value measured by the first group of current transformers is recorded as
The three-phase current value measured by the second group of current transformers is recorded as
. For historical period
History data set is D H ={（i 1A (0),i 1B (0),i 1C (0),i 2A (0),i 2B (0),i 2C (0)）, （i 1A (1),i 1B (1), i 1C (1), i 2A (1),i 2B (1), i 2C (1)）,…, （i 1A (t),i 1B (t), i 1C (t), i 2A (t),i 2B (t), i 2C (t)）,…,( i 1A (T-1),i 1B (T-1), i 1C (T-1), i 2A (T-1),i 2B (T-1), i 2C (T-1))}。
Wherein, the first and the second end of the pipe are connected with each other,
the current value of the j phase of the ith group of current transformers at the time t is represented,
，
。
s102, constructing a three-phase relation characteristic quantity data set based on three-phase zero-sequence imbalance and three-phase negative-sequence imbalance, constructing a three-phase zero-sequence imbalance and three-phase negative-sequence imbalance nuclear density function through nuclear density estimation, setting a preset boundary condition, setting a confidence interval, and obtaining a corresponding abnormal boundary threshold value based on the nuclear density function and the confidence interval;
respectively calculating a positive sequence component, a negative sequence component and a zero sequence component of the synthetic current, taking the ratio of the absolute value of the zero sequence component to the absolute value of the positive sequence component as three-phase zero sequence imbalance, and taking the ratio of the absolute value of the negative sequence component to the absolute value of the positive sequence component as three-phase negative sequence imbalance;
and taking the three-phase zero-sequence imbalance and the three-phase negative-sequence imbalance at the same moment of the two groups of current transformers as data pairs to obtain a three-phase imbalance characteristic quantity data set.
Specifically, according to historical data sets of two groups of current transformers on the same outlet line
Using three-phase zero-sequence imbalance
And three-phase negative sequence imbalance
Constructing a three-phase relationship featureThe data set is measured.
The three-phase zero-sequence unbalance and three-phase negative-sequence unbalance calculation process comprises the following steps:
positive sequence component of the resultant current
；
Negative sequence component of the resultant current
；
Zero sequence component of the resultant current
；
Then the
，
。
The construction process of the three-phase relation characteristic quantity data set is as follows:
due to historical data set
The three-phase current data values of the two groups of current transformers on the same outgoing line of the generator are measured in a normal state, and the measured data of the two groups of current transformers can be regarded as real current data of the outgoing line of the generator. Calculating the data of two sets of current transformers at corresponding time
Data pairs, inputting the same data set
In the method, three-phase unbalanced characteristic quantity data set of three-phase current of a real generator outgoing line is formed:
Based on the three-phase relation characteristic quantity data set, constructing a three-phase zero-sequence unbalanced and three-phase negative-sequence unbalanced nuclear density function as follows:
in the formula (I), the compound is shown in the specification,
a function representing the density of the nuclei is shown,hrepresents the window width, d represents the dimension,
in order to be a kernel function, the kernel function,
indicating the ith data in the data set,xrepresenting the density center point in the function, p represents the norm parameter for the minkowski distance, and n represents the number of data in the dataset.
Will be provided with
Substitution into
；
Here, a second order paradigm is used, i.e.
(ii) a The window width h is set here to
，
For the sample standard deviation, d is the dimension of X, where two dimensional features are included, then d =2.
Preferably, data in the three-phase relation characteristic quantity data set are projected to a first quadrant and a fourth quadrant of a plane coordinate system in a mirror image mode, a center is projected to a third quadrant in a symmetrical mode, and a new three-phase relation characteristic quantity data set is obtained through integration;
inputting the new three-phase relation characteristic quantity data set into a nuclear density function, and setting boundary constraint conditions.
Based on three-phase zero sequence imbalance and three-phase negative sequence imbalance calculation process
And is
Directly constructing a kernel density estimation function, which can not accurately represent probability density characteristics, and collecting three-phase imbalance characteristic quantities in order to make the probability density function more consistent with distribution characteristics
The data in the data collection is projected to a first quadrant and a fourth quadrant in a mirror image mode, and is projected to a third quadrant in a central symmetry mode, all the data are integrated into a new data set
,
. Will be provided with
Data in (2) is input into
In (2), obtain the corresponding kernel density function
And the constraint condition is added to the system,
。
the confidence intervals represent the reliability of the demarcated boundary threshold values, and are different, as well as the corresponding upper boundary threshold values.
S103, obtaining a three-phase current measured value in online operation, and judging whether each phase current transformer is abnormal or not based on an abnormal boundary threshold value and three-phase statistic parameters.
And the three-phase statistic parameters represent parameters for judging the abnormal fluctuation degree of the current value of each phase current transformer in a normal current state.
The method comprises the steps of obtaining online monitoring data of two groups of current transformers, calculating three-phase unbalance values, inputting the three-phase unbalance values of the two groups of current transformers into a kernel density function, and judging whether an output result exceeds an abnormal boundary threshold value or not;
and if the abnormal boundary threshold value is exceeded, calculating three-phase statistic parameters in the corresponding group according to the historical three-phase current extreme value and the current online three-phase current monitoring data, and acquiring the maximum value of the statistic parameters in the three phases as the abnormal phase.
In particular, from historical three-phase current data sets
In the method, the maximum and minimum current amplitudes of each group of phases are obtained,
，
；
according to the online data of the two groups of current transformers
Calculating real-time corresponding three-phase imbalance data
Inputting the three-phase unbalanced data of the two groups of current transformers into a kernel density function, judging whether the three-phase unbalanced data exceed an upper boundary threshold value, and if the three-phase unbalanced data do not exceed the upper boundary threshold value, indicating that the group of current transformers are normal;
if the current transformer exceeds the upper boundary threshold, regarding the current transformers exceeding the boundary threshold, the current transformers in the group are considered to have abnormal states, and the phases of the abnormal transformers need to be searched. Using a formula
And calculating three-phase statistic P according to the maximum and minimum extreme values in the historical three-phase current data and the three-phase data value acquired in real time so as to reflect the degree of abnormal fluctuation of each phase of real-time current.
Calculating the phase with the maximum P statistic in the three phases as the abnormal phase in the current transformer group, namely
。
In the embodiment, the on-line detection of the abnormal state of the current transformer can be realized, the error identification accuracy is high, the judgment result is reliable, and the requirement of long-time monitoring can be met.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
Fig. 2 is a schematic structural diagram of a state error identification system of a generator outgoing line dual current transformer according to an embodiment of the present invention, where the system includes:
a historical data obtaining module 210, configured to obtain a historical three-phase current measurement value of the dual current transformer in a normal state;
the boundary threshold calculation module 220 is configured to construct a three-phase relationship characteristic quantity data set based on three-phase zero-sequence imbalance and three-phase negative-sequence imbalance, construct a kernel density function of three-phase zero-sequence imbalance and three-phase negative-sequence imbalance through kernel density estimation, set a predetermined boundary condition, set a confidence interval, and obtain a corresponding abnormal boundary threshold based on the kernel density function and the confidence interval;
specifically, a positive sequence component, a negative sequence component and a zero sequence component of the synthetic current are respectively calculated, the ratio of the absolute value of the zero sequence component to the absolute value of the positive sequence component is used as three-phase zero sequence imbalance, and the ratio of the absolute value of the negative sequence component to the absolute value of the positive sequence component is used as three-phase negative sequence imbalance;
and taking the three-phase zero-sequence unbalance and the three-phase negative-sequence unbalance of the two groups of current transformers at the same moment as a data pair to obtain a three-phase unbalance characteristic quantity data set.
Wherein the constructing of the nuclear density function of the three-phase zero-sequence imbalance and the three-phase negative-sequence imbalance through the nuclear density estimation comprises:
based on the three-phase relation characteristic quantity data set, a three-phase zero-sequence unbalanced and three-phase negative-sequence unbalanced nuclear density function is constructed as follows:
in the formula (I), the compound is shown in the specification,
a function representing the density of the kernel is represented,hthe window width is represented, d represents the dimension,
is a function of the kernel, and is,
representing the ith data in the data set,xrepresenting the density center point in the function, p represents the norm parameter for the minkowski distance, and n represents the number of data in the dataset.
Wherein the setting of the predetermined boundary condition comprises:
the data in the three-phase relation characteristic quantity data set are subjected to mirror image projection to a first quadrant and a fourth quadrant of a plane coordinate system, the centers are symmetrically projected to a third quadrant, and a new three-phase relation characteristic quantity data set is obtained through integration;
inputting the new three-phase relation characteristic quantity data set into a nuclear density function, and setting boundary constraint conditions.
And the identification and judgment module 230 is configured to obtain a three-phase current measurement value running online, and judge whether each phase current transformer is abnormal based on an abnormal boundary threshold and a three-phase statistic parameter.
Specifically, the identification determining module 230 includes:
the judging unit is used for acquiring online monitoring data of the two groups of current transformers, calculating three-phase unbalance values, inputting the three-phase unbalance values of the two groups of current transformers into a kernel density function, and judging whether an output result exceeds an abnormal boundary threshold value;
and the identification unit is used for calculating three-phase statistical parameters in corresponding groups according to the historical three-phase current extreme value and the current online three-phase current monitoring data if the abnormal boundary threshold value is exceeded, and acquiring the maximum value of the statistical parameters in the three phases as an abnormal phase.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
It can be understood by those skilled in the art that all or part of the steps in the method for implementing the above embodiment may be implemented by instructing the relevant hardware through a program, where the program may be stored in a computer-readable storage medium, and when executed, the program implements part or all of the processes in steps S101 to S103, and the storage medium includes, for example, ROM/RAM.
In an embodiment, as shown in fig. 3, fig. 3 is a schematic structural diagram of an electronic device for detecting an abnormal state of a current transformer according to an embodiment of the present invention, where the electronic device may be a computer. As shown in fig. 3, the electronic apparatus 3 of this embodiment includes at least: a memory 310, a processor 320, and a system bus 330, the memory 310 including an executable program 3101 stored thereon, it being understood by those skilled in the art that the electronic device architecture shown in fig. 3 does not constitute a limitation of electronic devices, and may include more or fewer components than shown, or some components in combination, or a different arrangement of components.
The following specifically describes each constituent component of the electronic device with reference to fig. 3:
the memory 310 may be used to store software programs and modules, and the processor 320 executes various functional applications and data processing of the electronic device by operating the software programs and modules stored in the memory 310. The memory 310 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as cache data) created according to the use of the electronic device, and the like. Further, the memory 310 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.
An executable program 3101 of the network request method is embodied on the memory 310, the executable program 3101 may be divided into one or more modules/units, which are stored in the memory 310 and executed by the processor 320 to implement the state error detection of the dual current transformers, etc., and the one or more modules/units may be a series of computer program instruction segments capable of performing a specific function for describing an execution process of the computer program 3101 in the electronic device 3. For example, the computer program 3101 may be divided into a history data acquisition module, a boundary threshold calculation module, a recognition judgment module, and the like.
The processor 320 is a control center of the electronic device, connects various parts of the whole electronic device using various interfaces and lines, performs various functions of the electronic device and processes data by running or executing software programs and/or modules stored in the memory 310 and calling data stored in the memory 310, thereby performing overall status monitoring of the electronic device. Alternatively, processor 320 may include one or more processing units; preferably, the processor 320 may integrate an application processor, which mainly handles operating systems, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into processor 320.
The system bus 330 is used to connect various functional units inside the computer, and CAN transmit data information, address information, and control information, and the types of the functional units CAN be, for example, a PCI bus, an ISA bus, a CAN bus, etc. The instructions of the processor 320 are transferred to the memory 310 through the bus, the memory 310 feeds data back to the processor 320, and the system bus 330 is responsible for data and instruction interaction between the processor 320 and the memory 310. Of course, other devices, such as network interfaces, display devices, etc., may also be accessible to the system bus 330.
In this embodiment of the present invention, the executable program executed by the process 320 included in the electronic device includes:
acquiring historical three-phase current measurement values of the double current transformers in a normal state;
constructing a three-phase relation characteristic quantity data set based on three-phase zero-sequence unbalance and three-phase negative-sequence unbalance, constructing a nuclear density function of the three-phase zero-sequence unbalance and the three-phase negative-sequence unbalance through nuclear density estimation, setting a preset boundary condition, setting a confidence interval, and obtaining a corresponding abnormal boundary threshold value based on the nuclear density function and the confidence interval;
and acquiring a three-phase current measured value in online operation, and judging whether each phase current transformer is abnormal or not based on an abnormal boundary threshold value and three-phase statistic parameters.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (8)
1. A state error identification method for a generator outgoing line double-current transformer is characterized by comprising the following steps:
acquiring historical three-phase current measurement values of the double current transformers in a normal state;
constructing a three-phase relation characteristic quantity data set based on three-phase zero-sequence unbalance and three-phase negative-sequence unbalance, constructing a nuclear density function of the three-phase zero-sequence unbalance and the three-phase negative-sequence unbalance through nuclear density estimation, setting a preset boundary condition, setting a confidence interval, and obtaining a corresponding abnormal boundary threshold value based on the nuclear density function and the confidence interval;
wherein the setting of the predetermined boundary condition comprises:
the data in the three-phase relation characteristic quantity data set are subjected to mirror image projection to a first quadrant and a fourth quadrant of a plane coordinate system, the centers are symmetrically projected to a third quadrant, and a new three-phase relation characteristic quantity data set is obtained through integration;
inputting the new three-phase relation characteristic quantity data set into a kernel density function, and setting boundary constraint conditions;
and acquiring a three-phase current measured value running on line, and judging whether each phase current transformer is abnormal or not based on an abnormal boundary threshold value and three-phase statistic parameters.
2. The method of claim 1, wherein constructing a three-phase relational feature quantity data set based on the three-phase zero-sequence imbalance and the three-phase negative-sequence imbalance comprises:
respectively calculating a positive sequence component, a negative sequence component and a zero sequence component of the synthesized current, taking the ratio of the absolute value of the zero sequence component to the absolute value of the positive sequence component as three-phase zero sequence imbalance, and taking the ratio of the absolute value of the negative sequence component to the absolute value of the positive sequence component as three-phase negative sequence imbalance;
and taking the three-phase zero-sequence imbalance and the three-phase negative-sequence imbalance at the same moment of the two groups of current transformers as data pairs to obtain a three-phase imbalance characteristic quantity data set.
3. The method of claim 1, wherein constructing a kernel density function of three-phase zero-sequence imbalance and three-phase negative-sequence imbalance by kernel density estimation comprises:
based on the three-phase relation characteristic quantity data set, a three-phase zero-sequence unbalanced and three-phase negative-sequence unbalanced nuclear density function is constructed as follows:
in the formula (I), the compound is shown in the specification,
a function representing the density of the kernel is represented,hthe window width is represented, d represents the dimension,
in order to be a kernel function, the kernel function,
representing the ith data in the data set,xrepresenting the density center point in the function, p represents the norm parameter for the minkowski distance, and n represents the number of data in the dataset.
4. The method of claim 1, wherein the obtaining of three-phase current measurement values for online operation and the determining of whether each phase current transformer is abnormal based on abnormal boundary threshold values and three-phase statistical parameters comprises:
acquiring online monitoring data of two groups of current transformers, calculating three-phase imbalance values, inputting the three-phase imbalance values of the two groups of current transformers into a kernel density function, and judging whether an output result exceeds an abnormal boundary threshold value;
and if the abnormal boundary threshold value is exceeded, calculating three-phase statistical parameters in the corresponding group according to the historical three-phase current extreme value and the current online three-phase current monitoring data, and acquiring the maximum value of the statistical parameters in the three phases as the abnormal phase.
5. The utility model provides a generator is qualified for next round of competitions dual current transformer's state error identification system which characterized in that includes:
the historical data acquisition module is used for acquiring historical three-phase current measurement values of the double current transformers in a normal state;
the boundary threshold value calculation module is used for constructing a three-phase relation characteristic quantity data set based on three-phase zero-sequence unbalance and three-phase negative-sequence unbalance, constructing a nuclear density function of the three-phase zero-sequence unbalance and the three-phase negative-sequence unbalance through nuclear density estimation, setting a preset boundary condition, setting a confidence interval, and obtaining a corresponding abnormal boundary threshold value based on the nuclear density function and the confidence interval;
wherein the setting of the predetermined boundary condition comprises:
the data in the three-phase relation characteristic quantity data set are subjected to mirror image projection to a first quadrant and a fourth quadrant of a plane coordinate system, the centers are symmetrically projected to a third quadrant, and a new three-phase relation characteristic quantity data set is obtained through integration;
inputting the new three-phase relation characteristic quantity data set into a nuclear density function, and setting boundary constraint conditions;
and the identification and judgment module is used for acquiring a three-phase current measured value running on line and judging whether each phase current transformer is abnormal or not based on the abnormal boundary threshold value and the three-phase statistic parameters.
6. The system of claim 5, wherein the identification determination module comprises:
the judging unit is used for acquiring online monitoring data of the two groups of current transformers, calculating three-phase unbalance values, inputting the three-phase unbalance values of the two groups of current transformers into a kernel density function, and judging whether an output result exceeds an abnormal boundary threshold value;
and the identification unit is used for calculating three-phase statistic parameters in the corresponding group according to the historical three-phase current extreme value and the current online three-phase current monitoring data if the abnormal boundary threshold value is exceeded, and acquiring the maximum value of the statistic parameters in the three phases as an abnormal phase.
7. An electronic device comprising a memory, a processor and a computer program stored in said memory and executable on said processor, characterized in that said processor when executing said computer program implements the steps of a method for identification of status errors of a generator outlet dual current transformer according to any one of claims 1 to 4.
8. A computer-readable storage medium storing a computer program, wherein the computer program is executed to implement the steps of the method for identifying the state error of a generator outlet dual current transformer according to any one of claims 1 to 4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211158911.8A CN115248906B (en) | 2022-09-22 | 2022-09-22 | State error identification method and system for double current transformers on outgoing line of generator |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211158911.8A CN115248906B (en) | 2022-09-22 | 2022-09-22 | State error identification method and system for double current transformers on outgoing line of generator |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115248906A CN115248906A (en) | 2022-10-28 |
| CN115248906B true CN115248906B (en) | 2023-01-06 |
Family
ID=83700240
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211158911.8A Active CN115248906B (en) | 2022-09-22 | 2022-09-22 | State error identification method and system for double current transformers on outgoing line of generator |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115248906B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117169800B (en) * | 2023-10-25 | 2024-02-06 | 华中科技大学 | Knowledge-based current transformer online monitoring method and device |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108390390A (en) * | 2018-04-28 | 2018-08-10 | 长沙理工大学 | Random fuzzy power flow method for three-phase unbalanced active power distribution network containing router with priority wind energy consumption source |
| CN114935688A (en) * | 2022-07-25 | 2022-08-23 | 山东大学 | Electric arc furnace power supply system harmonic evaluation method and system based on power segmentation |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106921158B (en) * | 2017-02-09 | 2020-01-31 | 国网福建省电力有限公司 | demand coefficient analysis method for historical collected data based on time sequence of distribution transformer |
| US10823777B2 (en) * | 2018-04-16 | 2020-11-03 | Schweitzer Engineering Laboratories, Inc. | Detection and location of broken conductors for transmission lines |
| WO2021025612A1 (en) * | 2019-08-05 | 2021-02-11 | Sembcorp Industries Ltd | A method and a system of detecting winding fault under online operation of an electrical machine |
| CN112731260B (en) * | 2021-03-30 | 2021-07-09 | 华中科技大学 | Online evaluation method for error state of voltage transformer based on concept drift recognition |
| CN115018139A (en) * | 2022-05-25 | 2022-09-06 | 国网湖南省电力有限公司 | Current transformer error state online identification method and system based on interphase characteristics |
-
2022
- 2022-09-22 CN CN202211158911.8A patent/CN115248906B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108390390A (en) * | 2018-04-28 | 2018-08-10 | 长沙理工大学 | Random fuzzy power flow method for three-phase unbalanced active power distribution network containing router with priority wind energy consumption source |
| CN114935688A (en) * | 2022-07-25 | 2022-08-23 | 山东大学 | Electric arc furnace power supply system harmonic evaluation method and system based on power segmentation |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115248906A (en) | 2022-10-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9563722B2 (en) | Sigma algebraic approximants as a diagnostic tool in power networks | |
| CN112098915B (en) | Method for evaluating secondary errors of multiple voltage transformers under double-bus segmented wiring | |
| CN115469259B (en) | CT error state online quantitative evaluation method and device based on RBF neural network | |
| CN113985339B (en) | Error diagnosis method and system for intelligent ammeter, equipment and storage medium | |
| CN115480203B (en) | Online quantitative evaluation method and system for error state of current transformer | |
| CN115248906B (en) | State error identification method and system for double current transformers on outgoing line of generator | |
| CN115372881B (en) | Voltage transformer metering error evaluation method and system | |
| CN115392141B (en) | Self-adaptive current transformer error evaluation method | |
| CN115480204A (en) | Current transformer operation error online evaluation optimization method based on big data deduction | |
| CN103324858A (en) | Three-phase load flow state estimation method of power distribution network | |
| CN115508770A (en) | KL-NB algorithm-based electric energy meter operation state online evaluation method | |
| WO2020177706A1 (en) | Method for determining fault section and fault time of power distribution network | |
| CN113721182B (en) | Method and system for evaluating reliability of online performance monitoring result of power transformer | |
| CN109901022A (en) | Power distribution network area positioning method based on synchronous measure data | |
| CN114942402B (en) | Abnormal electric energy meter positioning method and system | |
| CN115267641B (en) | Method and system for identifying error abnormity of current transformer in same-tower double-circuit power transmission line | |
| CN115343579B (en) | Power grid fault analysis method and device and electronic equipment | |
| Abdolkarimzadeh et al. | A novel and efficient power system state estimation algorithm based on Weighted Least Square (WLS) approach service | |
| CN113376469A (en) | Analysis method of power quality disturbance data | |
| CN112749099A (en) | PAS application performance evaluation method, system, terminal equipment and medium | |
| CN111781553A (en) | Voltage divider calibration system and method | |
| CN117169804B (en) | Current transformer error state online identification method based on combined current vector analysis | |
| Bao et al. | Evaluation of power grid data quality based on state estimation results | |
| CN117421546A (en) | High-voltage current transformer error approximation evaluation method and system based on initial error | |
| CN115308477A (en) | Method, device, medium and equipment for judging reverse direction of power reverse transmission power flow |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CP01 | Change in the name or title of a patent holder |
Address after: Room 1803-1805, building 2-07, guanggu.core center, 303 Guanggu Avenue, Donghu New Technology Development Zone, Wuhan City, Hubei Province, 430000 Patentee after: Wuhan Gelanruo Intelligent Technology Co.,Ltd. Address before: Room 1803-1805, building 2-07, guanggu.core center, 303 Guanggu Avenue, Donghu New Technology Development Zone, Wuhan City, Hubei Province, 430000 Patentee before: WUHAN GLORY ROAD INTELLIGENT TECHNOLOGY Co.,Ltd. |
|
| CP01 | Change in the name or title of a patent holder |