District physical topology identification method based on dual-mode communication signal strength

Abstract

The invention relates to the technical field of electric power communication, and discloses a district physical topology identification method based on dual-mode communication signal strength, comprising the following steps: S1, building a district network; s2, topology identification is started, self initialization is completed, and necessary environment preparation before topology identification is carried out; s3, adding STA operation participation data one by one until all STA data are added; s4, identification calculation is started, branch calculation is carried out through HPLC signals of neighbor STAs by adopting a mode of selecting a rated threshold value, meter box calculation is carried out through HRF signals of the neighbor STAs, and relevancy ranking is determined; and S5, obtaining a topology result, and ending identification. According to the method, identification of the physical topology of the transformer area can be completed without additional equipment and manual intervention, and the method is safe, convenient and high in practicability. In the recognition process, the method is not affected by load voltage and current changes and the length of a power line, and compared with an existing impedance calculation and time delay calculation scheme, the recognition accuracy is high.

Description

Technical Field

[0001] The present invention relates to the technical field of power communication, and particularly to a method for identifying the physical topology of a low-voltage power distribution area based on the signal strength of dual-mode communication. Background Art

[0002] With the continuous advancement of the construction of China's power system and the rapid development of intelligent power grid technology, the importance of identifying the physical topology of low-voltage power distribution areas has become increasingly obvious. As the basis and prerequisite for the construction of intelligent power grids and other advanced applications, topology identification helps to sort out the composition structure of the power grid, the power flow path, and the mutual relationship between each sub-node. Through accurate physical topology modeling of the power distribution area, the monitoring of power quality and the management of the power system can be made more efficient, and it is also more conducive to the implementation of in-depth applications such as subsequent potential perception of power distribution area regulation.

[0003] The existing physical topology identification technologies mainly include the following methods: 1. Adding physical identification devices. This method requires manually installing separate topology identification hardware devices on the meter side, which has a large workload and will increase the data processing pressure on the terminal side.

[0004] 2. Calculating the topology through line impedance. This method collects voltage and current data of all meters at a certain moment, calculates the correlation, and then evaluates the topological relationship. The amount of data measurement is large, and due to the volatility of voltage and current easily affected by the environment, the identification accuracy is not high.

[0005] 3. Constructing the topology by calculating the node distance through time delay. This method constructs the topology through the intermediate variable of distance, but the line between nodes is not necessarily a straight line. When the difference between the length of the power line between nodes and the straight-line distance is too large, it will lead to incorrect results.

[0006] For example, in Chinese Patent CN116505659A, a method and system for identifying the topology of a power distribution area are disclosed. An intelligent circuit breaker with topology identification function is installed and numbered at each node. The area integration terminal sends a command message of topology identification type each time. After receiving the command message with the command number the same as its own number, the intelligent circuit breaker returns the topology identification result to the area integration terminal. After all the command messages of all command numbers are sent, the area integration terminal restores the topology information according to the results returned by each intelligent circuit breaker.

[0007] Another example is Chinese Patent CN118472923A, which discloses a method and system for identifying the topology of a power distribution area in a low-voltage power grid. The singular value matrix of the user voltage data matrix is calculated by the SDV algorithm, and then the phase relationship of each user is calculated and judged by the DTW distance, so as to obtain the topology of the power distribution area.

[0008] Although the above - disclosed technical solution can achieve the effect of topology recognition, it requires additional equipment, and sending separate topology - recognition messages will occupy the communication channel. Moreover, calculating through voltage, current, or delay methods still has deficiencies in recognition accuracy. Summary of the Invention

[0009] In view of the deficiencies and defects existing in the prior art, the present invention provides a method for identifying the physical topology of a distribution area based on the signal strength of dual - mode communication, which realizes the identification of branches and meter boxes in the entire distribution area, and further obtains the physical topology of the entire distribution area.

[0010] The object of the present invention can be achieved by the following technical solutions: A method for identifying the physical topology of a distribution area based on the signal strength of dual - mode communication, including a dual - mode module capable of HPLC and HRF communication, comprising the following steps: S1: Establish a distribution - area network; S2: Start topology recognition, complete its own initialization, and perform necessary environmental preparations before topology recognition; S3: Add STA operation - participating data one by one until all STA data is added completely; S4: Start recognition calculation. By adopting the method of selecting a rated threshold, perform branch calculation through the HPLC signal of neighbor STAs and perform meter - box calculation through the HRF signal of neighbor STAs to determine the relevance ranking; S5: Obtain the topology result and end the recognition.

[0011] Further, in the method for identifying the physical topology of a distribution area based on the signal strength of dual - mode communication, in step S3, the STA operation - participating data includes the own meter number and TEI number of the STA, the meter number and TEI number of neighbor STAs, and the signal strength between the own STA and neighbor STAs.

[0012] Further, in the method for identifying the physical topology of a distribution area based on the signal strength of dual - mode communication, the signal strength between the own STA and surrounding STAs includes HPLC signal strength and HRF signal strength.

[0013] Further, in the method for identifying the physical topology of a distribution area based on the signal strength of dual - mode communication, in step S4, the neighbor STA refers to an adjacent STA that can directly communicate with this STA through the HPLC or HRF channel.

[0014] Further, in the method for identifying the physical topology of a distribution area based on the signal strength of dual - mode communication, in step S4, the recognition calculation methods are divided into two types: first perform branch calculation and then meter - box calculation, and first perform meter - box calculation and then branch calculation.

[0015] Furthermore, for the method for identifying the physical topology of a power distribution area based on the signal strength of dual-mode communication, the specific steps of the "calculate branches first and then meter cabinets" method are as follows: S41a: Perform branch clustering based on the HPLC neighbors of the STA. Select strong HPLC signal neighbors of each STA by choosing a rated threshold. Traverse all STAs and recursively traverse their strong HPLC signal neighbor tables. Skip the STAs with assigned branch numbers during the recursive process until all STAs are exhausted.

[0016] S42a: Traverse all branches according to the identified number of branches. Perform meter cabinet clustering on all STAs under the same branch. Also select strong HRF signal neighbors of each STA by choosing a rated threshold. Traverse all STAs under this branch and recursively traverse their strong HRF signal neighbor tables. Skip the STAs with assigned meter cabinet numbers under this branch during the recursive process until all STAs under this branch are exhausted.

[0017] S43a: Perform meter cabinet clustering on the STAs without branch numbers. The principle is the same as in step S42a.

[0018] Furthermore, for the method for identifying the physical topology of a power distribution area based on the signal strength of dual-mode communication, the specific steps of the "calculate meter cabinets first and then branches" method are as follows: S41b: Perform meter cabinet clustering based on the HRF neighbors of the STA. Select strong HRF signal neighbors of each STA by choosing a rated threshold. Traverse all STAs and recursively traverse their strong HRF signal neighbor tables. Skip the STAs with assigned meter cabinet numbers during the recursive process until all STAs are exhausted.

[0019] S42b: From the perspective of meter cabinets according to the identified number of meter cabinets, perform clustering through the correlation between meter cabinets and based on the correlation neighbor table of meter cabinets to complete the calculation of meter cabinets under branches. Calculate the correlation between meter cabinets. Traverse all meter cabinets, and through the statistics and correlation evaluation of the HPLC neighbors of all electric meters in the selected meter cabinet belonging to other meter cabinets, determine all related meter cabinets of the selected meter cabinet and determine the ranked neighbor table.

[0020] S43b: Determine the branches for the unrecognized STAs. Through step S41b, all STAs that have obtained wireless neighbors have completed meter cabinet clustering, so branch clustering can also be completed. Therefore, in this step, for STAs that have not successfully obtained wireless neighbors but have obtained carrier neighbors, determine the branches.

[0021] S44b: Smooth the branch numbers. During the specific implementation process of step S42b, there will be branch mergers. Therefore, after the compensation in step S43b is completed, perform continuous branch number operations in this step.

[0022] Advantageous technical effects of the present invention: Based on the existing dual-mode communication module substation area, making full use of the HPLC signal and HRF signal characteristics of the STA, it is possible to realize the identification of branches and meter boxes in the entire substation area, and then complete the identification of the physical topology of the substation area. There is no need to install additional equipment, nor is it necessary to manually intervene in the identification process. It is safe, convenient, and highly practical. During the identification process, the signal characteristics of the STA are not affected by changes in the load voltage and current, and whether each STA is located in the same HPLC branch has nothing to do with the length of the power line connecting the STA. Compared with the existing impedance calculation and time-delay calculation schemes, the identification accuracy is greatly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a flowchart of an embodiment of the present invention.

[0024] Figure 2 It is a schematic diagram of the branch of the substation area line in an embodiment of the present invention.

[0025] Figure 3 It is the physical topology diagram of the substation area obtained in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0026] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and do not limit the present invention.

[0027] As Figure 1 shown, a method for identifying the physical topology of a substation area based on the signal strength of dual-mode communication disclosed in this embodiment includes a dual-mode module for HPLC and HRF communication, and includes the following steps: S1: Establish a substation area network; Specifically, the substation area is from the 4th to the 12th floors of a certain building as Figure 2 shown, where there is one branch from the 4th to the 10th floors, one branch for the 11th and 12th floors, one meter box on each floor, and 24 meters in each meter box, for a total of 216 meters.

[0028] Table 1 gives the distribution of the meter addresses in the meter boxes on each floor, specifically: Table 1 Meter Address Distribution in the Substation Area of this Embodiment S2: Start topology identification, complete its own initialization, and perform necessary environmental preparations before topology identification; S3: Add STA operation participation data, one by one, until all STA data is added; S4: Start identification calculation, adopt the method of selecting a rated threshold, perform branch calculation through the HPLC signal of the neighbor STA, perform meter box calculation through the HRF signal of the neighbor STA, and determine the relevance ranking.

[0029] Further, in this embodiment, a method of first performing branch calculation and then meter box calculation is adopted.

[0030] Further, the specific steps of the above-mentioned method of first performing branch calculation and then meter box calculation are as follows: S41a: Perform branch clustering based on the HPLC neighbors of the STA. Select strong HPLC signal neighbors of each STA by selecting a rated threshold. Traverse all STAs and recursively traverse their strong HPLC signal neighbor tables. Skip the STAs with issued branch numbers during the recursive process until all STAs are exhausted.

[0031] S42a: Traverse all branches according to the identified number of branches. Perform meter box clustering on all STAs under the same branch. Also select strong HRF signal neighbors of each STA by selecting a rated threshold. Traverse all STAs under this branch and recursively traverse their strong HRF signal neighbor tables. Skip the STAs with issued meter box numbers under this branch during the recursive process until all STAs under this branch are exhausted.

[0032] S43a: Perform meter box clustering on the STAs without branch numbers. The principle is the same as that in step S42a.

[0033] Further, in step S41a, clustering is performed based on the HPLC signal strength starting from a certain STA. If finally there is only this STA in this branch, select the branch number of the strongest HPLC signal neighbor of this STA as the branch number of this STA.

[0034] Further, in step S42a, clustering is performed based on the HRF signal strength starting from a certain STA. If finally there is only this STA in this meter box, select the meter box number of the strongest HRF signal neighbor of this STA as the meter box number of this STA.

[0035] Further, in step S42a, if the wireless neighbor table of a certain STA is successfully obtained in the last link but there is no meter box number, issue a separate meter box number for it.

[0036] S5: Obtain the topology result and the identification ends.

[0037] Based on the above steps, the physical topology of the substation area obtained in this embodiment is as Figure 3 shown. Comparing with the meter address distribution in Table 1, the identification coverage rate and accuracy rate of this embodiment both reach 100%.

[0038] The above embodiments are illustrative of the specific embodiments of the present invention, rather than limiting the present invention. Those skilled in the relevant art can make various transformations and changes without departing from the spirit and scope of the present invention to obtain corresponding equivalent technical solutions. Therefore, all equivalent technical solutions should be included in the patent protection scope of the present invention.

Claims

1. A method for identifying the physical topology of a substation based on the strength of a dual-mode communication signal, comprising a dual-mode module capable of performing HPLC and HRF communications, characterized in that: The method for identifying the physical topology of a substation area comprises the following steps: S1: Establishment of regional network; S2: Start topology recognition, complete self-initialization, and make necessary environment preparations before topology recognition; S3: Add STA operation participating data one by one until all STA data are added; S4: Start the identification calculation, adopt the method of selecting the rated threshold, perform branch calculation through the HPLC signal of the neighbor STA, perform table box calculation through the HRF signal of the neighbor STA, and determine the correlation ranking; S5: Obtain the topology result and the recognition is completed.

2. A method for identifying a physical topology of a substation based on dual-mode communication signal strength according to claim 1, characterized in that: In the step S3, the STA operation participation data includes the STA's own table number and TEI number, the table number and TEI number of the neighboring STA, and the signal strength between the STA itself and the neighboring STA.

3. A method for identifying a physical topology of a substation based on dual-mode communication signal strength according to claim 2, characterized in that: The signal intensity between the self and surrounding STA includes HPLC signal intensity and HRF signal intensity.

4. The method for identifying the physical topology of a substation based on the strength of a dual-mode communication signal according to claim 1, characterized in that: In the step S4, the neighbor STA refers to an adjacent STA that can directly communicate with the STA through the HPLC or HRF channel.

5. The method for identifying the physical topology of a substation based on the strength of a dual-mode communication signal according to claim 1, characterized in that: In step S4, the identification calculation method is divided into two methods: first branch calculation and then meter box calculation and first meter box calculation and then branch calculation.

6. A method for identifying physical topology of a substation based on dual-mode communication signal strength according to claim 5, characterized in that: The specific steps of the method of first branch calculation and then meter box calculation are: S41a: traverse all STAs, screen out the strong HPLC signal neighbors of each STA and recursively calculate its strong HPLC signal neighbor table. In the recursive process, skip the STAs that have been issued branch numbers until all STAs are exhausted and branch clustering is completed; S42a: According to the number of identified branches, all STAs under all branches are traversed and their strong HRF signal neighbor tables are recursively calculated. During the recursive process, the STAs under this branch that have been issued table box numbers are skipped until all STAs are exhausted; S43a: Perform table-box clustering on STAs without branch numbers, the principle is the same as step S42a, and the table-box clustering is completed.

7. The method for identifying the physical topology of a substation based on the strength of a dual-mode communication signal according to claim 5, characterized in that: The specific steps of the method of first calculating the meter box and then calculating the branches are: S41b: traverse all STAs, filter out the strong HRF signal neighbors of each STA and recursively calculate its strong HRF signal neighbor table. In the recursive process, skip the STAs that have been issued table box numbers until all STAs are exhausted and the table box clustering is completed; S42b: according to the number of identified meter boxes, traverse all meter boxes, determine all related meter boxes of the selected meter box by counting and evaluating the correlation of the meter boxes to which the HPLC neighbors of all the electric meters in the selected meter box belong, and determine a ranking neighbor table; S43b: performing branch determination on unidentified STAs and completing branch clustering; S44b: Smoothing the branch numbers to avoid branch merging that may occur during the specific implementation of step S42b.

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