CN115580010A - Topology identification method, device, equipment and storage medium for low-voltage distribution station area - Google Patents

Topology identification method, device, equipment and storage medium for low-voltage distribution station area Download PDF

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Publication number
CN115580010A
CN115580010A CN202211093380.9A CN202211093380A CN115580010A CN 115580010 A CN115580010 A CN 115580010A CN 202211093380 A CN202211093380 A CN 202211093380A CN 115580010 A CN115580010 A CN 115580010A
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sample
samples
low
sample set
singular
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叶晓君
李波
林冠强
李惠松
王晓光
陈军宏
黄俊辉
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Guangdong Power Grid Co Ltd
Huizhou Power Supply Bureau of Guangdong Power Grid Co Ltd
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Guangdong Power Grid Co Ltd
Huizhou Power Supply Bureau of Guangdong Power Grid Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00001—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00004—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by the power network being locally controlled
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
    • H02J13/00016—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment using a wired telecommunication network or a data transmission bus
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
    • H02J13/00022—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment using wireless data transmission
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
    • H02J13/00022—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment using wireless data transmission
    • H02J13/00026—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment using wireless data transmission involving a local wireless network, e.g. Wi-Fi, ZigBee or Bluetooth
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]

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  • Power Engineering (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Human Computer Interaction (AREA)
  • Remote Monitoring And Control Of Power-Distribution Networks (AREA)

Abstract

The invention discloses a topology identification method, a device, equipment and a storage medium of a low-voltage distribution area, wherein the method comprises the following steps: obtaining at least one sample set, and carrying out singular sample primary identification processing on each sample in each sample set to obtain a primary identification result; when the preliminary identification result comprises one or more suspicious samples, determining the target sample type of the suspicious samples based on clustering analysis; when the one or more suspicious samples comprise at least one singular sample, removing all singular samples from the corresponding sample set to update the sample set, wherein the type of the target sample is a normal sample or a singular sample; and carrying out feeder line identification on each current sample set, and taking the feeder line identification result as a topology identification result of the corresponding low-voltage distribution station area. The method simplifies the determining process of the low-voltage distribution area topology, and improves the speed, efficiency and accuracy of the low-voltage distribution area topology identification.

Description

Topology identification method, device, equipment and storage medium for low-voltage distribution station area
Technical Field
The invention relates to the technical field of distribution station maintenance, in particular to a topology identification method, a device, equipment and a storage medium for a low-voltage distribution station.
Background
With the development and construction of the low-voltage power distribution area, the topological relation of the low-voltage power distribution area is updated frequently, the wiring is complex, and the data volume of the low-voltage power distribution area is large. The topological relation of the low-voltage power distribution area generally refers to the connection relation between the low-voltage power distribution area and a plurality of users in the area, and the topology of the low-voltage power distribution area is determined to be favorable for power consumption management, so that management in the aspects of power personnel division, power equipment maintenance, electric quantity calculation, power line loss statistics and the like is more standard and scientific. The problems of high manual troubleshooting cost and low accuracy rate exist in the low-voltage distribution area topology identification, and the low-voltage distribution area topology is difficult to accurately identify.
At present, topology identification of a low-voltage distribution area is carried out on the basis of a monitoring framework model, but the method has the problems that the complexity of the model is high, and the topology of the low-voltage distribution area cannot be determined quickly.
Disclosure of Invention
The invention provides a topology identification method, a device, equipment and a storage medium for a low-voltage distribution area, and aims to solve the problems that the existing topology identification of the low-voltage distribution area has high model complexity and the topology of the distribution area cannot be quickly determined.
According to an aspect of the present invention, there is provided a topology identification method of a low voltage distribution substation, including:
obtaining at least one sample set, wherein the sample set comprises reference samples corresponding to voltage time series of a corresponding low-voltage power distribution station area and comparison samples corresponding to voltage time series of each user in the low-voltage power distribution station area;
performing singular sample primary identification processing on each sample in each sample set to obtain a primary identification result;
when the preliminary identification result comprises one or more suspicious samples, determining the target sample type of the suspicious samples based on clustering analysis; when one or more suspicious samples comprise at least one singular sample, removing all singular samples from a corresponding sample set to update the sample set, wherein the type of a target sample is a normal sample or a singular sample;
and carrying out feeder line identification on each current sample set, and taking the feeder line identification result as a topology identification result of the corresponding low-voltage distribution station area.
According to another aspect of the present invention, there is provided a topology recognition apparatus of a low voltage distribution substation, including:
the system comprises a preliminary identification module, a comparison module and a processing module, wherein the preliminary identification module is used for acquiring at least one sample set, and the sample set comprises a reference sample corresponding to a voltage time sequence of a corresponding low-voltage distribution area and a comparison sample corresponding to a voltage time sequence of each user in the low-voltage distribution area;
the sample type determining module is used for carrying out singular sample primary identification processing on each sample in the sample set aiming at each sample set to obtain a primary identification result; when the preliminary identification result comprises one or more suspicious samples, determining the target sample type of the suspicious samples based on clustering analysis; when the one or more suspicious samples comprise at least one singular sample, removing all singular samples from the sample set to update the sample set, wherein the type of the target sample is a normal sample or a singular sample;
and the result determining module is used for carrying out feeder line identification on the updated sample set and taking the feeder line identification result as a topology identification result of the low-voltage distribution substation area.
According to another aspect of the present invention, there is provided an electronic apparatus including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to enable the at least one processor to perform the method of topology identification of low voltage power distribution bays of any of the embodiments of the present invention.
According to another aspect of the present invention, there is provided a computer readable storage medium storing computer instructions for causing a processor to implement the topology identification method of a low voltage distribution substation of any of the embodiments of the present invention when executed.
According to the technical scheme, at least one sample set is obtained, wherein the sample set comprises a reference sample corresponding to a voltage time sequence of a low-voltage power distribution area and a comparison sample corresponding to a voltage time sequence of each user in the low-voltage power distribution area; performing singular sample primary identification processing on each sample in each sample set to obtain a primary identification result; when the preliminary identification result comprises one or more suspicious samples, determining the target sample type of the suspicious samples based on clustering analysis; when the one or more suspicious samples comprise at least one singular sample, removing all singular samples from the corresponding sample set to update the sample set, wherein the type of the target sample is a normal sample or a singular sample; and carrying out feeder line identification on each current sample set, and taking the feeder line identification result as a topology identification result of the corresponding low-voltage distribution station area. Compared with the prior art that the topology of the low-voltage power distribution area is determined through the model, the determination process of the topology of the low-voltage power distribution area is simplified through a mode of combining cluster analysis and feeder line identification, and the speed, the efficiency and the accuracy of the topology identification of the low-voltage power distribution area are improved.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present invention, nor do they necessarily limit the scope of the invention. Other features of the present invention will become apparent from the following description.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a flowchart of a topology identification method for a low-voltage distribution substation according to an embodiment of the present invention;
fig. 2 is a flowchart of a topology identification method for a low-voltage distribution area according to a second embodiment of the present invention;
fig. 3 is an initial topology diagram of a low voltage distribution area provided by the second embodiment of the present invention;
FIG. 4 is a topological diagram of an updated low-voltage distribution substation provided by a second embodiment of the present invention;
fig. 5 is a flowchart of a topology identification method for a low-voltage distribution substation according to a third embodiment of the present invention;
fig. 6 is a schematic diagram of a final topology of a low-voltage distribution area provided by a third embodiment of the present invention;
fig. 7 is a block diagram of a topology identification apparatus for a low-voltage distribution area according to a fourth embodiment of the present invention;
fig. 8 is a block diagram of an electronic device implementing the topology identification method of the low-voltage distribution substation according to the embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," "target," and the like in the description and claims of the present invention and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example one
Fig. 1 is a flowchart of a topology identification method for a low-voltage power distribution area according to an embodiment of the present invention, where the embodiment is applicable to topology identification for a low-voltage power distribution area, the method may be performed by a topology identification device for a low-voltage power distribution area, the topology identification device for a low-voltage power distribution area may be implemented in a form of hardware and/or software, and the topology identification device for a low-voltage power distribution area may be configured in an electronic device. As shown in fig. 1, the method includes:
s110, obtaining at least one sample set, wherein the sample set comprises reference samples corresponding to the voltage time series of the corresponding low-voltage power distribution station area and comparison samples corresponding to the voltage time series of each user in the low-voltage power distribution station area.
The method comprises the steps of obtaining a voltage time sequence of a low-voltage power distribution area to be identified and voltage time sequences of all users in the area, and using the voltage time sequences as a sample set, wherein the voltage time sequence of the low-voltage power distribution area to be identified is used as a reference sample, and the voltage time sequences of all users in the area are used as comparison samples.
Optionally, a plurality of sample sets may be obtained, including a voltage time series corresponding to a plurality of zones and a voltage time series corresponding to each user in the plurality of zones, for example, three sample sets may be obtained: sample set 1, sample set 2, and sample set 3, which may include:
reference sample x corresponding to voltage time sequence of station A area 0 Comparison sample x corresponding to all user voltage time series in current topology of A station area m (ii) a Wherein m is a positive integer. Reference sample y corresponding to voltage time sequence of B station area adjacent to A station area 0 Comparison sample y corresponding to all user voltage time series in current topology of B station area m . Reference sample z corresponding to C station zone voltage time series adjacent to A station zone 0 Comparison sample z corresponding to voltage time series of all users in current topology of C station area m 。
Wherein, the reference sample x of the sample set 1 0 ＝[x 0 (1)，x 0 (2)，…，x 0 (i m1 )]Comparative sample x of sample set 1 m ＝[x m (1)，x m (2)，…，x m (i m1 )]，i m1 Is the sample size of the reference sample of sample set 1, m1 is a positive integer; reference sample y of sample set 2 0 ＝[y 0 (1)，y 0 (2)，…，y 0 (i m2 )]Comparative sample y of sample set 2 m ＝[y m (1)，y m (2)，…，y m (i m2 )]，i m2 Is the sample size of the reference sample of sample set 2, m2 is a positive integer; reference sample z of sample set 3 0 ＝[z 0 (1)，z 0 (2)，…，z 0 (i m3 )]Comparative sample z of sample set 3 m ＝[z m (1)，z m (2)，…，z m (i m3 )]，i m3 Is the sample size of the reference sample of sample set 3, m3 is a positive integer; obtaining the reference sample and the comparison sample is the basic condition for performing the preliminary identification process.
And S120, performing singular sample preliminary identification processing on each sample in each sample set to obtain a preliminary identification result.
The singular samples are voltage time sequences of users with wrong topological relations in the low-voltage distribution station area.
Because the difference of each sample in the sample set is large, in order to facilitate the preliminary identification processing of singular samples, the sample set is subjected to initialization processing so as to update the sample set.
In particular, reference sample x for sample set 1 0 Performing initialization processing to obtain updated reference sample, specifically x' 0 ＝x 0 /x 0 (1) Performing initialization processing on the ith comparison sample of the sample set 1 to update the comparison sample, specifically x' i ＝[x i (k)/x i (1)]Wherein k =1,2, \8230, n, n is the length of the voltage time series of the user, and the corresponding sample set is updated by the updated reference sample and the updated comparison sample.
And performing singular sample primary identification processing on the updated sample set, and determining whether suspicious samples exist in each sample set of the primary identification processing result.
S130, when the primary identification result comprises one or more suspicious samples, determining the target sample type of the suspicious samples based on cluster analysis; when the one or more suspicious samples comprise at least one singular sample, all singular samples are removed from the corresponding sample set to update the sample set, wherein the target sample type is a normal sample or a singular sample.
It can be understood that when the preliminary singular sample identification result includes one or more suspicious samples, whether the suspicious samples are singular samples or not needs to be further identified through cluster analysis, if the cluster analysis result indicates that the suspicious samples are singular samples, the singular samples need to be removed, and the corresponding sample set is updated to update the topology of the corresponding low-voltage distribution station area; and if the cluster analysis result shows that the suspicious sample is a normal sample, the corresponding sample set is not updated, and the topology of the corresponding low-voltage distribution area is not updated.
Where cluster analysis attempts to classify samples in a data set into several different classes or sets, each set being called a "cluster", by means of a clustering algorithm, the same cluster may correspond to some potential concepts or categories, with samples in the same cluster having great similarity and samples between different clusters having great dissimilarity. Clustering analysis is an exploratory analysis, which can automatically classify samples based on the sample data. And carrying out clustering analysis on the same group of data aiming at different clustering purposes, wherein the obtained clustering results are not necessarily consistent.
Specifically, determining the target sample type of the suspicious sample based on the cluster analysis includes:
step a1: one or more suspect samples are removed from the sample set to update the sample set.
In order to determine the target sample type of the suspicious sample through cluster analysis, the suspicious sample in the sample set needs to be removed first to update the sample set, and the updated sample set does not contain the suspicious sample.
Step a2: and aiming at each suspicious sample, performing cluster analysis on the updated sample set by taking the low-voltage distribution station area as a class center, and if the class center in the clustering result is not changed due to the addition of the suspicious sample, taking the suspicious sample as a normal sample, otherwise, taking the suspicious sample as a singular sample.
Specifically, in order to further identify the suspicious sample, a reference sample of a sample set corresponding to the suspicious sample is used as a class center, the updated sample set is subjected to cluster analysis, euclidean distances between the class center and all comparison samples in the corresponding sample set are calculated, then the suspicious sample is added into the current sample set for clustering again, and if the class center does not change, the suspicious sample is indicated to be a normal sample; if the class center changes, it indicates that the suspicious sample does not belong to the class, that is, the user does not belong to the low-voltage distribution area.
Further, after S130, the method further includes: when one or more suspicious samples do not include singular samples, keeping the corresponding sample set unchanged.
It will be appreciated that when one or more of the suspect samples do not include singular samples, the sample set does not include singular samples, thus leaving the corresponding sample set unchanged.
And S140, carrying out feeder line identification on each current sample set, and taking the feeder line identification result as a topology identification result of the corresponding low-voltage distribution transformer area.
The feeder line identification principle is as follows: the voltage is gradually reduced along with the feeder line, so that the position of a user in the feeder line of the low-voltage distribution station area can be more accurately positioned. And feeder line identification can be carried out on each current sample set according to the absolute correlation of the two comparison samples of the corresponding low-voltage distribution station area in the current sample set.
It can be understood that after the identification of the low-voltage distribution area corresponding to the user is completed, the topology of the low-voltage distribution area needs to be further identified by feeder connection, the sample set without the singular sample needs to be subjected to feeder identification, the topology of the low-voltage distribution area is further determined, and a feeder identification result is obtained and is used as the topology identification result of the corresponding low-voltage distribution area.
Further, after S130, the method further includes: and performing cluster analysis on all the sample sets, adding the singular samples to the sample set corresponding to the class center closest to the singular samples to update the corresponding sample set, and returning to the step of performing singular sample primary identification processing on each sample in each sample set to obtain a primary identification result.
The step is to determine a sample set corresponding to a low-voltage distribution area to which the eliminated singular samples belong, determine whether singular samples exist in the sample set according to the topology identification method for the low-voltage distribution area described in the foregoing embodiment, perform feeder line identification on the sample set when the sample set does not include the singular samples to obtain topology identification results corresponding to the sample set, and perform feeder line identification on the sample set from which the corresponding singular samples are eliminated to obtain topology identification results corresponding to the sample set when the sample set includes the singular samples.
According to the technical scheme, at least one sample set is obtained, wherein the sample set comprises a reference sample corresponding to a voltage time sequence of a low-voltage power distribution area and a comparison sample corresponding to a voltage time sequence of each user in the low-voltage power distribution area; performing singular sample primary identification processing on each sample in each sample set to obtain a primary identification result; when the preliminary identification result comprises one or more suspicious samples, determining the target sample type of the suspicious samples based on clustering analysis; when the one or more suspicious samples comprise at least one singular sample, removing all singular samples from the corresponding sample set to update the sample set, wherein the type of the target sample is a normal sample or a singular sample; and carrying out feeder line identification on each current sample set, and taking the feeder line identification result as a topology identification result of the corresponding low-voltage distribution station area. The method simplifies the determining process of the low-voltage distribution station topology, and improves the speed, efficiency and accuracy of the low-voltage distribution station topology identification.
Example two
Fig. 2 is a flowchart of a topology identification method for a low-voltage distribution substation area according to a second embodiment of the present invention, where the preliminary identification processing of singular samples is optimized and expanded based on the foregoing embodiment, and may be combined with various optional technical solutions in the foregoing embodiment, as shown in fig. 2, the method may include:
s210, at least one sample set is obtained, wherein the sample set comprises reference samples corresponding to the voltage time series of the corresponding low-voltage power distribution station area and comparison samples corresponding to the voltage time series of each user in the low-voltage power distribution station area.
In a specific embodiment, fig. 3 is an initial topology diagram of a low voltage distribution substation provided in the second embodiment of the present invention, where the low voltage distribution substation 100 includes: a first user 200 of the low voltage distribution substation 100, a second user 300 of the low voltage distribution substation 100, a third user 400 of the low voltage distribution substation 100, a fourth user 500 of the low voltage distribution substation 100, a fifth user 600 of the low voltage distribution substation 100, and a sixth user 700 of the low voltage distribution substation 100.
S2201, determining the absolute correlation degree of the reference sample and each comparison sample in each sample set.
Wherein the absolute correlation represents the correlation between the degree of change of the reference sample and each of the comparison samples at the corresponding time points. The calculation steps of the absolute correlation are as follows:
voltage difference value deltax of each sample in sample set i (k) The calculation formula of (c):
Δx i (k)＝x i (k+1)-x i (k)，k＝1，2，…，n-1，i＝0，1，2，…，m
correlation coefficient delta between reference sample and comparison sample xi The calculation formula of (2):
Figure BDA0003837915820000091
absolute degree of correlation mu between reference sample and comparison sample xi The calculation formula of (2):
Figure BDA0003837915820000092
s2202, determining a preliminary identification result of the sample set according to the magnitude relation between the absolute correlation corresponding to each comparison sample and a first set threshold.
The first set threshold is a threshold set to determine whether there is a user who does not belong to the low-voltage distribution grid topology among all users of the current low-voltage distribution grid, and may be 0.5, for example.
Further, S2202 includes the steps of:
step b1: and if the absolute correlation degree corresponding to the comparison sample is less than or equal to a first set threshold value, taking the comparison sample as a suspicious sample.
It is understood that if the absolute correlation corresponding to the comparison sample is less than or equal to the first set threshold, the comparison sample may not belong to the sample set, and the comparison sample is regarded as a suspicious sample.
Step b2: and if the absolute correlation corresponding to the comparison sample is greater than a first set threshold, taking the comparison sample as a normal sample.
It can be understood that, if the absolute correlation corresponding to the comparison sample is greater than the first set threshold, it indicates that the comparison sample belongs to the sample set, and the comparison sample is regarded as a normal sample.
And b3, taking the initial sample types of all the comparative samples as a primary identification result, wherein the initial sample types are suspicious samples or normal samples.
For any sample set, the preliminary identification result includes one or more suspicious samples and/or one or more normal samples, and specifically includes one or more suspicious comparative samples and/or normal comparative samples.
In a specific embodiment, fig. 3 is an initial topological diagram of the low voltage distribution substation provided in the second embodiment of the present invention, an absolute correlation between each voltage time series of the user in the low voltage distribution substation 100 and the voltage time series of the low voltage distribution substation 100 is calculated, an average value of the absolute correlations of all the users is used as a first set threshold, an absolute correlation between the voltage time series of the user six 700 and the voltage time series of the low voltage distribution substation 100 is lower than the first set threshold, and a comparison sample corresponding to the voltage time series of the user six 700 is a suspicious sample.
S230, when the primary identification result comprises one or more suspicious samples, determining the target sample type of the suspicious samples based on cluster analysis; and when the one or more suspicious samples comprise at least one singular sample, removing all singular samples from the corresponding sample set to update the sample set, wherein the type of the target sample is a normal sample or a singular sample.
The cluster analysis method includes many methods, such as a K-means algorithm (K-means clustering algorithm), a KNN algorithm (proximity algorithm), an LVQ algorithm (learning vector quantization algorithm), a DBSCAN algorithm (density clustering algorithm), and a gaussian mixture model. In a specific embodiment, in order to further determine whether the suspicious sample comprises a singular sample, a K-means algorithm is adopted for clustering, the reference sample is used as a class center, and the euclidean distance between each comparison sample in the corresponding sample set and the reference sample is calculated.
The K-means algorithm is a typical unsupervised learning algorithm and is a clustering analysis algorithm which is solved by iteration, data are divided into K groups in advance, K objects are randomly selected to serve as initial clustering centers, then the distance between each object and each initial class center is calculated, and each object is assigned to the initial class center closest to the object. The class centers and the objects assigned to them represent a cluster. For each sample assigned, the class center is recalculated based on the existing objects in the cluster. This process will be repeated until some termination condition is met. The termination condition may be that no (or a minimum number) of objects are reassigned to different clusters, and no (or a minimum number) of class centers are changed.
Specifically, each object is assigned to the initial class center closest to the object for distance measurement, and common distance measurements include euclidean distance, manhattan distance, cosine similarity, and the like. Taking the euclidean distance as an example, the euclidean distance formula is:
Figure BDA0003837915820000111
wherein the content of the first and second substances,
Figure BDA0003837915820000112
and calculating the Euclidean distance between each comparison sample in the updated sample set and the reference sample for the clustering center, and adding each comparison sample to the classification of the reference sample.
In a specific embodiment, fig. 3 is an initial topology schematic diagram of low-voltage power distribution provided by the second embodiment of the present invention, where a user six 700 of the low-voltage power distribution area 100 in fig. 3 is a suspicious sample, the user six 700 is removed from the sample set of the low-voltage power distribution area 100, and the sample set is updated, and fig. 4 is a topology schematic diagram of an updated low-voltage power distribution area provided by the second embodiment of the present invention, where the updated low-voltage power distribution area 100 topology does not contain the user six 700. Taking a reference sample corresponding to the low-voltage distribution area 100 as a class center, performing cluster analysis on the updated sample set, calculating Euclidean distances between the class center and a comparison sample corresponding to a voltage time sequence of each user in the low-voltage distribution area 100, adding a suspicious sample into the current sample set, clustering again, and removing the user six 700 from the topology of the low-voltage distribution area 100 if the class center changes, which indicates that the suspicious sample user six 700 does not belong to the class, namely the user six 700 does not belong to the low-voltage distribution area. Fig. 4 is a schematic topology diagram of an updated low-voltage distribution substation provided in the second embodiment of the present invention.
And S240, carrying out feeder line identification on each current sample set, and taking the feeder line identification result as a topology identification result of the corresponding low-voltage distribution station area.
According to the technical scheme of the embodiment of the invention, the singular sample is preliminarily identified and processed by determining the absolute correlation degree between the reference sample in each sample set and each comparison sample. Singular samples of each sample set can be rapidly identified, and the efficiency of topology identification of the low-voltage distribution substation area is improved.
EXAMPLE III
Fig. 5 is a flowchart of a topology identification method for a low-voltage distribution substation according to a third embodiment of the present invention. Based on the foregoing embodiment, the feeder line identification is further optimized and expanded, and may be combined with various optional technical solutions in the foregoing embodiment, as shown in fig. 5, the method includes:
s310, obtaining at least one sample set, wherein the sample set comprises reference samples corresponding to the voltage time series of the corresponding low-voltage power distribution station area and comparison samples corresponding to the voltage time series of each user in the low-voltage power distribution station area.
And S320, performing singular sample preliminary identification processing on each sample in each sample set to obtain a preliminary identification result.
S330, when the primary identification result comprises one or more suspicious samples, determining the target sample type of the suspicious samples based on cluster analysis; and when the one or more suspicious samples comprise at least one singular sample, removing all singular samples from the corresponding sample set to update the sample set, wherein the type of the target sample is a normal sample or a singular sample.
And S3401, if the absolute value of the difference between the absolute correlation degrees corresponding to the two comparison samples is greater than the set feeder threshold, determining that the feeder relationship between the two comparison samples is wrong.
Wherein, the absolute correlation degrees corresponding to every two comparison samples are u 0i And u 0j Absolute correlation corresponding to two-by-two comparison samplesAbsolute value of the difference a ij Comprises the following steps:
a ij ＝|u 0i -u 0j |
the set feeder threshold is a threshold set for determining whether the connection relationship of the feeder between the current low-voltage distribution area users is wrong, and an average value of absolute correlation difference values between each user in the area corresponding to each current sample set is used as the set feeder threshold, and may be, for example, 0.5.
The calculation formula for setting the feeder threshold t is as follows:
Figure BDA0003837915820000131
wherein p is the total number of target combinations, and the target combinations are the combinations of two comparative samples.
Further, the difference absolute value a of the absolute correlation corresponding to the two comparison samples is utilized ij Performing feeder line identification, and when a corresponding to two comparison samples is identified ij And if the comparison result is larger than the set feeder threshold t corresponding to the sample set, judging that the feeder relation between every two comparison samples is wrong. Further identification is required.
S3402, determining the difference absolute value of the absolute correlation degree between each two comparison samples and other comparison samples in the sample set to obtain a difference absolute value set; and determining a minimum difference absolute value in the difference absolute value set, and when the minimum difference absolute value is less than or equal to a set feeder line threshold, connecting the comparison sample to another comparison sample corresponding to the minimum difference absolute value so as to update the feeder line relation among the samples in the current sample set.
In order to further determine the feeder relationship of the comparison sample, it is necessary to determine a difference absolute value of absolute correlation between the comparison sample and other comparison samples in the sample set, determine a minimum difference absolute value of the absolute correlation, and determine whether the minimum difference absolute value is less than or equal to a set feeder threshold, and when the minimum difference absolute value is less than or equal to the set feeder threshold, connect the comparison sample with another comparison sample corresponding to the minimum difference absolute value, and update the feeder relationship of each sample in the corresponding sample set.
In a specific embodiment, fig. 4 is a schematic topology diagram of an updated low-voltage distribution substation provided in the second embodiment of the present invention. The feeder identification is carried out on the low-voltage distribution area 100, the absolute value of the difference of the absolute correlation degrees between every two users is calculated, after the absolute value of the difference of all the absolute correlation degrees is obtained, the absolute value of the difference of all the absolute correlation degrees is added and then divided by the target combination number of the users to obtain a set feeder threshold, the magnitude relation between the absolute value of the difference of all the absolute correlation degrees and the set feeder threshold is compared, the absolute value of the difference of the absolute correlation degrees of the first user 200 and the fifth user 600 is obtained and is larger than the set feeder threshold, the feeder relation is wrong, the absolute value of the difference of the absolute correlation degrees of the fifth user 600 and the fourth user 500 is determined, the absolute value of the difference of the absolute correlation degrees of the fifth user 600 and the fourth user 500 is obtained and is the minimum absolute value, and the minimum value is smaller than the set feeder threshold, so the fifth user 600 is connected with the fourth user 500, and the feeder relation of the low-voltage distribution area 100 is updated.
And S3403, taking the feeder line relation among the samples in the updated current sample set as a topology identification result of the corresponding low-voltage power distribution station area.
It can be understood that the feeder line relationship between the reference sample and the comparison sample in the updated current sample set is used as the topology identification result of the corresponding low-voltage distribution station area.
In a specific embodiment, fig. 6 is a schematic diagram of a final topology of the updated low-voltage distribution substation 100 provided in the third embodiment of the present invention, and a feeder relationship of the updated low-voltage distribution substation 100 is used as a result of topology identification of the low-voltage distribution substation 100.
According to the technical scheme of the embodiment of the invention, feeder identification is carried out on the feeder relation between every two comparison samples through the relation between the absolute value of the difference value between the absolute correlation degrees corresponding to every two comparison samples and the set feeder threshold. The position of a user in the feeder line to which the user belongs can be determined more accurately, and the accuracy of topology identification of the low-voltage distribution area is improved.
Example four
Fig. 7 is a block diagram of a topology identification apparatus for a low-voltage distribution substation according to a fourth embodiment of the present invention. As shown in fig. 7, the apparatus includes:
the preliminary identification module 201 is configured to obtain at least one sample set, where the sample set includes a reference sample corresponding to a voltage time series of a corresponding low-voltage distribution area and a comparison sample corresponding to a voltage time series of each user in the low-voltage distribution area.
The sample type determining module 202 is configured to perform, for each sample set, preliminary singular sample identification processing on each sample in the sample set to obtain a preliminary identification result; when the preliminary identification result comprises one or more suspicious samples, determining the target sample type of the suspicious samples based on clustering analysis; when the one or more suspicious samples comprise at least one singular sample, removing all singular samples from the sample set to update the sample set, wherein the target sample type is a normal sample or a singular sample.
And the result determining module 203 is configured to perform feeder line identification on the updated sample set, and use a feeder line identification result as a topology identification result of the low-voltage distribution area.
Optionally, the sample type determining module 202 is further configured to:
removing one or more suspicious samples from the sample set to update the sample set;
and aiming at each suspicious sample, performing cluster analysis on the updated sample set by taking the low-voltage distribution station area as a class center, and if the class center in the clustering result is not changed due to the addition of the suspicious sample, taking the suspicious sample as a normal sample, otherwise, taking the suspicious sample as a singular sample.
Optionally, the sample type determining module 202 is further configured to:
determining the absolute correlation degree of the reference sample and each comparison sample in each sample set;
and determining the preliminary identification result of the sample set according to the magnitude relation between the absolute correlation corresponding to each comparison sample and the first set threshold.
Optionally, the sample type determining module 202 is further configured to:
if the absolute correlation degree corresponding to the comparison sample is smaller than or equal to a first set threshold, taking the comparison sample as a suspicious sample;
if the absolute correlation degree corresponding to the comparison sample is larger than a first set threshold, taking the comparison sample as a normal sample;
and taking the initial sample types of all the comparison samples as the initial identification result, wherein the initial sample types are suspicious samples or normal samples.
Optionally, the sample type determining module 202 is further configured to:
if the absolute value of the difference between the absolute correlation degrees corresponding to every two comparison samples is larger than the set feeder threshold, judging that the feeder relation between every two comparison samples is wrong;
determining the difference absolute value of the absolute correlation degree between each comparison sample and other comparison samples in the sample set to obtain a difference absolute value set; determining a minimum difference absolute value in the difference absolute value set, and when the minimum difference absolute value is less than or equal to a set feeder line threshold value, connecting the comparison sample to another comparison sample corresponding to the minimum difference absolute value to update the feeder line relation among the samples in the current sample set;
and taking the updated feeder line relation among the samples in the current sample set as a topology identification result of the corresponding low-voltage distribution station area.
Optionally, the sample type determining module 202 is further configured to: when one or more suspect samples do not include singular samples, the corresponding sample set is kept unchanged.
Optionally, the sample type determining module 202 is further configured to: and performing cluster analysis on all the sample sets, adding the singular samples to the sample set corresponding to the class center closest to the singular samples to update the corresponding sample set, and returning to the step of performing singular sample primary identification processing on each sample in each sample set to obtain a primary identification result.
According to the technical scheme of the embodiment, at least one sample set is obtained through mutual matching of the modules, wherein the sample set comprises a reference sample corresponding to a voltage time sequence of a corresponding low-voltage power distribution station area and a comparison sample corresponding to a voltage time sequence of each user in the low-voltage power distribution station area; performing singular sample primary identification processing on each sample in each sample set to obtain a primary identification result; when the primary identification result comprises one or more suspicious samples, determining the target sample type of the suspicious samples based on cluster analysis; when the one or more suspicious samples comprise at least one singular sample, removing all singular samples from the corresponding sample set to update the sample set, wherein the type of the target sample is a normal sample or a singular sample; and carrying out feeder line identification on each current sample set, and taking the feeder line identification result as a topology identification result of the target low-voltage distribution station area. The method simplifies the determining process of the low-voltage distribution station topology, and improves the speed, efficiency and accuracy of the low-voltage distribution station topology identification.
The topology identification device for the low-voltage power distribution area, provided by the embodiment of the invention, can execute the topology identification method for the low-voltage power distribution area, provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
EXAMPLE five
Fig. 8 is a block diagram of an electronic device 10 implementing the topology identification method of the low voltage power distribution substation of the present embodiment, the electronic device being intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 8, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, and the like, wherein the memory stores a computer program executable by the at least one processor, and the processor 11 can perform various suitable actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from a storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data necessary for the operation of the electronic apparatus 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
A number of components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, or the like; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, or the like. The processor 11 performs the various methods and processes described above, such as a method of topology identification of low voltage distribution substations.
In some embodiments, a method of topology identification of a low voltage distribution substation may be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, it may perform one or more steps of a method for topology identification of low voltage distribution substations of the kind described above. Alternatively, in other embodiments, the processor 11 may be configured by any other suitable means (e.g., by means of firmware) to perform a topology identification method of low voltage distribution substations.
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be performed. A computer program can execute entirely on a machine, partly on a machine, as a stand-alone software package partly on a machine and partly on a remote machine or entirely on a remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user may provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service are overcome.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present invention may be executed in parallel, sequentially, or in different orders, and are not limited herein as long as the desired results of the technical solution of the present invention can be achieved.
The above-described embodiments should not be construed as limiting the scope of the invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. A topology identification method of a low-voltage distribution area is characterized by comprising the following steps:
obtaining at least one sample set, wherein the sample set comprises reference samples corresponding to voltage time series of a corresponding low-voltage power distribution station area and comparison samples corresponding to voltage time series of each user in the low-voltage power distribution station area;
performing singular sample preliminary identification processing on each sample in each sample set to obtain a preliminary identification result;
when the preliminary identification result comprises one or more suspicious samples, determining the target sample type of the suspicious samples based on cluster analysis; when the one or more suspicious samples comprise at least one singular sample, removing all singular samples from a corresponding sample set to update the sample set, wherein the target sample type is a normal sample or a singular sample;
and carrying out feeder line identification on each current sample set, and taking the feeder line identification result as a topology identification result of the corresponding low-voltage distribution station area.
2. The method of claim 1, wherein the determining a target sample type for the suspicious sample based on cluster analysis comprises:
removing the one or more suspect samples from the sample set to update the sample set;
and aiming at each suspicious sample, performing cluster analysis on the updated sample set by taking the low-voltage distribution area as a class center, and if the class center in the clustering result cannot be changed due to the addition of the suspicious sample, taking the suspicious sample as a normal sample, otherwise, taking the suspicious sample as a singular sample.
3. The method according to claim 1, wherein the performing singular sample preliminary identification processing on each sample in the sample set to obtain a preliminary identification result comprises:
determining an absolute correlation of the reference sample with each comparison sample in each of the sample sets;
and determining the preliminary identification result of the sample set according to the magnitude relation between the absolute correlation degree corresponding to each comparison sample and a first set threshold value.
4. The method according to claim 3, wherein the determining the preliminary identification result of the sample set according to the magnitude relationship between the absolute correlation corresponding to each comparison sample and the first set threshold comprises:
if the absolute correlation degree corresponding to the comparison sample is smaller than or equal to a first set threshold, taking the comparison sample as a suspicious sample;
if the absolute correlation corresponding to the comparison sample is larger than a first set threshold, taking the comparison sample as a normal sample;
and taking the initial sample types of all the comparison samples as the initial identification result, wherein the initial sample types are suspicious samples or normal samples.
5. The method of claim 1, wherein the performing feeder line identification on each current sample set and using the feeder line identification result as a topology identification result of a corresponding low-voltage distribution area comprises:
if the absolute value of the difference between the absolute correlation degrees corresponding to every two comparison samples is larger than the set feeder threshold, judging that the feeder relation between every two comparison samples is wrong;
determining the difference absolute value of the absolute correlation degree between each comparison sample and other comparison samples in the sample set to obtain a difference absolute value set; determining a minimum difference absolute value in the difference absolute value set, and when the minimum difference absolute value is less than or equal to a set feeder line threshold, connecting the comparison sample to another comparison sample corresponding to the minimum difference absolute value to update a feeder line relation among samples in the current sample set;
and taking the updated feeder line relation among the samples in the current sample set as a topology identification result of the corresponding low-voltage distribution station area.
6. The method according to claim 1, wherein after determining a target sample type of the suspicious sample based on cluster analysis when the preliminary identification result includes one or more suspicious samples, the method further comprises:
when the one or more suspicious samples do not include singular samples, keeping the corresponding sample set unchanged.
7. The method of claim 6, wherein after removing all singular samples from the corresponding sample set to update the sample set when the one or more suspicious samples include singular samples, further comprising:
and performing cluster analysis on all sample sets, adding the singular samples to the sample set corresponding to the class center closest to the singular samples to update the corresponding sample sets, and returning to the step of performing singular sample primary identification processing on each sample in each sample set to obtain a primary identification result.
8. A topology identification device of a low voltage distribution substation, comprising:
the system comprises a preliminary identification module, a comparison module and a processing module, wherein the preliminary identification module is used for acquiring at least one sample set, and the sample set comprises reference samples corresponding to voltage time sequences of a corresponding low-voltage distribution area and comparison samples corresponding to voltage time sequences of each user in the low-voltage distribution area;
the sample type determining module is used for carrying out singular sample primary identification processing on each sample in the sample set aiming at each sample set to obtain a primary identification result; when the preliminary identification result comprises one or more suspicious samples, determining the target sample type of the suspicious samples based on cluster analysis; when the one or more suspicious samples comprise at least one singular sample, removing all singular samples from the sample set to update the sample set, wherein the target sample type is a normal sample or a singular sample;
and the result determining module is used for carrying out feeder line identification on the updated sample set and taking the feeder line identification result as a topology identification result of the low-voltage distribution substation area.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein, the first and the second end of the pipe are connected with each other,
the memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to enable the at least one processor to perform the method of topology identification of low voltage power distribution bays of any one of claims 1-7.
10. A computer-readable storage medium, characterized in that it stores computer instructions for causing a processor to carry out, when executed, the method of topology identification of low voltage distribution substations according to one of claims 1 to 7.
CN202211093380.9A 2022-09-08 2022-09-08 Topology identification method, device, equipment and storage medium for low-voltage distribution station area Pending CN115580010A (en)

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