CN105117512B - The evaluation method and device of transformer early warning value - Google Patents
The evaluation method and device of transformer early warning value Download PDFInfo
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- CN105117512B CN105117512B CN201510438809.7A CN201510438809A CN105117512B CN 105117512 B CN105117512 B CN 105117512B CN 201510438809 A CN201510438809 A CN 201510438809A CN 105117512 B CN105117512 B CN 105117512B
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Abstract
The invention discloses a kind of evaluation methods and device of transformer early warning value.Wherein, this method includes：Obtain the concentration of institute's dissolved gas and the cumulative distribution function of factor of created gase in the transformer oil of transformer；Corresponding inverse cumulative distribution function is determined according to cumulative distribution function；The defects of obtaining transformer rate and/or failure rate；After ratio of defects is got, according to ratio of defects and inverse cumulative distribution function estimated concentration and the demand value of factor of created gase are utilized；After failure rate is got, according to failure rate and inverse cumulative distribution function estimated concentration and the warning value of factor of created gase are utilized；Export demand value and warning value.The present invention solve due in the relevant technologies to transformer carry out early warning when, the early warning value used does not account for the failure rate and ratio of defects of transformer attribute difference in itself and transformer, and caused by be susceptible to the technical issues of failing to report alert or false alarm when carrying out fault pre-alarming to transformer.
Description
Technical field
The present invention relates to power electronics field, a kind of evaluation method in particular to transformer early warning value and
Device.
Background technology
For transformer as important power transmission and transforming equipment, operational reliability is directly related to the safety fortune of entire electric system
Row.At present, the online prison based on Gases Dissolved in Transformer Oil analysis (Dissolved Gas Analysis, referred to as DGA)
Survey technology realizes fault pre-alarming by monitoring in transformer the content of oil dissolved gas and the factor of created gase of gas in real time.Work as prison
When the content and factor of created gase of certain gas measured are more than some preset value, monitoring system provides corresponding alarm signal
Breath.Therefore, situations such as setting rational alarming value, generation wrong report can be effectively prevented from, failed to report, and monitored on-line to improving
The early warning accuracy of system has great importance.
In recent years, some study to chromatography online monitoring system for transformer oil threshold value both at home and abroad.For example, article《Base
In the oil-immerged inversed current transformer hydrogen Threshold Analysis of significant difference》(Sun Xiang, Zhejiang electric power, 2014) utilize significance difference
The amounts of hydrogen dissolved in Oil of Current Transformer in specific analysis regional power grid calculates the relevant parameter threshold value of hydrogen.This method
A kind of relevant parameter threshold value of dissolved gas is only calculated, and the failure rate and defect of equipment are not accounted in calculating process
Rate causes result of calculation inaccurate.Article《The research of transformer diagnosis threshold value based on live oil colours modal data》(Song Anqi,
North China Electric Power University, 2013) using the part oil chromatographic data at scene, calculating transformer oil dissolved gas reaches national standard and pays attention to
Failure rate when value, minimal error critical value and least disadvantage critical value, and the critical value of Selective dissolution gas accordingly.This method
Without reference to the calculating of the relevant parameter threshold value of oil dissolved gas, but the failure rate for laying particular emphasis on equipment calculates, and critical
The selection of value is largely dependent upon the experience of field personnel, causes data decimation unreliable.Article《Based on oil colours
The transformer Reliability assessment method of modal data》(Zhang Yuning, power science and engineering, 2013) also utilizes the oil chromatography number at scene
The reliability of transformer when reaching national standard demand value according to, calculating transformer oil dissolved gas, and to transformer exception state
Divided rank.This method is also without reference to the calculating of the relevant parameter threshold value of oil dissolved gas, and do not have in calculating process
Consider the failure rate and ratio of defects of equipment, cause result of calculation inaccurate.
In addition, patent《A kind of power market optimal hedging ratio estimation method》(Wang Yuanyuan, Institutes Of Technology Of Changsha,
2010) to the power market transaction historical data of acquisition, the electricity market dynamic hedge guarantor based on T-Copula-GARCH is constructed
It is worth model, finally estimates Optimal Hedge Ratio.Patent《A kind of computational methods of hedging efficiency of electric power future market》
(simple treasure, Guangxi University, 2010) using GARCH models and binary conditions G-Copula joint density functions, construction is based on G-
The electricity market Dynamic Hedging model of Copula-GARCH calculates hedging efficiency of electric power future market.More than two
Patent is to be directed to the related data of power economy to be calculated, and builds dynamic model, calculates corresponding estimated value.Due to
Economic data is not related to equipment failure rate and ratio of defects, and the structure of above-mentioned model is unrelated with failure rate and ratio of defects.
The existing determining scheme about Dissolved Gas Content in Transformer Oil and the standard demand value of factor of created gase both at home and abroad,
Gas of the generally existing based on type less in transformer classifies the problem of excessively rough to transformer.And in transformer reality
In operation, early warning is carried out to transformer by a certain or demand value of two kinds of gas contents and factor of created gase, it is easy to lead
Cause is failed to report or is reported by mistake, and only sets one " demand value " so that early warning system strategy is excessively single, increases the cost of overhaul.
It is that the classification of transformer is excessively rough to set demand value, does not fully consider the difference between transformer.
For it is above-mentioned the problem of, currently no effective solution has been proposed.
Invention content
An embodiment of the present invention provides a kind of evaluation method and device of transformer early warning value, at least to solve due to correlation
In technology when carrying out early warning to transformer, the early warning value that uses does not account for transformer attribute difference in itself and transformation
The failure rate and ratio of defects of device, and caused by the skill for failing to report alert or false alarm is susceptible to when carrying out fault pre-alarming to transformer
Art problem.
One side according to embodiments of the present invention provides a kind of evaluation method of transformer early warning value, including：It obtains
The concentration of institute's dissolved gas and the cumulative distribution function of factor of created gase in the transformer oil of transformer；According to above-mentioned cumulative distribution function
Determine corresponding inverse cumulative distribution function；The defects of obtaining above-mentioned transformer rate and/or failure rate；Get ratio of defects it
Afterwards, the demand value of above-mentioned concentration and above-mentioned factor of created gase is estimated according to drawbacks described above rate and using above-mentioned inverse cumulative distribution function；
After getting failure rate, above-mentioned concentration and above-mentioned aerogenesis are estimated according to above-mentioned failure rate and using above-mentioned inverse cumulative distribution function
The warning value of rate；Export above-mentioned demand value and above-mentioned warning value.
Further, it is determined that the step of above-mentioned cumulative distribution function, includes：Obtain the different lower transformer oil of transformer classification
The concentration and factor of created gase data of middle institute's dissolved gas；The cumulative distribution letter under different transformer classification is determined according to above-mentioned data
Number.
Further, the concentration of institute's dissolved gas and factor of created gase data packet in the different lower transformer oil of transformer classification are obtained
It includes：Obtain the concentration data of institute's dissolved gas in the transformer oil of all transformers in target area；According to above-mentioned all transformations
The attribute information of device carries out differentiation classification to above-mentioned concentration data, obtains being dissolved in the different lower transformer oil of transformer classification
The concentration data of gas；Any two adjacent data calculates such concentration numbers in concentration data under being classified according to each transformer
According to the factor of created gase of corresponding gas, the factor of created gase data of institute's dissolved gas in the different lower transformer oil of transformer classification are obtained.
Further, the concentration of institute's dissolved gas and factor of created gase data in transformer oil in the case where obtaining the classification of different transformers
Later, the above method further includes：According to the concentration numbers and factor of created gase of institute's dissolved gas in the lower transformer oil of different transformers classification
Data draw corresponding statistic histogram and matched curve；It is determined according to the above-mentioned statistic histogram of drafting and above-mentioned matched curve
The concentration of institute's dissolved gas and the distributed model of factor of created gase in each lower transformer oil of transformer classification；By above-mentioned distributed model pair
The distribution function answered is as the concentration of institute's dissolved gas and the accumulation of factor of created gase in above-mentioned each lower transformer oil of transformer classification
Distribution function.
Further, above-mentioned cumulative distribution function is Weibull Function, and above-mentioned inverse cumulative distribution function is above-mentioned prestige
The inverse function of boolean's distribution function.
Further, the defects of obtaining above-mentioned transformer rate and/or failure rate include：It obtains under each transformer classification
Transformer field service information；The transformer under above-mentioned each transformer classification is extracted from above-mentioned transformer field service information
The defects of rate and/or failure rate.
Further, above-mentioned concentration and above-mentioned aerogenesis are estimated according to drawbacks described above rate and using above-mentioned inverse cumulative distribution function
The demand value of rate includes：When variate-value is 1- ratio of defects, the functional value estimated by above-mentioned inverse cumulative distribution function is made
For above-mentioned demand value.
Further, above-mentioned concentration and above-mentioned aerogenesis are estimated according to above-mentioned failure rate and using above-mentioned inverse cumulative distribution function
The warning value of rate includes：When variate-value is 1- failure rates, the functional value estimated by above-mentioned inverse cumulative distribution function is made
For above-mentioned warning value.
Another aspect according to embodiments of the present invention additionally provides a kind of estimation device of transformer early warning value, including：The
One acquiring unit, for obtaining the concentration of institute's dissolved gas and the cumulative distribution function of factor of created gase in the transformer oil of transformer；
First determination unit, for determining corresponding inverse cumulative distribution function according to above-mentioned cumulative distribution function；Second acquisition unit is used
Rate and/or failure rate in obtain above-mentioned transformer the defects of；Evaluation unit, for after ratio of defects is got, according to above-mentioned
Ratio of defects and the demand value that above-mentioned concentration and above-mentioned factor of created gase are estimated using above-mentioned inverse cumulative distribution function；Getting failure rate
Later, above-mentioned concentration and the warning value of above-mentioned factor of created gase are estimated according to above-mentioned failure rate and using above-mentioned inverse cumulative distribution function；
Output unit, for exporting above-mentioned demand value and above-mentioned warning value.
Further, above device further includes：Second determination unit, for determining above-mentioned cumulative distribution function, above-mentioned
Two determination units include：First acquisition module, for obtaining the dense of institute's dissolved gas in the lower transformer oil of different transformers classification
Degree and factor of created gase data；Determining module, for determining the cumulative distribution function under different transformer classification according to above-mentioned data.
Further, above-mentioned first acquisition module includes：Acquisition submodule, for obtaining all transformers in target area
Transformer oil in institute's dissolved gas concentration data；Classification submodule, for the attribute information according to above-mentioned all transformers
Differentiation classification is carried out to above-mentioned concentration data, obtains the concentration numbers of institute's dissolved gas in the different lower transformer oil of transformer classification
According to；Computational submodule, it is dense for calculating such according to any two adjacent data in the concentration data under the classification of each transformer
The factor of created gase of the corresponding gas of degrees of data obtains the factor of created gase number of institute's dissolved gas in the different lower transformer oil of transformer classification
According to.
Further, above device further includes：Image-drawing unit, in the transformer oil in the case where obtaining different transformer classification
After the concentration of institute's dissolved gas and factor of created gase data, classified the dense of institute's dissolved gas in lower transformer oil according to different transformers
The number of degrees and factor of created gase data draw corresponding statistic histogram and matched curve；Third determination unit, for according to drafting
It states statistic histogram and above-mentioned matched curve determines the concentration of institute's dissolved gas and production in the lower transformer oil of each transformer classification
The distributed model of gas rate, and using the corresponding distribution function of above-mentioned distributed model as above-mentioned each lower transformer oil of transformer classification
The concentration of middle institute's dissolved gas and the cumulative distribution function of factor of created gase.
Further, above-mentioned second acquisition unit includes：Second acquisition module, for obtaining under each transformer classification
Transformer field service information；Extraction module, for extracting above-mentioned each transformer from above-mentioned transformer field service information
The defects of transformer under classification rate and/or failure rate.
Further, above-mentioned evaluation unit is additionally operable to when variate-value is 1- ratio of defects, will be by above-mentioned inverse cumulative distribution letter
The functional value that number estimation obtains is as above-mentioned demand value.
Further, above-mentioned evaluation unit is additionally operable to when variate-value is 1- failure rates, will be by above-mentioned inverse cumulative distribution letter
The functional value that number estimation obtains is as above-mentioned warning value.
In embodiments of the present invention, using rate the defects of the attributive character and transformer for combining transformer itself and failure rate
Mode, the concentration of institute's dissolved gas and the cumulative distribution function of factor of created gase in the transformer oil by obtaining transformer；According to
Cumulative distribution function determines corresponding inverse cumulative distribution function；The defects of obtaining transformer rate and/or failure rate；It is scarce getting
After the rate of falling into, according to ratio of defects and inverse cumulative distribution function estimated concentration and the demand value of factor of created gase are utilized；Getting failure
After rate, according to failure rate and inverse cumulative distribution function estimated concentration and the warning value of factor of created gase are utilized；Export demand value and police
Indicating value has reached using molten in the oil of rate the defects of the attributive character difference and transformer for considering transformer itself and failure rate
The purpose of the early warning value progress early warning of gas and factor of created gase is solved, it is achieved thereby that the technique effect that prevents from failing to report or report by mistake, and then
It solves since, when carrying out early warning to transformer, the early warning value used does not account for the category of transformer in itself in the relevant technologies
The failure rate and ratio of defects of sex differernce and transformer, and caused by be susceptible to and fail to report when carrying out fault pre-alarming to transformer
The technical issues of alert or false alarm.
Description of the drawings
Attached drawing described herein is used to provide further understanding of the present invention, and forms the part of the application, this hair
Bright illustrative embodiments and their description do not constitute improper limitations of the present invention for explaining the present invention.In the accompanying drawings：
Fig. 1 is a kind of flow chart of the evaluation method of optional transformer early warning value according to embodiments of the present invention；
Fig. 2 is the statistic histogram and plan for the content that hydrogen is dissolved in 220kV transformer oil according to embodiments of the present invention
Close curve；
Fig. 3 be in 220kV transformer oil according to embodiments of the present invention dissolve ethylene factor of created gase statistic histogram and
Matched curve；And
Fig. 4 is a kind of schematic diagram of the estimation device of optional transformer early warning value according to embodiments of the present invention.
Specific embodiment
In order to which those skilled in the art is made to more fully understand the present invention program, below in conjunction in the embodiment of the present invention
The technical solution in the embodiment of the present invention is clearly and completely described in attached drawing, it is clear that described embodiment is only
The embodiment of a part of the invention, instead of all the embodiments.Based on the embodiments of the present invention, ordinary skill people
Member's all other embodiments obtained without making creative work should all belong to the model that the present invention protects
It encloses.
It should be noted that term " first " in description and claims of this specification and above-mentioned attached drawing, "
Two " etc. be the object for distinguishing similar, and specific sequence or precedence are described without being used for.It should be appreciated that it uses in this way
Data can be interchanged in the appropriate case, so as to the embodiment of the present invention described herein can in addition to illustrating herein or
Sequence other than those of description is implemented.In addition, term " comprising " and " having " and their any deformation, it is intended that cover
Cover it is non-exclusive include, be not necessarily limited to for example, containing the process of series of steps or unit, method, system, product or equipment
Those steps or unit clearly listed, but may include not listing clearly or for these processes, method, product
Or the intrinsic other steps of equipment or unit.
Embodiment 1
According to embodiments of the present invention, a kind of embodiment of the method for the evaluation method of optional transformer early warning value is provided,
It should be noted that step shown in the flowchart of the accompanying drawings can be in the department of computer science of such as a group of computer-executable instructions
It is performed in system, although also, show logical order in flow charts, it in some cases, can be to be different from herein
Sequence perform shown or described step.
Fig. 1 is a kind of flow chart of the evaluation method of optional transformer early warning value according to embodiments of the present invention, such as Fig. 1 institutes
Show, this method comprises the following steps：
Step S102 obtains the cumulative distribution letter of the concentration of institute's dissolved gas and factor of created gase in the transformer oil of transformer
Number；
Step S104 determines corresponding inverse cumulative distribution function according to cumulative distribution function；
Step S106, the defects of obtaining transformer rate and/or failure rate；
Step S108, after ratio of defects is got, according to ratio of defects and using inverse cumulative distribution function estimated concentration and
The demand value of factor of created gase；
Step S110, after failure rate is got, according to failure rate and using inverse cumulative distribution function estimated concentration and
The warning value of factor of created gase；
Step S112 exports demand value and warning value.
By above-mentioned steps, the concentration of institute's dissolved gas and the difference of factor of created gase in using distribution function estimation transformer oil
During alienation early warning value, due to fully considered difference under the conditions of different attribute between the different lower transformers of transformers classification and
The defects of transformer the rate and factors such as failure rate, therefore can obtain more accurate early warning value threshold value (including：Demand value and police
Indicating value etc.), in this way, use early warning is carried out by the present invention obtained early warning value threshold value when, can prevent to fail to report it is alert or
Situations such as false alarm.
Optionally it is determined that the step of cumulative distribution function, includes：
S2 obtains the concentration of institute's dissolved gas and factor of created gase data in the different lower transformer oil of transformer classification；
S4 determines the cumulative distribution function under different transformer classification according to data.
It it should be noted that can be according to the attributive character (such as transformer grade) of transformer, by some specific region
Power grid in all transformers carry out classification processing, it is molten so as to collect in the transformer oil under different transformer classifications institute
Solve the concentration of gas and factor of created gase data.In this way, using distribution function estimation transformer oil in institute's dissolved gas concentration and
During the differentiation early warning value of factor of created gase, fully considered transformer the defects of in the case of the factors such as rate and failure rate, then mend
The difference considered under the conditions of different attribute between the different lower transformers of transformers classification is filled, more accurate early warning value can be obtained
Threshold value (including：Demand value and warning value etc.) so that it, can when using the early warning value threshold value progress early warning obtained by the present invention
Situations such as to prevent to fail to report alert or false alarm.
Still optionally further, the concentration of institute's dissolved gas and factor of created gase number in the different lower transformer oil of transformer classification are obtained
According to including：
S6 obtains the concentration data of institute's dissolved gas in the transformer oil of all transformers in target area；
S8 carries out differentiation classification to concentration data according to the attribute information of all transformers, obtains different transformers point
Under class in transformer oil institute's dissolved gas concentration data；
S10 calculates such concentration data according to any two adjacent data in the concentration data under the classification of each transformer
The factor of created gase of corresponding gas obtains the factor of created gase data of institute's dissolved gas in the different lower transformer oil of transformer classification.
It should be noted that real time on-line monitoring can be carried out by the sensor installed on the transformer, one section is acquired
The online monitoring data of transformer in time, and therefrom extract the concentration of institute's dissolved gas in the transformer oil of all kinds of transformers
Data, and then corresponding factor of created gase is calculated, obtain factor of created gase data.For example, oil chromatography monitoring data are obtained in the present embodiment altogether
114326, the form of data in original oil chromatogram monitoring data, includes biography as shown in table 1 (only showing partial information)
8 dissolved in the information for the transformer that sensor is installed, the number of sensor, monitoring place, monitoring date, ordinal number date, oil
The information of kind gas (such as hydrogen, carbon monoxide, carbon dioxide, methane, ethane, ethylene, acetylene, total hydrocarbon).Wherein, the ordinal number date
It is relative-date, it is 1 such as to set corresponding ordinal number date on January 1st, 2013, then on January 2nd, 2013 on the corresponding ordinal number date is then
It is 365 on December 31st, 2,2013 on the corresponding ordinal number date to be, the effect on ordinal number date is to calculate opposite factor of created gase for convenience.
Table 1
The attribute of transformer refers to the build-in attribute of transformer.Embodiment, can use transformer voltage class this
Attribute carries out differentiation classification processing to oil chromatography monitoring data.For example, 114326 above-mentioned data information come from
The transformer of tri- kinds of voltage class of 110kV, 220kV and 500kV, thus count transformer under each voltage class number of units and
Data amount information, as shown in table 2 (result classified according to voltage class)：
Table 2
| Voltage class/kV | Number of units/platform | Data volume/item |
| 110 | 8 | 1844 |
| 220 | 173 | 51236 |
| 500 | 220 | 61246 |
| It amounts to | 401 | 114326 |
During implementation, 8 kinds of gases under each classification can be calculated as unit of day (including hydrogen, carbon monoxide, titanium dioxide
Carbon, methane, ethane, ethylene, acetylene and total hydrocarbon) opposite factor of created gase.Calculation formula with respect to factor of created gase is：
γ in formulai+1Represent the opposite gas production rate in i+1 day, unit is %/day；Ci+1Represent what i+1 day monitored
Oil Dissolved Gases Concentration, unit are μ L/L；CiIt is μ L/L to represent i-th day Oil Dissolved Gases Concentration unit monitored.
Through the embodiment of the present invention, the historical datas such as the concentration based on a large amount of Gases Dissolved in Transformer Oil, according to change
The self attributes of depressor carry out data differentiation classification, and ratio of defects and failure rate is associated with distribution function, utilize inverse point
Cloth function calculates 8 kinds of oil dissolved gas (hydrogen, carbon monoxide, carbon dioxide, first of the transformer under different attribute classification
Alkane, ethane, ethylene, acetylene and total hydrocarbon) content and its demand value of factor of created gase and warning value.By the way that transformer is belonged to according to it
Property is classified, and has been reached and has been overcome in the relevant technologies due to not accounting for difference between transformer attribute or according to attribute
During classification excessively it is thick it is mad caused by threshold value it is inaccurate the defects of.
Optionally, in the case where obtaining the classification of different transformers in transformer oil the concentration of institute's dissolved gas and factor of created gase data it
Afterwards, method further includes：
S12, the concentration numbers of institute's dissolved gas and factor of created gase data are drawn in transformer oil under being classified according to different transformers
Corresponding statistic histogram and matched curve；
S14 determines that institute is molten in the lower transformer oil of each transformer classification according to the statistic histogram of drafting and matched curve
Solve the concentration of gas and the distributed model of factor of created gase；
S16, institute's dissolved gas in transformer oil under the corresponding distribution function of distributed model is classified as each transformer
Concentration and factor of created gase cumulative distribution function.
It should be noted that cumulative distribution function is Weibull Function, inverse cumulative distribution function is Weibull distribution
The inverse function of function.
During implementation, Dissolved Gas Content in Transformer Oil is being obtained, and after calculating opposite factor of created gase according to formula (1),
Can be for statistical analysis to 8 groups of dissolved gas contents under each classification and 8 groups of dissolved gas factor of created gase data respectively, it draws
The content of oil dissolved gas and the statistic histogram of factor of created gase and matched curve, as shown in Figures 2 and 3 (with 220kV transformers
For dissolving the content of hydrogen and the factor of created gase of ethylene in oil), that is, when implementing, will a large amount of live oil colours modal data according to
Transformer self attributes carry out differentiation classification, will have the oil colours modal data corresponding to the transformer of a certain same alike result to make
For one kind, and calculate as unit of day the absolute factor of created gase of transformer under the classification.Later, to the transformer under each classification
Oil Dissolved Gases Concentration and factor of created gase data are for statistical analysis, build corresponding distributed model and estimate model parameter.Into
And the defects of counting each classification lower transformer rate and failure rate, and by itself and point of Oil Dissolved Gases Concentration and its factor of created gase
Cumulative probability in cloth model is associated, and phase is calculated using the inverse cumulative distribution function of the distributed model of oil chromatography and its factor of created gase
The demand value and warning value answered.
For example, the content of oil dissolved gas and its factor of created gase are basic it can be seen from statistic histogram and matched curve
Meet Weibull distribution, thus build Weibull distribution model, and calculate the relevant parameter of Weibull distribution model.Wherein, prestige
Boolean distribution probability density function and its corresponding cumulative distribution function be respectively：
Wherein, β represents Weibull slope, also referred to as form parameter；η characterization values, also referred to as scale parameter, by greatly seemingly
Right method estimation form parameter and scale parameter, the corresponding likelihood function of Weibull distribution model are：
Likelihood equations are：
(4) substitution (5) be can obtain into the estimated value of β and η namely the parameter value of distribution function.
Optionally, the defects of obtaining transformer rate and/or failure rate can include：
S18 obtains the transformer field service information under each transformer classification；
S20, the defects of lower transformer of each transformer classification is extracted from transformer field service information rate and/or former
Barrier rate.
During implementation, the site examining and repairing data of transformer can be searched from the record of examination at scene, and extract transformer
Ratio of defects and failure rate.Since ratio of defects and failure rate are all from recording with site examining and repairing, ratio of defects and failure are improved
Rate reliability and validity.According to the record of examination at scene, failure rate and ratio of defects such as 3 institute of table of each voltage gradation counted
Show：
Table 3
| Voltage class/kV | Ratio of defects/% | Failure rate/% |
| 110 | 2.82 | 0.05 |
| 220 | 4.54 | 0.18 |
| 500 | 1.79 | 0.9 |
Optionally, include according to ratio of defects and using the demand value of inverse cumulative distribution function estimated concentration and factor of created gase：
S22, variate-value be 1- ratio of defects when, using by the functional value that inverse cumulative distribution function is estimated as attention
Value.
Similarly, according to failure rate and the warning value packet of the inverse cumulative distribution function estimated concentration of utilization and factor of created gase：
S24, variate-value be 1- failure rates when, using by the functional value that inverse cumulative distribution function is estimated as warn
Value.
Wherein, the inverse cumulative distribution function of Weibull function is：
X=F-1(p | η, β)=- η [ln (1-p)]1/β,p∈[0,1] (6)
Wherein, p represent cumulative distribution probability, x represent when cumulative probability be p when corresponding value.Specifically, it is inverse when setting
When the cumulative probability of cumulative distribution function is equal to 1- ratio of defects, obtained estimated value is demand value, sets inverse cumulative distribution function
Cumulative probability when being equal to 1- failure rates, obtained estimated value is warning value.It can be obtained under each classification by formula (6)
The content of oil dissolved gas and its demand value of factor of created gase and warning value.Wherein, based on 3 table 1, table 2 and table column datas, root
The content of dissolved gas and its demand value of factor of created gase and warning value calculated according to the present invention is respectively such as (each grade transformation of table 4
The demand value of the content of the oil dissolved gas of 7 kinds of gases and total hydrocarbon and warning value (μ L/L) in device) and (each grade transformation of table 5
The demand value of the factor of created gase of the oil dissolved gas of 7 kinds of gases and total hydrocarbon and warning value (%) in device) shown in：
Table 4
Table 5
Embodiment 2
According to embodiments of the present invention, a kind of device embodiment of the estimation device of transformer early warning value is provided.
Fig. 4 be a kind of optional transformer early warning value according to embodiments of the present invention estimation device schematic diagram, such as Fig. 4
Shown, which includes：First acquisition unit 402, the first determination unit 404, second acquisition unit 406,408 and of evaluation unit
Output unit 410.First acquisition unit 402, for obtaining the concentration and aerogenesis of institute's dissolved gas in the transformer oil of transformer
The cumulative distribution function of rate；First determination unit 404, for determining corresponding inverse cumulative distribution letter according to cumulative distribution function
Number；Second acquisition unit 406, rate and/or failure rate the defects of for obtaining transformer；Evaluation unit 408, for getting
After ratio of defects, according to ratio of defects and inverse cumulative distribution function estimated concentration and the demand value of factor of created gase are utilized；Getting event
After barrier rate, according to failure rate and inverse cumulative distribution function estimated concentration and the warning value of factor of created gase are utilized；Output unit 410,
For in output demand value and warning value..
Through the embodiment of the present invention, in the concentration and factor of created gase that institute's dissolved gas in transformer oil is estimated using distribution function
Differentiation early warning value when, due to having fully considered the difference under the conditions of different attribute between the different lower transformers of transformers classification
And the factors such as the defects of transformer rate and failure rate, therefore can obtain more accurate early warning value threshold value (including：Demand value
With warning value etc.), in this way, use early warning is carried out by the early warning value threshold value that the present invention obtains when, can prevent to fail to report
Situations such as alert or false alarm.
Further, above device further includes：Second determination unit, for determining cumulative distribution function, second determines list
Member includes：First acquisition module, for obtaining the concentration and aerogenesis of institute's dissolved gas in the different lower transformer oil of transformer classification
Rate data；Determining module, for determining the cumulative distribution function under different transformer classification according to data.
It it should be noted that can be according to the attributive character (such as transformer grade) of transformer, by some specific region
Power grid in all transformers carry out classification processing, it is molten so as to collect in the transformer oil under different transformer classifications institute
Solve the concentration of gas and factor of created gase data.In this way, using distribution function estimation transformer oil in institute's dissolved gas concentration and
During the differentiation early warning value of factor of created gase, fully considered transformer the defects of in the case of the factors such as rate and failure rate, then mend
The difference considered under the conditions of different attribute between the different lower transformers of transformers classification is filled, more accurate early warning value can be obtained
Threshold value (including：Demand value and warning value etc.) so that it, can when using the early warning value threshold value progress early warning obtained by the present invention
Situations such as to prevent to fail to report alert or false alarm.
Still optionally further, the first acquisition module includes：Acquisition submodule, for obtaining all transformers in target area
Transformer oil in institute's dissolved gas concentration data；Classify submodule, for according to the attribute information of all transformers to dense
Degrees of data carries out differentiation classification, obtains the concentration data of institute's dissolved gas in the different lower transformer oil of transformer classification；It calculates
Submodule, for calculating such concentration data pair according to any two adjacent data in the concentration data under the classification of each transformer
The factor of created gase for the gas answered obtains the factor of created gase data of institute's dissolved gas in the different lower transformer oil of transformer classification.
It should be noted that real time on-line monitoring can be carried out by the sensor installed on the transformer, one section is acquired
The online monitoring data of transformer in time, and therefrom extract the concentration of institute's dissolved gas in the transformer oil of all kinds of transformers
Data, and then corresponding factor of created gase is calculated, obtain factor of created gase data.For example, oil chromatography monitoring data are obtained in the present embodiment altogether
114326, the form of data in original oil chromatogram monitoring data, includes biography as shown in table 1 (only showing partial information)
8 dissolved in the information for the transformer that sensor is installed, the number of sensor, monitoring place, monitoring date, ordinal number date, oil
The information of kind gas (such as hydrogen, carbon monoxide, carbon dioxide, methane, ethane, ethylene, acetylene, total hydrocarbon).Wherein, the ordinal number date
It is relative-date, it is 1 such as to set corresponding ordinal number date on January 1st, 2013, then on January 2nd, 2013 on the corresponding ordinal number date is then
It is 365 on December 31st, 2,2013 on the corresponding ordinal number date to be, the effect on ordinal number date is to calculate opposite factor of created gase for convenience.
The property value of transformer refers to the build-in attribute of transformer.Embodiment, can use transformer voltage class this
One attribute carries out differentiation classification processing to oil chromatography monitoring data.For example, 114326 above-mentioned data information come from
The transformer of tri- kinds of voltage class of 110kV, 220kV and 500kV, thus count transformer under each voltage class number of units and
Data amount information, as shown in table 2 (result classified according to voltage class).
During implementation, 8 kinds of gases under each classification can be calculated as unit of day (including hydrogen, carbon monoxide, titanium dioxide
Carbon, methane, ethane, ethylene, acetylene and total hydrocarbon) opposite factor of created gase.Calculation formula with respect to factor of created gase is formula (1).
Through the embodiment of the present invention, based on a large amount of oil dissolved gas historical data, according to the self attributes of transformer
Data are carried out with differentiation classification, ratio of defects and failure rate is associated with distribution function, it is calculated using Inverse distribution function unified
Transformer under attribute 8 kinds of oil dissolved gas (hydrogen, carbon monoxide, carbon dioxide, methane, ethane, ethylene, acetylene and
Total hydrocarbon) content and its demand value of factor of created gase and warning value.By the way that transformer is classified according to its property value, reach
Overcome in the relevant technologies due to the monitoring parameters of oil chromatography are not classified or are classified it is relatively thick it is mad caused by estimate knot
The defects of fruit is inaccurate.
Further, above device further includes：Image-drawing unit, in the transformer oil in the case where obtaining different transformer classification
After the concentration of institute's dissolved gas and factor of created gase data, classified the dense of institute's dissolved gas in lower transformer oil according to different transformers
The number of degrees and factor of created gase data draw corresponding statistic histogram and matched curve；Third determination unit, for the system according to drafting
Meter histogram and matched curve determine the concentration of institute's dissolved gas and point of factor of created gase in the lower transformer oil of each transformer classification
Cloth model, and classify the dense of institute's dissolved gas in lower transformer oil using the corresponding distribution function of distributed model as each transformer
The cumulative distribution function of degree and factor of created gase.
During implementation, Dissolved Gas Content in Transformer Oil is being obtained, and after calculating opposite factor of created gase according to formula (1),
Can be for statistical analysis to 8 groups of dissolved gas contents under each classification and 8 groups of dissolved gas factor of created gase data respectively, it draws
The content of oil dissolved gas and the statistic histogram of factor of created gase and matched curve, as shown in Figures 2 and 3 (with 220kV transformers
For dissolving the content of hydrogen and the factor of created gase of ethylene in oil), that is, when implementing, will a large amount of live oil colours modal data according to
Transformer self attributes value carries out differentiation classification, will have the oil colours modal data corresponding to the transformer of a certain same alike result
As one kind, and calculate as unit of day the absolute factor of created gase of transformer under the classification.Later, to the transformer under each classification
Oil Dissolved Gases Concentration and factor of created gase data it is for statistical analysis, build corresponding distributed model and estimate model parameter.
And then the defects of counting each classification lower transformer rate and failure rate, and by its in the distributed model of oil chromatography and its factor of created gase
Cumulative probability be associated, the inverse cumulative distribution function of the distributed model of oil chromatography and its factor of created gase is utilized to calculate and corresponding is paid attention to
Value and warning value.
For example, the content of oil dissolved gas and its factor of created gase are basic it can be seen from statistic histogram and matched curve
Meet Weibull distribution, thus build Weibull distribution model, and calculate the relevant parameter of Weibull distribution model.Wherein, prestige
The probability density function and its corresponding cumulative distribution function of boolean's distribution are respectively formula (2) and formula (3), pass through pole
Maximum-likelihood method estimates form parameter and scale parameter, and the corresponding likelihood function of Weibull distribution model is formula (4), likelihood equation
Group is formula (5), and (4) substitution (5) can obtain the estimated value of β and η namely the parameter value of distribution function.
Further, second acquisition unit includes：Second acquisition module, for obtaining the transformation under each transformer classification
Device site examining and repairing information；Extraction module, for extracting the transformation under each transformer classification from transformer field service information
The defects of device rate and/or failure rate.
During implementation, the site examining and repairing data of transformer can be searched from the record of examination at scene, and extract transformer
Ratio of defects and/or failure rate.Since ratio of defects and failure rate are all from recording with site examining and repairing, ratio of defects and event are improved
Barrier rate reliability and validity.According to the record of examination at scene, failure rate and the ratio of defects such as table 3 of each voltage gradation counted
It is shown.
Further, evaluation unit is additionally operable to, when variate-value is 1- ratio of defects, to be estimated by inverse cumulative distribution function
The functional value arrived by inverse cumulative distribution function as demand value and for that when variate-value is 1- failure rates, will be estimated to obtain
Functional value as warning value.
Wherein, the inverse cumulative distribution function of Weibull function is formula (6).Specifically, when the inverse cumulative distribution function of setting
Cumulative probability when being equal to 1- ratio of defects, obtained estimated value is demand value, sets cumulative probability etc. of inverse cumulative distribution function
When 1- failure rates, obtained estimated value is warning value.The oil dissolved gas under each classification can be obtained by formula (6)
Content and its demand value of factor of created gase and warning value.Wherein, it based on 3 table 1, table 2 and table column datas, is calculated according to the present invention
The content of the dissolved gas gone out and its demand value of factor of created gase and warning value respectively as table 4 (in each grade transformer 7 kinds of gases and
The demand value and warning value (μ L/L) of the content of the oil dissolved gas of total hydrocarbon) and table 5 (in each grade transformer 7 kinds of gases and
The demand value of the factor of created gase of the oil dissolved gas of total hydrocarbon and warning value (%)) shown in.
The embodiments of the present invention are for illustration only, do not represent the quality of embodiment.
In the above embodiment of the present invention, all emphasize particularly on different fields to the description of each embodiment, do not have in some embodiment
The part of detailed description may refer to the associated description of other embodiment.
In several embodiments provided herein, it should be understood that disclosed technology contents can pass through others
Mode is realized.Wherein, the apparatus embodiments described above are merely exemplary, such as the division of the unit, Ke Yiwei
A kind of division of logic function, can there is an other dividing mode in actual implementation, for example, multiple units or component can combine or
Person is desirably integrated into another system or some features can be ignored or does not perform.Another point, shown or discussed is mutual
Between coupling, direct-coupling or communication connection can be INDIRECT COUPLING or communication link by some interfaces, unit or module
It connects, can be electrical or other forms.
The unit illustrated as separating component may or may not be physically separate, be shown as unit
The component shown may or may not be physical unit, you can be located at a place or can also be distributed to multiple
On unit.Some or all of unit therein can be selected according to the actual needs to realize the purpose of this embodiment scheme.
In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, it can also
That each unit is individually physically present, can also two or more units integrate in a unit.Above-mentioned integrated list
The form that hardware had both may be used in member is realized, can also be realized in the form of SFU software functional unit.
If the integrated unit is realized in the form of SFU software functional unit and is independent product sale or uses
When, it can be stored in a computer read/write memory medium.Based on such understanding, technical scheme of the present invention is substantially
The part to contribute in other words to the prior art or all or part of the technical solution can be in the form of software products
It embodies, which is stored in a storage medium, is used including some instructions so that a computer
Equipment (can be personal computer, server or network equipment etc.) perform each embodiment the method for the present invention whole or
Part steps.And aforementioned storage medium includes：USB flash disk, read-only memory (ROM, Read-Only Memory), arbitrary access are deposited
Reservoir (RAM, Random Access Memory), mobile hard disk, magnetic disc or CD etc. are various can to store program code
Medium.
The above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications also should
It is considered as protection scope of the present invention.
Claims (9)
1. a kind of evaluation method of transformer early warning value, which is characterized in that including：
Obtain the concentration of institute's dissolved gas and the cumulative distribution function of factor of created gase in the transformer oil of transformer；
Corresponding inverse cumulative distribution function is determined according to the cumulative distribution function；
The defects of obtaining transformer rate and/or failure rate；
After ratio of defects is got, the concentration and institute are estimated according to the ratio of defects and using the inverse cumulative distribution function
State the demand value of factor of created gase；
After failure rate is got, the concentration and institute are estimated according to the failure rate and using the inverse cumulative distribution function
State the warning value of factor of created gase；
Export the demand value and the warning value；
Wherein it is determined that the step of cumulative distribution function, includes：
Obtain the concentration of institute's dissolved gas and factor of created gase data in the different lower transformer oil of transformer classification；
The cumulative distribution function under different transformer classification is determined according to the data；
Wherein, the attention of the concentration and the factor of created gase is estimated according to the ratio of defects and using the inverse cumulative distribution function
Value includes：
When variate-value is " 1- ratio of defects ", using the functional value estimated by the inverse cumulative distribution function as the attention
Value；
Wherein, the warning of the concentration and the factor of created gase is estimated according to the failure rate and using the inverse cumulative distribution function
Value includes：
When variate-value is " 1- failure rates ", using the functional value estimated by the inverse cumulative distribution function as the warning
Value.
2. it according to the method described in claim 1, is dissolved in the different lower transformer oil of transformer classification it is characterized in that, obtaining
The concentration and factor of created gase data of gas include：
Obtain the concentration data of institute's dissolved gas in the transformer oil of all transformers in target area；
Differentiation classification is carried out to the concentration data according to the attribute information of all transformers, obtains different transformers point
Under class in transformer oil institute's dissolved gas concentration data；
Any two adjacent data calculates the corresponding gas of such concentration data in concentration data under being classified according to each transformer
The factor of created gase of body obtains the factor of created gase data of institute's dissolved gas in the different lower transformer oil of transformer classification.
3. according to the method described in claim 1, it is characterized in that, institute is molten in transformer oil in the case where obtaining different transformer classification
After solving the concentration of gas and factor of created gase data, the method further includes：
The concentration numbers of institute's dissolved gas and factor of created gase data draw corresponding system in transformer oil under being classified according to different transformers
Count histogram and matched curve；
Determine that institute is molten in the lower transformer oil of each transformer classification according to the statistic histogram of drafting and the matched curve
Solve the concentration of gas and the distributed model of factor of created gase；
Using the corresponding distribution function of the distributed model as institute's dissolved gas in each lower transformer oil of transformer classification
Concentration and factor of created gase cumulative distribution function.
4. according to the method described in claim 1, it is characterized in that, the cumulative distribution function be Weibull Function, institute
State the inverse function that inverse cumulative distribution function is the Weibull Function.
5. according to the method described in claim 1, it is characterized in that, the defects of obtaining transformer rate and/or failure rate packet
It includes：
Obtain the transformer field service information under each transformer classification；
The defects of transformer under each transformer classification is extracted from transformer field service information rate and/or event
Barrier rate.
6. a kind of estimation device of transformer early warning value, which is characterized in that including：
First acquisition unit, for obtaining the concentration of institute's dissolved gas and the cumulative distribution of factor of created gase in the transformer oil of transformer
Function；
First determination unit, for determining corresponding inverse cumulative distribution function according to the cumulative distribution function；
Second acquisition unit, rate and/or failure rate the defects of for obtaining the transformer；
Evaluation unit, for after ratio of defects is got, estimating according to the ratio of defects and using the inverse cumulative distribution function
Calculate the demand value of the concentration and the factor of created gase；After failure rate is got, according to the failure rate and utilize described inverse
Cumulative distribution function estimates the concentration and the warning value of the factor of created gase；
Output unit, for exporting the demand value and the warning value；
Wherein, described device further includes：Second determination unit, for determining the cumulative distribution function, described second determines list
Member includes：
First acquisition module, for obtaining the concentration of institute's dissolved gas and factor of created gase number in the different lower transformer oil of transformer classification
According to；
Determining module, for determining the cumulative distribution function under different transformer classification according to the data；
Wherein, the evaluation unit is additionally operable to when variate-value is " 1- ratio of defects ", will be estimated by the inverse cumulative distribution function
Obtained functional value is as the demand value；
Wherein, the evaluation unit is additionally operable to when variate-value is " 1- failure rates ", will be estimated by the inverse cumulative distribution function
Obtained functional value is as the warning value.
7. device according to claim 6, which is characterized in that first acquisition module includes：
Acquisition submodule, for obtaining the concentration data of institute's dissolved gas in the transformer oil of all transformers in target area；
Classification submodule carries out differentiation classification for the attribute information according to all transformers to the concentration data,
Obtain the concentration data of institute's dissolved gas in the different lower transformer oil of transformer classification；
Computational submodule, it is dense for calculating such according to any two adjacent data in the concentration data under the classification of each transformer
The factor of created gase of the corresponding gas of degrees of data obtains the factor of created gase number of institute's dissolved gas in the different lower transformer oil of transformer classification
According to.
8. device according to claim 6, which is characterized in that described device further includes：
Image-drawing unit, for the concentration of institute's dissolved gas and factor of created gase data in the transformer oil in the case where obtaining different transformer classification
Later, the concentration numbers of institute's dissolved gas and factor of created gase data draw corresponding system in transformer oil under being classified according to different transformers
Count histogram and matched curve；
Third determination unit determines each transformer classification for the statistic histogram according to drafting and the matched curve
The distributed model of the concentration of institute's dissolved gas and factor of created gase in lower transformer oil, and by the corresponding distribution function of the distributed model
As the concentration of institute's dissolved gas and the cumulative distribution function of factor of created gase in each lower transformer oil of transformer classification.
9. device according to claim 6, which is characterized in that the second acquisition unit includes：
Second acquisition module, for obtaining the transformer field service information under each transformer classification；
Extraction module, for extracting the transformer under each transformer classification from the transformer field service information
Ratio of defects and/or failure rate.
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| CN106442830B (en) * | 2016-09-29 | 2018-04-13 | 广州供电局有限公司 | The detection method and system of gas content in transformer oil warning value |
| CN106771513A (en) * | 2016-11-22 | 2017-05-31 | 华北电力大学 | The determination method and device of arrester early warning value |
| CN106596754B (en) * | 2016-11-22 | 2019-07-23 | 华北电力大学 | The appraisal procedure and device of oil chromatography sensor availability |
| CN109187809A (en) * | 2018-10-27 | 2019-01-11 | 国网山东省电力公司电力科学研究院 | A kind of Gases Dissolved in Transformer Oil data generate in real time and analysis system |
| CN109541096A (en) * | 2018-11-09 | 2019-03-29 | 福建和盛高科技产业有限公司 | 220kV Gases Dissolved in Transformer Oil volume fraction dynamic early-warning method |
| CN110674983A (en) * | 2019-09-05 | 2020-01-10 | 辽宁工程技术大学 | Working face gas early warning method based on copula function tail correlation analysis |
| CN112345678B (en) * | 2020-11-10 | 2022-03-01 | 重庆大学 | Transformer fault rate prediction model obtaining method and system and readable storage medium |
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