CN109598644A - Stealing user identification method and terminal device based on Gaussian Profile - Google Patents
Stealing user identification method and terminal device based on Gaussian Profile Download PDFInfo
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Abstract
The present invention provides a kind of stealing user identification method and terminal device based on Gaussian Profile, comprising: according to user each under selected route electricity consumption within a preset period of time, generate user's electricity matrix Pc；The selected line loss electricity of route within a preset period of time is obtained, line loss electricity matrix P is obtainedl；According to PcObtain user's fluctuant electricity quantity matrix Δ Pc；According to Pl, obtain line loss fluctuant electricity quantity matrix Δ Pl；According to Δ PcWith Δ Pl, construct relational matrix R；The average value for seeking every a line of R respectively obtains the average value matrix R of Rμ；The standard deviation for seeking every a line of R respectively obtains the standard deviation matrix R of Rσ；According to RμAnd Rσ, construct upper limit matrix U and lower limit matrix L；According to Δ Pc, U and L, construct discrimination matrix P；According to P, user's evaluation matrix Q is constructed；Differentiate whether user is stealing user according to Q, improves the accuracy rate and efficiency of identification stealing user.
Description
Technical field
The invention belongs to electric power big data applied technical field more particularly to a kind of stealing user knowledges based on Gaussian Profile
Other method and terminal device.
Background technique
As China quickens the modernization drive, country is also constantly increasing energy consumption, especially to electric power
Increased situation year by year is presented in demand.In this context, some criminals steal electric power resource by various means,
Even some areas are very rampant.Electricity stealing not only seriously affects normally for electricity consumption order, brings seriously to power grid enterprises
Economic loss, but also will cause and damaged for transmission facility, or even jeopardize power grid security.Therefore, carry out work of maintaining order at a public gathering of opposing electricity-stealing
It is imperative.Each enterprise of national grid mostly takes the mode of Daily Round Check to carry out behavior discovery of opposing electricity-stealing, but this row at present
The mode working efficiency looked into is low, seems helpless for more hidden electricity filching means.
Therefore, lack a kind of efficient, accurate stealing user identification method in the prior art.
Summary of the invention
In view of this, the stealing user identification method and terminal that the embodiment of the invention provides a kind of based on Gaussian Profile are set
It is standby, to solve the problems, such as stealing user recognition accuracy and low efficiency in the prior art.
The first aspect of the embodiment of the present invention provides a kind of stealing user identification method based on Gaussian Profile, comprising:
All users obtained under selected route obtain the user and exist for any user in all users
Daily electricity consumption in preset time period generates user's electricity matrix Pc；
Selected route line loss electricity daily in the preset time period is obtained, line loss electricity is obtained
Matrix Pl；
For any user in all users, according to user's electricity matrix PcThe user is obtained described
The difference of the electricity consumption in i+1 day and i-th day electricity consumption in preset time period obtains user's fluctuant electricity quantity matrix Δ Pc, wherein institute
Stating preset time period includes t days, 1≤i≤t-1；
According to the line loss electricity matrix Pl, obtain the selected route in the line loss electricity in i+1 day and
The selected route obtains line loss fluctuant electricity quantity matrix Δ P in the difference of i-th day line loss electricityl, 1≤i≤t-1；
According to user's fluctuant electricity quantity matrix Δ PcWith the line loss fluctuant electricity quantity matrix Δ Pl, construct user's wave
The relational matrix R of dynamic electricity and line loss fluctuant electricity quantity；
The average value for seeking every a line of the relational matrix R respectively obtains the average value matrix R of relational matrix Rμ；
The standard deviation for seeking every a line of the relational matrix R respectively obtains the standard deviation matrix R of relational matrix Rσ；
According to RμAnd Rσ, construct upper limit matrix U and lower limit matrix L, wherein U=Rμ+kRσ, L=Rμ-kRσ, k is first pre-
If constant；
According to user's fluctuant electricity quantity matrix Δ Pc, the upper limit matrix U and the lower limit matrix L, building differentiates square
Battle array P；
According to the discrimination matrix P, user's evaluation matrix Q is constructed；
The element is judged if the value of the element is greater than preset value according to the either element in the user's evaluation matrix Q
Corresponding user is stealing user.
The second aspect of the embodiment of the present invention provides a kind of computer readable storage medium, the computer-readable storage
Media storage has computer-readable instruction, and the computer-readable instruction realizes following steps when being executed by processor:
All users obtained under selected route obtain the user and exist for any user in all users
Daily electricity consumption in preset time period generates user's electricity matrix Pc；
Selected route line loss electricity daily in the preset time period is obtained, line loss electricity is obtained
Matrix Pl；
For any user in all users, according to user's electricity matrix PcThe user is obtained described
The difference of the electricity consumption in i+1 day and i-th day electricity consumption in preset time period obtains user's fluctuant electricity quantity matrix Δ Pc, wherein institute
Stating preset time period includes t days, 1≤i≤t-1；
According to the line loss electricity matrix Pl, obtain the selected route in the line loss electricity in i+1 day and
The selected route obtains line loss fluctuant electricity quantity matrix Δ P in the difference of i-th day line loss electricityl, 1≤i≤t-1；
According to user's fluctuant electricity quantity matrix Δ PcWith the line loss fluctuant electricity quantity matrix Δ Pl, construct user's wave
The relational matrix R of dynamic electricity and line loss fluctuant electricity quantity；
The average value for seeking every a line of the relational matrix R respectively obtains the average value matrix R of relational matrix Ru；
The standard deviation for seeking every a line of the relational matrix R respectively obtains the standard deviation matrix R of relational matrix Rσ；
According to RμAnd Rσ, construct upper limit matrix U and lower limit matrix L, wherein U=Rμ+kRσ, L=Rμ-kRσ, k is first pre-
If constant；
According to user's fluctuant electricity quantity matrix Δ Pc, the upper limit matrix U and the lower limit matrix L, building differentiates square
Battle array P；
According to the discrimination matrix P, user's evaluation matrix Q is constructed；
The element is judged if the value of the element is greater than preset value according to the either element in the user's evaluation matrix Q
Corresponding user is stealing user.
The third aspect of the embodiment of the present invention provides a kind of terminal device, including memory, processor and is stored in
In the memory and the computer-readable instruction that can run on the processor, the processor executes the computer can
Following steps are realized when reading instruction:
All users obtained under selected route obtain the user and exist for any user in all users
Daily electricity consumption in preset time period generates user's electricity matrix Pc；
Selected route line loss electricity daily in the preset time period is obtained, line loss electricity is obtained
Matrix Pl；
For any user in all users, according to user's electricity matrix PcThe user is obtained described
The difference of the electricity consumption in i+1 day and i-th day electricity consumption in preset time period obtains user's fluctuant electricity quantity matrix Δ Pc, wherein institute
Stating preset time period includes t days, 1≤i≤t-1；
According to the line loss electricity matrix Pl, obtain the selected route in the line loss electricity in i+1 day and
The selected route obtains line loss fluctuant electricity quantity matrix Δ P in the difference of i-th day line loss electricityl, 1≤i≤t-1；
According to user's fluctuant electricity quantity matrix Δ PcWith the line loss fluctuant electricity quantity matrix Δ Pl, construct user's wave
The relational matrix R of dynamic electricity and line loss fluctuant electricity quantity；
The average value for seeking every a line of the relational matrix R respectively obtains the average value matrix R of relational matrix Ru；
The standard deviation for seeking every a line of the relational matrix R respectively obtains the standard deviation matrix R of relational matrix Rσ；
According to RμAnd Rσ, construct upper limit matrix U and lower limit matrix L, wherein U=Rμ+kRσ, L=Rμ-kRσ, k is first pre-
If constant；
According to user's fluctuant electricity quantity matrix Δ Pc, the upper limit matrix U and the lower limit matrix L, building differentiates square
Battle array P；
According to the discrimination matrix P, user's evaluation matrix Q is constructed；
The element is judged if the value of the element is greater than preset value according to the either element in the user's evaluation matrix Q
Corresponding user is stealing user.
The present invention provides a kind of stealing user identification method and terminal device based on Gaussian Profile, it is selected by obtaining
The electricity consumption data of the user of route within a preset period of time obtain user's electricity matrix Pc, route is selected when default according to this
Between line loss daily in section, obtain line loss electricity matrix Pl, to each row of data in user's electricity matrix, take cunning
The mode of difference calculates daily electricity fluctuation, and thus constructs user's fluctuant electricity quantity matrix Δ Pc；Similarly, line is handled in a like fashion
Road loss matrix obtains line loss fluctuant electricity quantity matrix Δ Pl.According to Δ PcWith Δ PlConstruct user's fluctuant electricity quantity and route damage
The relational matrix R of fluctuant electricity quantity is consumed, and according to Pauta criterion, calculates the average value matrix and standard deviation matrix of R.According to R's
Average value matrix and standard deviation matrix construct upper current limiting matrix and lower current limiting matrix by setting coefficient k, and further building differentiates square
Battle array, and user's evaluation matrix is obtained by judgement matrix, by the way that rational evaluation coefficient is arranged, identify stealing user.The present invention is based on
The incidence relation of line loss electricity and user's electricity realizes the screening to multiplexing electric abnormality user, improves the knowledge to stealing user
Other efficiency and accuracy rate.
Detailed description of the invention
It to describe the technical solutions in the embodiments of the present invention more clearly, below will be to embodiment or description of the prior art
Needed in attached drawing be briefly described, it should be apparent that, the accompanying drawings in the following description is only of the invention some
Embodiment for those of ordinary skill in the art without any creative labor, can also be according to these
Attached drawing obtains other attached drawings.
Fig. 1 is a kind of process signal of stealing user identification method based on Gaussian Profile provided in an embodiment of the present invention
Figure；
Fig. 2 is a kind of structural block diagram of the stealing customer identification device based on Gaussian Profile provided in an embodiment of the present invention；
Fig. 3 is a kind of signal of stealing user's identification terminal equipment based on Gaussian Profile provided in an embodiment of the present invention
Figure.
Specific embodiment
In being described below, for illustration and not for limitation, the tool of such as particular system structure, technology etc is proposed
Body details, to understand thoroughly the embodiment of the present invention.However, it will be clear to one skilled in the art that there is no these specific
The present invention also may be implemented in the other embodiments of details.In other situations, it omits to well-known system, device, electricity
The detailed description of road and method, in case unnecessary details interferes description of the invention.
In order to illustrate technical solutions according to the invention, the following is a description of specific embodiments.
The embodiment of the invention provides a kind of stealing user identification method based on Gaussian Profile.In conjunction with Fig. 1, this method packet
It includes:
S101, all users obtained under selected route obtain the use for any user in all users
Family daily electricity consumption within a preset period of time, generates user's electricity matrix Pc。
Specifically, in embodiments of the present invention, all users under the selected route include m user altogether, described default
Period includes t days altogether, user's electricity matrix PcIt is defined by following formula:
Wherein, PcijIt is user j in the i-th daily power consumption, 1≤i≤t, 1≤j≤m.
S102 obtains selected route line loss electricity daily in the preset time period, obtains route damage
Power consumption moment matrix Pl。
It is specific:
For i-th day in the preset time period, the selected route was by n power supply power supply, if wherein each power supply
Power supply volume be Psi, then line powering amount P of the selected route at i-th day is calculated by following equationig:
If all users under the selected route include m user altogether, each user was at i-th day in the m user
Electricity consumption be Pcj, then use electricity P of the selected route at i-th day is calculated by following equationiy:
Line loss electricity P of the selected route at i-th day is calculated by following formulail, wherein 1≤i≤t:
Pil=Pig-Piy
The then line loss electricity matrix PlAre as follows:
Pl=[P1l, P2l... P(t-1)l, Ptl]T
Wherein, PilLine loss electricity for the selected route on 1st, 1≤i≤t.
S103, for any user in all users, according to user's electricity matrix PcObtain the user
The difference of the electricity consumption in i+1 day and i-th day electricity consumption in the preset time period obtains user's fluctuant electricity quantity matrix Δ Pc,
Wherein, the preset time period includes t days, 1≤i≤t-1.
Specifically, defining user's fluctuant electricity quantity matrix Δ P by following formula on the basis of step S101c:
Wherein, Δ Pcij=Pc(i+1)j-Pcij, 1≤i≤t-1,1≤j≤m.
S104, according to the line loss electricity matrix Pl, the selected route is obtained in the line loss electricity in i+1 day
Amount and the selected route obtain line loss fluctuant electricity quantity matrix Δ P in the difference of i-th day line loss electricityl。
Specifically, defining line loss fluctuant electricity quantity matrix Δ P by following formula on the basis of step S102l:
ΔPl=[Δ P1l, Δ P2l... Δ P(t-1)l]T
Wherein, Δ Pil=P(i+1)l-Pil, 1≤i≤t-1.
S105, according to user's fluctuant electricity quantity matrix Δ PcWith the line loss fluctuant electricity quantity matrix Δ Pl, building use
The relational matrix R of family fluctuant electricity quantity and line loss fluctuant electricity quantity.
Specifically, defining relational matrix R by following formula on the basis of step S101- step S104:
R=Δ Pc-ΔPlI
Wherein, I is t-1 rank unit matrix.
S106 seeks the average value of every a line of the relational matrix R respectively, obtains the average value matrix of relational matrix R
Rμ。
It is specific:
Rμ=[R1μ, R2μ... R(t-1)μ]T
Wherein,
S107 seeks the standard deviation of every a line of the relational matrix R respectively, obtains the standard deviation matrix of relational matrix R
Rσ。
It is specific:
Rσ=[R1σ, R2σ... R(t-1)σ]T
Wherein,
S108, according to RμAnd Rσ, construct upper limit matrix U and lower limit matrix L, wherein U=Rμ+kRσ, L=Rμ-kRσ, k
One preset constant.
Gaussian Profile (Gaussian distribution) also known as normal distribution (Normal distribution), are one
It is a in all very important probability distribution in the fields such as mathematics, physics and engineering, have great shadow at statistical many aspects
Ring power.If stochastic variable obeys the probability distribution that location parameter, a scale parameter are, be denoted as: its probability density function is
The mathematical expectation or desired value of normal distribution are equal to location parameter, determine the position of distribution；The extraction of square root or mark of its variance
Quasi- difference is equal to scale parameter, determines the amplitude of distribution.The probability density function curve of normal distribution is bell-like.
The expression formula of Gaussian Profile:
Wherein μ is mean value, and σ is standard deviation.
Following table provides, under normal curve, the different corresponding areas in horizontal axis section.
| Horizontal axis section | Area |
| (μ-σ, μ+σ) | 68.27% |
| (+1.96 σ of μ -1.96 σ, μ) | 95.00% |
| (+2 σ of μ -2 σ, μ) | 95.44% |
| (+2.58 σ of μ -2.58 σ, μ) | 99.00% |
| (+3 σ of μ -3 σ, μ) | 99.73% |
According to central-limit theorem, for great amount of samples, it is distributed close to Gaussian Profile, therefore can pass through the method
Outlier threshold is set, abnormal electricity consumption user is judged, to support work of electricity anti-stealing.
According to above-mentioned principle, in embodiments of the present invention, the first preset constant k is pre-seted, according to RμAnd Rσ, construct the upper limit
Matrix U and lower limit matrix L, wherein U=Rμ+kRσ, L=Rμ-kRσ。
Optionally, k=3.
S109, according to user's fluctuant electricity quantity matrix Δ Pc, the upper limit matrix U and the lower limit matrix L, building sentence
Other matrix P.
Specifically, defining discrimination matrix P by following formula:
Wherein:
S1010 constructs user's evaluation matrix Q according to the discrimination matrix P.
Specifically, being directed to any column element of the discrimination matrix P, the sum of the column all elements is sought, user is obtained and comments
Valence matrix Q=[Q1, Q2... Qm], wherein
S1011 judges according to the either element in the user's evaluation matrix Q if the value of the element is greater than preset value
User corresponding to the element is stealing user.
Specifically, pre-set the second preset constant, i.e. evaluation coefficient e, if Qj> et then judges element QjCorresponding use
Family j is stealing user.
Optionally, e=0.5.
Further, the stealing in order to quantify the stealing suspicion of user, in the case where obtaining the selected route by step S1011
After user, method provided by the embodiment of the present invention further include:
All stealing users under the selected route are obtained, and successively calculate each stealing user's by following formula
Stealing index Ij:
Descending sort is carried out to the stealing index of all stealing users.
The stealing index of user is higher, illustrates that the stealing suspicion of the user is bigger, passes through the stealing to all stealing users
Index carries out descending sort, and the foundation of stealing user is checked and confirmed as network operation personnel.
Further, the embodiment of the present invention provides following example:
All user power consumptions and daily line powering amount are as shown in the table in continuous 5 days under certain selected route:
| 1 day | 2 days | 3 days | 4 days | 5 days | |
| User 1 | 408 | 391 | 381 | 393 | 380 |
| User 2 | 402 | 404 | 382 | 408 | 400 |
| User 3 | 408 | 380 | 415 | 417 | 405 |
| User 4 | 398 | 406 | 388 | 387 | 411 |
| User 5 | 800 | 905 | 1003 | 798 | 705 |
| User 6 | 388 | 412 | 401 | 397 | 406 |
| User 7 | 383 | 382 | 403 | 404 | 416 |
| User 8 | 393 | 403 | 404 | 409 | 389 |
| User 9 | 418 | 406 | 380 | 406 | 418 |
| User 10 | 100 | 90 | 80 | 100 | 110 |
| User 11 | 420 | 399 | 403 | 392 | 404 |
| User 12 | 392 | 410 | 395 | 417 | 415 |
| User 13 | 380 | 419 | 391 | 391 | 384 |
| User 14 | 403 | 419 | 407 | 380 | 380 |
| User 15 | 404 | 408 | 418 | 416 | 383 |
| User 16 | 393 | 406 | 392 | 381 | 409 |
| User 17 | 393 | 402 | 385 | 414 | 380 |
| User 18 | 399 | 396 | 390 | 382 | 410 |
| User 19 | 411 | 395 | 387 | 417 | 412 |
| User 20 | 384 | 399 | 390 | 393 | 402 |
| Power supply volume | 8477 | 8732 | 8795 | 8502 | 8319 |
Then user's electricity matrix PcAre as follows:
Then line loss electricity matrix PlAre as follows:
Pl=[400,500,600,400,300]T
Then user's fluctuant electricity quantity matrix Δ PcAre as follows:
Then line loss fluctuant electricity quantity matrix Δ PlAre as follows:
ΔPl=[100,100, -200, -100]T
Then relational matrix R are as follows:
The then average value matrix R of RμAre as follows:
Rμ=[- 92.25, -101.85,195.35,95.85]T
The then standard deviation matrix R of RσAre as follows:
Rσ=[27.5534,27.3336,48.3780,26.6857]T
If threshold coefficient, i.e. the first preset constant k=3 obtains upper limit matrix U and lower limit matrix L:
U=Rμ+kRσ=[- 9.5899, -19.8491,340.4839,175.9072]T
L=Rμ-kRσ=[- 174.9101, -183.8509,50.2161,15.7929]T
According to user's fluctuant electricity quantity matrix Δ Pc, the upper limit matrix U and the lower limit matrix L, building differentiates square
Battle array P:
Obtain the evaluations matrix Q of user:
Q=[0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
If the second preset constant, i.e. evaluation coefficient e=0.5, due to t=5, Q5> et thinks that user 5 has stealing suspicion
It doubts.
The present invention provides a kind of stealing user identification method based on Gaussian Profile, this method is by obtaining selected route
User's electricity consumption data within a preset period of time obtain user's electricity matrix Pc, route is selected in preset time period according to this
Interior daily line loss obtains line loss electricity matrix Pl, to each row of data in user's electricity matrix, take slippage
Mode calculates daily electricity fluctuation, and thus constructs user's fluctuant electricity quantity matrix Δ Pc；Similarly, process circuit is damaged in a like fashion
Matrix is consumed, line loss fluctuant electricity quantity matrix Δ P is obtainedl.According to Δ PcWith Δ PlConstruct user's fluctuant electricity quantity and line loss wave
The relational matrix R of dynamic electricity, and according to Pauta criterion, calculate the average value matrix and standard deviation matrix of R.According to being averaged for R
Value matrix and standard deviation matrix construct upper current limiting matrix and lower current limiting matrix by setting coefficient k, further construct discrimination matrix, and
User's evaluation matrix is obtained by judgement matrix, by the way that rational evaluation coefficient is arranged, identifies stealing user.The present invention is based on route damages
The incidence relation of power consumption and user's electricity realizes the screening to multiplexing electric abnormality user, improves the recognition efficiency to stealing user
And accuracy rate.
Fig. 2 is a kind of stealing customer identification device schematic diagram based on Gaussian Profile provided in an embodiment of the present invention, in conjunction with
Fig. 2, the device include: user's electricity matrix generation unit 21, line loss electricity matrix generation unit 22, user's fluctuant electricity quantity
Matrix generation unit 23, line loss fluctuant electricity quantity matrix generation unit 24, relational matrix generation unit 25, average value matrix are raw
At unit 26, standard deviation matrix generation unit 27, upper current limiting matrix and lower current limiting matrix generation unit 28, discrimination matrix generation unit
29, user's evaluation matrix generation unit 210 and stealing user identification unit 211；
User's electricity matrix generation unit 21, for obtaining all users under selected route, for described all
Any user in user obtains the user daily electricity consumption within a preset period of time, generates user's electricity matrix Pc；
The line loss electricity matrix generation unit 22, for obtaining the selected route in the preset time period
Daily line loss electricity obtains line loss electricity matrix Pl；
User's fluctuant electricity quantity matrix generation unit 23, any user for being directed in all users, according to
User's electricity matrix PcObtain the user electricity consumption in i+1 day and i-th day electricity consumption in the preset time period
Difference, obtain user's fluctuant electricity quantity matrix Δ Pc, wherein the preset time period includes t days, 1≤i≤t-1；
The line loss fluctuant electricity quantity matrix generation unit 24, for according to the line loss electricity matrix Pl, obtain
Take the selected route i+1 day line loss electricity and the selected route i-th day line loss electricity difference,
Obtain line loss fluctuant electricity quantity matrix Δ Pl；
The relational matrix generation unit 25, for according to user's fluctuant electricity quantity matrix Δ PcWith the line loss
Fluctuant electricity quantity matrix Δ Pl, construct the relational matrix R of user's fluctuant electricity quantity and line loss fluctuant electricity quantity；
The average value matrix generation unit 26, the average value of every a line for seeking the relational matrix R respectively obtain
To the average value matrix R of relational matrix Rμ；
The standard deviation matrix generation unit 27, the standard deviation of every a line for seeking the relational matrix R respectively, obtains
To the standard deviation matrix R of relational matrix Rσ；
The upper current limiting matrix and lower current limiting matrix generation unit 28, for according to RμAnd Rσ, construct upper limit matrix U and lower limit square
Battle array L, wherein U=Rμ+kRσ, L=Rμ-kRσ, k is the first preset constant；
The discrimination matrix generation unit 29, for according to user's fluctuant electricity quantity matrix Δ Pc, the upper limit matrix U
With the lower limit matrix L, discrimination matrix P is constructed；
The user's evaluation matrix generation unit 210, for constructing user's evaluation matrix Q according to the discrimination matrix P；
The stealing user identification unit 211, for according to the either element in the user's evaluation matrix Q, if this yuan
The value of element is greater than preset value, then judges user corresponding to the element for stealing user.
Specifically, user's electricity matrix PcAre as follows:
Wherein, all users under the selected route include m user altogether, and the preset time period includes t days altogether,
PcijIt is user j in the i-th daily power consumption, 1≤i≤t, 1≤j≤m；
It is then described to obtain user's fluctuant electricity quantity matrix Δ PcAre as follows:
Wherein, Δ Pcij=Pc(i+1)j-Pcij, 1≤i≤t-1,1≤j≤m.
Specifically, line loss electricity matrix generation unit 22 is used for:
For i-th day in the preset time period, the selected route was by n power supply power supply, if wherein each power supply
Power supply volume be Psj, then line powering amount P of the selected route at i-th day is calculated by following equationig:
If all users under the selected route include m user altogether, each user was at i-th day in the m user
Electricity consumption be Pcj, then use electricity P of the selected route at i-th day is calculated by following equationiy:
Line loss electricity P of the selected route at i-th day is calculated by following formulail, wherein 1≤i≤t:
Pil=Pig-Piy
The then line loss electricity matrix PlAre as follows:
Pl=[P1l, P2l... P(t-1)l, Ptl]T
Wherein, PilLine loss electricity for the selected route on 1st, 1≤i≤t；
Specifically, line loss fluctuant electricity quantity matrix generation unit 24 is used for:
ΔPl=[Δ P1l, Δ P2l... Δ P(t-1)l]T
Wherein, Δ Pil=P(i+1)l-Pil, 1≤i≤t-1.
Specifically, relational matrix generation unit 25 is used for:
R=Δ Pc-ΔPlI
Wherein, I is t-1 rank unit matrix；
Average value matrix generation unit 26 is used for:
The average value of described every a line for seeking the relational matrix R respectively obtains the average value matrix R of relational matrix Ru
Include:
Rμ=[R1μ, R2μ... R(t-1)μ]T
Wherein,
Standard deviation matrix generation unit 27 is used for:
The standard deviation of described every a line for seeking the relational matrix R respectively obtains the standard deviation matrix R of relational matrix Rσ
Include:
Rσ=[R1σ, R2σ... R(t-1)σ]T
Wherein,
Specifically, discrimination matrix generation unit 29 is used for:
Wherein:
User's evaluation matrix generation unit 210 is used for:
For any column element of the discrimination matrix P, the sum of the column all elements is sought, obtains user's evaluation matrix Q
=[Q1, Q2... Qm], wherein
Specifically, stealing user identification unit 211 is used for:
If Qj> et then judges element QjCorresponding user j is stealing user, wherein e is the second preset constant in formula.
Specifically, stealing user identification unit 211 is also used to:
All stealing users under the selected route are obtained, and successively calculate each stealing user's by following formula
Stealing index Ij:
Descending sort is carried out to the stealing index of all stealing users.
Optionally, the first preset constant k=3, the second preset constant e=0.5.
The present invention provides a kind of stealing customer identification device based on Gaussian Profile, the device is by obtaining selected route
User's electricity consumption data within a preset period of time obtain user's electricity matrix Pc, route is selected in preset time period according to this
Interior daily line loss obtains line loss electricity matrix Pl, to each row of data in user's electricity matrix, take slippage
Mode calculates daily electricity fluctuation, and thus constructs user's fluctuant electricity quantity matrix Δ Pc；Similarly, process circuit is damaged in a like fashion
Matrix is consumed, line loss fluctuant electricity quantity matrix Δ P is obtainedl.According to Δ PcWith Δ PlConstruct user's fluctuant electricity quantity and line loss wave
The relational matrix R of dynamic electricity, and according to Pauta criterion, calculate the average value matrix and standard deviation matrix of R.According to being averaged for R
Value matrix and standard deviation matrix construct upper current limiting matrix and lower current limiting matrix by setting coefficient k, further construct discrimination matrix, and
User's evaluation matrix is obtained by judgement matrix, by the way that rational evaluation coefficient is arranged, identifies stealing user.The present invention is based on route damages
The incidence relation of power consumption and user's electricity realizes the screening to multiplexing electric abnormality user, improves the recognition efficiency to stealing user
And accuracy rate.
Fig. 3 is a kind of schematic diagram of terminal device provided in an embodiment of the present invention.As shown in figure 3, the terminal of the embodiment
Equipment 3 includes: processor 30, memory 31 and is stored in the memory 31 and can run on the processor 30
Computer program 32, such as stealing user's recognizer based on Gaussian Profile.The processor 30 executes the computer journey
The step in above-mentioned each stealing user identification method embodiment based on Gaussian Profile is realized when sequence 32, such as shown in FIG. 1
Step 101 is to 1011.Alternatively, the processor 30 is realized in above-mentioned each Installation practice respectively when executing the computer program 32
Module/unit function, such as the function of module 21 to 211 shown in Fig. 2.
Illustratively, the computer program 32 can be divided into one or more module/units, it is one or
Multiple module/units are stored in the memory 31, and are executed by the processor 30, to complete the present invention.Described one
A or multiple module/units can be the series of computation machine program instruction section that can complete specific function, which is used for
Implementation procedure of the computer program 32 in the terminal device 3 is described.
The terminal device 3 can be the calculating such as desktop PC, notebook, palm PC and cloud server and set
It is standby.The terminal device may include, but be not limited only to, processor 30, memory 31.It will be understood by those skilled in the art that Fig. 3
The only example of terminal device 3 does not constitute the restriction to terminal device 3, may include than illustrating more or fewer portions
Part perhaps combines certain components or different components, such as the terminal device can also include input-output equipment, net
Network access device, bus etc..
The processor 30 can be central processing unit (Central Processing Unit, CPU), can also be
Other general processors, digital signal processor (Digital Signal Processor, DSP), specific integrated circuit
(Application Specific Integrated Circuit, ASIC), ready-made programmable gate array (Field-
Programmable Gate Array, FPGA) either other programmable logic device, discrete gate or transistor logic,
Discrete hardware components etc..General processor can be microprocessor or the processor is also possible to any conventional processor
Deng.
The memory 31 can be the internal storage unit of the terminal device 3, such as the hard disk or interior of terminal device 3
It deposits.The memory 31 is also possible to the External memory equipment of the terminal device 3, such as be equipped on the terminal device 3
Plug-in type hard disk, intelligent memory card (Smart Media Card, SMC), secure digital (Secure Digital, SD) card dodge
Deposit card (Flash Card) etc..Further, the memory 31 can also both include the storage inside list of the terminal device 3
Member also includes External memory equipment.The memory 31 is for storing needed for the computer program and the terminal device
Other programs and data.The memory 31 can be also used for temporarily storing the data that has exported or will export.
The embodiment of the present invention also provides a kind of computer readable storage medium, and the computer-readable recording medium storage has
Computer program, the computer program realize stealing based on Gaussian Profile described in any of the above-described embodiment when being executed by processor
The step of electric user identification method.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of software functional units.
If the integrated unit is realized in the form of SFU software functional unit and sells or use as independent product
When, it can store in a computer readable storage medium.Based on this understanding, technical solution of the present invention is substantially
The all or part of the part that contributes to existing technology or the technical solution can be in the form of software products in other words
It embodies, which is stored in a storage medium, including some instructions are used so that a computer
Equipment (can be personal computer, server or the network equipment etc.) executes the complete of each embodiment the method for the present invention
Portion or part steps.And storage medium above-mentioned includes: USB flash disk, mobile hard disk, read-only memory (ROM, Read-Only
Memory), random access memory (RAM, Random Access Memory), magnetic or disk etc. are various can store journey
The medium of sequence code.
Embodiment described above is merely illustrative of the technical solution of the present invention, rather than its limitations；Although referring to aforementioned reality
Applying example, invention is explained in detail, those skilled in the art should understand that: it still can be to aforementioned each
Technical solution documented by embodiment is modified or equivalent replacement of some of the technical features；And these are modified
Or replacement, the essence of corresponding technical solution is departed from the spirit and scope of the technical scheme of various embodiments of the present invention, it should all
It is included within protection scope of the present invention.
Claims (10)
1. a kind of stealing user identification method based on Gaussian Profile, which is characterized in that this method comprises:
All users under selected route are obtained, for any user in all users, obtain the user default
Daily electricity consumption in period generates user's electricity matrix Pc；
Selected route line loss electricity daily in the preset time period is obtained, line loss electricity matrix is obtained
Pl；
For any user in all users, according to user's electricity matrix PcThe user is obtained described default
The difference of the electricity consumption in i+1 day and i-th day electricity consumption in period obtains user's fluctuant electricity quantity matrix Δ Pc, wherein it is described pre-
If the period includes t days, 1≤i≤t-1；
According to the line loss electricity matrix Pl, obtain line loss electricity and the choosing of the selected route in i+1 day
Alignment road obtains line loss fluctuant electricity quantity matrix Δ P in the difference of i-th day line loss electricityl, 1≤i≤t-1；
According to user's fluctuant electricity quantity matrix Δ PcWith the line loss fluctuant electricity quantity matrix Δ Pl, building user is fluctuated electric
The relational matrix R of amount and line loss fluctuant electricity quantity；
The average value for seeking every a line of the relational matrix R respectively obtains the average value matrix R of relational matrix Rμ；
The standard deviation for seeking every a line of the relational matrix R respectively obtains the standard deviation matrix R of relational matrix Rσ；
According to RμAnd Rσ, construct upper limit matrix U and lower limit matrix L, wherein U=Rμ+kRσ, L=Rμ-kRσ, k is first default normal
Number；
According to user's fluctuant electricity quantity matrix Δ Pc, the upper limit matrix U and the lower limit matrix L, construct discrimination matrix P；
According to the discrimination matrix P, user's evaluation matrix Q is constructed；
According to the either element in the user's evaluation matrix Q, if the value of the element is greater than preset value, judge that element institute is right
The user answered is stealing user.
2. the stealing user identification method according to claim 1 based on Gaussian Profile, which is characterized in that user's electricity
Moment matrix PcAre as follows:
Wherein, all users under the selected route include m user altogether, and the preset time period includes t days altogether, PcijFor
User j is in the i-th daily power consumption, 1≤i≤t, 1≤j≤m；
It is then described to obtain user's fluctuant electricity quantity matrix Δ PcAre as follows:
Wherein, Δ Pcij=Pc(i+1)j-Pcij, 1≤i≤t-1,1≤j≤m.
3. the stealing user identification method according to claim 2 based on Gaussian Profile, which is characterized in that the acquisition institute
Selected route line loss electricity daily in the preset time period is stated, line loss electricity matrix P is obtainedlInclude:
For i-th day in the preset time period, the selected route was by n power supply power supply, if the wherein confession of each power supply
Electricity is Psj, then line powering amount P of the selected route at i-th day is calculated by following equationig:
If all users under the selected route include m user altogether, use of each user at i-th day in the m user
Electricity is Pcj, then use electricity P of the selected route at i-th day is calculated by following equationiy:
Line loss electricity P of the selected route at i-th day is calculated by following formulail, wherein 1≤i≤t:
Pil=Pig-Piy
The then line loss electricity matrix PlAre as follows:
Pl=[P1l, P2l... P(t-1)l, Ptl]T
Wherein, PilLine loss electricity for the selected route on 1st, 1≤i≤t；
It is then described to obtain line loss fluctuant electricity quantity matrix Δ PlAre as follows:
ΔPl=[Δ P1l, Δ P2l... Δ P(t-1)l]T
Wherein, Δ Pil=P(i+1)l-Pil, 1≤i≤t-1.
4. the stealing user identification method according to claim 3 based on Gaussian Profile, which is characterized in that described according to institute
State user's fluctuant electricity quantity matrix Δ PcWith the line loss fluctuant electricity quantity matrix Δ Pl, construct user's fluctuant electricity quantity and route damage
Consumption fluctuant electricity quantity relational matrix R include:
R=Δ Pc-ΔPlI
Wherein, I is t-1 rank unit matrix；
The average value of described every a line for seeking the relational matrix R respectively obtains the average value matrix R of relational matrix RμInclude:
Rμ=[R1μ, R2μ... R(t-1)μ]T
Wherein,
The standard deviation of described every a line for seeking the relational matrix R respectively obtains the standard deviation matrix R of relational matrix RσInclude:
Rσ=[R1σ, R2σ... R(t-1)σ]T
Wherein,
5. the stealing user identification method according to claim 4 based on Gaussian Profile, which is characterized in that described according to institute
State user's fluctuant electricity quantity matrix Δ Pc, the upper limit matrix U and the lower limit matrix L, building discrimination matrix P includes:
Wherein:
It is described to include: according to the discrimination matrix P, building user's evaluation matrix Q
For any column element of the discrimination matrix P, the sum of the column all elements is sought, obtains user's evaluation matrix Q=[Q1,
Q2... Qm], wherein1≤j≤m。
6. the stealing user identification method according to claim 5 based on Gaussian Profile, which is characterized in that described according to institute
The either element in user's evaluation matrix Q is stated, if the value of the element is greater than preset value, judges that user corresponding to the element is
Stealing user includes:
If Qj> et then judges element QjCorresponding user j is stealing user, wherein e is the second preset constant in formula.
7. the stealing user identification method according to claim 6 based on Gaussian Profile, which is characterized in that judging this yuan
User corresponding to element is this method after stealing user further include:
All stealing users under the selected route are obtained, and successively calculate the stealing of each stealing user by following formula
Index Ij:
Descending sort is carried out to the stealing index of all stealing users.
8. the stealing user identification method according to claim 6 based on Gaussian Profile, which is characterized in that this method is also wrapped
It includes:
The first preset constant k=3, the second preset constant e=0.5.
9. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, and feature exists
In when the computer program is executed by processor the step of any one of such as claim 1 to 8 of realization the method.
10. a kind of terminal device, which is characterized in that the terminal device includes memory, processor, is stored on the memory
There is the computer program that can be run on the processor, is realized when the processor executes the computer program as right is wanted
The step of seeking any one of 1 to 8 the method.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110736888A (en) * | 2019-10-24 | 2020-01-31 | 国网上海市电力公司 | method for monitoring abnormal electricity consumption behavior of user |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103488867A (en) * | 2013-07-16 | 2014-01-01 | 深圳市航天泰瑞捷电子有限公司 | Method for automatically screening abnormal electricity consumption user |
| CN104424603A (en) * | 2013-08-30 | 2015-03-18 | 国际商业机器公司 | Method and device for metering power consumption in power distribution network |
| US20150116107A1 (en) * | 2012-09-21 | 2015-04-30 | Google Inc. | Initially detecting a visitor at a smart-home |
| CN106022951A (en) * | 2016-05-09 | 2016-10-12 | 北京智芯微电子科技有限公司 | Electricity consumption abnormity analysis method and apparatus |
| CN106650797A (en) * | 2016-12-07 | 2017-05-10 | 广东电网有限责任公司江门供电局 | Distribution network electricity stealing suspected user intelligent recognition method based on integrated ELM (Extreme Learning Machine) |
| CN106771568A (en) * | 2016-11-16 | 2017-05-31 | 国家电网公司 | Area distribution formula photovoltaic stealing supervisory systems |
| CN108734602A (en) * | 2018-04-09 | 2018-11-02 | 广东电网有限责任公司 | A kind of user's electricity stealing identification system based on higher-dimension random matrix |
-
2018
- 2018-12-13 CN CN201811525442.2A patent/CN109598644B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150116107A1 (en) * | 2012-09-21 | 2015-04-30 | Google Inc. | Initially detecting a visitor at a smart-home |
| CN103488867A (en) * | 2013-07-16 | 2014-01-01 | 深圳市航天泰瑞捷电子有限公司 | Method for automatically screening abnormal electricity consumption user |
| CN104424603A (en) * | 2013-08-30 | 2015-03-18 | 国际商业机器公司 | Method and device for metering power consumption in power distribution network |
| CN106022951A (en) * | 2016-05-09 | 2016-10-12 | 北京智芯微电子科技有限公司 | Electricity consumption abnormity analysis method and apparatus |
| CN106771568A (en) * | 2016-11-16 | 2017-05-31 | 国家电网公司 | Area distribution formula photovoltaic stealing supervisory systems |
| CN106650797A (en) * | 2016-12-07 | 2017-05-10 | 广东电网有限责任公司江门供电局 | Distribution network electricity stealing suspected user intelligent recognition method based on integrated ELM (Extreme Learning Machine) |
| CN108734602A (en) * | 2018-04-09 | 2018-11-02 | 广东电网有限责任公司 | A kind of user's electricity stealing identification system based on higher-dimension random matrix |
Non-Patent Citations (3)
| Title |
|---|
| 史玉良等: ""基于用电特征分析的窃电行为识别方法"", 《计算机研究与发展》 * |
| 李宁等: ""基于电量离群点挖掘的窃电辨识方法研究"", 《中国计量大学学报》 * |
| 王新霞等: ""基于正态分布离群点算法的反窃电研究"", 《电气应用》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110736888A (en) * | 2019-10-24 | 2020-01-31 | 国网上海市电力公司 | method for monitoring abnormal electricity consumption behavior of user |
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