A power-off power-on based substation area identification method

Abstract

The present application relates to the technical field of power grid, and particularly relates to a transformer area identification method based on power-off and power-on, comprising the following steps: a data acquisition step: connecting an external gateway module to a state grid electric meter to collect electric data of the electric meter; a high-frequency data monitoring step: monitoring and recording power-on and power-off events at high frequency; a high-frequency time synchronization correction step: synchronizing high-frequency time of the external gateway module and the electric meter; a high-frequency data processing step: edge networking the gateway module and constructing an edge data calculation center; comparing and analyzing the electric data with the high-frequency power-on and power-off events, and then reconstructing transformer area attribution of each metering point; an anti-interference shielding step: performing anti-interference shielding processing; and a transformer area model construction step: constructing a transformer area model according to the reconstruction processing result. The present application can quickly and accurately identify transformer areas and construct transformer area models, and does not damage existing distribution lines and structures and does not need to replace equipment, with low installation cost.

Description

Technical Field

[0001] This invention relates to the field of power grid technology, and more specifically to a method for identifying transformer substations based on power outages and power restorations. Background Technology

[0002] In a power system, a distribution area refers to the power supply range or region of a single transformer. The establishment and accuracy of distribution area models are essential for energy consumption analysis. However, currently, industrial and commercial enterprises lack awareness of standardized management of distribution areas. Firstly, industrial and commercial enterprises have a large number of low-voltage distribution areas, and their models are complex. Secondly, with the handover of ownership in industrial and commercial enterprises, the connection and disconnection of power during operation will change the distribution area models. This makes it difficult to clarify the distribution area models later, requiring a significant amount of manpower.

[0003] There are two existing methods to solve the above problems or defects: characteristic current area identification scheme and power line carrier area identification scheme.

[0004] Characteristic current transformer area identification scheme: This scheme requires equipment to identify transformer areas based on pulse current, which requires the modification of power distribution equipment, resulting in high costs. Moreover, for lines in harsh environments such as long distances and severe interference, the identification success rate is not high, making it impossible to accurately establish transformer area models.

[0005] Power line carrier identification scheme: This scheme uses carrier communication between the secondary and primary sides of the distribution transformer. However, for lines in harsh environments such as long distances and severe interference, the power line carrier signal may not be able to be transmitted effectively, making it impossible to accurately establish the distribution area model. Summary of the Invention

[0006] The technical problem solved by this invention is to provide a transformer substation identification method based on power outage and power-on, which can quickly and accurately identify transformer substations and build accurate transformer substation models, without damaging existing power distribution lines and structures or requiring equipment replacement, and with low installation costs.

[0007] The basic solution provided by this invention is a method for identifying transformer substations based on power-off and power-on cycles, comprising the following steps:

[0008] Data acquisition steps: Connect an external gateway module to the State Grid electricity meters at various metering points in multiple distribution areas to collect the electricity consumption data of the meters;

[0009] High-frequency data monitoring steps: Analyze the power consumption data collected by the external gateway module, analyze and record power-on and power-off events;

[0010] High-frequency time synchronization calibration steps: Perform high-frequency time synchronization between the external gateway module and the built-in clock module of the electricity meter;

[0011] High-frequency data processing steps: connect the external gateway modules of each metering point to the edge network and build an edge data computing center; receive and store the power consumption data provided by the external gateway modules, compare and analyze the power consumption data and historical data with high-frequency power-on and power-off events, and then reconstruct the distribution area of ​​each metering point based on the analysis results;

[0012] The steps for constructing the transformer substation model are as follows: Construct the transformer substation model based on the reconstruction results of the substation affiliation of each metering point.

[0013] Furthermore, the high-frequency data processing step includes the following steps:

[0014] By using the edge data computing center, the power consumption data provided by several external gateway modules are jointly analyzed to determine whether it is a large-scale power outage or a small-scale power outage.

[0015] When a small-scale power outage or power failure is identified, all external gateway modules corresponding to the power-on and power-off events are temporarily stored in the cache area of ​​the suspected same transformer area, based on the time of the power-on and power-off events.

[0016] Analyze the historical data of each external gateway module temporarily stored in the cache to see if there are any power outage or interruption events. Based on the power outage or interruption events, determine whether they have been assigned to a specific distribution area. If they have been assigned to another distribution area, remove the corresponding external gateway module from the cache. If they have not been assigned to another distribution area, keep the corresponding external gateway module in the cache and refactor the distribution area affiliation in the cache.

[0017] Furthermore, the high-frequency data processing step includes the following steps:

[0018] Determine if multiple transformer substations experience a simultaneous power outage. If so, analyze the cause of the overall power outage based on the intersection of the multiple substations, and push the cause of the overall power outage and the corresponding external gateway module of the metering point to the business side for confirmation.

[0019] The principles and advantages of this invention are as follows:

[0020] 1. In commercial operations, changes in metering points caused by transformer maintenance, distribution area shutdowns, installation of power equipment, or sudden power outages will all require distribution area structure reconstruction. This solution connects State Grid meters to an external gateway module. Millisecond-level analysis of power outage and restoration events is possible, ultimately identifying the actual distribution area where the power consumption node is located. Time synchronization via the external gateway module ensures high accuracy in power data analysis and processing. Combined with high-frequency command processing and analysis, distribution area identification can be performed quickly and accurately.

[0021] 2. This solution has anti-interference characteristics and will not have positioning deviations due to circuit complexity, distance, or harsh environment. It has a high positioning accuracy, so as to build an accurate transformer area model.

[0022] 3. This solution primarily relies on an external gateway module connected to the State Grid electricity meter, thus allowing for flexible installation and removal without damaging existing power distribution lines and structures. Therefore, it eliminates the need for excessive time, materials, and manpower for upgrades and modifications, significantly reducing costs. Attached Figure Description

[0023] Figure 1 This is a flowchart of a method for identifying transformer substations based on power-off and power-on cycles, according to an embodiment of the present invention. Detailed Implementation

[0024] The following detailed description illustrates the specific implementation method:

[0025] The basic implementation examples are as follows: Figure 1 As shown: A method for identifying transformer substations based on power-off and power-on cycles, comprising the following steps:

[0026] Data acquisition steps: An external gateway module is connected to the State Grid electricity meters at various metering points within multiple distribution areas to collect the electricity consumption data of the meters. The external gateway module includes: a 4G module, which is used to read and transmit the electricity consumption data from the smart meters; the 4G module is connected to a power system, which is used to convert AC power to DC power; the power system is connected to a supercapacitor, which is used to store electrical energy and provide power during power outages. The supercapacitor provides power for 30 seconds, which is sufficient time to report the electricity consumption data from the smart meters after a power outage. This prevents insufficient power supply time for data reporting while avoiding excessively long power supply times that would increase related costs. The power system operates at 220V, which is compatible with the operating voltage of various electronic components and can prevent damage to these components.

[0027] The 4G module is connected to an RTC clock module, which provides time information to the gateway. The RTC clock module provides accurate time information to ensure the validity of the electricity consumption data read from the smart meter. The 4G module is also connected to an RS485 interface, which transmits the electricity consumption data from the smart meter. This provides a communication interface between the gateway and the smart meter, facilitating data transmission and enhancing communication reliability. Finally, the 4G module is connected to a memory, which stores the electricity consumption data from the smart meter. This memory can store the read electricity consumption data, including configuration parameters and log functions, allowing for direct retrieval after a power outage.

[0028] High-frequency data monitoring steps: Analyze the power consumption data collected by the external gateway module, analyze and record power-on and power-off events; in this embodiment, the external gateway module can achieve millisecond-level data monitoring, improve the accuracy of data detection, and provide data support for subsequent reconstructing of transformer area affiliation and building transformer area models.

[0029] High-frequency time synchronization calibration steps: The external gateway module and the electricity meter are synchronized at a high frequency. Each electricity meter has a built-in clock module, but the built-in clock can be affected by insufficient battery power, leading to time zone inconsistencies. Power outages, network outages, or settings missynchronization can also easily cause time discrepancies. Time synchronization via an external gateway module ensures high accuracy in electricity data analysis and processing. Combined with high-frequency command processing and analysis, transformer substation identification can be performed quickly and accurately.

[0030] High-frequency data processing steps: Connecting the external gateway modules of each metering point to the edge network and constructing an edge data computing center; receiving and storing electricity consumption data provided by the external gateway modules, comparing and analyzing the electricity consumption data and historical data with high-frequency power-on and power-off events, and then reconstructing the distribution area affiliation of each metering point based on the analysis results; the high-frequency data processing steps include the following steps:

[0031] By using the edge data computing center, the power consumption data provided by several external gateway modules are jointly analyzed to determine whether it is a large-scale power outage or a small-scale power outage.

[0032] When a small-scale power outage or power failure is identified, all external gateway modules corresponding to the power-on and power-off events are temporarily stored in the cache area of ​​the suspected same transformer area, based on the time of the power-on and power-off events.

[0033] Analyze the historical data of each external gateway module temporarily stored in the cache to see if there are any power outage or interruption events. Based on the power outage or interruption events, determine whether they have been assigned to a specific distribution area. If they have been assigned to another distribution area, remove the corresponding external gateway module from the cache. If they have not been assigned to another distribution area, keep the corresponding external gateway module in the cache and refactor the distribution area affiliation in the cache.

[0034] Determine if multiple transformer substations experience a simultaneous power outage. If so, analyze the intersection points of these substations to identify the cause of the overall power outage. Then, push the cause of the overall power outage and the corresponding external gateway module of the metering point to the service end for confirmation. A simultaneous power outage in multiple substations may be caused by circuit switching in the interconnection cabinet or a complete power failure of a particular transformer.

[0035] Anti-interference shielding steps: Perform anti-interference shielding treatment on the external gateway module;

[0036] The steps for constructing the transformer substation model are as follows: Construct the transformer substation model based on the reconstruction results of the substation affiliation of each metering point.

[0037] In typical scenarios for transformer substation identification, transformers are shut down in a planned and sequential manner. However, this solution allows for rapid and accurate identification of substations without the need for additional monitoring sensors, simply by altering the power supply structure.

[0038] The above are merely embodiments of the present invention. Commonly known structures and characteristics are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the field prior to the application date or priority date, are aware of all existing technologies in that field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can, under the guidance of this application, improve and implement this solution in combination with their own capabilities. Some typical known structures or methods should not be obstacles for those skilled in the art to implement this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the structure of the present invention. These should also be considered within the scope of protection of the present invention, and will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A power-down power-up based identification method of a substation, characterized in that, Comprise the following steps: Data acquisition step: connect external gateway module on the state grid meter of each metering point in multiple transformer areas, collect power consumption data of the meter; High-frequency data monitoring step: according to the power consumption data collected by the external gateway module, analyze the power-on and power-off events and record them; High-frequency time synchronization step: synchronize the external gateway module and the built-in clock module in the meter at high frequency; High-frequency data processing step: edge networking of external gateway modules of each metering point, and construction of edge data computing center; And receive and store the power consumption data provided by the external gateway module, and compare the power consumption data and the historical data of the power consumption data with the high-frequency power-on and power-off events, and then reconstruct the transformer area attribution of each metering point according to the analysis result; Through the edge data computing center, jointly analyze the power consumption data provided by the external gateway module, and analyze and judge whether it is large-scale power failure or small-scale power failure; When judging as small-scale power failure, according to the time of power-on and power-off events, all corresponding external gateway modules are classified into the cache area of suspected same transformer area for temporary storage; Analyze whether there is a power-off history event in the historical data of each external gateway module temporarily stored in the cache area, and determine whether it is in the determined transformer area according to the power-off history event. If it has been inducted into other transformer areas, the corresponding external gateway module will be excluded from the cache area. If it is not inducted into other transformer areas, the corresponding external gateway module will be kept in the cache area, and the cache area will be reconstructed for transformer area attribution; Transformer area model construction step: according to the reconstruction result of the transformer area attribution of each metering point, construct the transformer area model.

2. The method for identifying a subarea based on power-on and power-off according to claim 1, characterized in that: The high-frequency data processing step comprises the following steps: Determine whether there is a common power failure in multiple transformer areas, if so, analyze the cause of the overall power failure according to the intersection of multiple transformer areas, and push the cause of the overall power failure and the corresponding metering point external gateway module to the business end for confirmation.

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