CN106646332A - Collection abnormality emergency degree calculating method based on number of days before meter-reading day - Google Patents
Collection abnormality emergency degree calculating method based on number of days before meter-reading day Download PDFInfo
- Publication number
- CN106646332A CN106646332A CN201611125744.1A CN201611125744A CN106646332A CN 106646332 A CN106646332 A CN 106646332A CN 201611125744 A CN201611125744 A CN 201611125744A CN 106646332 A CN106646332 A CN 106646332A
- Authority
- CN
- China
- Prior art keywords
- days
- factor
- meter
- power consumption
- user
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- 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
- G01R35/04—Testing or calibrating of apparatus covered by the other groups of this subclass of instruments for measuring time integral of power or current
Abstract
The invention discloses a collection abnormality emergency degree calculating method based on the number of days before a meter-reading day, and belongs to the technical field of power equipment. A conventional collection abnormality emergency degree calculating method cannot determine the emergency degree of each abnormal point quickly and accurately, so some emergency abnormal conditions cannot be solved timely, and there is short of a scientific, reasonable and accurate technical scheme. The method comprises the steps: firstly determining influence factors of the emergency degree; secondly building a standard power utilization user group, converting the influence factors into the emergency degree of the standard power utilization user group, building a calculation model of the influence factors, and building a relation formula of a single variable of the number of days before the meter-reading day. The method effectively simplifies the calculation and complexity, achieves the systematization, layering and simplifying of a complex solution, provides a feasible technical scheme, and solves an emergency calculation problem more completely.
Description
Technical field
The present invention relates to a kind of acquisition abnormity urgency level computational methods of day number of days of being checked meter based on distance, are belonged to electric power and are set
Standby technical field.
Background technology
Currently in the whole country, the failure produced by the acquisition system of electric power is substantially all beyond local O＆M strength, various places
Square office is also that the acquisition system normal operating devices total effective rate in its range of management is examined, it is impossible to ensure armamentarium
Can effective gathered data.At present system maintenance work management is in the extensive stage, exist resource use it is unreasonable, it is impossible to it is quick
Accurately judge the urgency level of each abnormity point, cause some urgent abnormal conditions to solve in time, and then more serious feelings
Condition occurs.Abnormal urgency level judges the experience for relying primarily on people and subjective estimation to carry out distribute leaflets process that this method is present
Very big not scientific and randomness, lacks a kind of science, reasonable, accurate technical scheme.For depositing in currently available technology
Drawbacks described above, be necessary to be researched and developed in fact, solve prior art present in defect.
The content of the invention
For the defect of prior art, it is an object of the invention to provide a kind of science, reasonable, accurate electricity consumption gather different
Normal computational methods of urgency level, more science and accurately judge the urgency level of each abnormity point, are follow-up accurate to send work
There is provided basis so that resource is more reasonably utilized.
For achieving the above object, the technical scheme is that：
A kind of acquisition abnormity urgency level computational methods of day number of days of being checked meter based on distance, are comprised the following steps：
The first step, primarily determines that the factor of influence of acquisition abnormity urgency
The factor of influence of acquisition abnormity urgency is determined by electric power operational system expert discussion, the factor of influence include away from
From number of days of checking meter.
Second step, the data of collecting circuit runtime
The data include collection in worksite data and trouble ticket dispatch data, are related to one section of various users of multiple regions
Power consumption in time, and then the power consumption to high-volume user carries out fluction analysis.
3rd step, sets up standard electricity consumer
Standard electricity consumer is to put down the moon that all types of user is counted on the basis of the actual electricity consumption situation for extracting most of user
Equal power consumption, then according to the most eurypalynous electricity consumer average electricity of user as standard electricity consumer power consumption, have an impact because
Finally all conversion is standard electricity consumer for impact of the son to urgency.
For accurate evaluation factor of influence, setting standard electricity consumer is needed.Standard electricity consumer is to extract most of user
The monthly average power consumption of all types of user is counted on the basis of actual electricity consumption situation, is then put down according to the most eurypalynous electricity consumer of user
Used as standard electricity consumer power consumption, finally all conversion is standard electricity consumer to electricity for impact of all factors of influence to urgency.
At present the abnormal urgency level of system judges that the experience for relying primarily on people and subjectivity are estimated to carry out distribute leaflets process, this
There is very big not scientific and randomness in the method for kind.In order that the judgement of abnormal urgency can be more scientific and can be measured,
Present invention introduces standard electricity consumer concept, by impact of all factors of influence to urgency, finally all conversion is standard electricity consumer.
And during actual O＆M, on the one hand abnormal urgency factor of influence is more and belongs to different type, on the other hand complete
There is the Different Effects factor each place in the range of state, and various factors affects size to there is also difference final urgency, it is difficult to be
System grasps at the very start all factors of influence comprehensively, there is addition, the possibility deleted and change.Therefore, using standard electricity consumer
Concept, by impact of all factors of influence to urgency, finally all conversion is standard electricity consumer.Standard electricity consumer is to extract greatly
The monthly average power consumption of all types of user is counted on the basis of the actual electricity consumption situation of certain customers, then according to the most types of user
Electricity consumer average electricity as standard electricity consumer power consumption.
4th step, the analyzing influence factor simultaneously sets up model
Urgency factor of influence judgment models are exactly, by the existing service data of system, to affect to carry out data according to each factor
Analysis, when result show factor of influence and final result then show when there are obvious paradigmatic relation or continuous should by this because
Number counts urgency calculating, then shows that the factor is counted into urgency calculates when result is discrete discontinuous.Set up
Distance is checked meter the computation model of day number of days, and the meter reading data of example of checking meter day is mostly important in the middle of one month, this day shortage of data
Manual metering will be caused, the cost of manual metering will be calculated, if relatively costly, need distance to check meter day number of days as impact
The factor of influence of urgency, if cost is relatively low, need not.
5th step, according to computation model, determines the precedence of abnormality processing, and circuit runtime is safeguarded.
Further, nearer apart from next day of checking meter, abnormality processing urgency is higher, and statistics continues N days without meter reading data
Electric energy meter number distribution situation, analyze the relation of failure ammeter and continuous dayses, determine that one can process most failures electricity
The number of days n of table.N days are selected as threshold value, the factor for exceeding threshold values apart from number of days affects to be 0, gets in threshold values apart from number of days
Little process emergency value is bigger.
Further, according to the theory of standard electricity consumer, electricity consumer to be collected is converted to r (xi) individual standard electricity consumption
Family.
Further, distance day number of days abnormality processing urgency Controlling model of checking meter is as follows：
(n：Process time threshold value, m：Distance is checked meter a day number of days), r (xi)：Standard amount).
Further, the factor of influence also includes：Intermittent defect, monthly average power consumption, Abnormal lasting, electric energy
Table value of utility.
Further, intermittent defect decision model is set up, analyzes whether various electrical energy meter fault rates have discrete feature,
If various electrical energy meter fault rates have discrete type, the factor of influence that the factor is exported not as emergency value, conversely, the factor
As the factor of influence of emergency value output.
Further, according to concentrator type, region, concentrator producer carry out respectively count failure electric energy meter quantity,
Electric energy meter quantity.Calculate same concentrator type, the electrical energy meter fault rate of different geographical.Same concentrator type is calculated, it is different
The electrical energy meter fault rate of manufacturer.
Further, the computation model of monthly power consumption is set up, monthly power consumption is analyzed to acquisition abnormity urgency level
Influence degree, directly with user the moon power consumption as input, can cause the factor impact fluctuate it is excessive, it is therefore desirable to will use
The family moon, power consumption divided by certain interval.Platform area is classified according to capacity, and it is public to count a certain annual platform area
Become power consumption and the public change of respective volume lower resident, non-resident charge condition.
Further, if only using electricity as the unit of emergency value, the numeric ratio for finally calculating is larger, needs
Converted, concrete distributed area of the user in statistics is determined according to the actual moon power consumption of user, final determination should
User is N number of standard electricity consumer.
Further, the computation model of aberrant continuation number of days is set up, each household is carried out point per daily power consumption standard deviation degree
Whether analysis, the daily power consumption fluctuation for analyzing user is gentle, can be by exception if the daily power consumption fluctuation of most of user is gentle
The electricity that continuous dayses are lost calculates the factor as urgency level, if the daily power consumption fluctuation of most of user is larger not
The electricity that can be lost aberrant continuation number of days calculates the factor as urgency level.
Compared with prior art, the invention has the advantages that：
The present invention determines first the factor of influence for affecting urgency, then sets up standard electricity consumer, and factor of influence is changed
It is the urgency to standard electricity consumer, and then computation model is set up to factor of influence, sets up and checked meter the single of number of days with regard to distance
The relational expression of variable, is effectively simplified amount of calculation and complexity, and complicated solution, systematization is hierarchical, simply
Change, there is provided a kind of practicable technical scheme, more perfect solves urgency computational problem.
The present invention provides a kind of science, the more computational methods of reasonable, accurate electricity consumption acquisition abnormity urgency level, science
Accurately judge the urgency level of each abnormity point, accurate send work to provide basis for follow-up so that the more rational profit of resource
With.
Description of the drawings
Fig. 1 is influencing factors analysis flow chart of the present invention；
Fig. 2 becomes power consumption, public change lower resident, non-resident charge condition for the public varying capacity classification of the present invention and public affairs；
Fig. 3 is resident, non-resident (single, three-phase) charge condition under the corresponding public affairs varying capacity of the present invention；
Fig. 4 is the line loss stability bandwidth tables of data that single household resident, non-resident electricity disappearance cause under public change of the invention；
Fig. 5 is the line loss stability bandwidth broken line graph that single household resident, non-resident electricity disappearance cause under public change of the invention；
Fig. 6 is low pressure resident daily power consumption standard deviation curves figure of the present invention；
Fig. 7 is the non-resident user's daily power consumption standard deviation curves figure of low pressure of the present invention；
Fig. 8 is that the present invention continues the N days electric energy meter distributed number statistical forms without recording electric energy meter data；
Fig. 9 is that the present invention continues the N days electric energy meter number distribution maps without recording electric energy meter data
Figure 10 is that the present invention occurs the meter of intermittent defect by geographic classification statistical form (I type concentrators)；
Figure 11 is that the present invention occurs the meter of intermittent defect by geographic classification statistical chart (I type concentrators)；
Figure 12 is that the present invention occurs the user of intermittent defect by geographic classification statistical form (II type concentrators)；
Figure 13 is that the present invention occurs the user of intermittent defect by geographic classification statistical form (II type concentrators)；
Figure 14 is that the present invention occurs the user of intermittent defect by electric energy meter producer categorised statistical form (I type concentrators)；
Figure 15 is that the present invention occurs the user of intermittent defect by concentrator producer categorised statistical form (I type concentrators)；
Figure 16 is that the present invention occurs the user of intermittent defect by electric energy meter producer categorised statistical form (II type concentrators)；
Figure 17 is that the present invention occurs the user of intermittent defect by concentrator producer categorised statistical form (II type concentrators)；
Figure 18 is each fault type statistical form of I type concentrators that the present invention occurs intermittent defect；
Figure 19 is each fault type statistical chart of I type concentrators that the present invention occurs intermittent defect；
Figure 20 is each fault type statistical form of II type concentrators that the present invention occurs intermittent defect；
Figure 21 is the failure electric energy meter number and handling duration statistical form of different faults patterns affect of the present invention；
Figure 22 is the failure electric energy meter number and handling duration statistical chart of different faults patterns affect of the present invention；
Figure 23 is II types collector of the present invention mounting electric energy meter distributed number statistics；
Figure 24 is that II types collector of the present invention mounts electric energy meter distributed number figure.
Specific embodiment
In order that the objects, technical solutions and advantages of the present invention become more apparent, it is right below in conjunction with drawings and Examples
The present invention is further elaborated.It should be appreciated that specific embodiment described herein is only to explain the present invention, and
It is not used in the restriction present invention.
Conversely, the present invention covers any replacement done in the spirit and scope of the present invention being defined by the claims, repaiies
Change, equivalent method and scheme.Further, in order that the public has a better understanding to the present invention, below to the thin of the present invention
It is detailed to describe some specific detail sections in section description.Part without these details for a person skilled in the art
Description can also completely understand the present invention.
A kind of acquisition abnormity urgency level computational methods of day number of days of being checked meter based on distance, are comprised the following steps：
The first step, primarily determines that the factor of influence of acquisition abnormity urgency
The factor of influence of acquisition abnormity urgency is determined by electric power operational system expert discussion, the factor of influence include away from
From number of days of checking meter.
Second step, the data of collecting circuit runtime
The data include collection in worksite data and trouble ticket dispatch data, are related to one section of various users of multiple regions
Power consumption in time, and then the power consumption to high-volume user carries out fluction analysis.
3rd step, sets up standard electricity consumer
For accurate evaluation factor of influence, setting standard electricity consumer is needed.Standard electricity consumer is to extract most of user
The monthly average power consumption of all types of user is counted on the basis of actual electricity consumption situation, is then put down according to the most eurypalynous electricity consumer of user
Used as standard electricity consumer power consumption, finally all conversion is standard electricity consumer to electricity for impact of all factors of influence to urgency.
At present the abnormal urgency level of system judges that the experience for relying primarily on people and subjectivity are estimated to carry out distribute leaflets process, this
There is very big not scientific and randomness in the method for kind.In order that the judgement of abnormal urgency can be more scientific and can be measured,
Present invention introduces standard electricity consumer concept, by impact of all factors of influence to urgency, finally all conversion is standard electricity consumer.
And during actual O＆M, on the one hand abnormal urgency factor of influence is more and belongs to different type, on the other hand complete
There is the Different Effects factor each place in the range of state, and various factors affects size to there is also difference final urgency, it is difficult to be
System grasps at the very start all factors of influence comprehensively, there is addition, the possibility deleted and change.Therefore, using standard electricity consumer
Concept, by impact of all factors of influence to urgency, finally all conversion is standard electricity consumer.Standard electricity consumer is to extract greatly
The monthly average power consumption of all types of user is counted on the basis of the actual electricity consumption situation of certain customers, then according to the most types of user
Electricity consumer average electricity as standard electricity consumer power consumption.
4th step, the analyzing influence factor simultaneously sets up model
As shown in figure 1, on the one hand due in the whole country each region acquisition system specific requirement is had differences, in addition one
Aspect acquisition abnormity urgency factor of influence is a lot, thus each region need according to its actual conditions carry out judging each impact because
Whether son should count urgency calculating.Urgency factor of influence judgment models are exactly to have service data by system, according to
Each factor affects to carry out data analysis, when result shows that factor of influence has obvious paradigmatic relation or continuous with final result
Shi Ze shows that the factor is counted into urgency calculates, and then showing when result is discrete discontinuous should not be by the factor meter
Enter urgency calculating.
Set up distance to check meter the computation model of day number of days, the meter reading data of example of checking meter day is mostly important in the middle of one month,
This day shortage of data will cause manual metering, calculate the cost of manual metering, if relatively costly, need distance to check meter day
Number of days, if cost is relatively low, is not needed as the factor of influence for affecting urgency.
Set up distance to check meter the computation model of day number of days
The meter reading data of example of typically checking meter day is mostly important in the middle of one month, and this day shortage of data will cause manually to copy
Table so that cost is improved.Nearer apart from next day of checking meter, abnormality processing urgency is higher.Accordingly, it would be desirable to distance is checked meter day day
Number is used as the factor of influence for affecting urgency.
Statistics continues the N days electric energy meter number distribution situations without meter reading data, analyzes the relation of failure ammeter and continuous dayses,
It is determined to process the number of days M of most failure ammeters.Data are counted using section statistical, counts a certain section
Still unrecovered abnormal electric energy meter in time, record continues the N days electric energy meter number distribution situations without meter reading data.
It can be seen that the failure ammeter user for continuing 2 days to 8 days accounts for the 59.06% of total failare number of users from Fig. 8-9, will
Nearly 60%, continue 9 days to the 21 days users without recording electric energy meter data and account for the 30.72% of total failare number of users, nearly 30%, continue
22 days and above accounting 10.22%, nearly 10%.
Find out from analyze data, nearly 60% acquisition abnormity all can be processed within 8 day time, so selection 8 is heaven-made
For threshold value, factor impact that threshold values is exceeded apart from number of days is 0, and apart from number of days, less process emergency value is bigger in threshold values.
According to the theory of standard electricity consumer, electricity consumer to be collected is converted to the individual standard electricity consumers of r (x_i).
Distance day number of days abnormality processing urgency computation model of checking meter is as follows：
(n：Process time threshold value, m：Distance is checked meter a day number of days), r (xi)：Standard amount).
The factor of influence also includes：Intermittent defect, monthly average power consumption, Abnormal lasting, intermittent defect, electricity
Can table value of utility.
Set up the computation model of intermittent defect
Specific aim analysis is carried out by operational system data, is substantially closed when result shows that factor of influence exists with final result
Then show that the factor is counted into urgency calculates, and should then show when result is discrete discontinuous when system or continuous
The factor is counted urgency and is calculated by this.
Producer according to concentrator type, region, concentrator carries out counting failure electric energy meter quantity, electric energy meter number respectively
Amount.Calculate same concentrator type, the electrical energy meter fault rate of different geographical.Calculate same concentrator type, different manufacturers
Electrical energy meter fault rate.Analyze whether various electrical energy meter fault rates have discrete feature, if various electrical energy meter fault rates have
Discrete type, the factor of influence that the factor is exported not as emergency value, conversely, the impact that exports as emergency value of the factor because
Son.
In the seminar and basic unit's investigation process discovery of optimization collection O＆M closed loop management system, meter reading data is presently, there are
The intermittent phenomena for cutting in and out, i.e., for single meter collection failure but the phenomenon that can voluntarily recover without manpower intervention compared with
For obvious.Quantitative analysis is carried out to meter reading data situation：1 representative is checked meter successfully, and 0 representative is checked meter unsuccessfully, the group of its meter reading data
Be combined into 101 ..., 1001 ..., 10001.....There is phenomenon for 101 repeatedly in such failed subs criber in one month ..., 1001 ...,
10001...., the combined situation of 100001.....
Certain January is collected, certain region 24907294 family low-voltage customer whole month meter reading data is analysis sample, i.e., one month
Inside at least occur three times and the above 101 ..., 1001 ..., the user of 10001...., 100001.... combined situation is according to concentrator
Type, region are counted.
As shown in figs. 10-11, calculating analysis is carried out to data：There is the meter collection event of intermittent defect in I type concentrators
Barrier rate mean value is 5.49%, and the standard deviation value of the dispersion degree in sign group between individuality is 0.0107.
Likewise, the single meter collection fault rate under the II type concentrators of the intermittent defect occurred for certain January
Counted by region,
As illustrated by figs. 12-13, data are carried out calculating analysis analysis：The meter that intermittent defect occur in II type concentrators is adopted
Collection fault rate mean value is 2.73%, and the standard deviation value of the dispersion degree in sign group between individuality is 0.0071.
Understood according to Figure 10-13, when analyzing different types of concentrator, need to refer to platform area lines branch quantity, extend
Region area, live power utilization environment and line style.I type concentrators occur intermittent defect meter gather fault rate apparently higher than
II type concentrators, main cause is many, wide, live power utilization environment complexity in extension region of low-voltage platform area lines branch etc., is caused low
Piezoelectricity powerline carrier communication is unstable, and II type concentrator downlink communications are mainly RS485 twisted-pair communications, therefore more steady
It is fixed, but for same type concentrator, intermittent defect occurrence rate is relatively stable.
Press continuing with the user's inventory under the I type concentrators for occurring 3 times, 5 times, 6 times and 7 times intermittent defects for month
Electric energy meter producer is counted, it is found that failure focuses primarily upon Shenzhen Spacefight Techrise Electronics Co., Ltd, Shenzhen section land, Hangzhoupro
State Haixing County, the western power in Hangzhou, Zhejiang Maxwell, but the installation number of this five electric energy meter producers are also very big, further calculate this five
Individual electric energy meter producer breaks down ratio, substantially 0.227% or so, as shown in figure 14.
In the same manner, we have been also carried out statistics to terminal producer, it is found that failure focuses primarily upon Jiangsu light one, Hangzhou torch China Tech
Skill, Skyworth, Jiangsu Linyang Electronics Co., Ltd., Qingdao GaoKe Communications Technology Co., Ltd., equally, this five terminal producers
Installation number it is also very big, further calculate the ratio that breaks down of this five terminal producers, substantially 0.247% or so,
As shown in figure 15.
For the user's inventory under the II type concentrators of 4 times, 5 times, the 6 times and 7 times intermittent defects of an appearance in month by electricity
Can table counted, find failure focus primarily upon electric energy meter producer for Hangzhou Haixing County, De Lixi, the positive Thailand in Zhejiang, the western power in Hangzhou,
Zhejiang Maxwell, but the installation number of this five electric energy meter producers is also very big, further calculates this five electric energy meter producers and occurs
Failure ratio, substantially 0.061% or so, as shown in figure 16.
In the same manner, we have been also carried out statistics to terminal producer, find failure focus primarily upon eight reach, Jiangsu Lin Yang electronics shares
Part Co., Ltd, Hangzhou torch China Tech skill, Hangzhou torch China Tech, the skill of Jiangsu light one, equally, the installation number of this five terminal producers
It is very big, further calculate this five terminal producers and break down ratio, substantially 0.055% or so, as shown in figure 17.
It is seen from the above data that intermittent defect is not presented aggregation effect (as by meter producer, terminal factory
Family, Distribution Area, concentrator type etc.), there is certain discrete feature.
Continue type (101..., 1001..., the 10001...., 100001...) quantity and ratio to there is each failure
Counted.As depicted in figures 18-20, either I types concentrator or II type concentrators, occur 3 times and above interval for one month
Property failure concentrator fault type be concentrated mainly in 101,1001 both types, the intermittence recovered automatically in three days therefore
Barrier accounts for more than the 90% of intermittent defect total quantity.
Intermittent defect is not presented aggregation effect (such as meter producer, terminal producer, terminal type, Area distribution
Deng), there is the intermittent defect accounting more than 90% recovered automatically in certain discrete feature, and three days, therefore gather O＆M
The troubleshooting time limit in closed loop management can not the complexity that processes of characterization failure, therefore the factor is defeated not as emergency value
The factor of influence for going out.
Set up the computation model of monthly power consumption
Analyze influence degree of the monthly power consumption to acquisition abnormity urgency level, directly with user the moon power consumption as defeated
Enter, the impact fluctuation of the factor can be caused excessive, it is therefore desirable to divided user's moon power consumption by certain interval.By platform area
Classified according to capacity, and counted that a certain annual platform area is public to become power consumption and respective volume is public becomes lower resident, non-resident
(single-phase, three-phase) charge condition.
Concrete statistical analysis process is as described below, and the Ge Tai areas of a certain region 242402 are classified according to capacity,
And count that a certain annual platform area is public to become power consumption and respective volume is public becomes lower resident, non-resident (single-phase, three-phase) charge condition.
As Figure 2-3, with 250 dry volt-ampere and following resident's electricity as 100 kilowatt hours or so, 315 dry volt-ampere and
More than single-phase user be its 2 times or so, 250 dry volt-ampere and following non-resident three-phase meter are its 3 times or so, 315 dry volt-ampere and with
Upper non-resident three-phase meter is its 10 times or so.
If only using electricity as the unit of emergency value, the numeric ratio for finally calculating is larger, and needs are converted,
Concrete distributed area of the user in statistics is determined according to the actual moon power consumption of user, is finally determined that the user is N number of
Standard electricity consumer.
From Fig. 4-5, when single-phase user's electricity is lacked, platform area line loss will be caused to fluctuate in 0.6%-0.7%,
When one it is non-occupy three-phase user electricity and lack when, platform area line loss will be caused to fluctuate 3.5% or so.Therefore, monthly power consumption energy
Enough factors of influence as impact urgency.
(200,000 are less than or equal to resident and non-resident single-phase meter user moon power consumption as standard family electricity separation
Watt-hour) it is 1 family standard family, (more than 200 kilowatt hours and less than or equal to 1000 kilowatt hours) are 2 family standard families, (are more than 1000 kilowatts
When) it is 3 family standard families.
The standard amount r (x of the actual moon power consumption equivalent of useri)：
g(xi) be specify user's current moon power consumption, XiFor the user of i-th electric energy meter
Set up the computation model of aberrant continuation number of days
Each household is analyzed per daily power consumption standard deviation degree, whether the daily power consumption fluctuation for analyzing user is gentle, such as
The electricity that the daily power consumption fluctuation of the most of user of fruit gently can then be lost aberrant continuation number of days is calculated as urgency level
The factor, the electricity that can not be lost aberrant continuation number of days if the daily power consumption fluctuation of most of user is larger is used as urgent
Degree calculates the factor.
Certain January 10000 family resident and non-resident daily power consumption data are collected, are calculated per daily power consumption standard deviation,
And arrange from small to large, show that curve map is as shown in Figure 6.Determine that number of users of its electric standard deviation less than 17 accounts for sum
92%, it is the flex point of standard deviation curves figure.
Likewise, it is non-resident to select 10000 families immediately in a certain region, calculate per daily power consumption standard deviation, and from little
To longer spread, show that curve map is as shown in Figure 7.Determine that number of users of its electric standard deviation less than 17 accounts for sum
88.75%, it is the flex point of standard deviation curves figure.
From Fig. 6 and Fig. 7, assert that 90% or so the average daily electricity fluctuation of user is little, therefore, aberrant continuation number of days can
As the factor of influence for affecting urgency.
The odd-numbered day loss monitoring electricity that the present invention is caused using the per day electricity within month as failure number of days.It is abnormal
The electricity that continuous dayses are lost=aberrant continuation number of days is multiplied by the average daily power consumption of the specified user current moon, it is intended that user works as
The power consumption of the front moon needs to refer to user's upper one year with month power consumption, a upper month power consumption and first three daily power consumption.
Computing formula is as follows：
More accurately to estimate the moon power consumption of specified user, increase the lunar calendar Gregorian calendar, temperature humidity over the years impact, this use
Family year increases by the factor to affect of power consumption etc. on a year-on-year basis.
The emergency value formula of Abnormal lasting is as follows：
Set up under terminal and mount the computation model of electric energy meter value of utility
The number of faults that whole acquisition abnormities that certain time period in current acquisition system is produced are affected and handling duration system
Meter analysis.
As shown in fig. 21-22, existing problems one：The electric energy meter number of one fault type impact is more, then processing priority
Higher, the sequence of troubleshooting benefit should be：Under I type concentrators completely without data ＞ I types terminal with main website without the ＞ II type collection that communicates
Middle device completely without data ＞ II types terminal and main website without ammeter under the ＞ collectors that communicate completely without data ＞ N days without recording electric energy meter data,
Successively decrease arrangement according to urgency level is processed, the process limited should be incremented by principle, but in I types concentrator and main website without communicating and N days
The class of no data two occurs in that the average treatment time limit declines obvious trend extremely, illustrates existing problems.
Existing problems two：Ammeter distribution proportion is mounted under II type collectors under electric energy meter
As shown in figs. 23-24, it can be seen that the situation of II type collector 1 piece of electric energy meter of carry account for 94.91%.According to
Data result is investigated and analysed, due to grass-roots unit and do not know about the type calculating is the mounting 2 pieces of electric energy meters and above
II type collector exceptions, blindness thinks that the II types collector mounting electric energy meter overwhelming majority is 1 piece of electric energy meter, causes maintenance positive
Property is not high.Value of utility is exported in O＆M to be needed to consider carry failure electric energy meter number, and not exclusively mounts electric energy meter under terminal
Number, can not otherwise reach the maximization of O＆M effectiveness.
To sum up analyze, needs are using electric energy meter quantitative utility value is mounted under terminal as the factor of influence for affecting urgency
System can judge its priority, overall utility value mould by analyzing the value of utility summation of each process lower faulty ammeter of work order
Type is as follows：
Y (emergency value)=Σ f (Xi) (i represents the 1st after collecting ... the electric energy meter of n)
XiFor the user of i-th electric energy meter, f (Xi) represent i-th electric energy meter user urgency
Set up total acquisition abnormity urgency level computation model
By the acquisition abnormity urgency level influencing factors analysis to existing collection, for single meter emergency value comes
Say mainly there is " distance check meter number of days ", " Abnormal lasting " and " monthly average power consumption ", " electric energy meter value of utility " four directions at present
Face rings, and " intermittent defect " does not occur direct relation, therefore the factor does not consider.The emergency value of abnormal work order is the work order
Comprising failure ammeter emergency value it is cumulative.Total acquisition abnormity urgency level computation model is：
Y (emergency value)=Σ f (Xi) (i represents the 1st after collecting ... the electric energy meter of n)
f(xi)=j (xi)+s(xi), wherein：
Thus total emergency value of single table is obtained, for instructing the precedence of abnormality processing, daily collection is enabled to
Maintenance work is shot the arrow at the target, and reaches the effect got twice the result with half the effort.
5th step, according to computation model, determines the precedence of abnormality processing, and circuit runtime is safeguarded.
Presently preferred embodiments of the present invention is the foregoing is only, not to limit the present invention, all essences in the present invention
Any modification, equivalent and improvement made within god and principle etc., should be included within the scope of the present invention.
Claims (10)
1. a kind of acquisition abnormity urgency level computational methods of day number of days of being checked meter based on distance, it is characterised in that including following step
Suddenly：
The first step, primarily determines that the factor of influence of acquisition abnormity urgency
The factor of influence of acquisition abnormity urgency is determined by electric power operational system expert discussion, the factor of influence includes that distance is copied
Table number of days；
Second step, the data of collecting circuit runtime
The data include collection in worksite data and trouble ticket dispatch data, are related to a period of time of the various users in multiple regions
Interior power consumption, and then the power consumption to high-volume user carries out fluction analysis；
3rd step, sets up standard electricity consumer
Standard electricity consumer is that the monthly average that all types of user is counted on the basis of the actual electricity consumption situation for extracting most of user is used
Electricity, then according to the most eurypalynous electricity consumer average electricity of user as standard electricity consumer power consumption, all factors of influence pair
Finally all conversion is standard electricity consumer for the impact of urgency；
4th step, the analyzing influence factor simultaneously sets up model
Urgency factor of influence judgment models are exactly, by the existing service data of system, to affect to carry out data point according to each factor
Analysis, then showing when result shows factor of influence and final result there are obvious paradigmatic relation or continuous should be by the factor
Urgency calculating is counted, then shows that the factor is counted into urgency calculates when result is discrete discontinuous；Set up away from
From the computation model of day number of days of checking meter, the meter reading data of example of checking meter day is mostly important in the middle of one month, and shortage of data will within this day
Cause manual metering, calculate the cost of manual metering, if relatively costly, day number of days that needs the distance to check meter is tight as affecting
The factor of influence of anxious degree, if cost is relatively low, need not；
5th step, according to computation model, determines the precedence of abnormality processing, and circuit runtime is safeguarded.
2. a kind of acquisition abnormity urgency level computational methods of day number of days of being checked meter based on distance as claimed in claim 1, it is special
Levy and be, nearer apart from next day of checking meter, abnormality processing urgency is higher, statistics continues the N days electric energy meter numbers without meter reading data
Distribution situation, analyzes the relation of failure ammeter and continuous dayses, determines a number of days n that can process most failure ammeters；
N days are selected as threshold value, the factor for exceeding threshold values apart from number of days affects to be 0, less process is urgent in threshold values apart from number of days
Angle value is bigger.
3. a kind of acquisition abnormity urgency level computational methods of day number of days of being checked meter based on distance as claimed in claim 2, it is special
Levy and be, according to the theory of standard electricity consumer, electricity consumer to be collected is converted to r (xi) individual standard electricity consumer.
4. a kind of acquisition abnormity urgency level computational methods of day number of days of being checked meter based on distance as claimed in claim 3, it is special
Levy and be, distance day number of days abnormality processing urgency Controlling model of checking meter is as follows：
(n：Process time threshold value, m：Distance is checked meter a day number of days), r (xi)：Standard amount).
5. a kind of acquisition abnormity urgency level computational methods of day number of days of being checked meter based on distance as claimed in claim 4, it is special
Levy and be, the factor of influence also includes：Intermittent defect, monthly average power consumption, Abnormal lasting, electric energy meter value of utility.
6. a kind of acquisition abnormity urgency level computational methods of day number of days of being checked meter based on distance as claimed in claim 5, it is special
Levy and be, set up intermittent defect decision model, analyze whether various electrical energy meter fault rates have discrete feature, if various electricity
Energy table fault rate has discrete type, the factor of influence that the factor is exported not as emergency value, conversely, the factor is used as urgency
The factor of influence of value output.
7. a kind of acquisition abnormity urgency level computational methods of day number of days of being checked meter based on distance as claimed in claim 6, it is special
Levy and be, carry out counting failure electric energy meter quantity, electric energy meter quantity respectively according to the producer of concentrator type, region, concentrator；
Calculate same concentrator type, the electrical energy meter fault rate of different geographical；Calculate same concentrator type, the electricity of different manufacturers
Can table fault rate.
8. a kind of computational methods of acquisition abnormity urgency level as claimed in claim 7, it is characterised in that set up monthly electricity consumption
The computation model of amount, analyzes influence degree of the monthly power consumption to acquisition abnormity urgency level, directly with the moon power consumption of user
As input, the impact fluctuation of the factor can be caused excessive, it is therefore desirable to divided user's moon power consumption by certain interval；
Platform area is classified according to capacity, and count a certain annual platform area it is public become power consumption and respective volume it is public become lower resident,
Non-resident charge condition.
9. a kind of computational methods of acquisition abnormity urgency level as claimed in claim 8, it is characterised in that if only using electricity
The unit as emergency value is measured, the numeric ratio for finally calculating is larger, needs are converted, according to the actual moon power consumption of user
Determine concrete distributed area of the user in statistics, finally determine that the user is N number of standard electricity consumer.
10. a kind of computational methods of acquisition abnormity urgency level as claimed in claim 9, it is characterised in that set up abnormal holding
The computation model of continuous number of days, is analyzed to each household per daily power consumption standard deviation degree, analyzes the daily power consumption fluctuation of user and is
No gentle, the electricity that can be lost aberrant continuation number of days if the daily power consumption fluctuation of most of user is gentle is used as urgent
Degree calculates the factor, the electricity that can not be lost aberrant continuation number of days if the daily power consumption fluctuation of most of user is larger
The factor is calculated as urgency level.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611125744.1A CN106646332B (en) | 2016-12-08 | 2016-12-08 | method for calculating abnormal acquisition emergency degree based on distance meter reading days |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611125744.1A CN106646332B (en) | 2016-12-08 | 2016-12-08 | method for calculating abnormal acquisition emergency degree based on distance meter reading days |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106646332A true CN106646332A (en) | 2017-05-10 |
| CN106646332B CN106646332B (en) | 2019-12-13 |
Family
ID=58824755
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201611125744.1A Active CN106646332B (en) | 2016-12-08 | 2016-12-08 | method for calculating abnormal acquisition emergency degree based on distance meter reading days |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106646332B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2007034420A (en) * | 2005-07-22 | 2007-02-08 | Telemidic Ltd | Emergency reporting system |
| CN103473710A (en) * | 2013-08-20 | 2013-12-25 | 国家电网公司 | Graded handling method for faults of centralized operation and maintenance systems |
| CN103606024A (en) * | 2013-08-22 | 2014-02-26 | 国家电网公司 | Centralized operation and maintenance system and method thereof based on dispatching data network |
| CN104391202A (en) * | 2014-11-27 | 2015-03-04 | 国家电网公司 | Abnormal electricity consumption judging method based on analysis of abnormal electric quantity |
| CN104504495A (en) * | 2014-11-27 | 2015-04-08 | 北京百度网讯科技有限公司 | Operation and maintenance abnormity processing method, device and equipment |
-
2016
- 2016-12-08 CN CN201611125744.1A patent/CN106646332B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2007034420A (en) * | 2005-07-22 | 2007-02-08 | Telemidic Ltd | Emergency reporting system |
| CN103473710A (en) * | 2013-08-20 | 2013-12-25 | 国家电网公司 | Graded handling method for faults of centralized operation and maintenance systems |
| CN103606024A (en) * | 2013-08-22 | 2014-02-26 | 国家电网公司 | Centralized operation and maintenance system and method thereof based on dispatching data network |
| CN104391202A (en) * | 2014-11-27 | 2015-03-04 | 国家电网公司 | Abnormal electricity consumption judging method based on analysis of abnormal electric quantity |
| CN104504495A (en) * | 2014-11-27 | 2015-04-08 | 北京百度网讯科技有限公司 | Operation and maintenance abnormity processing method, device and equipment |
Non-Patent Citations (2)
| Title |
|---|
| 王丽莹 等: "变压器运行异常紧急检修业务的人员优化方法", 《山西电力》 * |
| 陈龙 等: "基于大数据的电网信息运维主动监控预警系统", 《电气应用》 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106646332B (en) | 2019-12-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105915398B (en) | Rural power grid fault based rapid detection and power restoration system and concentrator detection method thereof | |
| CN108573350B (en) | Distribution network line loss synchronization calculation and multidimensional analysis method | |
| CN106780125A (en) | A kind of acquisition abnormity urgency level computational methods based on monthly power consumption | |
| CN106405475A (en) | Electric energy meter abnormity diagnosis method | |
| CN107680368A (en) | A kind of metering device on-line monitoring and intelligent diagnosing method based on gathered data | |
| CN106771862B (en) | A kind of acquisition abnormity fault point polymerization that grid is combined with space length | |
| CN106803125B (en) | A kind of acquisition abnormity urgency level calculation method based on the conversion of standard electricity consumer | |
| CN113032454A (en) | Interactive user power consumption abnormity monitoring and early warning management cloud platform based on cloud computing | |
| CN110346661B (en) | Method and system for automatically inspecting abnormal user voltage | |
| CN101958544A (en) | System and method for calculating line loss rate of electric power distribution line | |
| CN104635198B (en) | Remote monitoring and diagnosing method for electric energy metering device with timely fault finding function | |
| CN110571925B (en) | Method for analyzing power quality by using data of power distribution network monitoring terminal | |
| CN110276511A (en) | A kind of line change relationship anomalous discrimination method based on electricity and line loss relevance | |
| CN107666148B (en) | Line fault studying and judging method based on distribution transformer power failure signal | |
| CN213750303U (en) | Electric energy metering abnormity diagnosis system based on electricity consumption information acquisition system | |
| CN113189418B (en) | Topological relation identification method based on voltage data | |
| CN112307003A (en) | Power grid data multidimensional auxiliary analysis method, system, terminal and readable storage medium | |
| CN114742488B (en) | Main transformer operation risk assessment method and system | |
| CN104714206B (en) | Remote monitoring and diagnosing method for electric energy metering device capable of finding faults timely | |
| CN112700144A (en) | Transformer substation operation state risk assessment method, device, equipment and storage medium | |
| CN115270974A (en) | Intelligent electricity stealing detection system based on big data analysis | |
| CN106682817B (en) | Judgment method for collecting abnormal emergency degree | |
| CN106814268A (en) | A kind of big data analysis method based on intermittent defect | |
| CN103018611A (en) | Non-invasive load monitoring method and system based on current decomposition | |
| CN106711998B (en) | A kind of acquisition abnormity urgency level calculation method based on Abnormal lasting |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information |
Address after: 311400 No. 3 Guangming Road, Hangzhou, Zhejiang, Fuyang Applicant after: Fuyang district power supply Co., Ltd., Hangzhou City, Zhejiang Applicant after: State Grid Zhejiang Electric Power Company Applicant after: State Grid Corporation Address before: 311400 No. 3 Guangming Road, Hangzhou, Zhejiang, Fuyang Applicant before: STATE GRID ZHEJIANG HANGZHOU FUYANG POWER SUPPLY COMPANY Applicant before: State Grid Zhejiang Electric Power Company Applicant before: State Grid Corporation |
|
| CB02 | Change of applicant information | ||
| CB03 | Change of inventor or designer information |
Inventor after: Xu Chuanzi Inventor after: Lou Jieni Inventor after: Shen Baiqiang Inventor after: Lang Jufen Inventor after: Che Liping Inventor after: Zhang Daqing Inventor after: Zhu Liyong Inventor after: Yang Muwei Inventor after: Wang Shuo Inventor after: Lou Ying Inventor before: Shen Baiqiang Inventor before: Lou Jieni Inventor before: Lang Jufen Inventor before: Xu Chuanzi Inventor before: Che Liping Inventor before: Zhang Daqing Inventor before: Zhu Liyong Inventor before: Yang Muwei Inventor before: Wang Shuo Inventor before: Lou Ying |
|
| CB03 | Change of inventor or designer information | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |