CN105277910A - Method and system for remotely assessing reliability of power quality on-line monitoring device - Google Patents
Method and system for remotely assessing reliability of power quality on-line monitoring device Download PDFInfo
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Abstract
The invention provides a method and a system for remotely assessing reliability of a power quality on-line monitoring device. The method comprises: a querying and calculating step of respectively calculating data integrity rate K1 and data accuracy K2 based on regularly recorded historical data of power quality stored in a database of the power quality on-line monitoring device; a calculating and processing step of calculating the reliability K of the monitoring device based on the data integrity rate K1 and the data accuracy K2. The beneficial effects of the method and the system are: the invention provides a method for remotely assessing the reliability of a power quality monitoring device based on the operation monitoring for data quality of the power quality, the monitoring device and network and communication software thereof. The method can be automatically implemented by application software. Besides reliability assessment of a single power quality monitoring device, the method can be applied to comprehensive assessments such as regional comprehensive reliability and comprehensive reliability of specific types of monitoring devices. The method is a high-efficient and low-cost management method.
Description
Technical field
The present invention relates to electric energy quality monitoring and administrative skill field, particularly relate to the method and system of remote evaluation electric energy quality on-line monitoring device reliability.
Background technology
The operational management of equipment for monitoring power quality is one of action of quality of power supply technical supervision.Equipment reliability management is one of important content of equipment operation management.The reliability decrease of so-called equipment for monitoring power quality, the device that finger device hardware fault causes on the one hand cannot normally run, although also comprising device can also maintain normal operation on the one hand, accuracy of measurement declines, produces invalid abnormal data etc.On-site experience shows, after electric energy quality on-line monitoring device long-time running unavoidable due to component aging, the interference of the severe running environment of transformer station that lost efficacy, is subject to, thus cause the rising of plant failure rate, accuracy of measurement decline or produce invalid abnormal data, namely device global reliability reduces.
Equipment dependability assessment conventional is at present mainly for device hardware classes reliability failure, and appraisal procedure mainly contains:
1, based on the reliability of the Calculation of Reliability Whole Equipment of device components.This method is the theoretical appraisal to equipment dependability, does not consider the impact of equipment operating environment, and therefore error is comparatively large, usually only for the Pre-Evaluation to equipment dependability.
2, periodic detection assessment apparatus reliability is carried out based on to equipment.This method cost is high, and needs arrestment to run, and be generally used for electric power primary equipment as transformer, Capacitor banks, and the secondary device of part particular importance is as Source of Gateway Meter etc.Equipment periodic detection can be divided into again Site Detection and test in laboratory two kinds.
3, manual patrol assessment apparatus reliability is carried out based on to equipment.This method cost of labor is high, cannot accomplish reliability prediction, and can not be applicable to unattended operation transformer station.
With regard to electric energy quality on-line monitoring device, " DL/T1228-2013 equipment for monitoring power quality operating standard " also proposes within every 3 years, to carry out periodic detection, apparatus for evaluating reliability to the electric energy quality on-line monitoring device after putting into operation.But, electric energy quality on-line monitoring device Main Basis " GB/T19862-2005 power quality monitoring device General Requirement " is developed, and in this standard, do not require that electric energy quality on-line monitoring device provides field-checking function and verification mouth, cause current electric energy quality on-line monitoring device to carry out field-checking, laboratory can only be dismantled go back to and detect.In addition, equipment for monitoring power quality One's name is legion, installation dispersion, if every 3 years dismantle back test in laboratory once, great manpower and materials cost will be needed to drop into, and realizability is poor.Therefore in practice, namely electric energy quality on-line monitoring device no longer detects after putting into operation often, and monitoring device reliability, especially the reliability hidden danger of data accuracy, correctness aspect is very big.
In sum, the effective technology of shortage and ladder of management are assessed electric energy quality on-line monitoring device reliability at present.One of most direct result that electric energy quality on-line monitoring device reliability reduces is the integrality and the correctness that have influence on power quality data, and quantity not, the power quality data of poor quality will cause the senior application of other qualities of power supply such as power quality disturbance location, region quality of power supply datum-plane evaluation, electric network reliability analysis etc. cannot carry out or the decline of application result confidence level.Therefore, the reliability estimation method of quick and easy, the low cost studying electric energy quality on-line monitoring device is necessary.
Summary of the invention
The invention provides a kind of method of remote evaluation electric energy quality on-line monitoring device reliability, comprise the steps:
Query count step: based on the quality of power supply time recording historical data stored in Electric Power Quality On-line Monitor System database, calculates data integrity rate K1 and data accuracy K2 respectively;
Computing step: calculate monitoring device reliability K based on data integrity rate K1 and data accuracy K2, K=K1* λ 1+K2* λ 2, wherein λ 1 and λ 2 is weights, λ 1 and λ 2 represents that the data integrity rate caused due to monitoring device reason declines and data reliability declines, λ 1+ λ 2=1 respectively;
Data integrity rate K1=(data amount check of 1-missing data number/expectation) * 100%, wherein, the data amount check expected calculated according to the time interval of quality of power supply time recording historical data;
Data accuracy K2=(data amount check of 1-abnormal data number/actual storage) * 100%.Wherein, abnormal data index is the data of FALSE according to quality factor.
As a further improvement on the present invention, the weight λ 2=1-λ 1 of weight λ 1=T1/ (the T1+T2+T3)+σ of described data integrity rate K1, data accuracy K2;
Wherein, T1 represents the total power down duration of monitoring device, and T2 represents the total duration of communication disruption, and T3 represents that communication software always exits duration, and as T1+T2+T3=0, T1/ (T1+T2+T3) gets 0;
σ is deviation factors, represents that σ value is 0 ~ 0.1, can artificially adjust within the scope of this because some inevitable ignorance factors cause data integrity rate to decline.
As a further improvement on the present invention, described weight λ 1 and λ 2 is determined by expert estimation.
As a further improvement on the present invention, the method also comprises comprehensive reliability calculation procedure, in comprehensive reliability calculation procedure:
By the monitoring device reliability K of separate unit, the comprehensive reliability K of multiple stage monitoring device in zoning
q;
By the monitoring device reliability K of separate unit, calculate the comprehensive reliability K of same model multiple stage monitoring device
x.
As a further improvement on the present invention, the method also comprises rating step, in rating step, according to monitoring device reliability K, carries out reliability split pole.
Present invention also offers a kind of system of remote evaluation electric energy quality on-line monitoring device reliability, comprising:
Query count module: based on the quality of power supply time recording historical data stored in Electric Power Quality On-line Monitor System database, calculates data integrity rate K1 and data accuracy K2 respectively;
Computing module: calculate monitoring device reliability K based on data integrity rate K1 and data accuracy K2, K=K1* λ 1+K2* λ 2, wherein λ 1 and λ 2 is weights, λ 1 and λ 2 represents that the data integrity rate caused due to monitoring device reason declines and data reliability declines, λ 1+ λ 2=1 respectively;
Data integrity rate K1=(data amount check of 1-missing data number/expectation) * 100%, wherein, the data amount check expected calculated according to the time interval of quality of power supply time recording historical data;
Data accuracy K2=(data amount check of 1-abnormal data number/actual storage) * 100%.Wherein, abnormal data index is the data of FALSE according to quality factor.
As a further improvement on the present invention, the weight λ 2=1-λ 1 of weight λ 1=T1/ (the T1+T2+T3)+σ of described data integrity rate K1, data accuracy K2;
Wherein, T1 represents the total power down duration of monitoring device, and T2 represents the total duration of communication disruption, and T3 represents that communication software always exits duration, and as T1+T2+T3=0, T1/ (T1+T2+T3) gets 0;
σ is deviation factors, represents that σ value is 0 ~ 0.1, can artificially adjust within the scope of this because some inevitable ignorance factors cause data integrity rate to decline.
As a further improvement on the present invention, described weight λ 1 and λ 2 is determined by expert estimation.
As a further improvement on the present invention, this system also comprises comprehensive reliability computing module, in comprehensive reliability computing module:
By the monitoring device reliability K of separate unit, the comprehensive reliability K of multiple stage monitoring device in zoning
q;
By the monitoring device reliability K of separate unit, calculate the comprehensive reliability K of same model multiple stage monitoring device
x.
As a further improvement on the present invention, this system also comprises grading module, in grading module, according to monitoring device reliability K, carries out reliability split pole.
The invention has the beneficial effects as follows: the present invention is directed to after electric energy quality on-line monitoring device puts into operation and lack high-level efficiency, the detection means of low cost, thus after causing monitoring device to run a period of time, easily there is the present situation of reliability decrease, propose a kind of based on to power quality data quality, monitoring device and network thereof, communication softwares etc. carry out operation monitoring, thus the method for remote evaluation equipment for monitoring power quality reliability, the method can be realized automatically by application software, except can realizing separate unit equipment for monitoring power quality reliability assessment, the comprehensive reliability in all right feasible region, the comprehensive assessments such as the comprehensive reliability of specific model monitoring device, it is a kind of high-level efficiency, the ladder of management of low cost.
Accompanying drawing explanation
Fig. 1 is method flow diagram of the present invention.
Embodiment
It is exactly that the quality of data declines that monitoring device reliability reduces the most direct result caused, be mainly reflected in data integrity rate aspect and data accuracy aspect, data integrity rate and data accuracy all can calculate based on the quality of power supply time recording historical data stored in database.
The invention discloses a kind of method of remote evaluation electric energy quality on-line monitoring device reliability, comprise the steps:
Query count step: based on the quality of power supply time recording historical data stored in Electric Power Quality On-line Monitor System database, calculates data integrity rate K1 and data accuracy K2 respectively;
Computing step: calculate monitoring device reliability K based on data integrity rate K1 and data accuracy K2, K=K1* λ 1+K2* λ 2, wherein λ 1 and λ 2 is weights, λ 1 and λ 2 represents that the data integrity rate caused due to monitoring device reason declines and data reliability declines, λ 1+ λ 2=1 respectively;
Data integrity rate K1=(data amount check of 1-missing data number/expectation) * 100%, wherein, the data amount check expected calculated according to the time interval of quality of power supply time recording historical data;
Data accuracy K2=(data amount check of 1-abnormal data number/actual storage) * 100%.Wherein, abnormal data index is the data of FALSE according to quality factor;
Weight acquiescence adopts expert graded to determine, and can adjust according to operation monitoring data automated intelligent.
In the present invention, electric energy quality on-line monitoring device can referred to as monitoring device.
What cause data integrity rate K1 to decline is a variety of because have, and except monitoring device reliability reduces, also has communication network failure, master station communication software fault etc.Therefore, calculate that data integrity rate is low can not judge that the reliability of electric energy quality on-line monitoring device is low, also needs to carry out diagnostic analysis at this point, get rid of other possible causes, data integrity rate weight λ 1 could be determined more accurately.
So, just need to carry out operation monitoring and diagnostic analysis to electric energy quality on-line monitoring device and communication network, master station communication software etc., confirm data integrity rate weight λ 1.
The content of operation monitoring and diagnostic analysis comprises:
1) operation exception of monitoring device comprises power down, communication module fault, deadlock etc.The device power down stored in the operation monitoring Main Basis database of monitoring device, power on event, adds up the essential information (device model, sequence number, company-information) of every platform monitoring device, power down number of times, each data such as power down time and power-on time, total power down duration, power down duration accounting.
2) communicating interrupt, the recovery event that store in the operation monitoring Main Basis database of monitoring device communication network, add up the network configuration (comprising IP, port) of every platform monitoring device, Current communications situation, communicating interrupt number of times, each data such as communication interruption time and release time, total communicating interrupt duration, communicating interrupt accounting.
3) System Operation Log stored in the operation monitoring Main Basis database of master station communication software, situation is moved back in the throwing of statistics communication software, comprises time of at every turn putting into operation and the data such as time out of service, total duration out of service.
In the present invention, by automatically calculating or having the mode determination data integrity rate of expert estimation and the weight of data accuracy.
The formula of automatic calculating weight is as follows, does not get rid of more advanced weighing computation method:
The weight λ 2=1-λ 1 of weight λ 1=T1/ (the T1+T2+T3)+σ of described data integrity rate K1, data accuracy K2; Wherein, T1 represents the total power down duration of monitoring device, and T2 represents the total duration of communication disruption, and T3 represents that communication software always exits duration.As T1+T2+T3=0, T1/ (T1+T2+T3) gets 0.
Consider that inevitable some ignorance factors of existence cause data integrity rate to decline, institute with the formula in devise σ be deviation factors, represent that σ value is 0 ~ 0.1, can artificially adjust within the scope of this because some inevitable ignorance factors cause data integrity rate to decline.
After λ 1 determines, λ 2 can determine.
From management view, what more pay close attention to is the overall target such as comprehensive reliability of comprehensive reliability in region, certain model monitoring device, and these indexs can the comprehensive reliability K of multiple stage monitoring device in zoning based on separate unit electric energy quality on-line monitoring device reliability K
q, the comprehensive reliability K of same model multiple stage monitoring device
xetc. overall target, that is, the method also comprises comprehensive reliability calculation procedure, in comprehensive reliability calculation procedure:
By the monitoring device reliability K of separate unit, the comprehensive reliability K of multiple stage monitoring device in zoning
q, computing method can adopt arithmetic to equal the methods such as nothing, analytical hierarchy process;
By the monitoring device reliability K of separate unit, calculate the comprehensive reliability K of same model multiple stage monitoring device
x, computing method can adopt arithmetic to equal the methods such as nothing, analytical hierarchy process.
The method also comprises rating step, in rating step, according to monitoring device reliability K, carries out reliability split pole.
That is, after monitoring device reliability K calculates, can reliability classification be carried out, according to grid company general management custom, equipment for monitoring power quality reliability can be divided into excellent, good, in, difference level Four.Excellent correspond to K be in 90 ~ 100 points of scopes, good correspond to K be in 80 ~ 90 points, in correspond to K be in 60 ~ 80 points, difference correspond to K be in 0 ~ 60 point.
The method of remote evaluation electric energy quality on-line monitoring device reliability of the present invention can be embedded in certain software program and uses.
The present invention is based on the diagnostic analysis to power quality data quality, can long-range realization to the reliability assessment of electric energy quality on-line monitoring device.
The invention also discloses a kind of system of remote evaluation electric energy quality on-line monitoring device reliability, comprising:
Query count module: based on the quality of power supply time recording historical data stored in Electric Power Quality On-line Monitor System database, calculates data integrity rate K1 and data accuracy K2 respectively;
Computing module: calculate monitoring device reliability K based on data integrity rate K1 and data accuracy K2, K=K1* λ 1+K2* λ 2, wherein λ 1 and λ 2 is weights, λ 1 and λ 2 represents that the data integrity rate caused due to monitoring device reason declines and data reliability declines, λ 1+ λ 2=1 respectively;
Data integrity rate K1=(data amount check of 1-missing data number/expectation) * 100%, wherein, the data amount check expected calculated according to the time interval of quality of power supply time recording historical data;
Data accuracy K2=(data amount check of 1-abnormal data number/actual storage) * 100%.Wherein, abnormal data index is the data of FALSE according to quality factor.
The weight λ 2=1-λ 1 of weight λ 1=T1/ (the T1+T2+T3)+σ of described data integrity rate K1, data accuracy K2;
Wherein, T1 represents the total power down duration of monitoring device, and T2 represents the total duration of communication disruption, and T3 represents that communication software always exits duration, and as T1+T2+T3=0, T1/ (T1+T2+T3) gets 0;
σ is deviation factors, represents that σ value is 0 ~ 0.1, can artificially adjust within the scope of this because some inevitable ignorance factors cause data integrity rate to decline.
As an embodiment of native system, described weight λ 1 and λ 2 is determined by expert estimation.
This system also comprises comprehensive reliability computing module, in comprehensive reliability computing module:
By the monitoring device reliability K of separate unit, the comprehensive reliability K of multiple stage monitoring device in zoning
q;
By the monitoring device reliability K of separate unit, calculate the comprehensive reliability K of same model multiple stage monitoring device
x.
This system also comprises grading module, in grading module, according to monitoring device reliability K, carries out reliability split pole.
The present invention is directed to after electric energy quality on-line monitoring device puts into operation and lack high-level efficiency, the detection means of low cost, thus after causing monitoring device to run a period of time, easily there is the present situation of reliability decrease, propose a kind of based on to power quality data quality, monitoring device and network thereof, communication softwares etc. carry out operation monitoring, thus the method for remote evaluation equipment for monitoring power quality reliability, the method can be realized automatically by application software, except can realizing separate unit equipment for monitoring power quality reliability assessment, the comprehensive reliability in all right feasible region, the comprehensive assessments such as the comprehensive reliability of specific model monitoring device, it is a kind of high-level efficiency, the ladder of management of low cost.
Above content is in conjunction with concrete preferred implementation further description made for the present invention, can not assert that specific embodiment of the invention is confined to these explanations.For general technical staff of the technical field of the invention, without departing from the inventive concept of the premise, some simple deduction or replace can also be made, all should be considered as belonging to protection scope of the present invention.
Claims (10)
1. a method for remote evaluation electric energy quality on-line monitoring device reliability, is characterized in that, comprises the steps:
Query count step: based on the quality of power supply time recording historical data stored in Electric Power Quality On-line Monitor System database, calculates data integrity rate K1 and data accuracy K2 respectively;
Computing step: calculate monitoring device reliability K based on data integrity rate K1 and data accuracy K2, K=K1* λ 1+K2* λ 2, wherein λ 1 and λ 2 is weights, λ 1 and λ 2 represents that the data integrity rate caused due to monitoring device reason declines and data reliability declines, λ 1+ λ 2=1 respectively;
Data integrity rate K1=(data amount check of 1-missing data number/expectation) * 100%, wherein, the data amount check expected calculated according to the time interval of quality of power supply time recording historical data;
Data accuracy K2=(data amount check of 1-abnormal data number/actual storage) * 100%.Wherein, abnormal data index is the data of FALSE according to quality factor.
2. method according to claim 1, is characterized in that, the weight λ 2=1-λ 1 of weight λ 1=T1/ (the T1+T2+T3)+σ of described data integrity rate K1, data accuracy K2;
Wherein, T1 represents the total power down duration of monitoring device, and T2 represents the total duration of communication disruption, and T3 represents that communication software always exits duration, and as T1+T2+T3=0, T1/ (T1+T2+T3) gets 0;
σ is deviation factors, represents that σ value is 0 ~ 0.1, can artificially adjust within the scope of this because some inevitable ignorance factors cause data integrity rate to decline.
3. method according to claim 1, is characterized in that, described weight λ 1 and λ 2 is determined by expert estimation.
4. method according to claim 1, is characterized in that, the method also comprises comprehensive reliability calculation procedure, in comprehensive reliability calculation procedure:
By the monitoring device reliability K of separate unit, the comprehensive reliability K of multiple stage monitoring device in zoning
q;
By the monitoring device reliability K of separate unit, calculate the comprehensive reliability K of same model multiple stage monitoring device
x.
5. the method according to any one of Claims 1-4, is characterized in that, the method also comprises rating step, in rating step, according to monitoring device reliability K, carries out reliability split pole.
6. the system of a remote evaluation electric energy quality on-line monitoring device reliability, it is characterized in that, comprise: query count module: based on the quality of power supply time recording historical data stored in Electric Power Quality On-line Monitor System database, calculate data integrity rate K1 and data accuracy K2 respectively;
Computing module: calculate monitoring device reliability K based on data integrity rate K1 and data accuracy K2, K=K1* λ 1+K2* λ 2, wherein λ 1 and λ 2 is weights, λ 1 and λ 2 represents that the data integrity rate caused due to monitoring device reason declines and data reliability declines, λ 1+ λ 2=1 respectively;
Data integrity rate K1=(data amount check of 1-missing data number/expectation) * 100%, wherein, the data amount check expected calculated according to the time interval of quality of power supply time recording historical data;
Data accuracy K2=(data amount check of 1-abnormal data number/actual storage) * 100%.Wherein, abnormal data index is the data of FALSE according to quality factor.
7. system according to claim 6, is characterized in that, the weight λ 2=1-λ 1 of weight λ 1=T1/ (the T1+T2+T3)+σ of described data integrity rate K1, data accuracy K2;
Wherein, T1 represents the total power down duration of monitoring device, and T2 represents the total duration of communication disruption, and T3 represents that communication software always exits duration, and as T1+T2+T3=0, T1/ (T1+T2+T3) gets 0;
σ is deviation factors, represents that σ value is 0 ~ 0.1, can artificially adjust within the scope of this because some inevitable ignorance factors cause data integrity rate to decline.
8. system according to claim 6, is characterized in that, described weight λ 1 and λ 2 is determined by expert estimation.
9. system according to claim 6, is characterized in that, this system also comprises comprehensive reliability computing module, in comprehensive reliability computing module:
By the monitoring device reliability K of separate unit, the comprehensive reliability K of multiple stage monitoring device in zoning
q;
By the monitoring device reliability K of separate unit, calculate the comprehensive reliability K of same model multiple stage monitoring device
x.
10. the system according to any one of claim 6 to 9, is characterized in that, this system also comprises grading module, in grading module, according to monitoring device reliability K, carries out reliability split pole.
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| CN105277910B (en) | 2018-06-26 |
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