Substation area topology identification method and system based on user branches

Abstract

The present invention belongs to the field of power topology big data analysis, and in particular to a method and system for identifying substation topology based on user branches. The following steps are included: S1: data access and processing: users are classified according to user collection characteristics, address characteristics and power consumption characteristics; S2: using power supply and distribution design specification analysis as the main analysis method, and collection topology analysis and voltage correlation analysis as auxiliary analysis methods to realize user branch identification; S3: after user branch identification, the substation to which the user branch belongs is diagnosed; S4: based on the voltage correlation analysis results and / or power supply and distribution design specifications, branch proximity identification and branch co-linear identification are used to realize automatic identification and output of substation topology. The present invention constructs a virtual power supply network based on user branches under the constraints of existing archival data and collection operation data. Since the operation data is limited by the actual power supply network, the accuracy of the data analysis results is very high, and it can fully reach the practical level.

Description

Technical Field

[0001] The present invention belongs to the field of power topology big data analysis, and in particular relates to a method and system for identifying substation topology based on user branches. Background Art

[0002] With the comprehensive coverage of the electricity consumption information collection system, the operating data of the electricity meters of power users in the low-voltage substation can be collected in quasi-real time. Since the changes in the operating data of the electricity meter at each moment depend on the changes in the user load and the different electrical parameters of the power supply line from the transformer end to the user end, the statistics and analysis of the changing rules of the operating data within a certain period provide the possibility for the intelligent diagnosis of the low-voltage substation topology.

[0003] The buildings of low-voltage power users belong to the category of civil buildings, and their electrical design must comply with the electrical design specifications for civil buildings. When the power user applies for power demand, the power supply department will design the power supply plan based on the design specifications, the nature of the user and the reported capacity, and conduct on-site surveys to establish relevant archive information for power supply to the user. When the construction department designs and constructs according to the power supply plan, it also records the installed meter boxes and electric energy meters. These archive information contains the location of the users in the power supply network under the station and the parameter information of the cable diameter that supplies power to them.

[0004] Currently, in order to obtain the low-voltage substation topology, manual data surveys are generally carried out on-site to record relevant information from transformer -> power supply line (overhead line or cable) -> distribution equipment (pole or branch box or distribution box or distribution cabinet in distribution room) -> power supply line -> meter box -> user. This method has a large workload, manual data recording may have errors, and the power grid is changing all the time, and it is impossible to monitor and make timely changes to the actual power supply network on site.

[0005] At the same time, intelligent monitoring equipment is installed on power distribution equipment such as branch boxes and meter boxes. All intelligent monitoring equipment under the substation can send distribution topology information in real time, automatically obtain information on new and deleted equipment, and realize substation topology identification. However, due to the large investment, it is impossible to install such equipment on all power distribution equipment. At the same time, the installation of such a large number of equipment will cause new problems in the maintenance of these intelligent devices.

[0006] Among the existing technical solutions for data analysis of substation topology, line loss correlation and voltage correlation are relatively mature methods. Both methods use the fact that if there is an ownership relationship between the substation and the user, there is a correlation between the power consumption and line loss, the voltage between the household meters, and the voltage between the household meters and the total meter. Generally, the Pearson correlation coefficient between power consumption, line loss, and voltage is used for diagnosis. The high or low correlation coefficient of power consumption and line loss can be used to diagnose the ownership relationship between the user and the substation, and the high or low voltage correlation coefficient can be used to diagnose whether the users are in the same meter box and the ownership of the user and the substation, thereby establishing a simple topological relationship between the substation-meter box-user.

[0007] Currently, when conducting big data analysis of substation topology, the results of data analysis are poor due to the complexity and frequent changes of substation topology analysis. An 80% accuracy rate in identifying abnormalities in household transformers is considered a good result, and the identifiable topology is also relatively simple and cannot be consistent with the actual power supply topology.

[0008] There are a large number of users under the substation, and the number of residential users accounts for the vast majority of them. Most users have low electricity consumption and a variety of power supply methods. It is impossible to accurately extract features for accurate identification of household transformers and topologies only through power consumption line loss correlation and voltage correlation analysis. As a result, the accuracy and detection rate of household transformer status identification are low, the identifiable topology level is simple, and it cannot be consistent with the actual power supply topology. As a result, the support for actual power supply business is insufficient and cannot reach a practical level. Summary of the invention

[0009] In view of the problems existing in the prior art, the present invention provides a method for identifying substation topology based on user branches which is easy to promote, low in cost and high in coverage, and a system for identifying substation topology based on user branches which implements the method.

[0010] The present invention is implemented in this way: the method for identifying the station area topology based on the user branch comprises the following steps:

[0011] S1: Data access and processing: Classify users according to their collection characteristics, address characteristics and electricity consumption characteristics;

[0012] S2: Use power supply and distribution design specification analysis as the main analysis method, and acquisition topology analysis and voltage correlation analysis as auxiliary analysis methods to achieve user branch identification;

[0013] S3: After the user branch is identified, the area to which the user branch belongs is diagnosed;

[0014] S4: Based on the voltage correlation analysis results and / or power supply and distribution design specifications, the substation topology is automatically identified and output through branch proximity identification and branch co-linear identification.

[0015] The power supply and distribution design specifications mentioned above refer to the electrical design standards for civil buildings. There are multiple different versions. The latest version, "Electrical Design Standards for Civil Buildings GB51348-2019" issued by the Ministry of Housing and Urban-Rural Development of the People's Republic of China in 2019, shall prevail.

[0016] The S2 user branch identification includes user branch distribution statistics, preliminary identification and optimization, and the optimization is divided into 1) voltage correlation analysis result optimization; 2) acquisition topology analysis result optimization.

[0017] After S2 is performed to identify user branches, step S2-1 is performed to identify abnormal branches according to the power supply and distribution design specifications. Identifying abnormal branches according to the power supply and distribution design specifications means that the power supply and distribution design analysis extracts two electrical design rules to diagnose abnormal branches based on the residential building electrical design specifications: 1) Users under a user branch are powered by one substation. If there are two or more substations, it is diagnosed as an abnormal branch; 2) The common power supply and backup power supply of important users such as elevators and public lighting come from different substations. If the common power supply and backup power supply of two user branches of the same important user are supplied by the same substation, these two user branches are diagnosed as abnormal branches.

[0018] The abnormal household change output means that after the substation to which the branch belongs is determined, the users under the branch that do not belong to the substation are diagnosed as abnormal household change and output in a graded manner.

[0019] The above S3: After the user branch is identified, the diagnosis of the substation to which the user belongs refers to calling distance analysis, voltage correlation analysis, line loss correlation analysis and power outage analysis in sequence to diagnose the substation to which the branch belongs; when the above analysis method lacks data or is not applicable to a certain type of user, the analysis method is ignored. After the user branch is identified, in the diagnosis of the substation to which the user belongs, if the above four analyses cannot accurately determine the substation to which the user belongs, the power supply and distribution design specification determines that the user branch should belong to the substation according to the principle of minority obeys majority.

[0020] A system for realizing the above-mentioned method of identifying substation topology based on user branches, comprising an electrically connected server, a topology analysis platform, a network data interface and a display operation terminal, characterized in that the network data interface is provided with a data acquisition unit 201 connected to a big data platform to obtain the required list of power business data, and the topology analysis platform is provided with a substation topology analysis establishment model 202 and a substation topology analysis unit 203.

[0021] The substation topology analysis unit 203 includes a data preprocessing service, and its CSV check program automatically monitors the data update status of the data cache area. When new data is found in the data cache area, it first checks the data quality according to the established inspection rules and outputs a data quality inspection report; after the data inspection is qualified, the data merging program is called to perform preprocessing work such as data merging on the new data in the cache area according to predetermined rules, and the processed data is saved to the ES data cluster through the data input program.

[0022] The advantages and positive effects of the present invention are as follows: the present invention starts from the perspective of power supply and distribution business in the substation, summarizes relevant power business rules, and based on the electrical design rules extracted from the electrical design specifications for residential buildings, classifies users under the substation according to their address characteristics, collection characteristics and power consumption characteristics, introduces the concept of user branches, and establishes a substation topology recognition model with power supply and distribution design analysis as the main trunk, and optimizes the power supply and distribution design analysis results through distance analysis (composed of collection topology analysis + address analysis), voltage correlation analysis, line loss correlation analysis and power outage analysis, thereby solving the problem of low accuracy in topology recognition for users with small power consumption under the substation.

[0023] The core idea of ​​the present invention is to construct a virtual power supply network based on user branches under the constraints of existing archival data and collected operation data. Since the operation data is limited by the actual power supply network, the accuracy of the data analysis results is very high and can fully reach the practical level. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a principle block diagram of the present invention;

[0025] Figure 2 It is a typical schematic diagram of user branch identification in a building community of the present invention;

[0026] Figure 3 It is a schematic diagram of user branch identification for independent house users of the present invention;

[0027] Figure 4 It is a schematic diagram of building user branch distribution of the present invention;

[0028] Figure 5 It is a schematic diagram of the independent house user branch identification of the present invention;

[0029] Figure 6 It is a schematic diagram of abnormal identification of household transformers in single-branch multi-station areas of the present invention;

[0030] Figure 7 This is a schematic diagram of identifying abnormalities of power supply transformers for important users of the present invention using a common backup power supply in the same area;

[0031] Figure 8It is a flow chart of household change abnormal case identification of the present invention;

[0032] Fig. 9 is a schematic diagram of a topology recognition result of a topology recognition case of the present invention;

[0033] Fig.10 A schematic diagram of the application architecture of the identification system of the present invention;

[0034] Fig.11 Schematic diagram of the physical structure of the identification system;

[0035] Fig.12 It is a principle block diagram of the recognition system of the present invention;

[0036] Fig.13 It is a schematic diagram of the interface architecture between the identification system and the big data platform of the present invention. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments.

[0038] Embodiment 1:

[0039] like Figure 1 As shown, the present invention is implemented in this way: a method for identifying a station area topology based on a user branch comprises:

[0040] S1: Data access and processing: Classify users based on user collection characteristics, address characteristics and power consumption characteristics of power supply and distribution design;

[0041] S2: Using the power supply and distribution design specification analysis as the main analysis method, collecting the topological analysis in the archive power supply statistics for distance analysis, and using the voltage correlation analysis to achieve user branch identification;

[0042] S3: After the user branch is identified, multiple analysis methods are used to diagnose the area to which the user branch belongs;

[0043] S4: Based on the voltage correlation analysis results and / or power supply and distribution design specifications, the substation topology is automatically identified and output through branch proximity identification and branch co-linear identification.

[0044] S5: Diagnose the users under the branch that do not belong to the substation area as abnormal user change and output them in different levels.

[0045] in:

[0046] The technical solution adopted in the present invention classifies users based on user collection characteristics, address characteristics and electricity consumption characteristics, introduces the concept of user branches, takes power distribution design analysis as the main analysis method, and combines distance analysis (composed of collection topology analysis + address analysis), voltage correlation analysis, line loss correlation analysis and power outage and power-on analysis correlation analysis to realize automatic identification of household transformers and topologies in the substation area.

[0047] 1. Structural processing of electricity usage addresses, user branch definitions and classification standards

[0048] In the power supply design of the substation, the power supply path is generally from transformer -> power supply line (overhead line or cable) -> distribution equipment (pole or branch box or distribution box or distribution cabinet in distribution room) -> power supply line -> meter box (centralized or single meter box) -> electric energy meter -> user for power supply.

[0049] In view of the fact that the substations that need to be identified for household change are all public substations, and the vast majority of users in public substations are residential users, the address characteristics, collection characteristics and user electricity usage characteristics of the substation users are summarized, and the concept of user branches is introduced. The users in the substation are divided into two major categories and six minor categories, which makes it convenient to select appropriate analysis methods for each type of user to identify household change relationships. Figure 2 This is a typical schematic diagram of user branch identification in a building community. Figure 3 This is a schematic diagram of branch identification for independent house users.

[0050] 1. Structural processing of electricity usage addresses

[0051] Taking building users as an example, as shown in Table 1, the user electricity usage address in the collected archive data is processed into 11 levels of structured processing to obtain the building-floor-room number, which can facilitate the statistics of the power supply distribution relationship between the building floor and the substation.

[0052] Table 1 Structural processing of electricity address

[0053] Level 1 Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8 Level 9 Level 10 Level 11 Province city county Township road alley Number Dong unit layer room Shanghai Pudong New Area Sanlin Town Lingzhao Road 88 28 01 01

[0054] 2. User branch definition

[0055] A user branch refers to a power supply line and the power users under it. The user branch from the power supply line to the meter box is the final user branch. Power users under a user branch are supplied by the same transformer area. After the introduction of user branches, the identification of the relationship between users and transformers in the transformer area becomes the identification of the transformer area to which the branch belongs.

[0056] In a public substation, a terminal user branch can have more than 20 electricity users at most. The average number of electricity users in each substation in the national grid is only about 100. After introducing user branches, the number of analyses can be reduced by an order of magnitude. At the same time, compared with the analysis of a single electricity user, the branch can reflect more characteristics and the effectiveness of the analysis results can be greatly increased.

[0057] 3. User classification

[0058] The users in the substation area are divided into residential building type (referred to as buildings, multi-story and high-rise residential buildings, and the electricity use addresses show regular floor and room characteristics) users and non-residential building type (referred to as independent houses) users, and a user branch data model is constructed. Based on the collection characteristics and user electricity use characteristics, each major user branch is further subdivided into three subcategories. As shown in Table 2.

[0059] Table 2 Classification of user branches under the substation area

[0060]

[0061] Note ①: Among the private users of buildings in the plan, single meter box users are not regarded as a last-level user branch, while centralized meter boxes and their subordinate users can be regarded as a last-level user branch.

[0062] Note ②: Aggregate address user branch refers to multiple users with the same keyword in their user addresses, such as Lincang Road Youhao 12 Team Zhuangjiazhai.

[0063] Note ③: The aggregated address user branch can be composed of multiple terminal user branches.

[0064] 2. User branch distribution statistics, preliminary identification and optimization

[0065] The most critical step in the user change identification process in this solution is user branch identification, which includes three steps: user branch distribution statistics, preliminary identification, and branch optimization.

[0066] 1. User branch distribution statistics

[0067] According to the archive relationship between the substation and the electricity address, and based on the principle of consistent design of the same floor, the same number of users and the same contract capacity during the electrical design of the same community, the distribution relationship between the building floors and the substation power supply users can be statistically calculated, such as Figure 4 As shown in the figure, there are three types of user branches in the building: one on the 2nd floor, one on the 3rd floor, or one on the 4th floor.

[0068] For independent house users, the user branch is initially identified by collecting the terminal address + address keyword. Figure 5 The clustered addresses of Minjiazhai 56# to 399# are shown, and these addresses are powered by two substations. Terminal A + Minjiazhai is used as a feature to identify 56-215 as a user branch of Tianhua Minjia, and terminal B + Minjiazhai is used as a feature to identify 328-399 as a user branch of Tianhua Jinyidong.

[0069] 2. Preliminary identification of user branches

[0070] After the user branch distribution statistics are collected, the branches are initially identified. Table 3 shows the initially identified user branches and their numbers.

[0071] Table 3 Preliminary identification results of typical second-class high-rise (number of floors less than or equal to 18) user branches

[0072]

[0073]

[0074] 3. User branch optimization

[0075] After the user branches are initially identified, the initially identified user branches can be optimized through voltage correlation and acquisition topology.

[0076] 1) Optimization of voltage correlation analysis results

[0077] As shown in Table 4, the voltage correlation results between household meters in the same phase in a centralized meter box are significantly different from those of other phase meters. The 12 meters in the meter box form a final user branch.

[0078] Table 4 Correlation results of household meter voltage in centralized meter box

[0079] Room Number 101 102 201 202 301 302 401 402 501 502 601 602 101 1.00y 0.96y 0.95y 0.91y 0.17 0.19 0.16 0.15 0.11 0.07 0.07 0.08 102 0.96y 1.00y 0.92y 0.94y 0.16 0.17 0.13 0.12 0.11 0.06 0.04 0.05 201 0.95y 0.92y 1.00y 0.88y 0.18 0.20 0.18 0.17 0.07 0.07 0.08 0.09 202 0.91y 0.94y 0.88y 1.00y 0.15 0.11 0.11 0.11 0.12 0.07 0.02 0.01 301 0.17 0.16 0.18 0.15 1.00g 0.87g 0.92g 0.96g 0.11 0.06 0.06 0.09 302 0.19 0.17 0.20 0.11 0.87g 1.00g 0.92g 0.90g 0.17 0.13 0.10 0.11 401 0.16 0.13 0.18 0.11 0.92g 0.92g 1.00g 0.96g 0.12 0.07 0.04 0.07 402 0.15 0.12 0.17 0.11 0.96g 0.90g 0.96g 1.00g 0.13 0.07 0.07 0.09 501 0.11 0.11 0.07 0.12 0.11 0.17 0.12 0.13 1.00r 0.92r 0.87r 0.84r 502 0.07 0.06 0.07 0.07 0.06 0.13 0.07 0.07 0.92r 1.00r 0.92r 0.90r 601 0.07 0.04 0.08 0.02 0.06 0.10 0.04 0.07 0.87r 0.92r 1.00r 0.97r 602 0.08 0.05 0.09 0.01 0.09 0.11 0.07 0.09 0.84r 0.90r 0.97r 1.00r

[0080] The above analysis results can also be applied to user branches. The voltage correlation between household meters is calculated for each user branch, and the household meter phase distribution of the user branch can be obtained. As shown in Table 5, it can be seen from the distribution diagram that every three floors form an ABC three-phase distribution. Through the correlation analysis of the floor meter box archive data, there are two meter boxes on each floor of the building, and the meter position is 1. Therefore, it is determined that the private user branch 1 of the building can be further subdivided into 8 sub-branches 11-18, and the private user branch 1 of the residents is the parent branch of branches 11-18. The private user branch 2 of the residents can be further subdivided into 9 sub-branches 21-29, and the private user branch 2 of the residents is the parent branch of branches 21-29. Through the voltage correlation analysis results, the verification of the user branch identification results can be completed, thereby confirming or optimizing the preliminary identification results of the branches.

[0081] Table 5 Typical Class II high-rise (number of floors less than or equal to 18) user branch identification and phase identification verification

[0082]

[0083] If the floor meter boxes are arranged as centralized meter boxes, the two residential private user branches can be divided into multiple sub-branches according to the number of centralized meter boxes, with one final user branch for each centralized meter box.

[0084] After the introduction of branches, when using voltage correlation analysis to calculate the voltage correlation coefficient between household meters, by selecting a suitable strategy, only more than 10 points are needed to obtain the expected analysis results, which can greatly reduce the demand for computing resources.

[0085] 2) Optimize the collection of topological analysis results

[0086] In the half-load (narrowband carrier + 485) collection mode, the user branch optimization can be carried out according to the principle of replacing a collector with another one when the branch is cut off during the collection network construction. As shown in Table 6. According to the power supply relationship between the substation and the power consumption address, the 12th floor user is identified as a residential private user branch, but according to the fact that there are two collection points in the building and they are evenly distributed, it can be divided into two 6-story residential private user branches.

[0087] According to the distribution and number of meter boxes in the building, each branch can be further divided into multiple sub-branches.

[0088] Table 6 Relationship table of area users, areas, collection points, and user branches

[0089]

[0090] 3. Abnormal Branch Identification

[0091] The power supply and distribution design analysis is based on the residential building electrical design specifications and extracts two electrical design rules to diagnose abnormal branches:

[0092] 1) If a user branch is powered by one substation and there are two or more substations, it is diagnosed as an abnormal branch;

[0093] 2) The normal power supply and backup power supply of important users such as elevators and public lighting come from different substations. For example, the normal power supply and backup power supply of two user branches of the same important user are supplied by the same substation, and these two user branches are diagnosed as abnormal branches.

[0094] like Figure 6 As shown. There are 2 residential private user branches on the 11th floor, one for the 1st to 6th floors and one for the 7th to 11th floors, both of which are powered by Hongshan Yueju Chi. For the 1st to 6th floor user branches, the electric energy meter in the blue box in the file is not powered by Hongshan Yueju Chi, which violates the design principle that one user branch should be powered by the same substation.

[0095] like Figure 7 As shown, the normal power supply and backup power supply for the No. 2 public lighting in Lane 879 are supplied by the same substation, which violates the design principle that the normal power supply and backup power supply must come from different substations.

[0096] 4. Branch area identification and abnormal output of household change

[0097] The data analysis process of 19 six-story buildings is used as an example.

[0098] 1) User branch distribution statistics and preliminary identification of user branches

[0099] According to the electrical design rules, the low-voltage power supply of multi-storey residential areas is based on the residential building unit as the power supply unit, and the power supply is provided by cables with equal cross-section from the substation to the unit main power box. Multi-storey residential users without public facilities such as elevators are generally powered by the same substation during design. The distribution of user branches and the preliminary identification results of user branches are shown in Table 6.

[0100] Table 6 User branch distribution statistics and preliminary identification results of user branches

[0101]

[0102] 2) Abnormal branch identification

[0103] Residential private user branch 10 has two power supply areas, which violates the design principles and the user branch is diagnosed as an abnormal branch.

[0104] 3) Branches should be diagnosed in the area

[0105] The distance analysis results (a method for identifying household transformers in substations based on the collection of business rules and user load electrical design rules) are called. Building 10 is in substation 8732, and is an outlier compared to other power supply buildings, but is not outliers from other power supply buildings in substation 0532. The distance analysis diagnosis shows that user branch 10 belongs to substation 0532.

[0106] The line loss correlation analysis results (a method patent for identifying transformer substations based on daily frozen data and user load electrical design rules) are called. The Pearson correlation coefficient of the combined power consumption of the branches and line loss of the residential user branch 10 and the substation 8732 shows a negative correlation, but not with the substation 0532. The user branch 10 does not belong to the substation 8732. The line loss correlation diagnosis shows that the user branch 10 belongs to the substation 0532.

[0107] Voltage correlation and power-off analysis are ignored due to lack of data.

[0108] In the power supply and distribution design, since there are other analysis methods to confirm that the branch belongs to 0532, it is not necessary to output the substation according to the default principle of minority obeys majority.

[0109] Based on the above analysis method, user branch 10 belongs to station area 0532.

[0110] 4) Abnormal output of household change

[0111] User branch 10 belongs to station 0532, and outputs 10 users on layers 2-6 as abnormal user change. The entire user change abnormality identification process is as follows: Figure 8 shown.

[0112] 5. Automatic identification of substation topology

[0113] Combined with the electrical design specifications and voltage correlation analysis results (the result of a method for identifying substation topology based on voltage correlation analysis of time series data and user load electrical design rules), the substation topology is automatically identified through branch proximity identification and branch collinearity identification.

[0114] Take two building substations as an example to illustrate how to realize automatic identification of substation topology.

[0115] 1. Basic situation of the area

[0116] The power supply range of the two building substations is 1st 20-story residential building (Buildings 6-7) and 3rd 17-story residential building (Buildings 8 / 9 / 10) in Lane 199, Fuguo Road. The basic information of the substation is shown in Table 7.

[0117] Table 7 Basic information of two building areas

[0118] Area ID 10133300637 10133300639 District Name Yinkang No. 21_No. 1 distribution transformer Yinkang No. 21_No. 2 distribution transformer Transformer capacity 800 800 Comprehensive magnification 400 400 Number of energy meters 137 108

[0119] 2. User branch identification

[0120] The identification of the final user branches in Buildings 8 / 9 / 10 is shown in Table 8.

[0121] Table 8 User branch identification table for building 8 / 9 / 10

[0122]

[0123] The identification of the final user branch of Building 6-7 is shown in Table 9.

[0124] Table 9 User branch identification table for Building 6-7

[0125]

[0126] 3. Branch proximity identification

[0127] According to the electrical design specifications for residential buildings, the user branch processing methods for residential electrical designs are slightly different for floors 18 and below and floors 19 and above.

[0128] For Class A high-rise buildings with 18 floors or less, in the same building, user branches belonging to the same power source are drawn from the same section of the busbar in the building's power distribution room, and these user branches are drawn from different distribution cabinets to supply power to the users below. At the same time, because the public utility load is relatively small, when designing the power supply and distribution, multiple public utility user branches on the same busbar are generally drawn from one distribution cabinet, while private residential user branches are independently drawn from one distribution cabinet. As shown in Table 8, user branches 2 / 4 / 6 / 7 of buildings 8 / 9 / 10 are powered by the backup power busbar belonging to the distribution room, and 1 / 3 / 5 are powered by the common power busbar in the distribution room. When there are multiple private residential user branches under the common or backup power busbar, add a distribution cabinet to draw power at the common or backup power busbar.

[0129] For Class II high-rise buildings with 19 floors or more, in the same building, each private user branch is generally independently powered by a dedicated line from the residential substation, and each user branch has an incoming line cabinet and an outgoing line cabinet in the building distribution room. For public facilities such as elevators and public lighting, dedicated lines can be used for power supply, or they can be shared with a private user branch. As shown in Table 9, user branches 2 / 7 / 9 in Building 6-7 are a power supply line drawn from a residential substation to supply power to public lighting, elevators and users on the 16th to 18th floors, and 5 is a power supply line drawn from another residential substation to supply power to users on the 1st to 5th floors.

[0130] Through the above electrical design specifications, proximity identification of user branches can be achieved.

[0131] 4. Branch collinearity identification

[0132] Through the results of the voltage correlation analysis between branches and the use of the characteristics of the phase approximation average distribution presented by the collinear branch voltage correlation analysis results, it is possible to identify whether the branches of each user are collinear, thereby accurately diagnosing whether the public utility branches of elevators and public lighting in high-rise buildings of 19 floors and above are powered by dedicated lines from residential substations or share a line with private user branches.

[0133] The topological identification results of the two substations are as follows: Fig. 9 Each box represents a distribution cabinet.

[0134] Embodiment 2:

[0135] like Figure 10-13 As shown,

[0136] A system for automatically identifying low-voltage substation topology based on user electrical design rules for implementing the above method includes an electrically connected server, a topology analysis platform, a network data interface and a display operation terminal, characterized in that the network data interface is provided with a data acquisition unit 201 connected to a big data platform to obtain the required power business data list, and the topology analysis platform is provided with a substation topology analysis establishment model 202 and a substation topology analysis unit 203.

[0137] The application architecture of the area topology identification system describes the application function scope and relationship between modules, which can be divided into five parts: interface with the big data platform, data processing, analysis algorithm, Web application display and management tools. Fig.10 As shown. According to the analysis needs and different time periods, the collected data and archive data of the electric energy meter are extracted from the electricity consumption information collection big data platform, the data are checked and preprocessed, and a variety of big data analysis algorithm models are constructed to analyze the power supply topology and line loss of the substation area, and suggestions for adjusting the household-to-substation relationship and the impact of the adjusted substation line loss are given. Through the Web display function, a list of users with suspected household-to-substation relationship errors is displayed and the substation area to which they may belong is pointed out, and other related statements and reports are displayed at the same time.

[0138] A secondary development API interface is provided to embed the analysis results into the existing business system of the power grid company, providing technical support for line loss management, replacement of inaccurate electricity meters, fault repair and business expansion and new installation.

[0139] The patent of this invention relates to power supply and distribution design, analysis results of power supply and distribution design associated with other big data analysis methods, and a display system.

[0140] (1) Data access and storage service (Data Saving Processor)

[0141] Data access method: According to the list of power business data required by the system, the big data platform provides a CSV file of the corresponding original data and transmits it to the household-transformer relationship analysis module via FTP.

[0142] Data caching: The raw data will be cached in the server in the form of CSV files for use by the data preprocessing service.

[0143] Some intermediate calculation results generated during the operation of the computing service will also be cached in the data cache to improve computing efficiency.

[0144] ES Data Cluster: The data preprocessing results of the data preprocessing service (Preprocessor) are stored in the ES data cluster for subsequent analysis. The calculation results of the algorithm service (Algorithm Processor) are stored in the ES data cluster for the Web interface service (Web Processor) to call.

[0145] (2) Data preprocessing service (Preprocessor)

[0146] The CSV Check Process automatically monitors the data update status of the data cache. When new data is found in the data cache, it first checks the data quality according to the established inspection rules and outputs a data quality inspection report (Data Check Report). After the data inspection is qualified, the Data Merge Process is called to perform pre-processing such as data merging on the new data in the cache according to the predetermined rules. The processed data is saved to the ES data cluster through the Data Import Process.

[0147] (3) Algorithm Processor

[0148] The algorithm service (Algorithm Processor) contains an algorithm program pool (Process-pool), each algorithm program implements an algorithm. The management program (TaskFlow) calls different algorithm programs according to the calculation trigger identifier obtained from the ES data cluster as needed and the configuration, analyzes the business data according to certain rules, outputs the calculation results, and saves the calculation results to the ES data cluster and the big data platform through the data output program (Data Out Process).

[0149] (4) Web Interface Service (Web Processor)

[0150] The Rule Engine solidifies the data reading rules according to the data display requirements of the front-end Web, reads the required calculation result data from the ES data cluster, and the Web Background Processor processes the calculation results, combines the calculation results according to the interface protocol requirements, and outputs them to the Web front-end interface through the Web Interface Process after load balancing using the Http protocol through the reverse proxy service (Open Resty).

[0151] Experimental Proof

[0152] The present invention starts from the perspective of power supply and distribution business in the substation, summarizes the relevant power business rules, and classifies the users in the substation according to the address characteristics, collection characteristics and power consumption characteristics of the users based on the electrical design specifications of residential buildings. The concept of user branches is introduced, and a substation topology recognition model is established with power supply and distribution design analysis as the main trunk, and distance analysis (composed of collection topology analysis + address analysis), voltage correlation analysis, line loss correlation analysis and power outage analysis are used to optimize the power supply and distribution design analysis results, solving the problem of low accuracy of topology recognition for small power users in the substation. After simulation tests and actual on-site verification, the recognition accuracy of all users in the substation can reach more than 99%.

[0153] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for identifying a station area topology based on a user branch, characterized in that: The following steps are involved: S1: Data access and processing: Classify users according to their collection characteristics, address characteristics and electricity consumption characteristics; S2: Using power supply and distribution design specifications as the main analysis method, acquisition topology analysis and voltage correlation analysis as auxiliary analysis methods to achieve user branch identification; the S2 user branch identification includes user branch distribution statistics, preliminary identification and optimization, and the optimization is divided into 1) optimization of voltage correlation analysis results; 2) Optimize the acquisition topology analysis results; After the user branch identification is realized, step S2-1 is performed to identify abnormal branches according to the power supply and distribution design specifications; the abnormal branch identification according to the power supply and distribution design specifications refers to extracting two electrical design rules according to the power supply and distribution design specifications to diagnose abnormal branches: 1) Users under a user branch are powered by one substation, and if there are two or more substations, it is diagnosed as an abnormal branch; 2) The common power supply and backup power supply of important users such as elevators and public lighting come from different substations. If the common power supply and backup power supply of two user branches of the same important user are powered by the same substation, these two user branches are diagnosed as abnormal branches; S3: After the user branch is identified, multiple analysis methods are used to diagnose the substation to which the user branch belongs. After the user branch is identified, the diagnosis of the substation to which the user belongs refers to calling distance analysis, voltage correlation analysis, line loss correlation analysis and power outage analysis in sequence to diagnose the substation to which the branch belongs. When the above analysis method lacks data or is not applicable to a certain type of user, the analysis method is ignored. After the user branch is identified, in the diagnosis of the substation to which the user belongs, if the above four analyses cannot accurately determine the substation to which it belongs, the power supply and distribution design specification determines that the user branch belongs to the substation according to the principle of minority obeys majority. S4: Based on the voltage correlation analysis results and / or power supply and distribution design specifications, the substation topology is automatically identified and output through branch proximity identification and branch co-linear identification.

2. The method for identifying the area topology based on user branches according to claim 1, characterized in that: It also includes S5: abnormal output of household transformers determined according to the power supply and distribution design specifications.

3. The method for identifying the area topology based on user branches according to claim 2, characterized in that: The abnormal household change output means that after the substation to which the branch belongs is determined, the users under the branch that do not belong to the substation are diagnosed as abnormal household change and output in a graded manner.

4. A user branch-based substation topology identification system, used to implement the method for substation topology identification based on user branches as described in any one of claims 1 to 3, comprising an electrically connected server, a topology analysis platform, a network data interface and a display operation terminal, characterized in that: The network data interface sets a data acquisition unit 201 to connect to the big data platform to obtain the required power business list data, and the topology analysis platform sets a substation topology analysis establishment model 202 and a substation topology analysis unit 203.

5. The user branch-based area topology identification system according to claim 4, characterized in that: The substation topology analysis unit 203 includes a data preprocessing service, and its CSV check program automatically monitors the data update status of the data cache area. When new data is found in the data cache area, it first checks the data quality according to the established inspection rules and outputs a data quality inspection report; after the data inspection is qualified, the data merging program is called to perform preprocessing work such as data merging on the new data in the cache area according to predetermined rules, and the processed data is saved to the ES database cluster through the data input program.

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