CN-122001089-A - Low-voltage station household-phase-box-transformer substation identification method and system

CN122001089ACN 122001089 ACN122001089 ACN 122001089ACN-122001089-A

Abstract

The invention discloses a low-voltage station household-phase-box-transformer substation identification method and system, comprising the steps of constructing an optimization model based on a power conservation principle, calculating the similarity of a user ammeter power curve and each phase power curve of a meter box node, and distributing users to the phase with the highest similarity to finish household-correlation identification; and reading the ammeter address and collecting data through a physical communication interface between the low-voltage measuring switch and the user ammeter. The method provided by the invention fuses multi-source data, fully utilizes steady-state data and address information of the ammeter, simultaneously creatively provides a load transient event, improves the box transformer substation identification accuracy through the signal strong characteristic of the load transient event, realizes the identification of the household phase and the box transformer substation relation through steady-state power conservation on the lower side by taking the box transformer substation node as the middle node, realizes the box transformer substation relation identification through the load transient event on the upper side, and has simple calculation and high identification accuracy.

Inventors

HUANG LI
LI LEI
WU HENG
PEI FENG
QIN WEI
DENG SHIWEI

Assignees

江苏智臻能源科技有限公司

Dates

Publication Date: 20260508
Application Date: 20260407

Claims (5)

1. A low voltage station household-phase-box-transformer identification method, characterized in that the method comprises the following steps: s1, constructing an optimization model based on a power conservation principle, calculating the similarity of a power curve of a user electric meter and power curves of each phase of a meter box node, and distributing users to the phase with the highest similarity to finish the identification of a user-correlation system; S2, reading an ammeter address and collecting data through a physical communication interface between the low-voltage measuring switch and the user ammeter, and establishing a binding relation between an ammeter asset number and a meter box asset number through the ammeter address to realize household-box relation identification; s3, extracting a load transient event sequence of each table box node and each table transformer node, and representing each event by adopting a multidimensional feature vector; the clock deviation among the sequences is leveled by a self-synchronizing technology, the load transient event sequence of each table box node is matched with the load transient event sequences of all the station transformer nodes to be matched according to the multidimensional feature vector, and the box-transformer relation and the phase identification are determined according to the principle that the number of the matched events is the largest; And S4, carrying out association integration on the identification results of the user-phase, the user-box and the box-transformer to generate a complete user-phase-box-transformer topological relation diagram.
2. The identification method according to claim 1, wherein the optimization model in the step S1 takes the deviation between the power of each phase of the table box and the sum of the power of the hanging user as an optimization target, and performs ABC phase combination allocation on the users until A, B and C phases meet the optimization target, and the constructed optimization model can be expressed as: , Wherein, the For the power of the jth phase of the t-time table bin, For the power of user i at time t, Indicating a variable for the attribution relation between the user i and the phase j, wherein T is the total sampling time number; The similarity is calculated by adopting a user-by-user allocation strategy, specifically, for a user k to be allocated, the user k is allocated to the phase which maximizes the correlation coefficient, and the calculation is expressed as: , Wherein, the Representing calculating the correlation coefficient of the two power curve sequences, The power of the user k at the time t is represented, A, B and C respectively represent the A, B and C three-phase phases of the power grid, and U represents the total number of users.
3. The identification method according to claim 1, wherein the specific steps of the step S3 are as follows: S31, representing any load transient event L in the load transient event sequence by a five-dimensional feature vector as follows: , Wherein, the For the start-up time of the load transient event, As the event type of the load transient event, For the power after the transient event has stabilized, As a crest factor of the transient process, Transient duration for load transient event L; S32, searching a matching mode of event types in a load transient event sequence of a table box node and a load transient event sequence of a station transformer node through a self-synchronization technology to estimate clock deviation delta t, wherein for the found K pairs of matching events, the clock deviation delta t can be estimated by the following formula: , when matching, correcting the load transient event stamp at the side of the low-voltage intelligent measuring switch, specifically: , , In the above-mentioned method, the step of, Representing the start time of the load transient event of the kth table bin node, The start-up time of the transient event representing the load of the transformer node, The start time of the load transient event representing the kth station-change node, Indicating the start-up time after correction by the clock bias, Representing corrected load transient event transient duration; s33, counting the number of successful event matching between the load transient event sequence of the table box node and the load transient event sequence of the station transformer node Searching for a transformer with the largest number of matching events for table box B Phase and phase The specific formula is as follows: , In the above-mentioned method, the step of, And Respectively representing the transformer and the phase of the table box B after matching, T representing the transformer before matching, j representing the phase before matching, A load transient event type vector representing a table bin, Representing the load transient event type of the phase j of the transformer.
4. The method for identifying a load transient event according to claim 3, wherein the matching of the load transient event is specifically determining an event type Whether the same, the starting time, the steady-state power, the transient process duration and the crest factor all meet the preset matching conditions, wherein the starting time of the load transient event of the table box node The matching conditions of (2) are as follows: ; the matching conditions of the steady-state power are: ; The matching conditions for the transient duration are: ; The matching condition of the crest factor F crest is: ; Wherein, the The peak current representing the transient process is indicated, The current effective value representing the transient process, Indicating the power after the transient event of the meter box is stabilized, Representing the power after the plateau transient event stabilizes, Representing the duration of the transient for the bin load transient event L, The crest factor representing the bin transient, A crest factor representing a plateau transient; is a preset threshold.
5. An identification system suitable for use in the method of any one of claims 1-4, comprising an electricity meter, a low voltage measurement switch, a site transformer, and an edge processing unit; the electric meter is an intelligent electric meter, and steady-state power data of each time section of the user node are collected; The low-voltage intelligent measuring switch is connected with the intelligent ammeter through a 485 interface, is provided with an HPLC and small wireless dual-mode communication module, transmits data to the station area concentrator, acquires steady-state power data of each time section of the meter box node, and extracts load transient events of the meter box node in real time; The transformer in the transformer area extracts the load transient event of the transformer node in real time, and receives the user ammeter power curve data, the meter box node power curve data and the load transient event sequence uploaded by the low-voltage measuring switch; And the edge processing unit collects data of the ammeter, the low-voltage measuring switch and the station area concentrator and performs any one of the methods 1-4 to realize the identification of the household-phase-box-transformer.

Description

Low-voltage station household-phase-box-transformer substation identification method and system Technical Field The invention relates to the technical field of topology identification of power systems, in particular to a low-voltage transformer area household-phase-box-transformer identification method and system. Background In the daily operation and maintenance management of the low-voltage distribution network, the accurate identification of the topological relation (namely, the household transformer relation, the household phase relation and the box table relation) of the transformer area is an important basis for realizing accurate analysis of line loss, inspection of anti-electricity-theft, rapid fault positioning and intelligent operation and maintenance. However, for a long time, the problem that the actual topology is inconsistent with the record of the system file is very prominent due to the complex structure (common tree-shaped or fishbone-shaped topology), huge number of users, frequent line change and lack of effective automatic identification technology of the low-voltage power distribution network. Traditionally, topology identification has relied primarily on manual field investigation and archive record verification. The method has the advantages of huge workload, low efficiency and high cost, is difficult to deal with dynamic changes of the circuit, is easy to record lag or error, and cannot meet the real-time and accurate management requirements of the intelligent power distribution network. In order to overcome the limitation of manual investigation mode, various topology identification technical routes are developed gradually. Along with the popularization of intelligent electric meters, load curve data (such as 15 minutes or 1 hour intervals) based on low sampling density is provided, and user transformation relation judgment is performed through similarity analysis or an integer programming algorithm by utilizing an energy conservation law or a kirchhoff current law. However, these methods are limited by data acquisition quality and station operating characteristics, and the identification accuracy and detection rate are often difficult to guarantee under light load or noise interference of data. In addition, by utilizing the HPLC communication carrier signals, the topological connection relation is generated by analyzing the carrier signal-to-noise ratio, zero crossing point phase difference and other information among the communication nodes, but the method has the problem of electromagnetic coupling, so that the adjacent station areas are wrongly identified, and the identification accuracy is not high. With the application of the intelligent measuring switch, an intelligent measuring switch is installed at the outgoing line side, the branch box, the meter box and the like of the transformer, a specific topology identification current signal (such as distortion current with the duration of 1-1.5 ms) is injected into a switch installation node, and the connection relation is judged by whether the signal is received at each stage of nodes or not. The method is strong in initiative and high in identification accuracy, special hardware equipment is required to be deployed, and certain potential safety hazards exist in the injected power signals. In summary, the low-voltage area topology identification technology is evolving from relying on manpower and experience to an automation and intelligent direction. The various methods disclosed at present respectively face different challenges such as data quality dependence, hardware transformation cost, communication reliability, algorithm complexity and the like. Disclosure of Invention The invention aims to provide a low-voltage station household-phase-box-transformer substation identification method and system, which are used for solving the technical problems in the background technology. In order to achieve the above object, the present invention provides a low-voltage station household-phase-box-transformer identification method, comprising the following steps: s1, constructing an optimization model based on a power conservation principle, calculating the similarity of a power curve of a user electric meter and power curves of each phase of a meter box node, and distributing users to the phase with the highest similarity to finish the identification of a user-correlation system; S2, reading an ammeter address and collecting data through a physical communication interface between the low-voltage measuring switch and the user ammeter, and establishing a binding relation between an ammeter asset number and a meter box asset number through the ammeter address to realize household-box relation identification; s3, extracting a load transient event sequence of each table box node and each table transformer node, and representing each event by adopting a multidimensional feature vector; the clock deviation among the sequences is leveled by a se