CN113033666A - Transformer area household change identification method integrating acquisition service and load design rule - Google Patents
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Abstract
The invention belongs to the field of power topology big data analysis, and particularly relates to a transformer substation area outdoor transformer identification method fusing acquisition service and load design rules. The method comprises the following steps: s1: acquiring a district acquisition file and district user branch data; s2: establishing a collection topology analysis model; s3: analyzing the collection outliers, the measurement point outliers, the metering point outliers and the collection outliers based on the user branches by using a collection topological analysis model, and diagnosing the outliers and the cross-mining conditions; s4: and outputting the analysis result according to a standard output format. The invention realizes the station area user change identification by using a situation outlier data analysis method of data analysis and combining the collection service rule and the user load design rule of the power utilization information collection system. The data analysis method is improved in accordance with the power grid service, so that reasonable special cases or rules are allowed to be introduced into the actual power grid service, the use of devices such as collectors is reduced, the cost is reduced, and the working efficiency is improved.
Description
Technical Field
The invention belongs to the field of power topology big data analysis, and particularly relates to a transformer substation area outdoor transformer identification method fusing acquisition service and load design rules.
Background
A power user electricity utilization information acquisition system (power user electricity utilization data acquisition system) is a system for acquiring, processing and monitoring electricity utilization information such as the electricity, voltage and current of a user electric energy meter in real time through an acquisition terminal. Because the acquisition system is constructed on the basis of the actual power supply network, the acquisition is completed according to the power supply area in a centralized manner during construction, and the user information is generally completed in batches synchronously, a certain association relationship exists between the topological information generated by the acquisition of the transformer area and the user, the acquisition archive information and the actual power supply network topology.
The collection of power consumption information has multiple collection modes such as full carrier collection, half-load collection (carrier +485), 485 collection, micropower wireless mode and the like, and different collection modes have different influence degrees on the consistency of collection topology and power supply topology. The communication channel of the full-load mode is a power line, the consistency degree of the acquisition topology and the power supply topology is highest, the communication channels of the 485 mode and the micropower wireless mode are irrelevant to the power line, whether the acquisition of a certain acquisition terminal is related to the distance between the electric energy meter and whether a building covers the electric energy meter or not is judged, and the consistency of the acquisition topology and the power supply topology is lowest.
In a given dataset, one data object is a context outlier that deviates significantly from other objects if the particular context for the object is concerned. Context outliers are also referred to as conditional outliers because their condition depends on the selected context. In identifying the user variation by using the context outlier, the specifically selected context may be a combination of 2 or 3 of 3 conditions that the user is collected by a certain collection terminal, the user belongs to a certain user branch, and the user belongs to a certain station area.
In the existing scheme for identifying the user change through acquisition, the automatic identification of the home region of the user meter can be generally carried out through the characteristic that whether a certain phase of a voltage zero-crossing time acquisition terminal and a phase electric energy meter carrier command synchronously cross zero or not. The principle is that when load current reaches a user through a power supply line, voltage amplitude and phase change can be caused inevitably due to impedance of the power supply line, a carrier module collects power utilization information of the user electric energy meter, and communication between a collection terminal and the electric energy meter is realized by superposing carrier signals in a 3.3ms interval of voltage zero-crossing time. Due to the different loads of the stations, an offset value, which is generally larger than 150us, exists between the phases of the same-phase voltages of different stations.
In the existing scheme of realizing station-area outdoor transformer identification by relying on a collection carrier module, because the scheme relies on equipment, if the quality of the equipment is not over, or manufacturers of electric energy meter concentrators are not the same, the accuracy of outdoor transformer identification is limited, and meanwhile, when phase offsets of different station areas do not reach a threshold value or signal interference exists, an identification error may exist in an outdoor transformer.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides the station area subscriber identity change identification method which integrates the acquisition service and the load design rule, does not depend on equipment and does not need to carry out new equipment investment or upgrade.
The invention is a station area user change identification method which is realized in the way and integrates the collected service and the load design rule, and is characterized in that: the method comprises the following steps:
s1: acquiring a district acquisition file and district user branch data;
s2: establishing a collection topology analysis model according to the archive data and the station area user branch data;
s3: analyzing the collection outliers, the measurement point outliers, the metering point outliers and the collection outliers based on the user branches by using a collection topological analysis model, and diagnosing the outliers and the cross-mining conditions;
s4: and outputting the analysis result of the acquisition topology analysis model according to a standard output format.
The S1 performs the previous diagnosis of the neighboring station area through the analysis of the archival data.
The adjacent station area data comprises the name adjacent of the station area, the user profile data of the adjacent acquisition and/or power supply and distribution and whether the user table is successfully acquired.
The acquisition outlier refers to the situation that one acquisition terminal acquires 2 electric energy meters in the transformer area, and if the number of user meters in one terminal acquisition transformer area a and the number of user meters in one terminal acquisition transformer area b are greatly different, the difference is marked as k, users with small number can be regarded as outlier users.
The measurement point outlier means that due to technical or human factors, power utilization information of the electric energy meter is successfully collected, but the affiliation relationship of the electric energy meter and the station area is wrong, no more than 2 outlier measurement points belonging to the station area b appear in incremental numbers, and the station areas of the measurement points before and after the outlier measurement points are the station area a.
The metering point outlier refers to that a user belonging to another station area appears in regular acquisition point number belonging to one station area, so that the possibility of error of the station area change relationship is very high, and the probability of the user belonging to the station area is very high.
The collection outlier based on the user branch means that in the user branch formed by a plurality of users, metering points of the user branch may not present regularity characteristics, but due to the technical limitation of a collection mode, the electricity utilization information of the users of the same user branch is successfully collected by a plurality of collection terminals, and the terminals may belong to different transformer areas; the dual power supply user branch, because 2 measurement points are together, when building the collection network, in order to save the cost, 2 measurement points that have this user all gather by 1 collection terminal, above-mentioned 2 kinds of condition all should diagnose for striding and adopt, but not the house change mistake.
The invention has the advantages and positive effects that: the invention utilizes a situation outlier data analysis method of data analysis, combines an acquisition service rule and a user load design rule of an electricity information acquisition system, introduces an adjacent station concept, provides 3 adjacent station classification rules, provides 4 methods of acquisition outlier, measurement point outlier and acquisition outlier based on user branches, and can realize station area diversity identification through a data analysis mode.
The data analysis method is improved in accordance with the power grid service, so that reasonable special cases or rules are allowed to be introduced into the actual power grid service, the use of devices such as collectors is reduced, the cost is reduced, and the working efficiency is improved.
Drawings
FIG. 1 is a block flow diagram of the present invention;
FIG. 2 is a waveform diagram of zero-crossing synchronous transmission of carrier waves in the background of the invention;
FIG. 3 is a diagram of a zero crossing phase shift waveform in the background of the invention;
FIG. 4 is a schematic view of the user classification of the present invention;
FIG. 5 is a schematic diagram of the acquisition proximity and power supply and distribution design proximity of the present invention;
FIG. 6 is a schematic diagram of outliers of the present invention;
FIG. 7 is a block diagram of the subscriber identity module of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments.
Example 1:
as shown in fig. 1, the present invention is implemented as such, and a method for identifying station subscriber variation fusing acquisition service and load design rule includes the following steps:
s1: acquiring a district acquisition file and district user branch data;
s2: establishing a collection topology analysis model according to the archive data and the station area user branch data;
s3: analyzing the collection outliers, the measurement point outliers, the metering point outliers and the collection outliers based on the user branches by using a collection topological analysis model, and diagnosing the outliers and the cross-mining conditions;
s4: and outputting the analysis result of the acquisition topology analysis model according to a standard output format.
S1 performs the previous diagnosis of the neighboring station area through the analysis of the archival data.
The neighbor cell data includes cell name neighbor, acquisition neighbor, and/or power supply neighbor cell grouping data.
Since the household error generally occurs in the adjacent station area, when data analysis is carried out, the concept of the adjacent station area is introduced, including the name adjacency of the station area, the acquisition adjacency and the power supply and distribution adjacency.
In the power supply design of the transformer area, the power supply transformer of the transformer area is used as 10 kilovolt power distribution equipment, the naming rules thereof need to be complied with, such as 10kVABC-1 power distribution transformer and 10kVABC-2 transformer, ABC is used as a character string shared by 2 transformer areas, and the character string indicates that the power supply transformer is close to the distance or is in the same cell. The adjacent areas in this relationship are the areas with adjacent names.
When the acquisition system is built, due to the technical characteristics of the acquisition mode, for example, the micro-power wireless mode can acquire user electric energy meters of a plurality of nearby areas without blocking of the terminal accessories. The neighboring station areas of this relationship are acquisition neighbors.
The electric load is divided into a first-level load, a second-level load and a third-level load according to the reliability of power supply and the degree of political and economic loss or influence caused by power supply interruption. For the first-level and second-level users, dual power supplies can be provided during the electrical design of user loads, and 2 power areas for providing the dual power supplies are adjacent geographically due to the limitation of the power supply radius of the power areas. The adjacent stations in this relationship are designed to be adjacent for power supply and distribution. For example, three-phase important users may be supplied by 2 zones with completely different names, and elevator users of high-rise buildings may be supplied by 2 zones with adjacent names.
Fig. 4 shows a schematic diagram of acquisition proximity and supply and distribution design proximity, and the stations a/B/C may or may not be nominally adjacent. The user change error generally occurs in the adjacent station area, and the analysis range of the user attributive station area can be narrowed and the identification accuracy can be improved by analyzing and diagnosing the file data to obtain the adjacent station area.
In the power supply design of the transformer area, a power supply path generally supplies power from a transformer- > power supply line (overhead line or cable) - > power distribution equipment (electric pole or branch box or distribution room power distribution cabinet) - > power supply line- > meter box (centralized or single meter box) - > electric energy meter- > user.
For users under the transformer area, according to the power utilization address characteristics, the collection characteristics and the power utilization characteristics, the users (residents, charging piles and non-resident public utility users) can be divided into two major categories (building users and independent houses) and six minor categories (building resident private user branches, building elevator public lamp user branches, building water pump charging piles and other user branches, address gathering user branches, key collection user branches and isolated address user branches). As shown in table 1.
TABLE 1 subscriber Branch Classification under zone
Note that: in the scheme, in the private users of the residents of the buildings, the users of the single meter box are not regarded as a final-stage user branch, and the users of the centralized meter box and the users below the centralized meter box can be regarded as a final-stage user branch.
Note two: the user address clustering branch refers to the user addresses of a plurality of users, wherein the user addresses have the same keywords, such as the country of the Lincang road-friendly 12 teams.
Third, note: the aggregated address user branch may be composed of a plurality of last level user branches.
The method for identifying the user variable relationship by the acquisition mode can be summarized into four types. The method comprises the following steps: acquisition outliers, metering point outliers, measurement point outliers, and user-branch-based acquisition outliers.
1. Collecting outliers
The power consumption information of the user electric energy meter is collected through the collection terminal. When an acquisition system is built, in addition to 485 and micropower wireless modes, an acquisition service generally requires that one acquisition terminal only acquires an electric energy meter under one distribution area. However, in the actual operation process, due to the technical characteristics of the carrier communication mode, if 2 stations are zero, the station a can successfully collect the electric energy meter of the station B, which is an important reason for the user variable relationship error.
For the situation that one collection terminal collects 2 electric energy meters in a distribution area, as the collection service requires one terminal to collect the meters in one distribution area, if the number of the user meters in one terminal collection distribution area a and the distribution area b is greatly different, the difference is marked as k, users with small number (no more than j) can be regarded as outlier users, the distribution area with large number of the user attributive user meters has high possibility, and the larger the k value is, the higher the possibility of the distribution area with large number of the attributive meters is. The smaller the value of j, the higher the likelihood of identification accuracy.
2. Outlier of measurement points
When the electricity consumption information acquisition system is used for designing the information system, the acquisition terminal acquires the electric energy meter and establishes an incidence relation through an acquisition object meter, namely the acquisition point, the measurement point and the electric energy meter need to be in one-to-one correspondence to realize the successful acquisition of the electricity consumption information of the electric energy meter.
Due to technical or human factors, the electricity consumption information of the electric energy meter is successfully collected, but the affiliation relationship of the electric energy meter and the station area is wrong, and the measurement point data set is an increasing positive integer, so that the station area to which the measurement point corresponds to the electric energy meter of the user on schedule is classified, as shown in table 2. If no more than 2 outlier measurement points belonging to the station zone b appear in the increasing number, and the station zones of the measurement points before and after the outlier measurement points are the station zone a, the probability that the outlier measurement point user belongs to the station zone a is high.
TABLE 2
| Name of area | a | a | a | a | a | by | by | a | a | a |
| |
1 | 2 | 3 | 4 | 7 | 8 | 9 | 10 | 11 | 12 |
3. Outlier measurement
The acquisition system is generally constructed in a power supply network synchronously or after a delay, except a small amount of newly added users, the acquisition system is generally implemented in a batch and centralized manner according to power supply areas (a plurality of or one distribution area) during construction, and user information, acquired information and acquired information show certain regularity. Building resident private user branch collection point numbers for a 5-story residence as in table 3 exhibit a feature of numerical increments of 1.
Table 3: building private user branch power utilization address and acquisition point relation table
The regular user electric energy meter corresponding to the collection point number generally belongs to a certain user branch in the power supply network. If a user belonging to another station area appears in the regular acquisition point number belonging to one station area, the possibility of error of the station area user change relationship is very high, and the probability of the user belonging to the station area is very high. As 301 in table 1, 10 users in layers 1-5 belong to one user branch, and the difference between the metering point number of the user branch and the metering point numbers of other users in station area b is large, and the user branch and the user in station area a present the characteristic that the increment of the metering point number is 1 and is very regular. And 301, the metering point number of the user and the metering point number of the user in the station area b present a metering point outlier characteristic. Thus, outliers can diagnose 301 as belonging to station a.
The outlier features are used for secondary diagnosis of acquisition outliers. That is, measurement points of the acquisition outliers and the measurement outliers cannot be determined as a cross-sampling error if the measurement points are not outliers.
4. User branch based acquisition outliers
In a user branch composed of a plurality of users, such as a building resident private user branch and an aggregation address user branch, all the users under the branch can only be supplied with power by one distribution area because the users are on the same power supply line. Due to technical limitation of acquisition modes, electricity consumption information of users of the same user branch is successfully acquired by a plurality of acquisition terminals, and the terminals may belong to different transformer areas. For such acquisition outliers, cross-acquisitions should be diagnosed.
For a dual-power user branch, 2 metering points of the user are acquired by 1 acquisition terminal, and the situation is identified as cross-acquisition. If in a building distribution room, the acquisition terminal accessible collector of certain platform district adopts 485 cables to gather all users such as elevator user, public lighting user, water pump in this distribution room.
As shown in fig. 7, by obtaining the zone acquisition files and the zone user branch data, the acquisition topology analysis model is constructed by the above 4 methods to perform zone user change identification, and finally, the standard format of the identification result of the zone user change is output.
The implementation of the invention has the following characteristics:
1. the invention does not classify according to the distance in the geographic relation, but carries on the 3 classification methods of the adjacent platform district according to gathering the business rule and user's load electrical design rule, the new adjacent platform district is classified and fully covered various situations that the identification data analysis of the user change needs.
2. Combining situation outlier analysis of data analysis with collection business rules, and providing two methods of collection outliers and measurement point outliers for identifying the user variation.
3. Combining the situation outlier analysis of the data analysis with the user load electrical design rule, and providing a metering point outlier method for identifying the user variation.
4. And (3) taking the metering point outlier method as secondary diagnosis filtering of acquisition outliers and measuring point outliers to diagnose cross-platform acquisition of users.
5. For acquisition outliers based on user branch diagnostics, the diagnostics are cross-acquisitions.
6. By adopting the cross-sampling diagnosis, the problem that the identification error of the user change can exist in one terminal and one area type (all users under the type of terminal belong to one area) can be solved.
Experiments prove that
The accuracy can reach 95% through the verification of the actual platform area.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (7)
1. A method for identifying station area subscriber changes fusing acquisition service and load design rules is characterized in that: the method comprises the following steps:
s1: acquiring a district acquisition file and district user branch data;
s2: establishing a collection topology analysis model according to the archive data and the station area user branch data;
s3: analyzing the collection outliers, the measurement point outliers, the metering point outliers and the collection outliers based on the user branches by using a collection topological analysis model, and diagnosing the outliers and the cross-mining conditions;
s4: and outputting the analysis result of the acquisition topology analysis model according to a standard output format.
2. The method for identifying station change fusing collected service and load design rules according to claim 1, wherein said S1 is configured to diagnose adjacent station by archival data analysis.
3. The method for identifying the station transformer substation fusing the collected service and the design rule of the load according to claim 1 or 2, wherein the adjacent station area data comprises the name of the station area adjacent, the collected adjacent and/or the user profile data of the power supply and distribution adjacent and whether the user table is collected successfully.
4. The method for identifying station change fusing collected service and load design rule according to claim 1, wherein the collection outlier refers to a situation where there is 2 station electric energy meters collected by one collection terminal, and if there is a large difference between the user meters in one terminal collection station a and the user meters in station b, the difference is denoted as k, the users with small number can be regarded as outlier users.
5. The method as claimed in claim 1, wherein the measurement point outlier is that due to technical or human factors, the power consumption information of the electric energy meter is successfully collected, but the affiliation relationship between the electric energy meter and the station area is wrong, and no more than 2 outlier measurement points belonging to the station area b appear in the incremental number, and the station areas of the measurement points before and after the outlier measurement points are the station area a.
6. The method as claimed in claim 5, wherein the metering point outlier refers to a case where a user belonging to another station appears in regular acquisition point numbers belonging to a station, the probability of an error occurring in the station-to-station relationship is very high, and the probability of the user belonging to the station is very high.
7. The method as claimed in claim 5, wherein the user-branch-based acquisition outlier refers to a user branch formed by multiple users whose metering points may not exhibit regularity characteristics and whose acquisition terminal belongs to a different station.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115577993A (en) * | 2022-12-09 | 2023-01-06 | 江苏瑞电智芯信息科技有限公司 | Transformer area household change identification method based on time sequence matching |
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| CN113033666B (en) | 2024-04-26 |
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