Distributed fault positioning method and system for power transmission line

Abstract

The invention discloses a power transmission line distributed fault positioning method and system, and belongs to the technical field of line faults. The method comprises the steps that monitoring nodes are generated through distributed intelligent sensing equipment, line sections are dynamically divided, and the dynamic coverage relation between the monitoring nodes and the sections is established; constructing a power transmission line digital twin platform, mapping sections and nodes, and generating a multi-source operation parameter feature cluster; and based on an error accumulation boundary function, calculating a parameter correlation degree, dynamically quantifying a correlation coefficient, and screening a strong correlation section as a fault priority positioning object. The system comprises an intelligent sensing equipment cluster module, a digital twin mapping module, a data processing module and a fault positioning module, and realizes real-time monitoring of the running state of the power transmission line and efficient positioning of faults. Through dynamic coverage relation updating, multi-source data fusion and quantitative analysis, the accuracy and efficiency of fault positioning are improved, and the method is suitable for distributed fault diagnosis of a complex power transmission network.

Description

Technical Field

[0001] The present invention relates to the technical field of line faults, and specifically to a distributed fault location method and system for transmission lines. Background Art

[0002] During the operation of transmission lines, fault location is a key technology to ensure the safe and stable operation of the power grid. Traditional fault location methods rely on centralized monitoring systems and have the following deficiencies: Inflexible monitoring coverage: The fixed section division method cannot adapt to the dynamic changes in the operating state of transmission lines, and faults in monitoring nodes are likely to lead to coverage blind spots. Insufficient multi-source data fusion: There is a lack of comprehensive analysis of multi-source electrical parameters such as voltage, current, and temperature, making it difficult to accurately identify fault characteristics. Absence of priority ranking: There is no emergency degree evaluation mechanism for fault sections, resulting in low efficiency in the allocation of operation and maintenance resources. Poor dynamic adaptability: Existing systems rely on static configurations and cannot update the association relationship between monitoring nodes and line sections in real time, leading to a decline in location accuracy.

[0003] With the development of smart grids, the complexity of transmission lines is continuously increasing. There is an urgent need for a distributed fault location technology with dynamic monitoring, multi-source data fusion, and intelligent analysis to solve the deficiencies of traditional methods in terms of flexibility, accuracy, and efficiency. Summary of the Invention

[0004] The purpose of the present invention is to provide a distributed fault location method and system for transmission lines to solve the problems raised in the above background art.

[0005] To solve the above technical problems, the present invention provides the following technical solutions: A distributed fault location system for transmission lines, which includes: an intelligent perception device cluster module, a digital twin mapping module, a data processing module, and a fault location module; The intelligent perception device cluster module is distributedly deployed on the transmission line and is used to generate monitoring nodes and collect multi-source operation parameters of the transmission line in real time; The digital twin mapping module is used to build a digital twin platform for the transmission line, establish a dynamic coverage relationship between monitoring nodes and line sections, and map the line section set and the monitoring node set; The data processing module is used to generate an actual operation parameter feature cluster and an observed operation parameter feature cluster, and calculate the parameter correlation degree based on the error accumulation boundary function; The fault location module is used to dynamically quantify the correlation coefficient, screen strongly associated line sections as the priority objects for fault location, and output the fault emergency degree ranking result.

[0006] Furthermore, the intelligent perception device cluster includes multiple intelligent perception devices, and each intelligent perception device corresponds to a monitoring node. The monitoring node dynamically updates the line sections within its coverage according to the real-time connection status.

[0007] Furthermore, the digital twin mapping module includes a dynamic coverage relationship characterization unit and a feature classification unit; The dynamic coverage relationship characterization unit is used to establish a digital twin platform for the transmission line, map the line sections and the monitoring nodes, form a set of line sections and a set of monitoring nodes, and establish a dynamic coverage relationship; The feature classification unit collects multi-source operation parameters of the line section through the monitoring node. The multi-source operation parameters include several types of electrical state parameters, and generates dynamic feature clusters. The dynamic feature clusters include actual operation parameter feature clusters and observed operation parameter feature clusters.

[0008] Furthermore, the data processing module includes an error boundary processing unit and a correlation analysis unit; The error boundary processing unit is used to construct an error accumulation boundary function and calculate the error accumulation cost; The correlation analysis unit evaluates the correlation degree between the line section and the monitoring node regarding different types of electrical state parameters based on the error accumulation boundary function.

[0009] Furthermore, the fault location module includes a target screening unit and an emergency sorting unit; The target screening unit is used to dynamically quantify the correlation coefficient within the monitoring coverage of the monitoring node and screen out the line sections that have a strong correlation with the monitoring node; The emergency sorting unit is used to evaluate the fault urgency of the line section and arrange and send it to the operation and maintenance backend in descending order.

[0010] A distributed fault location method for transmission lines, this method includes the following steps: S1: Generate multiple monitoring nodes through intelligent perception devices distributed on the transmission line. Each monitoring node corresponds to an intelligent perception device, which is used to monitor the operation status of the transmission line within its coverage in real time; Dynamically divide the line sections according to the coverage of the monitoring node, and establish a dynamic coverage relationship between the monitoring node and the line section; S2: Construct a digital twin platform for the transmission line, map the line sections and the monitoring nodes, collect multi-source operation parameters of the line section, and generate actual operation parameter feature clusters and observed operation parameter feature clusters; S3: Based on the actual operation parameter feature clusters and the observed operation parameter feature clusters, construct an error accumulation boundary function, calculate the error accumulation cost, and evaluate the parameter correlation degree between the line section and the monitoring node; S4: Dynamically quantify the correlation coefficient of the dynamic coverage relationship that changes over time within the monitoring coverage of the monitoring node, achieve distributed fault location of the transmission line, and output the sorting result of the fault urgency.

[0011] Further, the specific implementation process of the S1 includes: Generate monitoring nodes through intelligent sensing devices distributed on the transmission line. Among them, one intelligent sensing device generates one monitoring node, and the monitoring node is used to monitor the operation state of the transmission line within the monitoring coverage; Divide the line section through the monitoring coverage of the monitoring node, so that there is a dynamic coverage relationship between the monitoring node and the line section, and one monitoring node corresponds to at least one line section. The dynamic coverage relationship is characterized based on the real-time connection state of the monitoring node during the operation of the transmission line; In the above method, by dynamically dividing the line section through the distributed intelligent sensing device and establishing the dynamic coverage relationship between the monitoring node and the section, the problem of monitoring blind spots caused by traditional fixed section division is solved, enabling the system to adapt to the change of the operation state of the transmission line in real time, flexibly adjust the monitoring coverage, and improve the comprehensiveness and flexibility of monitoring.

[0012] Further, the specific implementation process of the S2 includes: Establish a digital twin platform for the transmission line, map the line section and the monitoring node to form a line section set and a monitoring node set , and establish a dynamic coverage relationship , where represents the nth line section, represents the mth monitoring node, N and M respectively represent the total numbers of line sections and monitoring nodes, is the correlation coefficient of the dynamic coverage relationship that changes with time t; Collect multi-source operation parameters of the line section through the monitoring node. The multi-source operation parameters include several types of electrical state parameters, and generate dynamic feature clusters. The dynamic feature clusters include actual operation parameter feature clusters and observed operation parameter feature clusters. Denote the actual operation parameter feature cluster of the line section generated by the change of the ith type of electrical state parameter over time t as , and denote the observed operation parameter feature cluster of the monitoring node generated by the change of the ith type of electrical state parameter over time t as ; In the above method, a digital twin platform for transmission lines is constructed, integrating multi-source electrical parameters such as voltage, current, and temperature, generating characteristic clusters of actual and observed operating parameters, enabling comprehensive analysis of multi-source data. Compared with the single-parameter analysis of traditional methods, it can more accurately identify fault characteristics and improve the accuracy of fault location.

[0013] Further, the specific implementation process of S3 includes: Denote the xth electrical state parameter in the characteristic cluster of actual operating parameters as ; denote the yth electrical state parameter in the characteristic cluster of observed operating parameters as ; ; Construct an error accumulation boundary function and calculate the error accumulation cost : ; Based on the error accumulation boundary function, evaluate the correlation degree of the ith type of electrical state parameter between the line section and the monitoring node , where max{} and min{} are the maximum value function and the minimum value function respectively; In the above method, based on the error accumulation boundary function, calculate the parameter correlation degree, dynamically quantify the correlation coefficient, screen out the strongly correlated sections as the priority objects for fault location, and evaluate the fault urgency for ranking. This mechanism establishes a priority evaluation system for fault sections, solves the problem of missing priority ranking in traditional methods, enables efficient allocation of operation and maintenance resources, and improves the fault handling efficiency; the greater the error accumulation cost, the greater the correlation degree of the electrical state parameter between the line section and the monitoring node.

[0014] Further, the specific implementation process of S4 includes: Within the monitoring coverage of the monitoring node , dynamically quantify the correlation coefficient ; where I represents the total number of types of electrical state parameters; Configure the duration range of time t and regularly update the correlation coefficient , screen out the line sections that have strong correlation with the monitoring node . Within the regular range, if a fault event occurs within the monitoring coverage of the monitoring node , then take the line section as the priority object for fault location; Within the kth regular range, if the line section If it is the object of fault priority location, a distributed label is generated and denoted as and , the fault urgency of the line section is evaluated , where R represents the secondary number; Sorted in descending order according to the fault urgency and sent to the operation and maintenance backend; In the above method, the dynamic coverage relationship between the monitoring nodes and the line sections is characterized based on the real-time connection status, and the correlation coefficient is updated regularly, enabling the system to get rid of the limitations of traditional static configuration, being able to update the association relationship between the monitoring nodes and the line sections in real time, effectively coping with the challenges brought by the increasing complexity of the transmission line, and enhancing the dynamic adaptability and positioning accuracy of the system in the complex transmission network; the fault urgency reflects the continuous volatility of the strong correlation, the larger the value of , the smaller the value of

[0015] , the greater the fault urgency, indicating that the line section has been marked as the fault priority object multiple times in a short period of time (small time difference), reflecting a higher frequency or stronger urgency of faults in this section. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification, and are used to explain the present invention together with the embodiments of the present invention, and do not constitute a limitation to the present invention.

[0017] Figure 1 is a schematic diagram of the steps of a method for distributed fault location of a transmission line according to the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0018] Next, in combination with the accompanying drawings in the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0019] In the first embodiment: A distributed fault location system for transmission lines is provided. The system includes: an intelligent perception device cluster module, a digital twin mapping module, a data processing module, and a fault location module; The intelligent perception device cluster module is distributedly deployed on the transmission line and is used to generate monitoring nodes and collect multi-source operation parameters of the transmission line in real time; Among them, the intelligent perception device cluster includes multiple intelligent perception devices, each intelligent perception device corresponds to a monitoring node, and the monitoring node dynamically updates the line sections within the coverage according to the real-time connection status.

[0020] The digital twin mapping module is used to build a digital twin platform for the transmission line, establish a dynamic coverage relationship between the monitoring nodes and the line sections, and map the line section set and the monitoring node set; Among them, the digital twin mapping module includes a dynamic coverage relationship characterization unit and a feature classification unit; The dynamic coverage relationship characterization unit is used to build a digital twin platform for the transmission line, map the line sections and the monitoring nodes, form a line section set and a monitoring node set, and establish a dynamic coverage relationship; The feature classification unit collects multi-source operation parameters of the line section through the monitoring nodes. The multi-source operation parameters include several types of electrical state parameters, and generates dynamic feature clusters. The dynamic feature clusters include actual operation parameter feature clusters and observed operation parameter feature clusters.

[0021] The data processing module is used to generate actual operation parameter feature clusters and observed operation parameter feature clusters, and calculate the parameter correlation degree based on the error accumulation boundary function; Among them, the data processing module includes an error boundary processing unit and a correlation analysis unit; The error boundary processing unit is used to construct an error accumulation boundary function and calculate the error accumulation cost; The correlation analysis unit evaluates the correlation degree between the line section and the monitoring node regarding different types of electrical state parameters based on the error accumulation boundary function.

[0022] The fault location module is used to dynamically quantify the correlation coefficient, screen out strongly correlated line sections as the priority objects for fault location, and output the fault urgency ranking result; Among them, the fault location module includes a target screening unit and an emergency sorting unit; The target screening unit is used to dynamically quantify the correlation coefficient within the monitoring coverage of the monitoring node and screen out the line sections that have a strong correlation with the monitoring node; The emergency sorting unit is used to evaluate the fault urgency of the line section and arrange and send it to the operation and maintenance backend in descending order.

[0023] Please refer to Figure 1 , in the second embodiment: A distributed fault location method for transmission lines is provided to be applicable to the first embodiment above. The method includes the following steps: S1: Generate a plurality of monitoring nodes through intelligent sensing devices distributed on the transmission line. Each monitoring node corresponds to an intelligent sensing device and is used to monitor the operating state of the transmission line within the coverage range in real time; Dynamically divide the line sections according to the coverage range of the monitoring node, and establish a dynamic coverage relationship between the monitoring node and the line section; Exemplarily, monitoring nodes are generated through intelligent sensing devices distributed on the transmission line. Among them, one intelligent sensing device corresponds to generate one monitoring node, and the monitoring node is used to monitor the operating state of the transmission line within the coverage range; Divide the line sections through the monitoring coverage range of the monitoring node, so that there is a dynamic coverage relationship between the monitoring node and the line section, and one monitoring node corresponds to at least one line section. The dynamic coverage relationship is characterized based on the real-time connection state of the monitoring node during the operation of the transmission line.

[0024] S2: Build a digital twin platform for the transmission line, map the line section and the monitoring node, collect multi-source operating parameters of the line section, and generate an actual operating parameter feature cluster and an observed operating parameter feature cluster; Exemplarily, establish a digital twin platform for the transmission line, map the line section and the monitoring node, and form a line section set and a monitoring node set , and establish a dynamic coverage relationship , where represents the nth line section, represents the mth monitoring node, N and M respectively represent the total number of line sections and monitoring nodes, is the correlation coefficient of the dynamic coverage relationship that changes with time t; Collect multi-source operating parameters of the line section through the monitoring node. The multi-source operating parameters include several types of electrical state parameters, and generate a dynamic feature cluster. The dynamic feature cluster includes an actual operating parameter feature cluster and an observed operating parameter feature cluster. The line section generated by the change of the ith type of electrical state parameter with time t The actual operating parameter feature cluster is denoted as , and the observed operating parameter feature cluster of the monitoring node generated by the change of the i-th electrical state parameter over time t is denoted as .

[0025] S3: Based on the actual operating parameter feature cluster and the observed operating parameter feature cluster, construct an error accumulation boundary function, calculate the error accumulation cost, and evaluate the parameter correlation degree between the line section and the monitoring node; Exemplarily, the x-th electrical state parameter in the actual operating parameter feature cluster is denoted as , and the y-th electrical state parameter in the observed operating parameter feature cluster is denoted as ; Construct an error accumulation boundary function and calculate the error accumulation cost : ; Based on the error accumulation boundary function, evaluate the correlation degree of the i-th electrical state parameter between the line section and the monitoring node , where max{} and min{} are the maximum value function and the minimum value function respectively.

[0026] S4: In the monitoring coverage range of the monitoring node, dynamically quantify the correlation coefficient of the dynamic coverage relationship changing with time, realize the distributed fault location of the transmission line, and output the fault urgency ranking result; Exemplarily, in the monitoring coverage range of the monitoring node , dynamically quantify the correlation coefficient ; where I represents the total number of classes of electrical state parameters; Configure the duration range of time t, and regularly update the correlation coefficient , screen out the line sections that have a strong correlation with the monitoring node . In the regular range, if a fault event occurs in the monitoring coverage range of the monitoring node , then the line section is used as the fault priority location object; In the k-th regular range, if the line section is screened out as the fault priority location object for the r-th time, then generate a distributed label denoted as , and , evaluate the fault urgency of the line section ​ , where R represents the secondary number; Arrange in descending order according to the fault urgency and send them to the operation and maintenance backend.

[0027] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device.

[0028] Finally, it should be noted that the above are only preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A distributed fault location method for transmission lines, characterized in that, The method includes the following steps: S1: Generate multiple monitoring nodes through intelligent sensing devices distributedly deployed on the transmission line. Each monitoring node corresponds to an intelligent sensing device and is used to monitor the operating status of the transmission line within the coverage range in real time; Dynamically divide the line sections according to the coverage range of the monitoring nodes, and establish a dynamic coverage relationship between the monitoring nodes and the line sections; S2: Build a digital twin platform for the transmission line, map the line sections and the monitoring nodes, collect multi-source operating parameters of the line sections, and generate an actual operating parameter feature cluster and an observed operating parameter feature cluster; S3: Based on the actual operating parameter feature cluster and the observed operating parameter feature cluster, build an error accumulation boundary function, calculate the error accumulation cost, and evaluate the parameter correlation degree between the line sections and the monitoring nodes; S4: Dynamically quantify the correlation coefficient of the dynamic coverage relationship that changes with time within the monitoring coverage range of the monitoring nodes, realize the distributed fault location of the transmission line, and output the fault urgency sorting result.

2. A distributed fault location method for a transmission line according to claim 1, characterized in that, The specific implementation process of S1 includes: Generate monitoring nodes through intelligent sensing devices distributedly deployed on the transmission line. Among them, one intelligent sensing device corresponds to generating one monitoring node, and the monitoring node is used to monitor the operating status of the transmission line within the coverage range; Divide the line sections through the monitoring coverage range of the monitoring nodes, so that there is a dynamic coverage relationship between the monitoring nodes and the line sections, and one monitoring node corresponds to at least one line section. The dynamic coverage relationship is characterized based on the real-time connection status of the monitoring nodes during the operation of the transmission line.

3. A distributed fault location method for a transmission line according to claim 2, characterized in that, The specific implementation process of S2 includes: Build a digital twin platform for transmission lines, map line sections and monitoring nodes, and form a set of line sections and a set of monitoring nodes , and establish a dynamic coverage relationship , where represents the nth line section, represents the mth monitoring node, N and M respectively represent the total numbers of line sections and monitoring nodes, is the correlation coefficient of the dynamic coverage relationship varying with time t; Collect multi-source operation parameters of the line section through the monitoring nodes. The multi-source operation parameters include several types of electrical state parameters and generate dynamic feature clusters. The dynamic feature clusters include actual operation parameter feature clusters and observed operation parameter feature clusters. The actual operation parameter feature cluster of the line section generated by the change of the i-th type of electrical state parameter over time t is denoted as , and the observed operation parameter feature cluster of the monitoring node generated by the change of the i-th type of electrical state parameter over time t is denoted as .

4. A method for distributed fault location of a transmission line according to claim 3, characterized in that The specific implementation process of S3 includes: The x-th electrical state parameter in the actual operating parameter feature cluster is denoted as , and the y-th electrical state parameter in the observed operating parameter feature cluster is denoted as ; Construct an error accumulation boundary function and calculate the error accumulation cost : ； Evaluate the line section based on the error accumulation boundary function and the monitoring node The correlation degree of the i-th type of electrical state parameter between them , where max{} and min{} are the maximum value function and the minimum value function respectively.

5. A method for distributed fault location of a transmission line according to claim 4, characterized in that, The specific implementation process of S4 includes: Within the monitoring coverage of the monitoring node the correlation coefficient is dynamically quantified ; In the formula, I represents the total number of classes of electrical state parameters; Configure the duration range of time t, and regularly update the correlation coefficient to screen out the line sections that are strongly correlated with the monitoring nodes . Within the regular range, if a fault event occurs within the monitoring coverage of the monitoring node , then the line section will be used as the object for priority fault location; Within the k-th regular range, if the r-th screening selects a line section as the object for fault priority location, a distributed label is generated and denoted as , and , evaluate the fault urgency of the line section , where R represents the sequence number; Arrange in descending order according to the fault urgency and send them to the operation and maintenance backend.

6. A distributed fault location system for a transmission line, which executes the fault location method according to any one of claims 1-5, characterized in that, The system includes: an intelligent sensing device cluster module, a digital twin mapping module, a data processing module, and a fault location module; The intelligent sensing device cluster module is distributedly deployed on the transmission line and is used to generate monitoring nodes and collect multi-source operating parameters of the transmission line in real time; The digital twin mapping module is used to build a digital twin platform for the transmission line, establish a dynamic coverage relationship between the monitoring nodes and the line sections, and map the line section set and the monitoring node set; The data processing module is used to generate an actual operating parameter feature cluster and an observed operating parameter feature cluster, and calculate the parameter correlation degree based on the error accumulation boundary function; The fault location module is used to dynamically quantify the correlation coefficient, screen out strongly correlated line sections as the priority objects for fault location, and output the fault urgency sorting result.

7. A distributed fault location system for a transmission line according to claim 6, characterized in that, The intelligent sensing device cluster includes multiple intelligent sensing devices. Each intelligent sensing device corresponds to a monitoring node, and the monitoring node dynamically updates the line sections within the coverage range according to the real-time connection status.

8. A distributed fault location system for a transmission line according to claim 6, characterized in that, The digital twin mapping module includes a dynamic coverage relationship characterization unit and a feature classification unit; The dynamic coverage relationship characterization unit is used to build a digital twin platform for the transmission line, map the line sections and the monitoring nodes, form a line section set and a monitoring node set, and establish a dynamic coverage relationship; The feature classification unit collects multi-source operation parameters of a line section through a monitoring node. The multi-source operation parameters include several types of electrical state parameters, and generates dynamic feature clusters. The dynamic feature clusters include actual operation parameter feature clusters and observed operation parameter feature clusters.

9. A distributed fault location system for a transmission line according to claim 6, characterized in that, The data processing module includes an error boundary processing unit and a correlation analysis unit; The error boundary processing unit is used to construct an error accumulation boundary function and calculate the error accumulation cost; The correlation analysis unit evaluates the correlation degree between the line section and the monitoring node regarding different types of electrical state parameters based on the error accumulation boundary function.

10. The distributed fault location system for a transmission line according to claim 6, wherein, The fault location module includes a target screening unit and an emergency sorting unit; The target screening unit is used to dynamically quantify the correlation coefficient within the monitoring coverage of the monitoring node and screen out the line sections with strong correlation with the monitoring node; The emergency sorting unit is used to evaluate the fault urgency of the line section and arrange and send it to the operation and maintenance backend in descending order.

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