CN111222085A - Real-time evaluation method for health state of capacitive voltage transformer - Google Patents
Real-time evaluation method for health state of capacitive voltage transformer Download PDFInfo
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- CN111222085A CN111222085A CN202010294233.2A CN202010294233A CN111222085A CN 111222085 A CN111222085 A CN 111222085A CN 202010294233 A CN202010294233 A CN 202010294233A CN 111222085 A CN111222085 A CN 111222085A
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- G06—COMPUTING; CALCULATING OR COUNTING
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- G06F17/10—Complex mathematical operations
- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R35/00—Testing or calibrating of apparatus covered by the other groups of this subclass
- G01R35/02—Testing or calibrating of apparatus covered by the other groups of this subclass of auxiliary devices, e.g. of instrument transformers according to prescribed transformation ratio, phase angle, or wattage rating
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- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
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Abstract
The invention discloses a real-time evaluation method for the health state of a capacitor voltage transformer, which relates to the technical field of power grids and comprises the following steps: acquiring account information of the capacitor voltage transformer to be evaluated; acquiring a power grid topological structure, and constructing a comparison object group of the capacitor voltage transformer to be evaluated; acquiring historical data of voltage remote measurement values of all the capacitor voltage transformers in a comparison object group to form discrete voltage random variables; calculating a correlation coefficient as an evaluation index; judging whether the health standard is met; when the health standard is met, updating the discrete voltage random variable after the voltage telemetering value is refreshed, and returning to execute the calculation correlation coefficient as an evaluation index; an exception alarm is generated when the health criteria is not met. According to the invention, no hardware equipment is required to be added, and the real-time evaluation of the health state of the capacitor voltage transformer is realized under the condition of no power failure by using the historical data of the voltage telemetering value in the energy management system.
Description
Technical Field
The invention relates to the technical field of power grids, in particular to a real-time evaluation method for the health state of a capacitor voltage transformer.
Background
The capacitor voltage transformer is a high-voltage device widely applied to a power system, and is used as a voltage measuring element to measure the amplitude of high voltage, and the supervision and evaluation of the health state are realized by adopting a periodical power failure preventive test mode for a long time. The capacitor voltage transformer is structurally formed by connecting a main capacitor and a voltage division capacitor in series, the capacitance of the voltage division capacitor is generally five times that of the main capacitor, the two capacitors are connected in series, the larger the capacitance is, the smaller the voltage at two ends of the capacitor is, and therefore the principle of voltage division of the capacitors can be utilized to convert high voltage into low voltage to realize high voltage measurement.
The voltage dividing capacitor and the main capacitor are both formed by connecting a plurality of capacitor elements in series, in order to ensure the voltage to be uniformly distributed, the capacitance of each capacitor element is consistent during manufacturing, the smaller the number of the series elements is, the larger the capacitance is, when the elements are broken down, the equivalent number of the series elements is reduced, the capacitance is increased at the moment, and therefore, no matter whether the main capacitor or the voltage dividing capacitor breaks down, the measured voltage value, namely the voltage remote measurement value, can be changed along with the change, voltage measurement is inaccurate, when the deterioration develops to a certain degree, explosion can be caused, and therefore, the judgment of whether the elements of the capacitor voltage transformer break down is the most direct and effective method for evaluating the health state of the capacitor voltage transformer.
The preventive test is to judge whether an element of the capacitor voltage transformer breaks down or not by measuring the capacitance through periodic power failure, the method needs power failure and affects the reliability of power supply, the preventive test period is divided into three years and six years according to different voltage grades, and the health state of the capacitor voltage transformer is in control vacuum between the two periods, so that the real-time evaluation method of the health state of the capacitor voltage transformer, which does not need power failure and does not affect the reliability of power supply, is needed.
Disclosure of Invention
The invention provides a real-time evaluation method for the health state of a capacitor voltage transformer, which solves the problem of power supply reliability caused by a periodic power failure test and the problem that the health state of the capacitor voltage transformer is in vacuum control between two test periods.
In order to solve the technical problems, the technical scheme of the invention is as follows:
a real-time evaluation method for the health state of a capacitor voltage transformer comprises the following steps:
s1: acquiring account information of the capacitor voltage transformer to be evaluated;
s2: acquiring a power grid topological structure, and constructing a comparison object group of the capacitor voltage transformer to be evaluated;
s3: acquiring historical data of voltage remote measurement values of all the capacitor voltage transformers in a comparison object group to form discrete voltage random variables;
s4: calculating a correlation coefficient as an evaluation index, wherein the correlation coefficient is the correlation coefficient of the capacitor voltage transformer to be evaluated and all other capacitor voltage transformers in the comparison object group;
s5: judging whether the health standard is met;
s6: when the health standard is met, updating the discrete voltage random variable after the voltage telemetering value is refreshed, and returning to S4 to execute calculation of a correlation coefficient as an evaluation index; an exception alarm is generated when the health criteria is not met.
In the scheme, because the electrical distance between the capacitor voltage transformers at the same electrical node is short, the voltage fluctuation rule has strong similarity, if the health state changes, the principle that the high consistency of the voltage change trend can be broken can be realized through the mining analysis of historical data of voltage telemetering values of the capacitor voltage transformers, the real-time evaluation of the health state of the capacitor voltage transformers can be realized firstly under the condition of no equipment power failure, and the problems of power supply reliability caused by periodic power failure tests and the problem that the health state of the capacitor voltage transformers is in vacuum management and control between two test periods are solved.
Preferably, because the ledger information of each capacitive voltage transformer includes a site name, a voltage level, a function position, a manufacturer, factory time, a model, a factory number, main parameters, and the like, the ledger information described in step S1 is derived from the asset management system, and includes the site name, the voltage level, and the function position information of the capacitive voltage transformer to be evaluated.
Preferably, the power grid topology structure in step S2 is obtained from an energy management system, and includes SVG graphics, CIM models, and data files.
Preferably, any one of the capacitor voltage transformers and all the capacitor voltage transformers hung under the same high-voltage bus belong to the same electrical node, and the comparison object group in step S2 includes the capacitor voltage transformer to be evaluated and all the capacitor voltage transformers located at the same electrical node.
Preferably, the voltage telemetry value historical data of step S3 includes voltage measurement value historical data of the capacitor voltage transformer to be evaluated, and the voltage telemetry value historical data is obtained from a PI database of the energy management system.
Preferably, the discrete voltage random variable in step S3 is represented as:
in the formula of U1For comparing discrete voltage random variables, U, of the capacitive voltage transformers to be evaluated in the object group2～ UnFor comparing discrete voltage random variables, U, of other capacitive voltage transformers in the object groupijThe voltage telemetry value of the capacitor voltage transformer with the number i in the comparison object group at the time point j is i =1,2, …, n, j =1,2, …, n.
Preferably, the correlation coefficient of step S4
The specific calculation method is as follows:
in the formula (I), the compound is shown in the specification,
representing the correlation coefficients of the capacitor voltage transformer to be evaluated and other capacitor voltage transformers numbered n in the comparison object group,
representing discrete voltage random variables U1And discrete voltage random variable UnThe covariance of (a) of (b),
representing discrete voltage random variables U1The variance of (a) is determined,
representing discrete voltage random variables UnThe variance of (a) is determined,
representing the voltage remote measuring value of the capacitor voltage transformer to be evaluated at a time point i,
indicating voltage remote measurement values of other capacitor voltage transformers with the numbers of n in the comparison object group at the time point i,
represents the average value of all voltage remote measured values of the capacitor voltage transformer to be evaluated in a selected time period,
and the average value of all voltage remote measurement values of other capacitor voltage transformers with the number of n in the comparison object group in the selected time period is represented.
Preferably, the health criterion in step S5 is a judgment threshold of the correlation coefficient, specifically:
the judgment threshold is 95%, the correlation coefficient calculated by the capacitor voltage transformer which does not meet the health standard is less than 95%, and the correlation coefficient calculated by the capacitor voltage transformer which meets the health standard is not less than 95%.
Preferably, the step S6 updates the discrete voltage random variable, specifically:
step S6, the capacitor voltage transformers meeting the health standard form updated discrete voltage random variables after the voltage telemetry values are refreshed, because the health states of all the capacitor voltage transformers at the same electrical node are degraded and the conditions that the voltage variation trends are consistent belong to small probability events, it can be determined that the health standard is met as long as half or more of the correlation coefficients are not less than 0.95, in order to not increase the calculated amount on the premise of meeting the calculation accuracy, the updating of the discrete voltage random variables follows the principle of keeping the time window width unchanged, the earliest historical data is discarded when a new data occurs, the updated discrete voltage random variables perform the correlation coefficient calculation again, and the updated discrete voltage random variables are expressed as:
preferably, in step S6, an abnormal alarm is generated when all the correlation coefficients are less than 95%, and an abnormal alarm is generated when all the correlation coefficients are less than 95% because all the capacitor voltage transformers in the same electrical node have a degraded health status and the conditions that result in consistent voltage variation trends belong to a small probability event.
Compared with the prior art, the technical scheme of the invention has the beneficial effects that:
the invention can solve the problem of power supply reliability caused by periodic power failure tests and the problem that the health state of the capacitor voltage transformer is in vacuum control between two test periods, and can realize real-time evaluation of the health state of the capacitor voltage transformer under the condition of no power failure through mining and analyzing historical data of voltage telemetering value of the capacitor voltage transformer.
Drawings
FIG. 1 is a schematic flow chart of the method of the present invention.
Fig. 2 is a power grid topology diagram provided by the embodiment.
Detailed Description
The drawings are for illustrative purposes only and are not to be construed as limiting the patent;
for the purpose of better illustrating the embodiments, certain features of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product;
it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
Example 1
The embodiment provides a method for evaluating the health state of a capacitor voltage transformer in real time, which comprises the following steps of:
s1: acquiring account information of the capacitor voltage transformer to be evaluated;
s2: acquiring a power grid topological structure, and constructing a comparison object group of the capacitor voltage transformer to be evaluated;
s3: acquiring historical data of voltage remote measurement values of all the capacitor voltage transformers in a comparison object group to form discrete voltage random variables;
s4: calculating a correlation coefficient as an evaluation index, wherein the correlation coefficient is the correlation coefficient of the capacitor voltage transformer to be evaluated and all other capacitor voltage transformers in the comparison object group;
s5: judging whether the health standard is met;
s6: when the health standard is met, updating the discrete voltage random variable after the voltage telemetering value is refreshed, and returning to S4 to execute calculation of a correlation coefficient as an evaluation index; an exception alarm is generated when the health criteria is not met.
The standing book information in step S1 is derived from the asset management system, and includes the site name, the voltage class, and the functional position information of the to-be-evaluated capacitive voltage transformer.
The power grid topology result obtained in step S2 includes SVG graphics, CIM models, and data files.
The comparison object group in step S2 includes the capacitor voltage transformers to be evaluated and all the capacitor voltage transformers located at the same electrical node.
Step S3, the voltage telemetry value historical data includes voltage measurement value historical data of the capacitor voltage transformer to be evaluated, and the voltage telemetry value historical data is obtained from a PI database of the energy management system.
The discrete voltage random variable in step S3 is represented as:
in the formula (I), the compound is shown in the specification,U1for comparing discrete voltage random variables, U, of the capacitive voltage transformers to be evaluated in the object group2～ UnFor comparing discrete voltage random variables, U, of other capacitive voltage transformers in the object groupijThe voltage remote measurement value of the capacitor voltage transformer with the number i in the comparison object group at the time point j is obtained.
Step S4 of the correlation coefficient
The specific calculation method is as follows:
in the formula (I), the compound is shown in the specification,
representing the correlation coefficients of the capacitor voltage transformer to be evaluated and other capacitor voltage transformers numbered n in the comparison object group,
representing discrete voltage random variables U1And discrete voltage random variable UnThe covariance of (a) of (b),
representing discrete voltage random variables U1The variance of (a) is determined,
representing discrete voltage random variables UnThe variance of (a) is determined,
representing the voltage remote measuring value of the capacitor voltage transformer to be evaluated at a time point i,
indicating the electricity of other capacitor voltage transformers with the number n in the comparison object group at the time point iThe pressure is measured at a remote location,
represents the average value of all voltage remote measured values of the capacitor voltage transformer to be evaluated in a selected time period,
and the average value of all voltage remote measurement values of other capacitor voltage transformers with the number of n in the comparison object group in the selected time period is represented.
In step S5, the health criterion is a judgment threshold of the correlation coefficient, and specifically includes:
the judgment threshold is 95%, the correlation coefficient calculated by the capacitor voltage transformer which does not meet the health standard is less than 95%, and the correlation coefficient calculated by the capacitor voltage transformer which meets the health standard is not less than 95%.
In step S6, updating the discrete voltage random variable specifically includes:
updating the discrete voltage random variable follows the principle of keeping the time window width unchanged, discarding the earliest historical data when a new data appears, carrying out correlation coefficient calculation again on the updated discrete voltage random variable, and expressing the updated discrete voltage random variable as follows:
in step S6, an abnormality alarm is generated when all the correlation coefficients are less than 95%.
In the specific implementation process, as shown in fig. 2, the 110kV schwarz substation has 2 main transformers, the #1 main transformer is connected to the 110kV 1M bus, and the #2 main transformer is connected to the 110kV 2M bus. The 110kV 1M bus is provided with three outgoing lines, the 110kV 2M bus is provided with two outgoing lines, each outgoing line adopts a capacitive voltage transformer to measure the line voltage, the voltage measured by each capacitive voltage transformer changes along with the change of the bus voltage, so the voltage can show certain fluctuation, each capacitive voltage transformer can upload voltage measurement data to an energy management system every 15 minutes, 96 measurement points are arranged every day, and all the uploaded data are stored in a PI database.
And S1 is executed, and account information of the capacitor voltage transformer to be evaluated is obtained, specifically, the 110kV Wenhua station 110kV Rogowski line capacitor voltage transformer.
And 2, executing the step 2 to obtain a power grid topological structure of the 110kV Wenhua station, finding that the 110kV Rogowski line, the 110kV Rogowski line and the 110kV Rogowski line are all hung on the 110kV 1M bus and belong to the same electrical node through the topological structure, and forming a comparison object group by the three capacitance voltage transformers.
And 3, executing the step 3, obtaining the voltage telemetering value historical data of all the capacitive voltage transformers in the comparison object group, namely three capacitive voltage transformers of a 110kV Rogowski line, a 110kV Rogowski line and a 110kV Rogowski line, and forming discrete voltage random variables. Considering space limitation and the impracticality of exporting all historical data into space, the matching method provided by the invention is more accurate, and requires that the historical data should not be acquired for less than 10 days in practical application and the sampling time points of each day should not be less than 96. Historical data from 1 month to 30 days in 2020 is derived, and for convenience and comprehensibility, the historical data is represented by table 1, and part of the data limited by space is omitted.
TABLE 1
Step S4 is executed to calculate the correlation coefficient as
=0.9214、
=0.9223。
And step S5 is executed, all correlation coefficients are less than 0.95, and the health state of the 110kV Rogowski line capacitor voltage transformer is judged to be degraded and is consistent with the reality.
In order to make clear the effectiveness and the practicability of the technical scheme of the invention, the data from 1 month and 1 day to 15 days are adopted to carry out correlation coefficient calculation, specifically, the correlation coefficient calculation is carried out
=0.9726、
=0.9798, the correlation coefficient was greater than 0.95, indicating that the state of health of the 110kV roman first line capacitor voltage transformer was degraded only after 15 days 1 month.
The same or similar reference numerals correspond to the same or similar parts;
the terms describing positional relationships in the drawings are for illustrative purposes only and are not to be construed as limiting the patent;
it should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.
Claims (10)
1. A real-time evaluation method for the health state of a capacitor voltage transformer is characterized by comprising the following steps:
s1: acquiring account information of the capacitor voltage transformer to be evaluated;
s2: acquiring a power grid topological structure, and constructing a comparison object group of the capacitor voltage transformer to be evaluated;
s3: acquiring historical data of voltage remote measurement values of all the capacitor voltage transformers in a comparison object group to form discrete voltage random variables;
s4: calculating a correlation coefficient as an evaluation index, wherein the correlation coefficient is the correlation coefficient of the capacitor voltage transformer to be evaluated and all other capacitor voltage transformers in the comparison object group;
s5: judging whether the health standard is met;
s6: when the health standard is met, updating the discrete voltage random variable after the voltage telemetering value is refreshed, and returning to S4 to execute calculation of a correlation coefficient as an evaluation index; an exception alarm is generated when the health criteria is not met.
2. The method for evaluating the health status of the capacitor voltage transformer in real time according to claim 1, wherein the ledger information in step S1 is derived from an asset management system, and includes a site name, a voltage class, and functional location information of the capacitor voltage transformer to be evaluated.
3. The real-time health status evaluation method for the capacitor voltage transformer according to claim 1, wherein the power grid topology structure of step S2 is obtained from an energy management system, and comprises SVG graphics, CIM models, and data files.
4. The method for evaluating the health status of the capacitor voltage transformer in real time as claimed in claim 3, wherein the comparison object group in step S2 includes the capacitor voltage transformer to be evaluated and all capacitor voltage transformers located at the same electrical node.
5. The real-time health status evaluation method for the capacitor voltage transformer according to claim 1, wherein the voltage telemetry value historical data of step S3 comprises voltage measurement value historical data of the capacitor voltage transformer to be evaluated, and the voltage telemetry value historical data is obtained from a PI database of an energy management system.
6. The real-time evaluation method for the health status of the capacitor voltage transformer according to claim 5, wherein the discrete voltage random variable in step S3 is represented as:
in the formula of U1For comparing discrete voltage random variables, U, of the capacitive voltage transformers to be evaluated in the object group2～ UnFor comparing discrete voltage random variables, U, of other capacitive voltage transformers in the object groupijI =1,2, …, n, j =1,2, …, n, which is a voltage remote measurement value of the capacitor voltage transformer numbered i in the comparison object group at time j.
7. The real-time evaluation method for the health status of the capacitor voltage transformer according to claim 6, wherein the correlation coefficient of the step S4
The specific calculation method is as follows:
in the formula (I), the compound is shown in the specification,
representing the correlation coefficients of the capacitor voltage transformer to be evaluated and other capacitor voltage transformers numbered n in the comparison object group,
representing discrete voltage random variables U1And discrete voltage random variable UnThe covariance of (a) of (b),
representing discrete voltage random variables U1The variance of (a) is determined,
representing discrete voltage random variables UnThe variance of (a) is determined,
the voltage remote measuring value of the capacitor voltage transformer to be evaluated at the time point i is shown, the voltage remote measuring values of other capacitor voltage transformers with the numbers of n in the comparison object group at the time point i are shown,
represents the average value of all voltage remote measured values of the capacitor voltage transformer to be evaluated in a selected time period,
and the average value of all voltage remote measurement values of other capacitor voltage transformers with the number of n in the comparison object group in the selected time period is represented.
8. The real-time evaluation method for the health status of the capacitor voltage transformer according to claim 7, wherein the health criterion in step S5 is a judgment threshold of a correlation coefficient, and specifically comprises:
the judgment threshold is 95%, the correlation coefficient calculated by the capacitor voltage transformer which does not meet the health standard is less than 95%, and the correlation coefficient calculated by the capacitor voltage transformer which meets the health standard is not less than 95%.
9. The real-time evaluation method for the health status of the capacitor voltage transformer according to claim 8, wherein the step S6 is to update a discrete voltage random variable, specifically:
updating the discrete voltage random variable follows the principle of keeping the time window width unchanged, discarding the earliest historical data when a new data appears, carrying out correlation coefficient calculation again on the updated discrete voltage random variable, and expressing the updated discrete voltage random variable as follows:
10. the method for evaluating the health status of the capacitor voltage transformer according to any one of claims 7 to 9, wherein in step S6, an abnormal alarm is generated when all the correlation coefficients are less than 95%.
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