A 10kV power carrier topology identification method and device based on virtual ID and ad hoc network technology

Abstract

This invention belongs to the field of power system distribution network automation technology. It discloses a 10kV power line carrier topology identification method based on virtual ID and self-organizing network technology. This method achieves distributed collaborative identification based on intelligent topology terminals deployed at various nodes of the switching station, eliminating the need for centralized control from a master station. The core of the method includes four steps: virtual ID adaptive networking, signal strength acquisition and topology association modeling, load feature acquisition and time-series comparison verification, and topology fusion and dynamic updating. Each step is executed sequentially, forming a closed-loop dynamic verification mechanism. This invention achieves accurate physical topology identification of 10kV switching stations without master station dependence and through non-intrusive deployment; simultaneously, it enables real-time dynamic updating and autonomous verification of the topology, improving the anti-interference capability and dynamic adaptability of topology identification, and providing accurate topology data support for distribution network scheduling and fault location.

Description

Technical Field

[0001] This invention belongs to the field of power system distribution network automation technology, specifically relating to a 10kV power line carrier topology identification method and device based on virtual ID and self-organizing network technology. It is applicable to the power line carrier communication network of medium-voltage distribution network (10kV), and can accurately identify the physical topology of distribution lines, supporting lean operation and maintenance of distribution network and rapid fault location. Background Technology

[0002] 10kV switching stations are core nodes in the distribution network, undertaking critical functions such as line branching, fault isolation, and load transfer. The accuracy of their internal line topology directly determines the reliability of distribution network scheduling, fault location, and self-healing control. Currently, the topology identification and maintenance of 10kV switching stations mainly relies on manual surveying combined with traditional technical solutions, which have many technical shortcomings and can no longer meet the development needs of smart distribution networks. Specific problems are as follows: 1. Manual maintenance is inefficient, prone to errors, and lagging in updating. Traditional switchgear topology diagrams rely entirely on manual on-site surveys and mapping. However, the internal lines of switchgear are dense and the wiring methods are complex, making manual mapping prone to human error. At the same time, there are dynamic changes such as load increases and decreases, line modifications, and switch actions during the operation of the distribution network. The manual topology updates are highly lagging, which can easily lead to discrepancies between the topology diagram and the physical reality, resulting in problems such as misjudgment of distribution network scheduling and delays in fault repair.

[0003] 2. Existing topology identification technology solutions have poor adaptability and high implementation costs. The topology identification solutions proposed in the industry have obvious technical limitations and cannot be adapted to the actual operation scenarios of 10kV switching stations: (1) Identification solutions based on smart meter measurement data rely on high-density meter deployment and synchronous data collection. However, there are many branches inside the switching station and data is easily lost, which can easily cause topology chain breakage errors; (2) Active detection solutions such as impedance spectrum detection require power interruption to install special detection equipment, which has high engineering implementation costs and is seriously affected by line parasitic parameters, resulting in low accuracy of identification results; (3) Power line carrier communication identification solutions are significantly affected by multipath effects and harmonic distortion. The mapping relationship between channel characteristics and topology is easily distorted, resulting in insufficient identification reliability. 3. The carrier signal attenuation characteristics of different power distribution lines are affected by multiple factors such as conductor type, erection method, weather conditions and load status. It is difficult to guarantee the accuracy of inferring physical topology relationship by simply relying on geographical location.

[0004] Therefore, there is an urgent need for a method and device that can automatically identify the physical topology of 10kV distribution lines using existing carrier terminals without requiring manual surveys or additional hardware. Summary of the Invention

[0005] The purpose of this invention is to provide a 10kV power line carrier topology identification method and device based on virtual ID and self-organizing network technology, which realizes accurate identification of the physical topology of 10kV switching stations without master station dependence and non-intrusive deployment; at the same time, it realizes real-time dynamic updating and autonomous verification of the topology, improving the anti-interference capability and dynamic adaptability of topology identification.

[0006] To achieve the above objectives, the technical solution adopted in this invention consists of two parts: the first is a 10kV power line carrier topology identification method (or 10kV switchgear intelligent topology line identification method) based on virtual ID and self-organizing network technology; the second is a 10kV power line carrier topology identification device (or intelligent topology line identification device) that implements this method, completing the identification and dynamic updating of the switchgear topology lines. These are described in detail below: I. A 10kV power line carrier topology identification method based on virtual ID and self-organizing network technology. This method achieves distributed collaborative identification based on intelligent topology terminals deployed at each node of the switching station, without the need for centralized control from a master station. The core includes four steps: virtual ID adaptive networking, signal strength acquisition and topology association modeling, load feature acquisition and time-series comparison verification, and topology fusion and dynamic updating. Each step is executed sequentially and forms a closed-loop dynamic verification mechanism. The specific steps are as follows: Step S1, Virtual ID adaptive networking: 1) Pre-configure a unique virtual ID for each smart topology terminal deployed in the outgoing switches and branch nodes of the switchgear. The virtual ID contains three core pieces of information: device type (outgoing switch / branch node), installation location code, and communication frequency band parameters, to ensure the uniqueness and identifiability of the terminal's identity. 2) After the terminal is connected to the power grid, it automatically starts the built-in medium-voltage carrier communication module and continuously sends network access broadcast frames containing its own virtual ID in the preset frequency band; 3) After receiving the network broadcast frame, the smart topology terminal of the neighboring node parses and authenticates the virtual ID in the frame. After successful authentication, it establishes a point-to-point bidirectional communication link with the sender. At the same time, the receiving terminal records the virtual ID, communication timestamp and RSSI (Received Signal Strength Indicator) of the neighboring node in real time, and forms an initial neighbor list based on the above information. 4) Adaptive networking algorithm is used to dynamically optimize the communication topology: When a new terminal is added, relay broadcast is completed through the neighbor list of the already connected terminal to realize the rapid network access and communication link update of the new node; when a node experiences a communication interruption, the reconnection mechanism of the neighboring node is automatically triggered to ensure the overall stability of the network; the entire networking process does not require the laying of additional communication lines, and carrier communication is achieved by relying on the existing power lines.

[0007] Step S2, Signal strength acquisition and topology association modeling: 1) Each smart topology terminal collects carrier signals sent by other terminals at a preset period T1 (e.g., 30 seconds) and extracts the Received Signal Strength Indication (RSSI) value; the RSSI values ​​between all pairs of terminals are recorded as a matrix R[i,j], where i and j are the virtual IDs of the terminals; Based on the inherent transmission characteristics of 10kV lines, a mathematical model for signal attenuation is established, and the model formula is as follows: In the formula: For signal reception strength, The signal received strength (calibrated value) is used as a reference distance, k is the fixed signal attenuation coefficient of the 10kV line (typically 2.0~4.0, the specific value is determined according to the line construction method and conductor type), and L is the actual line length between the two nodes. Environmental disturbance correction value ( Typical values ​​range from -5dBm to +5dBm, used to compensate for signal deviations caused by strong electromagnetic interference. 2) The RSSI value acquired in a single acquisition is sampled multiple times and averaged to eliminate measurement errors caused by random environmental interference and obtain an effective RSSI value; 3) Based on the device installation location code corresponding to each terminal's virtual ID, establish a one-to-one mapping relationship of "virtual ID pair → valid RSSI value → line distance between nodes"; sort adjacent nodes according to the size of the valid RSSI value and determine the upstream and downstream connection relationship of the nodes: the stronger the signal reception strength, the closer the physical distance between the two nodes, and prioritize the direct physical connection relationship, thus forming a preliminary draft of the topology association relationship.

[0008] Step S3, Load Feature Collection and Time Series Comparison Verification: This step verifies the validity of the topological relationships initially determined in Step S2. By comparing the similarity of load time series features, falsely identified indirect connections are eliminated, as detailed below: 1) Each smart topology terminal collects the timing waveform data of its local load current or power at a preset period T2 (e.g., 5 minutes); and discretizes the load timing waveform into a load timing feature vector F; The vector formula is: Where: F is the load time sequence characteristic vector, I(t) is the line current at time t, U(t) is the line voltage at time t, P(t) is the active power at time t, and Q(t) is the reactive power at time t. 2) For all node pairs initially identified as directly physically connected in step S2, extract load time-series feature vector data within the same time window (preferably 1 minute). Using the Dynamic Time Warping (DTW) algorithm, compare the similarity of the load time-series feature vectors of any two terminals and calculate the cumulative distance of the optimal alignment path. The recursive formula for the DTW algorithm is: in: For nodes The optimal cumulative distance between node j and node j For nodes The optimal cumulative distance between -1 and node j For nodes The optimal cumulative distance between nodes j-1 For nodes The optimal cumulative distance between node j-1 and node j-1 For nodes The Euclidean distance between node j and its load feature vector; 3) Based on the actual load operation characteristics of the 10kV switchgear, a load similarity threshold θ=0.85 is preset: when the load similarity of a node pair is ≥θ, the direct physical connection relationship of the node pair is verified; when the load similarity is <θ, the node pair is determined to be an indirect connection or a misjudgment, and the connection relationship is removed from the initial draft of the topology relationship to obtain the verified topology relationship.

[0009] Step S4, Topology fusion and dynamic update: Based on the combined results of the RSSI-based topology association modeling in step S2 and the DTW-based load timing verification in step S3, a topology fusion judgment is performed: (1) If two terminals are determined to be directly physically connected in step S2 and their load timing characteristics are highly similar in step S3, then the two terminals are confirmed to be directly connected and the topology edge is output. (2) If two terminals are determined to be directly physically connected in step S2, but the load timing characteristics are not similar in step S3, then the terminal is re-verified in steps S2-S3 - the acquisition period is extended and the data is re-acquired. If the results are consistent after three re-verifications, then the result of step S2 is processed. (3) If two terminals are not determined to be directly physically connected in step S2, but have highly similar load timing characteristics in step S3, then the terminal pair is marked and manually confirmed to have special circumstances such as underground cables or concealed works. After traversing all terminal pairs, a complete physical topology diagram of the power distribution line is obtained and stored in the topology storage module in the form of an adjacency list or adjacency matrix for the power distribution master station to call.

[0010] II. A 10kV power line carrier topology identification device (or a 10kV switchgear intelligent topology line identification device) implementing the above method: This device features a distributed architecture, eliminating the need for a master station. Its core consists of two parts: an intelligent topology terminal and a topology storage and output module. The intelligent topology terminal and the topology storage and output module are connected via a plug-in interface. The hardware components and functions of each part are as follows: 1. The intelligent topology terminal is a field-deployed device, installed one-to-one at each outgoing switch and branch node of the switching station. The terminal has an integrated sealed structure, adaptable to the outdoor operating environment of the switching station with strong electromagnetic interference. It has four core units: a medium-voltage carrier communication module, an electrical quantity acquisition module, and a data processing unit. The functions and connections of each unit are as follows: 1) Medium-voltage carrier communication module: This is the communication unit of the terminal. It relies on the existing 10kV power line to realize carrier communication, complete the transmission of network access broadcast frames, receive signals from adjacent nodes, and collect RSSI values. It is bidirectionally electrically connected to the data processing unit, transmits the collected RSSI values ​​to the data processing unit, and receives communication control commands from the data processing unit. 2) Electrical quantity acquisition module: This is the terminal's sensing and acquisition unit, which has built-in current, voltage, and power sensors. It collects line load parameters at a sampling frequency of 10Hz and is electrically connected to the data processing unit to transmit the collected load data to the data processing unit. 3) Data Processing Unit: This is the core control unit of the intelligent topology terminal. It adopts an industrial-grade MCU chip and is electrically connected to the medium-voltage carrier communication module and the electrical quantity acquisition module. It is used to execute virtual ID adaptive networking algorithm, signal strength attenuation modeling, DTW load similarity calculation, graph theory topology fusion algorithm, etc., and triggers topology re-verification and update process to complete the core operation of distributed collaborative identification.

[0011] 2. Topology storage and output module: The topology storage and output module is integrated into the intelligent topology terminal of the core node of the switchgear (such as the No. 1 outgoing switch terminal), and is bidirectionally electrically connected to the data processing unit of the intelligent topology terminal. Its functions include: 1) Storage function: Stores the complete physical topology map of the switchgear after fusion and dynamic updates, and supports the tracing and querying of historical topology data; 2) Output function: Configure standard power distribution automation system communication interfaces (such as RS485, Ethernet) to upload real-time physical topology diagrams to the power distribution network master station, and support local visualization display (such as connecting to a display screen to display the topology diagram in real time), so as to realize local and remote sharing of topology data.

[0012] The key innovations of this invention, compared with the prior art, are as follows, and these innovations work together to form a complete technical solution: 1. A distributed adaptive networking technology based on virtual ID and medium-voltage carrier is proposed. It does not require the distribution network master station or additional communication lines. It enables nodes to form autonomous networks and adapt dynamically based on existing 10kV power lines, which greatly reduces the cost of equipment deployment and engineering implementation. 2. Construct a dual verification mechanism of signal strength attenuation modeling + load time sequence similarity comparison to overcome the technical limitations of existing single-dimensional identification. By determining physical distance through signal strength and verifying connection validity through load comparison, the influence of strong electromagnetic interference and random noise in the switchgear is effectively eliminated, and the accuracy of topology identification is improved. 3. Design a closed-loop topology dynamic update and autonomous verification mechanism, which can track topology dynamic changes such as switch actions and line switching in real time, with an update delay of ≤1 minute. At the same time, it can automatically trigger re-verification when the load or signal is abnormal, adapting to the dynamic operation scenario of 10kV switchgear. 4. Adopting a non-intrusive deployment method, the intelligent topology terminal is plug-and-play and can be installed and debugged without interrupting power supply, which greatly reduces the difficulty of project implementation and improves on-site deployment efficiency.

[0013] The beneficial effects of the present invention are as follows: The method and apparatus of the present invention, through the above technical solutions, effectively solve all the defects of the prior art, and achieve significant improvements in identification accuracy, deployment convenience, dynamic adaptability, and anti-interference ability. At the same time, it possesses outstanding engineering application value. Specific beneficial effects are as follows: 1. High accuracy of topology identification: Through the triple guarantee of "virtual ID networking to lock node association, signal strength modeling to determine physical distance, and load comparison to verify connection relationship", the topology identification accuracy rate is ≥99%, which is significantly better than the traditional single-dimensional identification scheme and effectively solves the problems of manual surveying error and misjudgment of technical solution; 2. Non-intrusive deployment with high implementation efficiency: Based on existing 10kV lines, medium-voltage carrier communication is achieved. The intelligent topology terminal is plug-and-play, requiring no power interruption or additional communication line laying. Equipment installation and commissioning time is reduced by more than 60%, significantly reducing the difficulty and cost of project implementation. 3. It has strong dynamic adaptability and high real-time update capability. It supports real-time response to topology changes such as node addition and removal, line switching, and switch action. The topology update delay is ≤1 minute, which can realize local dynamic update of the switch station topology and completely solve the problem of lag in manual topology update. 4. It has outstanding anti-interference ability and high operational stability. By averaging multiple samples, it eliminates random signal interference and offsets the influence of electromagnetic interference by comparing load timing. Even in the complex operating environment of strong electromagnetic interference in 10kV switchgear, it can still maintain stable topology identification performance without misjudgment or omission. 5. Significant engineering application value: Improved distribution network reliability, greatly reduced workload of manual topology mapping and maintenance, and reduced the frequency of manual maintenance from once a month to once a quarter; at the same time, it provides accurate real-time topology data for distribution network scheduling and fault location, shortening fault location and repair time by more than 30%, and significantly improving the reliability of distribution network power supply and the level of intelligent scheduling. Detailed Implementation

[0014] A 10kV switching station contains 3 outgoing switches and 8 branch nodes. The original topology relied on manual maintenance and contained 2 wiring errors, leading to delays in fault location. The proposed solution is used for modification: 1. Install smart topology terminals at each outgoing switch and branch node, and pre-configure virtual IDs (e.g., “CK-01-10kV-001” represents outgoing switch No. 1). 2. After the terminal connects, it automatically starts adaptive networking and completes the connection of all nodes within 3 minutes to form an initial neighbor list; 3. Real-time acquisition of signal strength and load data; calculation of line length between nodes using a signal attenuation model; and verification of connection relationships using load time sequence similarity (both ≥ 0.88). 4. Generate an accurate physical topology diagram, automatically identify and correct the two existing wiring errors; subsequently, when a branch node switch is activated, the system completes the topology update within 15 seconds and synchronizes it to the distribution automation master station.

[0015] The results show that the topology identification accuracy rate reached 99.5%, the frequency of manual maintenance was reduced from once a month to once a quarter, and the fault location time was shortened from an average of 45 minutes to 12 minutes.

[0016] This invention establishes distributed communication associations among nodes through virtual ID adaptive networking technology, and forms a dual verification mechanism by combining signal strength attenuation feature modeling and load time sequence comparison verification. This enables accurate identification of the physical topology of 10kV switching stations without master station dependence and through non-intrusive deployment. At the same time, it realizes real-time dynamic updates and autonomous verification of the topology, improves the anti-interference capability and dynamic adaptability of topology identification, and provides accurate topology data support for distribution network scheduling and fault location.

Claims

1. A method for identifying the topology of a 10kV power line carrier based on virtual ID and self-organizing network technology, characterized in that... Includes the following steps: Step S1, Virtual ID adaptive networking: 1) Pre-configure a unique virtual ID for each smart topology terminal deployed in the outgoing switches and branch nodes of the switchgear. The virtual ID contains three core pieces of information: device type (outgoing switch / branch node), installation location code, and communication frequency band parameters, to ensure the uniqueness and identifiability of the terminal's identity. 2) After the terminal is connected to the power grid, it automatically starts the built-in medium-voltage carrier communication module and continuously sends network access broadcast frames containing its own virtual ID in the preset frequency band; 3) After receiving the network broadcast frame, the smart topology terminal of the neighboring node parses and authenticates the virtual ID in the frame. After successful authentication, it establishes a point-to-point bidirectional communication link with the sender. At the same time, the receiving terminal records the virtual ID, communication timestamp and RSSI of the neighboring nodes in real time, and forms an initial neighbor list based on the above information. 4) Adaptive networking algorithm is used to dynamically optimize the communication topology: When a new terminal is added, relay broadcast is completed through the neighbor list of the already connected terminal to realize the rapid network access and communication link update of the new node; when a node experiences a communication interruption, the reconnection mechanism of neighboring nodes is automatically triggered to ensure the overall stability of the network. The entire networking process does not require laying additional communication lines; it relies on existing power lines to achieve carrier communication. Step S2, Signal strength acquisition and topology association modeling: 1) Each smart topology terminal collects carrier signals sent by other terminals at a preset period T1 and extracts the received signal strength indication value; the RSSI values ​​between all pairs of terminals are recorded as a matrix R[i,j], where i and j are the virtual IDs of the terminals; Based on the inherent transmission characteristics of 10kV lines, a mathematical model for signal attenuation is established, and the model formula is as follows: In the formula: For signal reception strength, The signal received strength is used as a reference distance, k is a fixed signal attenuation coefficient for a 10kV line, with typical values ​​ranging from 2.0 to 4.0, and L is the actual line length between the two nodes. This is a correction value for environmental disturbances. Typical values ​​range from -5dBm to +5dBm, used to compensate for signal deviations caused by strong electromagnetic interference. 2) The RSSI value acquired in a single acquisition is sampled multiple times and averaged to eliminate measurement errors caused by random environmental interference and obtain an effective RSSI value; 3) Based on the device installation location code corresponding to each terminal's virtual ID, establish a one-to-one mapping relationship of "virtual ID pair → valid RSSI value → line distance between nodes"; sort adjacent nodes according to the size of the valid RSSI value and determine the upstream and downstream connection relationship of the nodes: the stronger the signal reception strength, the closer the physical distance between the two nodes, and prioritize the direct physical connection relationship, thus forming a preliminary draft of the topology relationship; Step S3, Load Feature Collection and Time Series Comparison Verification: This step verifies the validity of the topological relationships initially determined in Step S2. By comparing the similarity of load time series features, falsely identified indirect connections are eliminated, as detailed below: 1) Each smart topology terminal collects the timing waveform data of the load current or power at a preset period T2; and discretizes the load timing waveform into a load timing feature vector F; The vector formula is: Where: F is the load time sequence characteristic vector, I(t) is the line current at time t, U(t) is the line voltage at time t, P(t) is the active power at time t, and Q(t) is the reactive power at time t. 2) For all node pairs initially identified as directly physically connected in step S2, extract load time-series feature vector data within the same time window. Using the Dynamic Time Warping (DTW) algorithm, compare the similarity of the load time-series feature vectors of any two terminals and calculate the cumulative distance of the optimal alignment path. The recursive formula for the DTW algorithm is: in: For nodes The optimal cumulative distance between node j and node j For nodes The optimal cumulative distance between -1 and node j For nodes The optimal cumulative distance between nodes j-1 For nodes The optimal cumulative distance between node j-1 and node j-1 For nodes The Euclidean distance between node j and its load feature vector; 3) Based on the actual load operation characteristics of the 10kV switchgear, a load similarity threshold θ=0.85 is preset: when the load similarity of a node pair is ≥θ, the direct physical connection relationship of the node pair is verified; when the load similarity is <θ, the node pair is determined to be an indirect connection or a misjudgment, and the relationship is removed from the initial draft of the topology relationship to obtain the verified topology relationship. Step S4, Topology fusion and dynamic update: Based on the combined results of the RSSI-based topology association modeling in step S2 and the DTW-based load timing verification in step S3, a topology fusion judgment is performed: (1) If two terminals are determined to be directly physically connected in step S2 and their load timing characteristics are highly similar in step S3, then the two terminals are confirmed to be directly connected and the topology edge is output. (2) If two terminals are determined to be directly physically connected in step S2, but the load timing characteristics are not similar in step S3, then the terminal is re-verified in steps S2-S3 - the acquisition period is extended and the data is re-acquired. If the results are consistent after three re-verifications, then the result of step S2 is processed. (3) If two terminals are not determined to be directly physically connected in step S2, but have highly similar load timing characteristics in step S3, then the terminal pair is marked and manually confirmed to have special circumstances such as underground cables or concealed works. After traversing all terminal pairs, a complete physical topology diagram of the power distribution line is obtained and stored in the topology storage module in the form of an adjacency list or adjacency matrix for the power distribution master station to call.

2. A 10kV power line carrier topology identification device that implements the above method, characterized in that... It consists of two parts: an intelligent topology terminal and a topology storage and output module. The intelligent topology terminal and the topology storage and output module are connected via a plug-in interface. The hardware composition and functions of each part are as follows:

1. The intelligent topology terminal is a field-deployed device, installed one-to-one at each outgoing switch and branch node of the switching station. The terminal has an integrated sealed structure, adapting to the strong electromagnetic interference of the outdoor operating environment of the switching station. It has four core units: a medium-voltage carrier communication module, an electrical quantity acquisition module, and a data processing unit. The functions and connections of each unit are as follows: 1) Medium-voltage carrier communication module: This is the communication unit of the terminal. It relies on the existing 10kV power line to realize carrier communication, complete the transmission of network access broadcast frames, receive signals from adjacent nodes, and collect RSSI values. It is bidirectionally electrically connected to the data processing unit, transmits the collected RSSI values ​​to the data processing unit, and receives communication control commands from the data processing unit. 2) Electrical quantity acquisition module: This is the terminal's sensing and acquisition unit, which has built-in current, voltage, and power sensors. It collects line load parameters at a sampling frequency of 10Hz and is electrically connected to the data processing unit to transmit the collected load data to the data processing unit. 3) Data processing unit: This is the core control unit of the intelligent topology terminal. It adopts an industrial-grade MCU chip and is electrically connected to the medium-voltage carrier communication module and the electrical quantity acquisition module. It is used to execute virtual ID adaptive networking algorithm, signal strength attenuation modeling, DTW load similarity calculation, graph theory topology fusion algorithm, etc., and triggers topology re-verification and update process to complete the core operation of distributed collaborative identification.

2. Topology storage and output module: The topology storage and output module is integrated into the intelligent topology terminal of the core node of the switching station, and is bidirectionally electrically connected to the data processing unit of the intelligent topology terminal. Its functions include: 1) Storage function: Stores the complete physical topology map of the switchgear after fusion and dynamic updates, and supports the tracing and querying of historical topology data; 2) Output function: Configured with a standard power distribution automation system communication interface, it can upload real-time physical topology map to the power distribution network master station, and at the same time support local visualization display, realizing local and remote sharing of topology data.

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