CN106022951A - Electricity consumption abnormity analysis method and apparatus - Google Patents
Electricity consumption abnormity analysis method and apparatus Download PDFInfo
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Abstract
The invention discloses an electricity consumption abnormity analysis method and apparatus. The method comprises the following steps: obtaining electricity consumption information, and distributing a corresponding index weight to each type of sub information in the electricity consumption information; respectively determining whether corresponding electricity consumption abnormity suspicious data exist in each type of sub information in the electricity consumption information; when the corresponding electricity consumption abnormity suspicious data exists in one type of sub information, increasing a preset increment corresponding to the electricity consumption information abnormity suspicious data to a preset electricity consumption abnormity suspicious index, wherein a preset increment sum of the type of sub information is not greater than a maximum index value corresponding to the index weight of the type of sub information; and when the electricity consumption abnormity suspicious index is greater than a preset threshold, determining that an electricity consumption abnormal event exists. According to the method, through integrated analysis determining, users with quite high electricity consumption abnormity degrees are quite accurately sought, the investigation difficulty is greatly reduced, and the work efficiency of electricity inspection personnel of an electric power company is improved.
Description
Technical field
The present invention relates to technical field of electric power, the method and device analyzed particularly to a kind of multiplexing electric abnormality.
Background technology
Along with expanding economy, constantly expanding the demand of electricity, the expansion of electric power selling market stimulates again
The development of whole power generation.But be as the growth of expanding economy and power consumption, especially along with
The foundation of market economy system, multiplexing electric abnormality problem becomes increasingly to highlight, and not only gives country and electric power warp
Battalion headquarter's door causes huge economic loss, but also severe jamming is normal for electricity consumption order, even draws
Ignition calamity, makes power supply unit damage and even causes large-area power-cuts, affect public electric wire net safety and society is steady
Fixed, some lawless persons privately on power supply facilities random wiring have when causing the safety problem of personal injury also
Occur.At present in addition to specially becoming user power utilization anomalous event and taking place frequently, resident's multiplexing electric abnormality case is also
Cumulative year after year, due to resident's substantial amounts, year power consumption sum the hugest, therefore resident uses
The multiplexing electric abnormality at family can not be out in the cold, it is necessary to uses corresponding measure to reduce resident's electricity consumption different
The generation of ordinary affair part, retrieves economic losses to country and power supply enterprise.
For resident's multiplexing electric abnormality case of current cumulative year after year, electric power enterprise has had taken up relevant
Measure is tackled, such as: strengthens Controlling line loss, improve electricity system of looking into, improve and check meter number of times etc., is carried
Power utility check instrument great majority be circuit tester or all kinds of corresponding electricity consumption monitoring instrument.Use circuit tester only
The information such as user's voltage, electric current can be detected, it is difficult to accurately obtain the power information of user.Use electricity consumption is supervised
Survey instrument the most also can only check electricity, load service condition, analyzes use by artificial contrast and summary
Family electricity consumption service condition, investigates and prosecutes time-consuming, laborious, investigation difficulty height, and efficiency is low.Existing there is also
According to the abnormal method carrying out judging of current/voltage, but such method judges that form is single, and accuracy is not
High.
The information being disclosed in this background section is merely intended to increase the reason of the general background to the present invention
Solve, and be not construed as recognizing or imply in any form that this information structure is for this area general technology
Prior art well known to personnel.
Summary of the invention
It is an object of the invention to provide the method and device that a kind of multiplexing electric abnormality is analyzed, thus overcome existing
The defect that electrical energy consumption analysis scheme efficiency is low and accuracy is the highest.
For achieving the above object, embodiments provide a kind of method that multiplexing electric abnormality is analyzed, including:
Obtain power information, and be that the sub-information of each class in power information distributes corresponding index weights；
Power information includes in the sub-information of logout, electricity quantum information, the sub-information of load and the sub-information of line loss
One class or multiclass；
Judge whether the sub-information of each class in power information exists corresponding multiplexing electric abnormality suspicion number respectively
According to；
When the sub-information of one type exists corresponding multiplexing electric abnormality suspicion data, for default multiplexing electric abnormality
Suspicion index increases the preset increments corresponding with multiplexing electric abnormality suspicion data, and such sub-information is default
Increment sum is not more than the Maximum Index value that the index weights of such sub-information is corresponding；
When multiplexing electric abnormality suspicion index is more than predetermined threshold value, determines and there is multiplexing electric abnormality event.
In a kind of possible implementation, the sub-information of logout include decompression event, full decompression event,
Disconnected phase event, cutout event, defluidization event, negative phase sequence event, the reverse event of trend, current imbalance
One or more in event, magnetic interference event, on-load switch misoperation event and game clock lid event；
When power information includes the sub-information of logout, divide according to the sub-information of each class in power information
Do not judge whether multiplexing electric abnormality data, including:
Obtain respectively each event is corresponding in the sub-information of logout start time electricity consumption data and at the end of
Carve electricity consumption data, and determine corresponding power change values；Change more than predetermined power in power change values
During value, determine that this event exists multiplexing electric abnormality data；And/or
Determine the time of origin of each event in the sub-information of logout respectively, and determine the first Preset Time
In section every day freeze electricity day, and the time of origin of event is positioned at the first preset time period；At two
Freeze difference between electricity continuous print day more than preset freeze electricity difference time, determine that this event exists
Multiplexing electric abnormality data.
In a kind of possible implementation, when power information includes electricity quantum information, according to by telecommunications
The sub-information of each class in breath judges whether multiplexing electric abnormality data respectively, including:
Determine the daily power consumption E of every day in the second preset time periodi, and determine the meansigma methods of daily power consumption
AvgE；At AvgE and EiBetween difference more than the first preset difference value time, determine i-th day and there is electricity consumption
Abnormal data；Wherein, i=1,2,3 ... n, n are the natural law that the second preset time period comprises；And/or
The history daily power consumption Eh of every day in history the second preset time period same period is obtained from main station systemi, and
Determine meansigma methods AvgEh of history daily power consumption；At AvgEh and daily power consumption EiBetween difference be more than
During the second preset difference value, determine i-th day and there are multiplexing electric abnormality data；Wherein, i=1,2,3 ... n, n are second
The natural law that preset time period comprises；And/or
Determine slip daily power consumption meansigma methods AvgE of k daysj, daily adjacent two slips k days
When difference between electricity meansigma methods is more than three preset difference values, determine AvgEjThere are multiplexing electric abnormality data；
Wherein,J is the slip initial natural law of k days, EiBe i-th day corresponding daily
Electricity.
In a kind of possible implementation, when power information includes the sub-information of load, according to by telecommunications
The sub-information of each class in breath judges whether multiplexing electric abnormality data respectively, including:
Determine the load record of each load point, a load point magnitude of voltage and rated voltage it
Between difference more than predeterminated voltage difference time, determine that this load point exists multiplexing electric abnormality data；Or
Determine the load record of each load point, a load point current value and rated current it
Between difference more than predetermined current difference time, determine that this load point exists multiplexing electric abnormality data.
In a kind of possible implementation, when power information includes the sub-information of line loss, according to by telecommunications
The sub-information of each class in breath judges whether multiplexing electric abnormality data respectively, including:
Obtain the line loss exception platform district mark in the sub-information of line loss, and determine corresponding line loss exception platform district；
When local stoichiometric point is located in one of in line loss exception platform district, determines and there are electrical anomaly suspicion data.
Based on same inventive concept, the embodiment of the present invention also provides for the device that a kind of multiplexing electric abnormality is analyzed,
Including:
Acquisition module, is used for obtaining power information, and is each class sub-information distribution phase in power information
The index weights answered；Power information include the sub-information of logout, electricity quantum information, the sub-information of load and
A class in the sub-information of line loss or multiclass；
Judge module, for judging whether the sub-information of each class in power information exists corresponding use respectively
Electrical anomaly suspicion data；
Processing module, is used for when the sub-information of one type exists corresponding multiplexing electric abnormality suspicion data, for
The multiplexing electric abnormality suspicion index preset increases the preset increments corresponding with multiplexing electric abnormality suspicion data, and should
The preset increments sum of the sub-information of class is not more than the Maximum Index value that the index weights of such sub-information is corresponding；
Determine module, for when multiplexing electric abnormality suspicion index is more than predetermined threshold value, determining that to there is electricity consumption different
Ordinary affair part.
In a kind of possible implementation, the sub-information of logout include decompression event, full decompression event,
Disconnected phase event, cutout event, defluidization event, negative phase sequence event, the reverse event of trend, current imbalance
One or more in event, magnetic interference event, on-load switch misoperation event and game clock lid event；
When power information includes the sub-information of logout, it is judged that module specifically for:
Obtain respectively each event is corresponding in the sub-information of logout start time electricity consumption data and at the end of
Carve electricity consumption data, and determine corresponding power change values；Change more than predetermined power in power change values
During value, determine that this event exists multiplexing electric abnormality data；And/or
Determine the time of origin of each event in the sub-information of logout respectively, and determine the first Preset Time
In section every day freeze electricity day, and the time of origin of event is positioned at the first preset time period；At two
Freeze difference between electricity continuous print day more than preset freeze electricity difference time, determine that this event exists
Multiplexing electric abnormality data.
In a kind of possible implementation, when power information includes electricity quantum information, it is judged that module has
Body is used for:
Determine the daily power consumption E of every day in the second preset time periodi, and determine the meansigma methods of daily power consumption
AvgE；At AvgE and EiBetween difference more than the first preset difference value time, determine i-th day and there is electricity consumption
Abnormal data；Wherein, i=1,2,3 ... n, n are the natural law that the second preset time period comprises；And/or
The history daily power consumption Eh of every day in history the second preset time period same period is obtained from main station systemi, and
Determine meansigma methods AvgEh of history daily power consumption；At AvgEh and daily power consumption EiBetween difference be more than
During the second preset difference value, determine i-th day and there are multiplexing electric abnormality data；Wherein, i=1,2,3 ... n, n are second
The natural law that preset time period comprises；And/or
Determine slip daily power consumption meansigma methods AvgE of k daysj, daily adjacent two slips k days
When difference between electricity meansigma methods is more than three preset difference values, determine AvgEjThere are multiplexing electric abnormality data；
Wherein,J is the slip initial natural law of k days, EiBe i-th day corresponding daily
Electricity.
In a kind of possible implementation, when power information includes the sub-information of load, it is judged that module has
Body is used for:
Determine the load record of each load point, a load point magnitude of voltage and rated voltage it
Between difference more than predeterminated voltage difference time, determine that this load point exists multiplexing electric abnormality data；Or
Determine the load record of each load point, a load point current value and rated current it
Between difference more than predetermined current difference time, determine that this load point exists multiplexing electric abnormality data.
In a kind of possible implementation, when power information includes the sub-information of line loss, it is judged that module has
Body is used for:
Obtain the line loss exception platform district mark in the sub-information of line loss, and determine corresponding line loss exception platform district；
When local stoichiometric point is located in one of in line loss exception platform district, determines and there are electrical anomaly suspicion data.
The method and device that a kind of multiplexing electric abnormality that the embodiment of the present invention provides is analyzed, presets multiplexing electric abnormality and dislikes
Doubt index, by power information being carried out classification indicator of distribution weight, according to the sub-information of each class respectively
Determine the multiplexing electric abnormality the most corresponding preset increments of suspicion data, and this multiplexing electric abnormality suspicion index is increased phase
The preset increments answered, when the multiplexing electric abnormality suspicion index after cumulative is more than predetermined threshold value, i.e. may determine that
There is multiplexing electric abnormality event.The method carries out classification indicator of distribution weight to power information, such that it is able to
Carry out comprehensive analysis and judgement according to electricity, event, load and line loss information, accurately search electricity consumption different
The user that Chang Chengdu is higher, and greatly reduce investigation difficulty, improve Utilities Electric Co. power utility check personnel's
Work efficiency.Meanwhile, power information classified and respectively multiplexing electric abnormality suspicion index added pre-
If increment, finally the multiplexing electric abnormality determined respectively suspicion index is carried out cumulative determine final
ELI, can improve treatment effeciency with the sub-information of the different class of synchronization process.
Other features and advantages of the present invention will illustrate in the following description, and, partly from froming the perspective of
Bright book becomes apparent, or understands by implementing the present invention.The purpose of the present invention is excellent with other
Point can come real by structure specifically noted in the description write, claims and accompanying drawing
Now and obtain.
Accompanying drawing explanation
Accompanying drawing is for providing a further understanding of the present invention, and constitutes a part for description, with this
Inventive embodiment is used for explaining the present invention together, is not intended that limitation of the present invention.In the accompanying drawings:
Fig. 1 is the method flow diagram that in the embodiment of the present invention, electrical anomaly is analyzed；
Fig. 2 is event class determination methods flow chart in the embodiment of the present invention one；
Fig. 3 is electricity class determination methods flow chart in the embodiment of the present invention one；
Fig. 4 is the structure drawing of device that in the embodiment of the present invention, electrical anomaly is analyzed.
Detailed description of the invention
For making the purpose of the embodiment of the present invention, technical scheme and advantage clearer, below in conjunction with this
Accompanying drawing in bright embodiment, is clearly and completely described the technical scheme in the embodiment of the present invention,
Obviously, described embodiment is a part of embodiment of the present invention rather than whole embodiments.Based on
Embodiment in the present invention, those of ordinary skill in the art are obtained under not making creative work premise
The every other embodiment obtained, broadly falls into the scope of protection of the invention.Reference table identical in accompanying drawing
Show the same or analogous element of function.Although the various aspects of embodiment shown in the drawings, but remove
Non-specifically is pointed out, it is not necessary to accompanying drawing drawn to scale.
The embodiment of the present invention provides a kind of method that multiplexing electric abnormality is analyzed, shown in Figure 1, including step
101-104:
Step 101: obtain power information, and be that each class sub-information distribution in power information refers to accordingly
Mark weight；Power information includes the sub-information of logout, electricity quantum information, the sub-information of load and line loss
A class in information or multiclass.
Preferably, power information includes at least the two sub-information of class.In the embodiment of the present invention, to above-mentioned electricity consumption
Information is classified, and specifically can be divided into event class, electricity class, load class, line loss class etc., relatively
The sub-information of logout, electricity quantum information, the sub-information of load and the sub-information of line loss that should be above-mentioned.Meanwhile,
Distribute corresponding index weights for the sub-information of each class in power information, judged by default index
Multiplexing electric abnormality degree.Concrete, can with the embodiment of the present invention utilizes multiplexing electric abnormality suspicion index (ELI,
Electric Larceny Index) assess the multiplexing electric abnormality degree of user, the highest then multiplexing electric abnormality of index is disliked
Doubt bigger.Such as, ELI, in terms of full marks 100 points, can distribute event class, electricity class, load class, line
Damage class index weights in the overall evaluation and be respectively 40%, 40%, 10%, 10%.
Step 102: judge whether the sub-information of each class in power information exists corresponding multiplexing electric abnormality respectively
Suspicion data.
Owing to power information can include the sub-information of many middle classifications, therefore information sub-to every class respectively is needed to enter
Row judges, it may be judged whether there are multiplexing electric abnormality suspicion data.It is big owing to the sub-information of every class all may comprise
Amount data, therefore and may incessantly there are multiplexing electric abnormality data in the sub-information of each class.
Step 103: when the sub-information of one type exists corresponding multiplexing electric abnormality suspicion data, for default
Multiplexing electric abnormality suspicion index increases the preset increments corresponding with multiplexing electric abnormality suspicion data, and such sub-letter
The preset increments sum of breath is not more than the Maximum Index value that the index weights of such sub-information is corresponding.
In the embodiment of the present invention, pre-setting multiplexing electric abnormality suspicion index, this multiplexing electric abnormality suspicion index has
There is initial value, typically this initial value can be set to zero, it is also possible to be set to other values.Meanwhile, as
Upper described, owing to the sub-information of each class and may exist multiplexing electric abnormality data incessantly, therefore this is preset and increases
Measure corresponding with multiplexing electric abnormality suspicion data.Such as, electricity consumption is being judged whether according to electricity quantum information
During abnormal data, can be according to the daily power consumption E of n days of electric energy meter recordiAnd meansigma methods AvgE is next
Judge, as the daily power consumption E of i-th dayiAnd the difference between this meansigma methods AvgE is preset more than one
Difference time, then may determine that i-th day and there are multiplexing electric abnormality data, the daily power consumption E of i.e. i-th dayiCorresponding
One multiplexing electric abnormality data；Meanwhile, the daily power consumption E in i+1 skyi+1And the difference between AvgE also may be used
The difference can preset more than this, then daily power consumption Ei+1Can also corresponding multiplexing electric abnormality data.Then in step
According to two above-mentioned multiplexing electric abnormality data, multiplexing electric abnormality suspicion index is increased by two accordingly in rapid 103
Preset increments.
Meanwhile, to be not more than the index weights of such sub-information corresponding for the preset increments sum of such sub-information
Maximum Index value；That is, even if there are a large amount of multiplexing electric abnormality data, only according to this in a certain sub-information of class
The electrical anomaly suspicion index that the sub-information of class can increase also is limited, and maximum is less than such sub-information
The Maximum Index value that index weights is corresponding.Such as, multiplexing electric abnormality suspicion index full marks are 100, and initial value is
Zero, the index weights of the sub-information (i.e. electricity quantum information) of electricity class is 40%, then electricity quantum information refers to
The Maximum Index value marking weight corresponding is 100 × 40%=40；If the n (100=60) according to electric energy meter record
It daily power consumption EiAnd meansigma methods AvgE carries out judging whether multiplexing electric abnormality data, if its
In the E of 25 daysiAnd the difference between this meansigma methods AvgE is more than a default difference, and each is used
Preset increments corresponding to electrical anomaly data is 2, then after multiplexing electric abnormality suspicion index is increased preset increments,
This multiplexing electric abnormality suspicion index can be 0+2 × 25=50；But the preset increments due to the sub-information of each class
Sum is not more than the Maximum Index value that the index weights of such sub-information is corresponding, electricity information index weight
Corresponding Maximum Index value is 40, therefore this multiplexing electric abnormality suspicion index is finally defined to 40.
Step 104: when multiplexing electric abnormality suspicion index is more than predetermined threshold value, determines and there is multiplexing electric abnormality event.
In the embodiment of the present invention, determining that the multiplexing electric abnormality suspicion data that the sub-information of each class exists are corresponding
Preset increments adds up, and increases in multiplexing electric abnormality suspicion index ELI, if the electricity consumption after Lei Jia is different
Often suspicion index is more than predetermined threshold value, then explanation power information comprises too much multiplexing electric abnormality suspicion data,
Therefore may determine that and there is multiplexing electric abnormality event.
The method that a kind of multiplexing electric abnormality that the embodiment of the present invention provides is analyzed, presets multiplexing electric abnormality suspicion index,
By power information being carried out classification indicator of distribution weight, determine electricity consumption respectively according to the sub-information of each class
The abnormal the most corresponding preset increments of suspicion data, and this multiplexing electric abnormality suspicion index is increased corresponding presetting
Increment, when the multiplexing electric abnormality suspicion index after cumulative is more than predetermined threshold value, i.e. may determine that and there is electricity consumption
Anomalous event.The method power information is carried out classification and indicator of distribution weight, such that it is able to according to electricity,
Event, load and line loss information carry out comprehensive analysis and judgement, accurately search multiplexing electric abnormality degree higher
User, and greatly reduce investigation difficulty, improve the work efficiency of Utilities Electric Co. power utility check personnel.
Preferably, as shown in above-mentioned steps 102, information sub-to every class judges respectively.Concrete,
In the embodiment of the present invention, the sub-information of logout include decompression event, full decompression event, disconnected phase event,
Cutout event, defluidization event, negative phase sequence event, the reverse event of trend, current imbalance event, magnetic field
One or more in interference incident, on-load switch misoperation event and game clock lid event.In power information
During information sub-including logout, step 102 judges respectively according to the sub-information of each class in power information
Whether there are multiplexing electric abnormality data, specifically include:
The start time electricity consumption data that in step A1, respectively the acquisition sub-information of logout, each event is corresponding
With finish time electricity consumption data, and determine corresponding power change values；
Step A2, power change values more than predetermined power changing value time, determine that this event exists electricity consumption
Abnormal data.
Such as, the sub-information of logout comprises the relevant information of decompression event, then in step A1
With determine the time started of decompression event, end time and start time electricity consumption data (as voltage,
Electric current, power etc.) and the electricity consumption data (voltage, electric current, power etc. can also be comprised) of finish time；
Before and after i.e. may determine that this decompression event of generation according to start time electricity consumption data and finish time electricity consumption data
Power change values.Meanwhile, may determine that decompression event according to decompression event start time and end time
Duration, step A2 determines the power change values under normal circumstances in identical duration
(as predetermined power changing value), at power change values and the power under normal circumstances of decompression event
When difference between changing value is excessive, (power change values such as decompression event becomes than power under normal circumstances
Change value more than 20% with first-class), then may determine that and there are multiplexing electric abnormality data, and then may determine that corresponding
Preset increments, and perform multiplexing electric abnormality suspicion index is increased by step 103 process of this preset increments.
Or, step 102 judges whether multiplexing electric abnormality data according to the sub-information of logout, tool
Body includes:
Step A3, determine the time of origin of each event in the sub-information of logout respectively, and determine first
Freeze electricity in preset time period the day of every day, and the time of origin of event is positioned at the first preset time period；
Step A4, the difference freezed two continuous print days between electricity more than preset freeze electricity difference time,
Determine that this event exists multiplexing electric abnormality data.
Concrete, what electric energy meter typically can store 62 days (two months) freezes electricity, in this event day
Record the time of origin of sub-information corresponding event within 62 days, then can perform step A3-A4.Such as,
Comprising the relevant information of decompression event in the sub-information of logout, the time of origin of this decompression event is ten days
Before (i.e. within 62 days), then can obtain this decompression event and the same day and the previous day and rear one occur
They totally 3 days (the i.e. first preset time period is 3 days) day freeze electricity, respectively Ei、Ei-1And Ei+1。
At difference (the i.e. E freezed day between electricityiWith Ei-1Between difference or EiWith Ei+1Between difference)
More than preset freeze electricity difference time, determine that this event exists multiplexing electric abnormality data.
It should be noted that when judging whether multiplexing electric abnormality data according to the sub-information of logout,
Above-mentioned steps A1-A2 can be only included, it is also possible to only include step A3-A4, it is also possible to include step simultaneously
Rapid A1-A4.Generally individually can bring the change of power or power consumption during due to generation anomalous event, therefore pass through
Change to power change values or the day amount of freezing can determine whether there is multiplexing electric abnormality number more accurately
According to.
Preferably, when power information includes electricity quantum information, believe according to each class in power information
Breath judges whether multiplexing electric abnormality data respectively, including:
Step B1, determine the daily power consumption E of every day in the second preset time periodi, and determine daily power consumption
Meansigma methods AvgE；
Step B2, at AvgE and EiBetween difference more than the first preset difference value time, determine i-th day and deposit
In multiplexing electric abnormality data；Wherein, i=1,2,3 ... n, n are the natural law that the second preset time period comprises.
Concrete,It should be noted that in the embodiment of the present invention, AvgE and Ei
Between difference mean " AvgE-E more than the first preset difference valueiMore than this first preset difference value ", or " Ei
-AvgE is more than this first preset difference value ", naturally it is also possible to only select one of which situation as judging bar
Part, as only at " AvgE-EiMore than this first preset difference value " time just determine and there are multiplexing electric abnormality data.
Other implications represented by similar description are identical.
Or, judge whether multiplexing electric abnormality data according to electricity quantum information, including:
Step B3, the history day electricity consumption of every day in main station system acquisition history the second preset time period same period
Amount Ehi, and determine meansigma methods AvgEh of history daily power consumption；
Step B4, at AvgEh and EiBetween difference more than the second preset difference value time, determine i-th day and deposit
In multiplexing electric abnormality data；Wherein, i=1,2,3 ... n, n are the natural law that the second preset time period comprises.
Wherein, freeze electricity bimestrial day owing to local electric energy meter typically may only preserve, history same period
Daily power consumption can be obtained by main station system.By by daily power consumption E theniWith history same period (as
Last year on corresponding date, or the most corresponding date etc. the year before last) meansigma methods compare, it is also possible to determine
Daily power consumption E theniThe most abnormal.Simultaneously as daily power consumption then and history same period is daily
Both there is normal error in electricity itself, therefore generally, the second preset difference value is more than above-mentioned first
Preset difference value；It can also be provided that it is identical.
Or, judge whether multiplexing electric abnormality data according to electricity quantum information, including:
Step B5, determine slip daily power consumption meansigma methods AvgE of k daysj；
Step B6, difference between adjacent two slips daily power consumption meansigma methods of k days are more than the 3rd
During preset difference value, determine AvgEjThere are multiplexing electric abnormality data；Wherein,J is for sliding
The initial natural law of dynamic k days, EiIt is i-th day corresponding daily power consumption.
In the embodiment of the present invention, " slip k days " mean " with some day (such as kth day) as starting point,
Continuity k days backward ", i.e. arrive jth+k sky, k days altogether.Such as, with on January 1st, 2016 as starting point
Slide 10 days, be then extended on January 11st, 2016, therefore in step B5, obtain in January, 2016
On January 11st, 1 day 1, the daily power consumption of totally 10 days, and determined its meansigma methods AvgEj。
Meanwhile, in step B6, adjacent two slips daily power consumption meansigma methods of k days is AvgEj
With AvgEj-1Between difference (or AvgEjWith AvgEj+1Between difference), wherein, AvgEj-1Also
For the daily mean of k days,
Preferably, when power information includes the sub-information of load, believe according to each class in power information
Breath judges whether multiplexing electric abnormality data respectively, including:
Determine the load record of each load point, a load point magnitude of voltage and rated voltage it
Between difference more than predeterminated voltage difference time, determine that this load point exists multiplexing electric abnormality data；Or
Determine the load record of each load point, a load point current value and rated current it
Between difference more than predetermined current difference time, determine that this load point exists multiplexing electric abnormality data.
In the embodiment of the present invention, whether existed abnormal by the magnitude of voltage or current value judging load point
To determine that this load point is the most abnormal, the most whether there are multiplexing electric abnormality data.
Preferably, when power information includes the sub-information of line loss, believe according to each class in power information
Breath judges whether multiplexing electric abnormality data respectively, including:
Obtain the line loss exception platform district mark in the sub-information of line loss, and determine corresponding line loss exception platform district；
When local stoichiometric point is located in one of in line loss exception platform district, determines and there are electrical anomaly suspicion data.
Platform district refers to supply district or the region of (one) transformator.Line can be obtained by main station system
Damaging abnormal platform district mark, it is abnormal that all stoichiometric points under line loss exception platform district all could be arranged to line loss.If
Local stoichiometric point is located in one of in line loss exception platform district, then may determine that and there are electrical anomaly suspicion data.
The flow process of the method is discussed in detail below by an embodiment.
Embodiment one
In embodiment one, power information specifically can be divided into event class, electricity class, load class, line loss
Class, and every class is set up multiplexing electric abnormality analysis model, index calculating is carried out respectively by each model.Its
In, multiplexing electric abnormality suspicion index ELI is in terms of full marks 100 points, and all kinds of is event at overall evaluation proportion
40%, electricity 40%, load 10%, line loss 10%.
For the sub-information of event class, event class judges that schematic flow sheet is shown in Figure 2, including
Following steps:
Step 201: by the decompression of record, full decompression, disconnected phase, defluidization, negative phase sequence, trend
Reversely, the event such as current imbalance, game clock lid, before and after carrying out event generation, historical data is reviewed.
Step 202: determine whether anomalous event record, when there is anomalous event record, continues
Continuous step 203.
Step 203: the above each event utilizing table meter recorded starts and the voltage of finish time,
The data such as electric current, power.If after event terminates, data are front and back contrasted, if power drop
More than 20%, then ELI=ELI+10；Otherwise ELI keeps constant.
In embodiment one, represent the change of ELI with the statement in programming, described above
" ELI=ELI+10 " is expressed as, and " ELI+10 " is assigned to ELI again, is i.e. equivalent to as ELI
Increase an increment 10 (i.e. preset increments).
Step 204: before and after there is event, the electricity that freezes day of 3 days compares, if
Ei＜ Ei-1(1-20%), ELI=ELI+8.
In embodiment one, if the time that event occurs is in 62 days (i.e. two months), the most permissible
Carry out step 204.In step 204, previous light is freezed the 20% of electricity as above-mentioned step
Default in rapid A4 freezes electricity difference.Meanwhile, step 202-204 is one of them event
Handling process, by could be final after in sub-for logout information, all of anomalous event processes
Determine the ELI after processing according to the sub-information of event class.Due to presetting of the sub-information of a certain class
Increment sum is not more than the Maximum Index value that the index weights of such sub-information is corresponding, therefore at the increment of ELI
When having reached the Maximum Index value corresponding to the sub-information of event class, i.e. can stop step 202-204.
In embodiment one, ELI is cumulative less than 40 in event class judges.
For the sub-information of electricity class, electricity class judges that schematic flow sheet is shown in Figure 3, including
Following steps:
Step 301: calculate electric quantity data meansigma methods AvgE of n days (n < 62) of electric energy meter record,EiFor the daily power consumption of in n days i-th day.
Step 302: calculate the history electric quantity data meansigma methods of the n days same period of history obtained from main website,EhiFor the history daily power consumption of i-th day in the n days same period of history.
Step 303: calculate the slip electric quantity data meansigma methods of k daysJ is for sliding
The initial natural law of k days.
Step 304: electricity every day is compared, such as one day with n days electricity statistical average
Ei＜ AvgE (1-10%) then ELI=ELI+1.
Step 305: electricity every day is compared with the history n days same period of electricity statistical average,
Such as E one dayi＜ AvgEh (1-10%)；Then ELI=ELI+1.
Step 306: the slip electric quantity data meansigma methods of k days front and back compares, if
AvgEj＜ AvgEj-1(1-20%), then ELI=ELI+3.
Wherein, circulation performs step 304, step 305 and step 306, until having processed institute respectively
Some daily power consumption related datas, or reach corresponding Maximum Index value.In embodiment one, ELI
Add up less than 40 in electricity class judges.
For the sub-information of load class, load class determination methods specifically includes that reading load record,
Judge whether the magnitude of voltage (split-phase) of each point is less than the 80% of rated voltage, if being less than, then
ELI=ELI+1.Wherein, ELI is cumulative less than 10 in load class judges.
For the sub-information of line loss class, line loss class determination methods is specifically included that and is obtained by main station system
Abnormal platform distinctive emblem is damaged in line taking, and under this district, all stoichiometric points are disposed as line loss extremely,
ELI=ELI+10.
In embodiment one, every class can be set up multiplexing electric abnormality respectively and analyze model, each model divides
Not determining corresponding multiplexing electric abnormality analysis indexes, carrying out adding up by all of ELI afterwards, it is final to determine
ELI, if ELI >=50, it is determined that there is multiplexing electric abnormality event.50 herein are predetermined threshold value,
60,70 other numerical value such as grade can also be set to according to practical situation.
The method that a kind of multiplexing electric abnormality that the embodiment of the present invention provides is analyzed, presets multiplexing electric abnormality suspicion and refers to
Mark, by power information carries out classification indicator of distribution weight, determines respectively according to the sub-information of each class
The most corresponding preset increments of multiplexing electric abnormality suspicion data, and this multiplexing electric abnormality suspicion index is increased corresponding
Preset increments, when the multiplexing electric abnormality suspicion index after cumulative is more than predetermined threshold value, i.e. may determine that existence
Multiplexing electric abnormality event.The method carries out classification indicator of distribution weight to power information, such that it is able to according to
Electricity, event, load and line loss information carry out comprehensive analysis and judgement, accurately search multiplexing electric abnormality journey
Spend higher user, and greatly reduce investigation difficulty, improve the work of Utilities Electric Co. power utility check personnel
Efficiency.Meanwhile, power information is classified and respectively multiplexing electric abnormality suspicion index is added preset increments,
Finally cumulative determine final ELI the multiplexing electric abnormality determined respectively suspicion index being carried out, place can be synchronized
Manage the sub-information of different classes, treatment effeciency can be improved.
Describing the method flow that multiplexing electric abnormality is analyzed in detail above, the method can also be by corresponding dress
Put realization, the 26S Proteasome Structure and Function of this device is described in detail below.
The device that a kind of multiplexing electric abnormality that the embodiment of the present invention provides is analyzed, shown in Figure 4, including:
Acquisition module 41, is used for obtaining power information, and is each class sub-information distribution in power information
Corresponding index weights；Power information includes the sub-information of logout, electricity quantum information, the sub-information of load
A class in information sub-with line loss or multiclass；
Judge module 42, for judging whether the sub-information of each class in power information exists accordingly respectively
Multiplexing electric abnormality suspicion data；
Processing module 43, is used for when the sub-information of one type exists corresponding multiplexing electric abnormality suspicion data,
The preset increments corresponding with multiplexing electric abnormality suspicion data is increased for default multiplexing electric abnormality suspicion index, and
The preset increments sum of such sub-information is not more than the Maximum Index that the index weights of such sub-information is corresponding
Value；
Determine module 44, for when multiplexing electric abnormality suspicion index is more than predetermined threshold value, determining and there is electricity consumption
Anomalous event.
In a kind of possible implementation, the sub-information of logout include decompression event, full decompression event,
Disconnected phase event, cutout event, defluidization event, negative phase sequence event, the reverse event of trend, current imbalance
One or more in event, magnetic interference event, on-load switch misoperation event and game clock lid event；
When power information includes the sub-information of logout, it is judged that module 42 specifically for:
Obtain respectively each event is corresponding in the sub-information of logout start time electricity consumption data and at the end of
Carve electricity consumption data, and determine corresponding power change values；Change more than predetermined power in power change values
During value, determine that this event exists multiplexing electric abnormality data；And/or
Determine the time of origin of each event in the sub-information of logout respectively, and determine the first Preset Time
In section every day freeze electricity day, and the time of origin of event is positioned at the first preset time period；At two
Freeze difference between electricity continuous print day more than preset freeze electricity difference time, determine that this event exists
Multiplexing electric abnormality data.
In a kind of possible implementation, when power information includes electricity quantum information, it is judged that module 42
Specifically for:
Determine the daily power consumption E of every day in the second preset time periodi, and determine the meansigma methods of daily power consumption
AvgE；At AvgE and EiBetween difference more than the first preset difference value time, determine i-th day and there is electricity consumption
Abnormal data；Wherein, i=1,2,3 ... n, n are the natural law that the second preset time period comprises；And/or
The history daily power consumption Eh of every day in history the second preset time period same period is obtained from main station systemi, and
Determine meansigma methods AvgEh of history daily power consumption；At AvgEh and daily power consumption EiBetween difference be more than
During the second preset difference value, determine i-th day and there are multiplexing electric abnormality data；Wherein, i=1,2,3 ... n, n are second
The natural law that preset time period comprises；And/or
Determine slip daily power consumption meansigma methods AvgE of k daysj, daily adjacent two slips k days
When difference between electricity meansigma methods is more than three preset difference values, determine AvgEjThere are multiplexing electric abnormality data；
Wherein,J is the slip initial natural law of k days, EiBe i-th day corresponding daily
Electricity.
In a kind of possible implementation, when power information includes the sub-information of load, it is judged that module 42
Specifically for:
Determine the load record of each load point, a load point magnitude of voltage and rated voltage it
Between difference more than predeterminated voltage difference time, determine that this load point exists multiplexing electric abnormality data；Or
Determine the load record of each load point, a load point current value and rated current it
Between difference more than predetermined current difference time, determine that this load point exists multiplexing electric abnormality data.
In a kind of possible implementation, when power information includes the sub-information of line loss, it is judged that module 42
Specifically for:
Obtain the line loss exception platform district mark in the sub-information of line loss, and determine corresponding line loss exception platform district；
When local stoichiometric point is located in one of in line loss exception platform district, determines and there are electrical anomaly suspicion data.
The method and device that a kind of multiplexing electric abnormality that the embodiment of the present invention provides is analyzed, presets multiplexing electric abnormality and dislikes
Doubt index, by power information being carried out classification indicator of distribution weight, according to the sub-information of each class respectively
Determine the multiplexing electric abnormality the most corresponding preset increments of suspicion data, and this multiplexing electric abnormality suspicion index is increased phase
The preset increments answered, when the multiplexing electric abnormality suspicion index after cumulative is more than predetermined threshold value, i.e. may determine that
There is multiplexing electric abnormality event.The method carries out classification indicator of distribution weight to power information, such that it is able to
Carry out comprehensive analysis and judgement according to electricity, event, load and line loss information, accurately search electricity consumption different
The user that Chang Chengdu is higher, and greatly reduce investigation difficulty, improve Utilities Electric Co. power utility check personnel's
Work efficiency.Meanwhile, power information classified and respectively multiplexing electric abnormality suspicion index added pre-
If increment, finally the multiplexing electric abnormality determined respectively suspicion index is carried out cumulative determine final
ELI, can improve treatment effeciency with the sub-information of the different class of synchronization process.
Device embodiment described above is only schematically, wherein said as separating component
The unit illustrated can be or may not be physically separate, the parts shown as unit
Can be or may not be physical location, i.e. may be located at a place, or can also divide
Cloth is on multiple NEs.Some or all of mould therein can be selected according to the actual needs
Block realizes the purpose of the present embodiment scheme.Those of ordinary skill in the art are not paying creativeness
In the case of work, i.e. it is appreciated that and implements.
Through the above description of the embodiments, those skilled in the art is it can be understood that arrive
Each embodiment can add the mode of required general hardware platform by software and realize, and the most also may be used
To pass through hardware.Based on such understanding, technique scheme is the most in other words to prior art
The part contributed can embody with the form of software product, and this computer software product can
With storage in a computer-readable storage medium, such as ROM/RAM, magnetic disc, CD etc., including
Some instructions with so that computer equipment (can be personal computer, server, or
The network equipment etc.) perform the method described in some part of each embodiment or embodiment.
Last it is noted that the foregoing is only the preferred embodiments of the present invention, and need not
In limiting the present invention, although the present invention being described in detail with reference to previous embodiment, for
For those skilled in the art, the technical scheme described in foregoing embodiments still can be entered by it
Row amendment, or wherein portion of techniques feature is carried out equivalent.All in the spirit and principles in the present invention
Within, any modification, equivalent substitution and improvement etc. made, should be included in protection scope of the present invention
Within.
Claims (10)
1. the method that a multiplexing electric abnormality is analyzed, it is characterised in that including:
Obtain power information, and be that the sub-information of each class in described power information distributes corresponding index power
Weight；Described power information includes the sub-information of logout, electricity quantum information, the sub-information of load and line loss
A class in information or multiclass；
Judge whether the sub-information of each class in described power information exists corresponding multiplexing electric abnormality suspicion respectively
Data；
When the sub-information of one type exists corresponding multiplexing electric abnormality suspicion data, for default multiplexing electric abnormality
The preset increments that the increase of suspicion index is corresponding with described multiplexing electric abnormality suspicion data, and such sub-information
Preset increments sum is not more than the Maximum Index value that the index weights of such sub-information is corresponding；
When described multiplexing electric abnormality suspicion index is more than predetermined threshold value, determines and there is multiplexing electric abnormality event.
Method the most according to claim 1, it is characterised in that the sub-information of described logout includes
Decompression event, full decompression event, disconnected phase event, cutout event, defluidization event, negative phase sequence event, tide
Flow reverse event, current imbalance event, magnetic interference event, on-load switch misoperation event and game clock
One or more in lid event；
When described power information includes the sub-information of described logout, described according in described power information
The sub-information of each class judge whether multiplexing electric abnormality data respectively, including:
Obtain start time electricity consumption data and knot that in the sub-information of described logout, each event is corresponding respectively
Bundle moment electricity consumption data, and determine corresponding power change values；In described power change values more than presetting
During power change values, determine that this event exists multiplexing electric abnormality data；And/or
Determine the time of origin of each event in the sub-information of described logout respectively, and determine that first presets
Freeze electricity in time period the day of every day, and the time of origin of event is positioned at described first preset time period；
The difference freezed two continuous print days between electricity more than preset freeze electricity difference time, determine this thing
There are multiplexing electric abnormality data in part.
Method the most according to claim 1, it is characterised in that include described in described power information
During electricity quantum information, described judge whether respectively according to the sub-information of each class in described power information
Multiplexing electric abnormality data, including:
Determine the daily power consumption E of every day in the second preset time periodi, and determine the meansigma methods of daily power consumption
AvgE；At AvgE and EiBetween difference more than the first preset difference value time, determine i-th day and there is electricity consumption
Abnormal data；Wherein, i=1,2,3 ... n, n are the natural law that described second preset time period comprises；And/or
The history daily power consumption Eh of every day in history the second preset time period same period is obtained from main station systemi, and
Determine meansigma methods AvgEh of history daily power consumption；At AvgEh and daily power consumption EiBetween difference be more than
During the second preset difference value, determine i-th day and there are multiplexing electric abnormality data；Wherein, i=1,2,3 ... n, n are described
The natural law that second preset time period comprises；And/or
Determine slip daily power consumption meansigma methods AvgE of k daysj, daily adjacent two slips k days
When difference between electricity meansigma methods is more than three preset difference values, determine AvgEjThere are multiplexing electric abnormality data；
Wherein,J is the slip initial natural law of k days, EiBe i-th day corresponding daily
Electricity.
4. according to the arbitrary described method of claim 1-3, it is characterised in that at described power information bag
When including the sub-information of load, described judge whether respectively to deposit according to the sub-information of each class in described power information
In multiplexing electric abnormality data, including:
Determine the load record of each load point, a load point magnitude of voltage and rated voltage it
Between difference more than predeterminated voltage difference time, determine that this load point exists multiplexing electric abnormality data；Or
Determine the load record of each load point, a load point current value and rated current it
Between difference more than predetermined current difference time, determine that this load point exists multiplexing electric abnormality data.
5. according to the arbitrary described method of claim 1-3, it is characterised in that at described power information bag
When vinculum damages sub-information, described judge whether respectively to deposit according to the sub-information of each class in described power information
In multiplexing electric abnormality data, including:
Obtain the line loss exception platform district mark in the sub-information of described line loss, and determine corresponding line loss exception platform
District；When local stoichiometric point is located in one of in line loss exception platform district, determines and there is electrical anomaly suspicion number
According to.
6. the device that a multiplexing electric abnormality is analyzed, it is characterised in that including:
Acquisition module, is used for obtaining power information, and divides for the sub-information of each class in described power information
Join corresponding index weights；Described power information includes the sub-information of logout, electricity quantum information, load
A class in sub-information and the sub-information of line loss or multiclass；
Judge module, for judging whether the sub-information of each class in described power information exists accordingly respectively
Multiplexing electric abnormality suspicion data；
Processing module, is used for when the sub-information of one type exists corresponding multiplexing electric abnormality suspicion data, for
The multiplexing electric abnormality suspicion index preset increases the preset increments corresponding with described multiplexing electric abnormality suspicion data,
And the preset increments sum of such sub-information is not more than the Maximum Index that the index weights of such sub-information is corresponding
Value；
Determine module, for when described multiplexing electric abnormality suspicion index is more than predetermined threshold value, determine that existence is used
Electrical anomaly event.
Device the most according to claim 6, it is characterised in that described logout information bag
Include decompression event, full decompression event, disconnected phase event, cutout event, defluidization event, negative phase sequence event,
The reverse event of trend, current imbalance event, magnetic interference event, on-load switch misoperation event and open
One or more in table cover event；
When described power information includes the sub-information of described logout, described judge module specifically for:
Obtain start time electricity consumption data and knot that in the sub-information of described logout, each event is corresponding respectively
Bundle moment electricity consumption data, and determine corresponding power change values；In described power change values more than presetting
During power change values, determine that this event exists multiplexing electric abnormality data；And/or
Determine the time of origin of each event in the sub-information of described logout respectively, and determine that first presets
Freeze electricity in time period the day of every day, and the time of origin of event is positioned at described first preset time period；
The difference freezed two continuous print days between electricity more than preset freeze electricity difference time, determine this thing
There are multiplexing electric abnormality data in part.
Device the most according to claim 6, it is characterised in that include described in described power information
Electricity quantum information time, described judge module specifically for:
Determine the daily power consumption E of every day in the second preset time periodi, and determine the meansigma methods of daily power consumption
AvgE；At AvgE and EiBetween difference more than the first preset difference value time, determine i-th day and there is electricity consumption
Abnormal data；Wherein, i=1,2,3 ... n, n are the natural law that described second preset time period comprises；And/or
The history daily power consumption Eh of every day in history the second preset time period same period is obtained from main station systemi, and
Determine meansigma methods AvgEh of history daily power consumption；At AvgEh and daily power consumption EiBetween difference be more than
During the second preset difference value, determine i-th day and there are multiplexing electric abnormality data；Wherein, i=1,2,3 ... n, n are described
The natural law that second preset time period comprises；And/or
Determine slip daily power consumption meansigma methods AvgE of k daysj, daily adjacent two slips k days
When difference between electricity meansigma methods is more than three preset difference values, determine AvgEjThere are multiplexing electric abnormality data；
Wherein,J is the slip initial natural law of k days, EiBe i-th day corresponding daily
Electricity.
9. according to the arbitrary described device of claim 6-8, it is characterised in that at described power information bag
When including the sub-information of load, described judge module specifically for:
Determine the load record of each load point, a load point magnitude of voltage and rated voltage it
Between difference more than predeterminated voltage difference time, determine that this load point exists multiplexing electric abnormality data；Or
Determine the load record of each load point, a load point current value and rated current it
Between difference more than predetermined current difference time, determine that this load point exists multiplexing electric abnormality data.
10. according to the arbitrary described device of claim 6-8, it is characterised in that at described power information bag
Vinculum damage sub-information time, described judge module specifically for:
Obtain the line loss exception platform district mark in the sub-information of described line loss, and determine corresponding line loss exception platform
District；When local stoichiometric point is located in one of in line loss exception platform district, determines and there is electrical anomaly suspicion number
According to.
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| CN107024641A (en) * | 2017-03-29 | 2017-08-08 | 国网上海市电力公司 | A kind of platform area line loss per unit exception monitoring system |
| CN107328974B (en) * | 2017-08-03 | 2020-06-02 | 北京中电普华信息技术有限公司 | Electricity stealing identification method and device |
| CN107328974A (en) * | 2017-08-03 | 2017-11-07 | 北京中电普华信息技术有限公司 | A kind of stealing recognition methods and device |
| CN107730395A (en) * | 2017-09-13 | 2018-02-23 | 国网天津市电力公司电力科学研究院 | A kind of multiplexing electric abnormality detection method based on power consumption deviation ratio for low-voltage customer |
| CN107730395B (en) * | 2017-09-13 | 2021-05-18 | 国网天津市电力公司电力科学研究院 | Power consumption abnormity detection method based on power consumption deviation rate for low-voltage users |
| CN108022043A (en) * | 2017-11-30 | 2018-05-11 | 北京汇通金财信息科技有限公司 | Abnormal electricity consumption behavior identification method and device and central server |
| CN108022043B (en) * | 2017-11-30 | 2021-08-20 | 北京汇通金财信息科技有限公司 | Abnormal electricity consumption behavior identification method and device and central server |
| CN108169597B (en) * | 2017-12-27 | 2020-08-14 | 华北电力大学 | Method for evaluating loss state of electric equipment |
| CN108169597A (en) * | 2017-12-27 | 2018-06-15 | 卢志旭 | A kind of method for assessing electrical equipment loss state |
| CN108776276B (en) * | 2018-06-29 | 2020-11-13 | 合肥工业大学 | Power consumption abnormity detection method and system |
| CN108776276A (en) * | 2018-06-29 | 2018-11-09 | 合肥工业大学 | Multiplexing electric abnormality detection method and system |
| CN109064660A (en) * | 2018-08-03 | 2018-12-21 | 广东电网有限责任公司 | Obtain the method and system of user power consumption abruptly increase |
| CN109443395A (en) * | 2018-09-18 | 2019-03-08 | 中国电力科学研究院有限公司 | A kind of Energy intensity multiple spot metering difference is more than limit value judgment method and system |
| CN109598644B (en) * | 2018-12-13 | 2020-12-08 | 国网河北省电力有限公司电力科学研究院 | Electricity stealing user identification method based on Gaussian distribution and terminal equipment |
| CN109598644A (en) * | 2018-12-13 | 2019-04-09 | 国网河北省电力有限公司电力科学研究院 | Stealing user identification method and terminal device based on Gaussian Profile |
| CN109726461A (en) * | 2018-12-21 | 2019-05-07 | 国网山西省电力公司长治供电公司 | A kind of multiplexing electric abnormality judgment method based on user power utilization data |
| CN110942236B (en) * | 2019-11-14 | 2023-05-09 | 国网浙江海宁市供电有限公司 | Abnormal user identification method for comprehensive power failure record and power consumption data |
| CN110942236A (en) * | 2019-11-14 | 2020-03-31 | 国网浙江海宁市供电有限公司 | Abnormal user identification method integrating power failure record and electricity utilization data |
| CN111856385A (en) * | 2020-07-27 | 2020-10-30 | 南方电网科学研究院有限责任公司 | Electric quantity sudden change fault detection method, device and equipment |
| CN112200436A (en) * | 2020-09-28 | 2021-01-08 | 上海钧正网络科技有限公司 | Method and device for monitoring delivery quality of shared equipment and server |
| CN113743755A (en) * | 2021-08-24 | 2021-12-03 | 安特仪表集团有限公司 | Data supervision method, ammeter, system and storage medium of multifunctional ammeter |
| CN113657872A (en) * | 2021-09-02 | 2021-11-16 | 南方电网数字电网研究院有限公司 | Method and device for analyzing abnormal archive information of power consumer and computer equipment |
| CN113657872B (en) * | 2021-09-02 | 2024-06-14 | 南方电网数字电网研究院有限公司 | File information anomaly analysis method and device for power users and computer equipment |
| CN114006473A (en) * | 2021-10-29 | 2022-02-01 | 南京康尼精密机械有限公司 | Electric equipment management method |
| CN116933986A (en) * | 2023-09-19 | 2023-10-24 | 国网湖北省电力有限公司信息通信公司 | Electric power data safety management system based on deep learning |
| CN116933986B (en) * | 2023-09-19 | 2024-01-23 | 国网湖北省电力有限公司信息通信公司 | Electric power data safety management system based on deep learning |
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