CN109325545A - Low-voltage network topological structure method of calibration, device, equipment and storage medium - Google Patents
Low-voltage network topological structure method of calibration, device, equipment and storage medium Download PDFInfo
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Abstract
The invention discloses a kind of low-voltage network topological structure methods of calibration, after forming contact potential series, just carry out clustering processing to the contact potential series, i.e., are three groups by contact potential series cluster;Again by comparing the similarity of each phase voltage sequence in the transformer monitoring terminal of contact potential series and Target Station area after clustering processing, to determine belonging to voltage monitoring equipment when foreground partition phase;The changed target voltage monitoring device of phase is finally determined again, and the phase of target voltage monitoring device is updated, and then realizes the verification to low-voltage network topological structure.The platform area information that this method defines voltage monitoring equipment defines the phase information of each voltage monitoring equipment again, and the verification accuracy of low-voltage network topological structure can be improved, and then is conducive to management and the wastage reducing and energy saving of low-voltage network.In addition, the invention also discloses a kind of low-voltage network topological structure calibration equipment, equipment and storage medium, effect are as above.
Description
Technical field
The present invention relates to low-voltage network topological structures to verify identification field, in particular to a kind of low-voltage distribution net topology knot
Structure method of calibration, device, equipment and storage medium.
Background technique
The topological relation correctness of low-voltage network, the especially correctness of the affiliated phase of user, are current low-voltage distributions
Basis and the research hotspot of net management fining and wastage reducing and energy saving.Currently, the topological relation data of low-voltage network are leaned on mostly
Manual entry computer system, still, since user's field connection is complicated, data volume is big, leads to operation side because load is unbalanced
Formula changes and family becomes relationship and changes frequently, so there are user's phase information is a large amount of in the data of manual entry computer system
The problem of missing and mistake etc., and then will cause the mistake of computer system low and medium voltage distribution network topological relation data, because low
Press-fitting topological structure of electric has the business such as power information acquisition system, Power System Analysis system and Electric Power Marketing System
Important function.Therefore, carrying out verification to low-voltage network topological relation is particularly important.
Currently, main by determining platform area (transformer) belonging to user's voltage monitoring equipment come to low-voltage distribution net topology
It is verified, particularly as being to be matched by judging whether platform area information belonging to user's voltage monitoring equipment changes to low pressure
Power network topology is updated verification.But platform area information belonging to voltage monitoring equipment is not meant to electricity there is no variation
Pressing the affiliated phase information of monitoring device, there is no variations, so in the prior art only by judging user's voltage monitoring equipment institute
The platform zone position of category verifies low-voltage network topological structure, eventually results in the verification accuracy of low-voltage network topological structure
It is low, so can management to low-voltage network and wastage reducing and energy saving have an impact.
It can be seen that how to improve the verification accuracy of low-voltage network topological structure in favor of the management of low-voltage network
And the problem of wastage reducing and energy saving is those skilled in the art's urgent problem to be solved.
Summary of the invention
The embodiment of the present application provides a kind of low-voltage network topological structure method of calibration, device, equipment and storage medium,
How to improve the verification accuracy of low-voltage network topological structure in the prior art with solution in favor of the management of low-voltage network
And the problem of wastage reducing and energy saving.
In order to solve the above technical problems, the present invention provides a kind of low-voltage network topological structure methods of calibration, comprising:
The voltage sample data of all voltage monitoring equipment in Target Station area are obtained in default collection period to form voltage
Sequence;
Clustering processing is carried out to the contact potential series;
Contact potential series after comparing clustering processing and each phase voltage sequence in the transformer monitoring terminal in the Target Station area
Similarity to determine belonging to the voltage monitoring equipment when foreground partition phase;
Determine it is described when foreground partition phase and the inconsistent target voltage monitoring device of pre-stored original phase, and
Update phase information of the target voltage monitoring device in the low-voltage network topological structure.
Preferably, in the voltage sample number for obtaining all voltage monitoring equipment in Target Station area in default collection period
It is formed after contact potential series accordingly, further includes:
Data cleansing is carried out to the contact potential series.
It is preferably, described that clustering processing is carried out to the contact potential series specifically:
Clustering processing is carried out to the contact potential series based on k-medoids clustering algorithm.
Preferably, each in the contact potential series relatively after clustering processing and the transformer monitoring terminal in the Target Station area
The similarity of phase voltage sequence is to determine belonging to the voltage monitoring equipment when foreground partition phase specifically includes:
The Pierre of each phase voltage sequence in contact potential series and the transformer monitoring terminal after calculating the clustering processing
Inferior related coefficient;
It determines belonging to the voltage monitoring equipment according to the related coefficient when foreground partition phase.
Preferably, it is described determine it is described when foreground partition phase and the inconsistent target electricity of pre-stored original phase
After pressure monitoring device, further includes:
Obtain the history phase of the target voltage monitoring device;
Judge the history phase with belonging to the voltage monitoring equipment determined work as foreground partition phase it is whether consistent;
If it is, characterization determine it is described when foreground partition phase it is correct;
If it is not, then characterization determine it is described when foreground partition phase it is incorrect.
Preferably, described when foreground partition phase is correct, further includes:
Show the target voltage monitoring device works as foreground partition phase.
In order to solve the above technical problems, the present invention also provides a kind of corresponding with low-voltage network topological structure method of calibration
Device, comprising:
Module is obtained, for obtaining the voltage sample number of all voltage monitoring equipment in Target Station area in default collection period
Contact potential series is formed accordingly;
Clustering processing module, for carrying out clustering processing to the contact potential series;
Comparison module, in the transformer monitoring terminal for comparing the contact potential series after clustering processing and the Target Station area
The similarity of each phase voltage sequence is to determine belonging to the voltage monitoring equipment when foreground partition phase;
Determining module, it is described when foreground partition phase and the inconsistent target electricity of pre-stored original phase for determining
Monitoring device is pressed, and updates phase information of the target voltage monitoring device in the low-voltage network topological structure.
Preferably, the clustering processing module be specifically used for based on k-medoids clustering algorithm to the contact potential series into
Row clustering processing.
In order to solve the above technical problems, the present invention also provides a kind of corresponding with low-voltage network topological structure method of calibration
Equipment, comprising:
Memory, for storing computer program;
Processor, for executing the computer program to realize that any one of the above low-voltage network topological structure verifies
The step of method.
In order to solve the above technical problems, the present invention also provides a kind of corresponding with low-voltage network topological structure method of calibration
Computer readable storage medium, be stored with computer program, the computer program on the computer readable storage medium
The step of being executed by processor to realize any one of the above low-voltage network topological structure method of calibration.
Compared with the prior art, a kind of low-voltage network topological structure method of calibration provided by the present invention is adopted default
The voltage sample data that all voltage monitoring equipment in Target Station area are got in the collection period are formed after contact potential series, just to the electricity
Sequence is pressed to carry out clustering processing, in fact just clustering contact potential series is three groups;Then again by comparing the electricity after clustering processing
Press the similarity of each phase voltage sequence in the transformer monitoring terminal in sequence and Target Station area, it is therefore an objective to determine that voltage monitoring is set
Work as foreground partition phase for affiliated;It finally determines again when foreground partition phase and the inconsistent target of pre-stored original phase
Voltage monitoring equipment, and update phase information of the target voltage monitoring device in low-voltage network topological structure, that is to say, that
It determines the changed target voltage monitoring device of phase, and then realizes the verification to low-voltage network topological structure.Therefore,
This method had not only defined the platform area information of voltage monitoring equipment but also had defined the phase information of each voltage monitoring equipment, and existing
Have and only determine that the platform area information of voltage monitoring equipment is compared in technology, the verification that low-voltage network topological structure can be improved is accurate
Property, and then it is conducive to management and the wastage reducing and energy saving of low-voltage network.In addition, the present invention also provides a kind of low-voltage distribution net topology knots
Structure calibration equipment, equipment and storage medium, effect are as above.
Detailed description of the invention
Fig. 1 is a kind of low-voltage network topological structure method of calibration flow chart provided by the embodiment of the present invention;
Fig. 2 is a kind of low-voltage distribution network users voltage monitoring equipment phase schematic diagram provided by the embodiment of the present invention;
Fig. 3 is a kind of low-voltage network topological structure calibration equipment composition schematic diagram provided by the embodiment of the present invention;
Fig. 4 is a kind of low-voltage network topological structure calibration equipment composition schematic diagram provided by the embodiment of the present invention.
Specific embodiment
Below in conjunction with the attached drawing in the embodiment of the present application, technical solutions in the embodiments of the present application carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, those of ordinary skill in the art without making creative work it is obtained it is all its
Its embodiment, shall fall within the protection scope of the present invention.
Core of the invention is to provide a kind of low-voltage network topological structure method of calibration, device, equipment and storage medium,
Can solve the pipe for how improving the verification accuracy of low-voltage network topological structure in the prior art in favor of low-voltage network
The problem of reason and wastage reducing and energy saving.
Scheme in order to enable those skilled in the art to better understand the present invention, with reference to the accompanying drawing and specific embodiment party
The present invention is described in further detail for formula.
Fig. 1 is a kind of low-voltage network topological structure method of calibration flow chart provided by the embodiment of the present invention, such as Fig. 1 institute
Show, this method comprises:
S101: the voltage sample data of all voltage monitoring equipment in Target Station area are obtained in default collection period to be formed
Contact potential series.
Low-voltage network is primarily referred to as 10kV power distribution network below, by the collection voltages sequence of voltage monitoring equipment
It realizes to verify low-voltage network topological structure and identify.Specifically, it exactly obtains and obtains target area in preset collection period
The voltage sample data of domain (such as certain cell) all voltage monitoring equipment form contact potential series by the sequencing of acquisition time
Value, i.e., contact potential series is voltage sample value in temporal sequence, and voltage monitoring equipment includes distribution transforming prison in the embodiment of the present application
Terminal, intelligent electric energy meter, voltage monitoring instrument and lines branch monitoring unit etc. are surveyed, default collection period can be according to the actual situation
It is determined, the present invention is simultaneously not construed as limiting.In practical applications, target area can be extracted from power information acquisition system to own
The contact potential series data that the voltage is formed are expressed as { (i, u by the voltage of user's voltage monitoring equipmenti)}I=1...n;Wherein, i is
The serial number of target area user, if the target area shares m user, uiIt is the voltage value of the voltage monitoring equipment of user i, n
For the quantity of the voltage value of the voltage monitoring equipment of user i;In order to improve data collection accuracy, in practical applications, voltage
The sampling period of value should be close enough, and general recommendations is 15 minutes sampled points, i.e. the sampling interval is 15 minutes, and one day is 96
Sampled point, the sampling interval is smaller, and the data of acquisition are more accurate;In view of the sampling time is too long, computationally intensive problem, in reality
In the application of border, 2 weeks sampling time sections can be chosen.Above-mentioned contact potential series can be write as matrix are as follows:
S102: clustering processing is carried out to contact potential series.
After the contact potential series for getting user's voltage monitoring equipment, need to carry out clustering processing to the sequence, specifically
It is three groups that exactly the contact potential series of formation, which is gathered, convenient for carrying out post-processing to data.Preferably embodiment, to voltage
Sequence carries out clustering processing specifically:
Clustering processing is carried out to contact potential series based on k-medoids clustering algorithm.
Specifically can be using k-medoids clustering algorithm be used, the contact potential series cluster that will acquire is three groups, including
Following step: the first step gives the preset value of J.Second step enables K=3, that is, all contact potential series that will acquire gather for three clusters.The
Three steps select K center vector [μ at randomk1 μk2 … μkn] initial vector.
The contact potential series of each voltage monitoring equipment is referred to cluster class where the center vector nearest from it by the 4th step
In, and calculate the contact potential series U of each voltage monitoring equipmentiWith three center vector [μk1 μk2 … μkn] distance, DikTable
Show the voltage curve of the voltage monitoring equipment of user i with a distance from center vector k, range formula is as follows:
By DikIt is worth the contact potential series U of lesser voltage monitoring equipmentiBelong to the cluster class where the center vector, DikValue
It is small, illustrate the contact potential series U of corresponding voltage monitoring equipmentiIt is small with corresponding centre distance.
5th step calculates the new center vector of each cluster, other all curves of the new center vector to the cluster
Sum of the distance it is minimum.Specifically new center vector can be determined using k-medoid.
6th step calculates the variation distance J of new and old center vector, and calculation formula is as follows:
7th step repeats the 4th step to the 6th step, until the new center of the maximum step number of iteration or front and back to
The variation distance J of amount is less than preset value.The contact potential series of all user's voltage monitoring equipment three clusters have been divided into just so.
S103: the contact potential series after comparing clustering processing and each phase voltage sequence in the transformer monitoring terminal in Target Station area
Similarity to determine belonging to voltage monitoring equipment when foreground partition phase.
Particularly as being that each contact potential series after clustering processing is formed voltage curve, then supervised with the transformer in Target Station area
And Target Station it surveys the voltage curve that each phase voltage sequence (including A, B and C three-phase voltage sequence) is formed in terminal to be compared, i.e.,
The phase voltage curve of all transformer monitoring terminals carries out Optimum Matching in area, and then determines belonging to user's voltage monitoring equipment
Work as foreground partition phase, that is, which phase in A, B and C three-phase belonged to.In practical applications, more can generally be picked out from substation
10kV feeder line hangs with multiple distribution transformers on every feeder line.Distribution transformer is generally 10kV/0.4kV transformer, the side 10kV
For three-phase, the side 0.4kV is three-phase four-wire system or three-phase five-wire mode, and in order to simplify wiring and be conducive to interpreting blueprints, common wiring pattern is single line
Figure, indicates three-phase with solid wire.
In order to more accurately determine belonging to voltage monitoring equipment when foreground partition phase, preferably embodiment party
In the transformer monitoring terminal in formula, contact potential series after comparing clustering processing and Target Station area the similarity of each phase voltage sequence with
It determines belonging to voltage monitoring equipment when foreground partition phase specifically includes:
The Pearson came phase relation of each phase voltage sequence in contact potential series and transformer monitoring terminal after calculating clustering processing
Number;
It determines belonging to voltage monitoring equipment according to related coefficient when foreground partition phase.
It is specifically exactly each phase voltage sequence of the three classes contact potential series for gathering step S102 and transformer monitoring terminal
It is compared, determines clustered phase, include the following steps:
The first step calculates each group's average voltage of above-mentioned three clustered groups, forms three new contact potential series,
Are as follows:
Wherein, matrix row element forms a contact potential series, and three row elements form three contact potential series
Second step, according toSampling instant, pre-process each phase voltage sequence of transformer monitoring terminal, treated
Contact potential series isThe reliability of each phase voltage sequence of transformer monitoring terminal is than user's voltage monitoring equipment voltage
The good reliability of sequence, and the phase of the contact potential series of transformer monitoring terminal is clear, can be used as phasing foundation.
Third step calculates separatelyWithPearson correlation coefficient, such as: calculate U1WithPearson came
Related coefficient, and compare size, that big phase of related coefficient is U1Phase.Successively calculate U2、U3WithPearson came
Related coefficient, and compare size, determine U2、U3Affiliated phase.In general,Adhere to different phases separately.
Pearson correlation coefficient is for measuring two linear dependences between variable X and Y, and Pearson correlation coefficient is fixed
Justice is as follows:
Wherein,Respectively represent the mean value of X, Y.
4th step determinesAfter affiliated phase, then its corresponding user's sequence belongs to the phase, thus can be true
The phase of fixed each user's voltage monitoring equipment.
S104: determining when foreground partition phase and the inconsistent target voltage monitoring device of pre-stored original phase,
And update phase information of the target voltage monitoring device in low-voltage network topological structure.
Specifically, determine each user's voltage monitoring equipment after the phase of foreground partition, each user for will determining
Being compared when foreground partition phase and pre-stored accordingly original phase for voltage monitoring equipment, is determined when foreground partition phase
Position and the inconsistent target voltage monitoring device of pre-stored original phase, after determining target voltage monitoring device,
The phase of the target voltage monitoring device in low-voltage network topological structure can be updated, and then realized to low pressure
The verification of power distribution network topological structure can effectively verify power grid computer information system low and medium voltage distribution network topology data
Correctness.That is the original phase with the user's voltage monitoring equipment stored in computer system is compared, if calculating
The original phase of the user's voltage monitoring equipment stored in machine system and above-mentioned gained user voltage monitoring equipment work as foreground partition
Phase is consistent, then illustrates that there is no becoming compared with original phase when foreground partition phase belonging to user's voltage monitoring equipment
Change, i.e., the phase of user's voltage monitoring equipment in low-voltage network topological structure is correct, does not have to modification and updates, it can gives
The user belongs to the recommendation opinion of the phase out, and staff is reminded to carry out related verification;If being stored in computer system
The original phase of user's voltage monitoring equipment and above-mentioned gained user voltage monitoring equipment when foreground partition phase it is inconsistent, then say
Work as foreground partition phase belonging to bright user's voltage monitoring equipment to be changed compared with original phase, i.e. low-voltage distribution net topology
The phase of user's voltage monitoring equipment in structure is incorrect, needs to modify update;In practical applications, if department of computer science
Phase belonging to user's voltage monitoring equipment is lacked in system, then works as foreground partition determine corresponding user's voltage monitoring equipment
After phase, need to indicate phase missing in low-voltage network topological structure or with the voltage monitoring equipment determined
When foreground partition, phase fills up missing phase.Goods and materials needed for method of calibration of the invention and human cost are low, accuracy is high, can grasp
The property made is good and strong real-time, can effectively examine the affiliated phase of user.
A kind of low-voltage network topological structure method of calibration provided by the present invention, a kind of low pressure provided by the present invention are matched
Topological structure of electric method of calibration gets the voltage sample of all voltage monitoring equipment in Target Station area in default collection period
Data are formed after contact potential series, just carry out clustering processing to the contact potential series, and in fact just clustering contact potential series is three groups;
Then again by comparing each phase voltage sequence in the transformer monitoring terminal of contact potential series and Target Station area after clustering processing
Similarity, it is therefore an objective to determine belonging to voltage monitoring equipment when foreground partition phase;Finally determine again when foreground partition phase and
The inconsistent target voltage monitoring device of pre-stored original phase, and target voltage monitoring device is updated in low-voltage network
Phase information in topological structure, that is to say, that determine the changed target voltage monitoring device of phase, and then realization pair
The verification of low-voltage network topological structure.Therefore, the platform area information that this method defines voltage monitoring equipment is determined again
The phase information of each voltage monitoring equipment can be with compared with the platform area information for only determining voltage monitoring equipment in the prior art
The verification accuracy of low-voltage network topological structure is improved, and then is conducive to management and the wastage reducing and energy saving of low-voltage network.
In order to improve the verification accuracy of low-voltage network topological structure, on the basis of the above embodiments, as preferred
Ground embodiment obtains the voltage sample data of all voltage monitoring equipment in Target Station area in default collection period to form electricity
After pressure sequence, further includes:
Data cleansing is carried out to contact potential series.
Particularly as be contact potential series is filtered with will have a power failure or obviously be not belonging to normal sample value voltage value etc. it is straight
It connects and deletes out contact potential series.The different voltages sampled value of different user voltage monitoring equipment, takes identical processing.It deletes
Afterwards, any acquisition moment lacks voltage data, deletes the acquisition moment.The voltage sample value at remaining all acquisition moment,
In the reasonable scope, it and is not zero.Filtered voltage acquisition sequence, can be used for subsequent processing.It simultaneously can be to voltage sequence
Column pre-processed, particularly as be per unit value that can be worth on the basis of 220V etc. processing.Pretreated voltage acquisition sequence, can
For subsequent processing.
In order to make the user's voltage monitoring equipment determined when foreground partition phase it is more accurate, in the base of above-described embodiment
On plinth, preferably embodiment is being determined when foreground partition phase and the inconsistent target of pre-stored original phase
After voltage monitoring equipment, further includes:
Obtain the history phase of target voltage monitoring device;
Judge history phase with belonging to the voltage monitoring equipment determined work as foreground partition phase it is whether consistent;
If it is, characterization determine when foreground partition phase it is correct;
If it is not, then characterization determine when foreground partition phase it is incorrect.
Particularly as being in conjunction with belonging to the history phase confirmation user of user's voltage monitoring equipment when foreground partition phase, i.e. needle
The affiliated phase error of user's voltage monitoring equipment and phase are lacked, not made hasty generalizations, because user's phase is less,
Can be mobile by time smoothing, user's phase is repeatedly judged using preceding method, for example, can be using preceding method to the use
The phase of family voltage monitoring equipment carries out 10 judgements, if being same phase after 10 judgements, illustrates that user's voltage is supervised
It is correct to work as foreground partition phase belonging to measurement equipment, then can determine that user's voltage monitoring equipment belongs to the phase;If aforementioned 10
Phase alternation changes in secondary judgement, illustrates that working as foreground partition phase belonging to user's voltage monitoring equipment is possible to incorrect, can
Wouldn't draw a conclusion, determined one time again by next collection period.In practical applications, not for the judgement of continuous 10 phases
The user of change can provide the user and belong to the recommendation opinion of the phase, and staff is reminded to carry out related verification.
In order to keep the method for calibration more intelligent, and the target electricity inconsistent convenient for related personnel's timely learning phase
That presses monitoring device works as foreground partition phase, and on the basis of the above embodiments, preferably embodiment, is working as foreground partition phase
When position is correct, further includes:
Displaying target voltage monitoring equipment works as foreground partition phase.
Particularly as being by affiliated when foreground partition phase and the inconsistent target voltage of pre-stored original phase monitor
The foreground partition phase of working as of equipment is shown, to allow related personnel in time by target voltage monitoring device in low-voltage distribution net topology
Phase in structure is updated, i.e., the phase of target voltage monitoring device is updated to when foreground partition phase.
In order to make those skilled in the art more fully understand this programme, this programme is carried out below with reference to practical application scene
It is described in detail, Fig. 2 is a kind of low-voltage distribution network users voltage monitoring equipment phase schematic diagram provided by the embodiment of the present invention, such as
Shown in Fig. 2, shown in Fig. 2 be transformer 20 is 0.4kV transformer, when transformer 20 is powered to user's voltage monitoring equipment, is
It is combined using phase a certain in A, B, C and zero curve to single-phase customer power supply.The three-phase voltage that transformer 20 exports is 400V, Yong Hujie
The voltage received is 200V, and wiring shown in Fig. 2 is schematic diagram, is not physical cabling figure and true topological diagram.With intelligence
The fining of power consumption management, wiring diagram and true topological diagram can really be reflected by specifying user's phase, be conducive to calculate split-phase line
The fine-grained management such as damage, abnormal line loss cause investigation, three-phase power balance, therefore have necessity of exploitation three-phase wiring diagram, this needs
Obtain the true phase of user's table.Exemplary diagram shown in Fig. 2 can clearly show that the affiliated phase of user.
In practical applications, first, select certain area (target area), it is assumed that there are 9 users, i.e. 9 voltages in this area
Monitoring device obtains the voltage monitoring equipment contact potential series value of 9 user's voltage monitoring equipment 2017.10.5-2017.10.19,
Every 15 minutes sampled values, each user totally 1344 sampled values, totally 9 contact potential series.When get 9 contact potential series it
Afterwards, this 9 contact potential series are filtered, i.e. the filtering of progress zero and exceptional value etc..Pair contact potential series is pre-processed, i.e.,
Filtered 9 contact potential series carry out the processing such as per unit value on the basis of 220V.
Second, the voltage value of time series using k-medoids clustering algorithm, clusters as three groups;Specific cluster
Step is identical as k-medoids clustering algorithm method mentioned above (mentioning in step S102), and details are not described herein.
The contact potential series of 9 user's voltage monitoring equipment can will be divided into three in this way by k-medoids clustering algorithm
Cluster.As shown in Fig. 2, the contact potential series of user 1, user 4 and user 7 be cluster, user 2, user 5 and user 8 contact potential series
For cluster, the contact potential series of user 3, user 6 and user 9 are cluster.The number of users of three clusters is in a basic balance, thus estimates that three clusters are used
Family load basis equalization.The contact potential series of this 9 user's voltage monitoring equipment is only divided into three clusters at present, not yet determines each cluster institute
The phase of category.
Third compares each phase voltage sequence of 20 summary table of three gathered clusters and platform area transformer, determines clustered phase
Position;The phase determination method of 9 contact potential series is identical as method mentioned above (mentioning in step S103), no longer superfluous herein
It states.Pearson correlation coefficient of the table 1 between user's cluster and summary table contact potential series, as shown in table 1:
Table 1
User U1 | User U2 | User U3 | |
Summary table UA | 0.927 | 0.998 | 0.919 |
Summary table UB | 0.978 | 0.925 | 0.923 |
Summary table UC | 0.920 | 0.920 | 0.988 |
According to the Pearson correlation coefficient between cluster and summary table contact potential series, user's U1 cluster is classified as B phase, user's U2 cluster is classified as
A phase, user's U3 cluster are classified as C phase.
It determinesAfter affiliated phase, then its corresponding user's sequence belongs to the phase, so that it is determined that each user
The phase of voltage monitoring equipment.
I.e. user 1, user 4 and user 7 belong to B phase, and user 2, user 5 and user 8 belong to A phase, user 3, user 6 and use
Family 9 belongs to C phase.Really meet with scene.
4th and computer system in pre-stored original phase be compared, determine the inconsistent target of phase
Then voltage monitoring equipment provides the recommendation opinion for working as foreground partition phase belonging to the target voltage monitoring device, and reminds work
Personnel carry out related verification.The embodiment of the present application extends 10 after the judgement of above-mentioned phase information, carries out 10 phase informations and sentence
The case where breaking, not found phase information change.Through verifying with field personnel, all users in this area (9) exist
2017.10.5-2017.10.30 work is changed without wiring during, account for voltage monitoring device phase remains unchanged, with power grid
Platform area scene truth matches.
It is described in detail above for a kind of embodiment of low-voltage network topological structure method of calibration, based on upper
The low-voltage network topological structure method of calibration for stating embodiment description, the embodiment of the invention also provides a kind of corresponding with this method
Low-voltage network topological structure calibration equipment.Since the embodiment of device part is corresponded to each other with the embodiment of method part,
Therefore the embodiment of device part please refers to the embodiment description of method part, and which is not described herein again.
Fig. 3 is a kind of low-voltage network topological structure calibration equipment composition schematic diagram provided by the embodiment of the present invention, such as
Shown in Fig. 3, which includes obtaining module 301, clustering processing module 302, comparison module 303 and determining module 304.
Module 301 is obtained, the voltage for obtaining all voltage monitoring equipment in Target Station area in default collection period is adopted
Sample data are to form contact potential series;
Clustering processing module 302, for carrying out clustering processing to contact potential series;
Comparison module 303, in the transformer monitoring terminal for comparing the contact potential series after clustering processing and Target Station area
The similarity of each phase voltage sequence is to determine belonging to voltage monitoring equipment when foreground partition phase;
Determining module 304, for determine when foreground partition phase and pre-stored original phase it is inconsistent target electricity
Monitoring device is pressed, and updates phase information of the target voltage monitoring device in low-voltage network topological structure.
A kind of low-voltage network topological structure calibration equipment provided by the present invention gets mesh in default collection period
The voltage sample data of all voltage monitoring equipment in the area Biao Tai are formed after contact potential series, are just carried out at cluster to the contact potential series
Reason, in fact just clustering contact potential series is three groups;Then again by comparing after clustering processing contact potential series and Target Station area
Transformer monitoring terminal in each phase voltage sequence similarity, it is therefore an objective to determine to work as foreground partition belonging to voltage monitoring equipment
Phase;It finally determines again when foreground partition phase and the inconsistent target voltage monitoring device of pre-stored original phase, and
Update phase information of the target voltage monitoring device in low-voltage network topological structure, that is to say, that determine that phase becomes
The target voltage monitoring device of change, and then realize the verification to low-voltage network topological structure.Therefore, which both defined
The platform area information of voltage monitoring equipment defines the phase information of each voltage monitoring equipment again, only determines in the prior art electric
The platform area information of pressure monitoring device is compared, and the verification accuracy of low-voltage network topological structure can be improved, and then be conducive to low pressure
The management of power distribution network and wastage reducing and energy saving.
On the basis of the above embodiments, preferably embodiment, clustering processing module 302 are specifically used for being based on k-
Medoids clustering algorithm carries out clustering processing to contact potential series.
It is described in detail above for a kind of embodiment of low-voltage network topological structure method of calibration, based on upper
The low-voltage network topological structure method of calibration for stating embodiment description, the embodiment of the invention also provides a kind of corresponding with this method
Low-voltage network topological structure calibration equipment.Since the embodiment of environment division is corresponded to each other with the embodiment of method part,
Therefore the embodiment of environment division please refers to the embodiment description of method part, and which is not described herein again.
Fig. 4 is a kind of low-voltage network topological structure calibration equipment composition schematic diagram provided by the embodiment of the present invention, such as
Shown in Fig. 4, which includes memory 401 and processor 402.
Memory 401, for storing computer program;
Processor 402 realizes low-voltage distribution provided by any one above-mentioned embodiment for executing computer program
The step of net topology structure method of calibration.
A kind of low-voltage network topological structure calibration equipment provided by the present invention, had both defined each voltage monitoring equipment
Platform area information define the phase information of each voltage monitoring equipment again, and only determine each voltage monitoring equipment in the prior art
Platform area information compare, can be improved the verification accuracy of low-voltage network topological structure, and then be conducive to the pipe of low-voltage network
Reason and wastage reducing and energy saving.
It is described in detail above for a kind of embodiment of low-voltage network topological structure method of calibration, based on upper
The low-voltage network topological structure method of calibration for stating embodiment description, the embodiment of the invention also provides a kind of corresponding with this method
Computer readable storage medium.Since the embodiment of computer readable storage medium part and the embodiment of method part are mutual
It is corresponding, therefore the embodiment of computer readable storage medium part please refers to the embodiment description of method part, it is no longer superfluous here
It states.
A kind of computer readable storage medium is stored with computer program, computer journey on computer readable storage medium
Sequence is executed by processor the step to realize low-voltage network topological structure method of calibration provided by any one above-mentioned embodiment
Suddenly.
A kind of computer readable storage medium provided by the present invention, processor can read in readable storage medium storing program for executing and store
Program, the low-voltage network topological structure method of calibration that above-mentioned any one embodiment provides both may be implemented, that is, determined
The platform area information of each voltage monitoring equipment defines the phase information of each voltage monitoring equipment again, and in the prior art only really
The platform area information of fixed each voltage monitoring equipment is compared, and the verification accuracy of low-voltage network topological structure, Jin Erli can be improved
Management and wastage reducing and energy saving in low-voltage network.
It is situated between above to a kind of low-voltage network topological structure method of calibration provided by the present invention, device, equipment and storage
Matter is described in detail.With several examples, principle and implementation of the present invention are described herein, the above reality
The explanation for applying example is merely used to help understand method and its core concept of the invention;Meanwhile for the general technology of this field
Personnel, according to the thought of the present invention, there will be changes in the specific implementation manner and application range, in conclusion this theory
Bright book content should not be construed as limiting the invention, those skilled in the art, under the premise of no creative work, to this
Made modification, equivalent replacement, improvement etc. are invented, should be included in the application.
It should also be noted that, in the present specification, relational terms such as first and second and the like be used merely to by
One operation is distinguished with another operation, without necessarily requiring or implying there are any between these entities or operation
This actual relationship or sequence.Moreover, the similar word such as term " includes ", so that including the unit of a series of elements, equipment
Or system not only includes those elements, but also including other elements that are not explicitly listed, or further includes for this list
Member, equipment or the intrinsic element of system.
Claims (10)
1. a kind of low-voltage network topological structure method of calibration characterized by comprising
The voltage sample data of all voltage monitoring equipment in Target Station area are obtained in default collection period to form contact potential series;
Clustering processing is carried out to the contact potential series;
Contact potential series and the phase of each phase voltage sequence in the transformer monitoring terminal in the Target Station area after comparing clustering processing
Like degree to determine belonging to the voltage monitoring equipment when foreground partition phase;
It determines described when foreground partition phase and the inconsistent target voltage monitoring device of pre-stored original phase, and updates
Phase information of the target voltage monitoring device in the low-voltage network topological structure.
2. low-voltage network topological structure method of calibration according to claim 1, which is characterized in that adopted described default
Collect and obtain the voltage sample data of all voltage monitoring equipment in Target Station area in the period to be formed after contact potential series, further includes:
Data cleansing is carried out to the contact potential series.
3. low-voltage network topological structure method of calibration according to claim 1, which is characterized in that described to the voltage
Sequence carries out clustering processing specifically:
Clustering processing is carried out to the contact potential series based on k-medoids clustering algorithm.
4. low-voltage network topological structure method of calibration according to claim 1, which is characterized in that at the relatively cluster
The similarity of each phase voltage sequence is in contact potential series after reason and the transformer monitoring terminal in the Target Station area to determine
It states belonging to voltage monitoring equipment when foreground partition phase specifically includes:
Contact potential series and the Pearson came phase of phase voltage sequence each in the transformer monitoring terminal after calculating the clustering processing
Relationship number;
It determines belonging to the voltage monitoring equipment according to the related coefficient when foreground partition phase.
5. low-voltage network topological structure method of calibration according to claim 1, which is characterized in that determine institute described
It states after foreground partition phase and pre-stored original phase inconsistent target voltage monitoring device, further includes:
Obtain the history phase of the target voltage monitoring device;
Judge the history phase with belonging to the voltage monitoring equipment determined work as foreground partition phase it is whether consistent;
If it is, characterization determine it is described when foreground partition phase it is correct;
If it is not, then characterization determine it is described when foreground partition phase it is incorrect.
6. low-voltage network topological structure method of calibration according to claim 5, which is characterized in that work as foreground partition described
When phase is correct, further includes:
Show the target voltage monitoring device works as foreground partition phase.
7. a kind of low-voltage network topological structure calibration equipment characterized by comprising
Obtain module, for obtained in default collection period the voltage sample data of all voltage monitoring equipment in Target Station area with
Form contact potential series;
Clustering processing module, for carrying out clustering processing to the contact potential series;
Comparison module, for comparing the contact potential series after clustering processing and each phase in the transformer monitoring terminal in the Target Station area
The similarity of contact potential series is to determine belonging to the voltage monitoring equipment when foreground partition phase;
Determining module, it is described when foreground partition phase and the inconsistent target voltage prison of pre-stored original phase for determining
Measurement equipment, and update phase information of the target voltage monitoring device in the low-voltage network topological structure.
8. low-voltage network topological structure calibration equipment according to claim 7, which is characterized in that the clustering processing mould
Block is specifically used for carrying out clustering processing to the contact potential series based on k-medoids clustering algorithm.
9. a kind of low-voltage network topological structure calibration equipment characterized by comprising
Memory, for storing computer program;
Processor, for executing the computer program to realize the low-voltage network as described in claim 1 to 6 any one
The step of topological structure method of calibration.
10. a kind of computer readable storage medium, which is characterized in that be stored with computer on the computer readable storage medium
Program, the computer program are executed by processor to realize that the low-voltage network as described in claim 1 to 6 any one is opened up
The step of flutterring structure method of calibration.
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Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20090040813A1 (en) * | 2007-08-10 | 2009-02-12 | Hee Bok Kang | Phase change memory device and operating method thereof |
CN106250927A (en) * | 2016-07-29 | 2016-12-21 | 国网河南省电力公司电力科学研究院 | Power distribution network topological structure method of calibration based on k arest neighbors sorting algorithm |
CN108535599A (en) * | 2018-04-16 | 2018-09-14 | 国网河南省电力公司电力科学研究院 | Low-voltage platform area user's phase recognition methods based on voltage curve clustering |
-
2018
- 2018-10-16 CN CN201811202287.0A patent/CN109325545A/en active Pending
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20090040813A1 (en) * | 2007-08-10 | 2009-02-12 | Hee Bok Kang | Phase change memory device and operating method thereof |
CN106250927A (en) * | 2016-07-29 | 2016-12-21 | 国网河南省电力公司电力科学研究院 | Power distribution network topological structure method of calibration based on k arest neighbors sorting algorithm |
CN108535599A (en) * | 2018-04-16 | 2018-09-14 | 国网河南省电力公司电力科学研究院 | Low-voltage platform area user's phase recognition methods based on voltage curve clustering |
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