Line branch identification system of power distribution area

Abstract

The invention discloses a line branch identification system of a power distribution area, and relates to the technical field of fault localization. A branch line monitoring module is arranged to collect monitoring parameters of each line branch in real time, and step-by-step fault judgment is carried out based on a digital number sequence of branch nodes; according to the method, the approximate position of a fault can be quickly identified, and the fault reference data can be generated, so that the fault diagnosis time is remarkably shortened; on the basis of the complexity of data format conversion of each monitoring parameter acquired by each branch node in different line branches, monitoring numerical values of different branch nodes are intelligently distributed to a local branch monitoring unit or a cloud preprocessing unit for data format conversion, so that reasonable utilization of computing resources is realized; and the priority and the path of data format conversion are dynamically adjusted by monitoring the conversion evaluation table of the parameters, so that the cloud processing burden is reduced, and the efficiency of locking the fault branch line is further improved.

Description

Technical Field

[0001] The present invention relates to the technical field of fault location, and particularly to a line branch identification system for a distribution substation area. Background Art

[0002] With the in-depth promotion of the construction of the smart grid, the line structure of the distribution substation area has become increasingly complex. As the core technology for sorting out the line topology relationship and clarifying the connection status of branch nodes, the line branch identification system for the distribution substation area is crucial for ensuring the stable operation and efficient management of the distribution network; However, in the prior art, most of such systems only achieve static identification of the line branch structure. When a fault occurs in the distribution substation area, it is difficult to quickly integrate the obtained line branch information with the fault location and identification requirements of the fault branch line, resulting in low fault location efficiency; In the actual distribution operation scenario, when a fault such as a short circuit or grounding occurs in a branch line, the fault information needs to be collected by various monitoring devices, such as smart meters, fault indicators, relay protection devices, etc.; however, since these devices are from different manufacturers, the communication protocols and data formats are significantly different. For example, some devices use a custom binary format to transmit current and voltage data, while others represent the fault status information based on XML or JSON text formats. This non-uniformity of data formats makes it impossible to directly and effectively process the fault information when it is transmitted to the fault location system, and a large amount of time is required for format conversion. As a result, even if the fault information is obtained during the fault location process, it is difficult to quickly lock the fault branch line; To solve the above problems, the present invention proposes a solution. Summary of the Invention

[0003] The purpose of the present invention is to provide a line branch identification system for a distribution substation area to solve the problems raised in the above background art.

[0004] The present invention provides a line branch identification system for a distribution substation area, including: A branch line monitoring module for real-time monitoring of all line branches separated from a target main line. Any line branch separated from the target main line contains a number of branch nodes, and for any line branch, all the branch nodes contained therein correspond to a digital number, and the digital numbers are sequentially arranged starting from 1; The branch line monitoring module includes a fault determination unit. After receiving the monitoring information of a line branch each time, the fault determination unit extracts the parameter information of all the branch nodes contained therein, and sequentially performs fault determination on the parameter information of the corresponding branch nodes in ascending order of the digital numbers, and selects and generates the fault reference data of the line branch based on the fault determination results; The branch interaction module is used for: when there is no conversion evaluation table of several monitoring parameters stored in the module, every time a fault reference data of a line branch is received, it is transmitted to the preprocessing unit for preprocessing, generating the fault ready data of the line branch based on the preprocessing result and recording the fault handling information of the line branch during the preprocessing process; The branch interaction module is also used for: when there is a conversion evaluation table of several monitoring parameters stored in the module, every time a fault reference data of a line branch is received, it is branched and transmitted according to the preset branch transmission rules; The information analysis unit is used for analyzing all the fault handling information stored therein to obtain a conversion evaluation table of several monitoring parameters.

[0005] Furthermore, the steps for the information analysis unit to analyze all the fault handling information stored therein to obtain a conversion evaluation table of several monitoring parameters are as follows: S11: Mark all the monitoring parameters selected by the monitoring personnel for monitoring as A1, A2,..., Aa, where a≥1; S12: Obtain all the original formats containing the monitoring parameter A1 from all the fault handling information stored in the information analysis unit and remove duplicates therefrom, and mark the remaining original formats after duplicate removal as B1, B2,..., Bb, where b≥1; S13: Extract from all the fault handling information all the fault handling information with the original format B1 of the monitoring parameter A1 contained therein according to the original format B1, and mark them as C1, C2,..., Cc, where c≥1; S14: Use the formula F1 = D1×ɑ1 + D2×ɑ2 + (D3×β1 + D4×β2)×ɑ3 to calculate and obtain the conversion evaluation complexity F1 of the monitoring parameter A1 in a branch node contained in the fault handling information C1. In the formula, D1, D2, D3, and D4 are the data capacity size, conversion duration, progress start duration, and progress end duration of the monitoring parameter A1 in the record information data of the branch node in the fault handling information C1 in sequence, ɑ1, ɑ2, ɑ3 are the preset first, second, and third dimension evaluation weights in sequence, used to adjust the dimensions of the four different dimensions of data capacity size, conversion duration, progress start duration, and progress end duration to a unified dimension for conversion evaluation, and β1, β2 are the preset progress ratio weights, and β1, β2 satisfy β1 + β2 = 1 numerically; S15: Calculate in sequence the conversion evaluation complexity of the monitoring parameter A1 in all the branch nodes in the fault handling information C1 according to S14, then use the discrete point filtering algorithm to process the obtained all conversion evaluation complexities, and calculate the average value of all the remaining conversion evaluation complexities after data processing, and calibrate the average value as the conversion complex feature G1 of the monitoring parameter A1 based on the fault handling information C1; S16: Calculate and obtain the conversion complex features G2, G3, ..., Gc of the monitoring parameter A1 based on the fault handling information C2, C3, ..., Cc in sequence according to S13 to S15; Similarly, use the discrete point filtering algorithm to process the obtained conversion complex features G1, G2, ..., Gc, and calculate the average value of all the remaining conversion complex features after data processing, and calibrate the average value as the conversion complexity of the monitoring parameter A1 relative to the original format B1; S17: Obtain the conversion complexities of the monitoring parameter A1 relative to the original formats B2, B3, ..., Bb in sequence according to S12 to S16, and generate a conversion evaluation table of the monitoring parameter A1 based on them. The conversion evaluation table contains the conversion complexities of the original formats B1, B2, ..., Bb; S18: Generate the conversion evaluation tables of the monitoring parameters A2, A3, ..., Aa in sequence according to S11 to S17.

[0006] Furthermore, the generation steps of the fault ready data of a line branch are as follows: Extract the parameter information of all branch nodes from the fault reference data. For the parameter information of any one branch node, obtain the standard format of all the monitoring parameters included in the parameter information, perform data format conversion on the monitoring values of the corresponding monitoring parameters in the parameter information according to the standard format, and generate transient ready data for the corresponding branch node according to the monitoring values of all the monitoring parameters after the data format conversion; generate the fault ready data of the line branch according to the transient ready data of all the branch nodes.

[0007] Furthermore, during the generation of the transient ready data of any one of the branch nodes, the preprocessing unit records the original format, data capacity size, conversion duration, progress start duration, and start and end duration of all the monitoring parameters in the parameter information of the branch node, and generates the transient record information of the branch node based on them, and generates the fault handling information of the line branch according to the transient record information of all the branch nodes.

[0008] Compared with the prior art, the following beneficial effects are achieved: By setting up a branch line monitoring module, the present invention can collect the monitoring parameters of each line branch in real time and perform step-by-step fault determination based on the digital number sequence of the branch nodes, quickly identify the approximate location of the fault and generate fault reference data, significantly shorten the fault diagnosis time, combine the preprocessing unit and the fault location unit, and use the impedance method or the traveling wave method for fault location to ensure the accuracy and reliability of the location information of the fault point, which is convenient for maintenance personnel to respond quickly; The present invention sets up a branch interaction module to adopt a dynamic branch transmission rule, and intelligently distributes the monitoring values of different branch nodes to the local branch monitoring unit or the preprocessing unit in the cloud for data format conversion based on the complexity of data format conversion of each monitoring parameter collected by each branch node in different line branches, so as to realize the reasonable utilization of computing resources. Moreover, through the conversion evaluation table of monitoring parameters, the priority and path of data format conversion are dynamically adjusted, reducing the processing burden on the cloud and improving the overall response speed of the system, and further improving the efficiency of locking the faulty branch line. When analyzing and obtaining the conversion evaluation table of monitoring parameters, the present invention introduces an evaluation logic for the processing order of each monitoring parameter during the data format conversion process of the system when calculating the conversion evaluation complexity of different monitoring parameters. In this way, the conversion evaluation complexity is made more accurate and reliable. Brief Description of the Drawings

[0009] Figure 1 It is a system block diagram of the present invention. Detailed Embodiments

[0010] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0011] Please refer to Figure 1 , this application provides a line branch identification system for a distribution substation area, including a branch line monitoring module, a branch interaction module, and a cloud positioning platform; The branch line monitoring module is used to monitor all line branches separated from the target main line in real time. In this application, there are several connection points on the target main line, and the starting point of any line branch separated from the target main line corresponds to a connection point included on the target main line. It should be noted here that any line branch separated from the target main line contains several branch nodes; In this application, the branch node included in the line branch refers to a physical unit that meets the following conditions: First, it realizes the line branch function in electrical connection, and the current or voltage parameters at the branch node can be independently measured; Second, it physically appears as a switch device (such as a pole-mounted switch, a ring main unit switch), a sectionalizer, a cable branch joint with a branch function, or an intelligent distribution terminal device integrated with metering and protection functions; Third, when the line topology changes, the number and position of the branch nodes are dynamically adjusted accordingly; The branch line monitoring module includes a fault determination unit and a number of branch monitoring units. One branch monitoring unit corresponds to a line branch branched from the target main line. The branch monitoring unit includes an intelligent terminal device, which is used to connect to sensors that collect various monitoring parameters at the corresponding branch node, and has relatively strong computing and analysis capabilities; In this application, for any line branch, all branch nodes are sequentially numbered digitally in ascending order of the physical distance between each branch node and the starting point of the line branch. The digital numbering starts from 1 and continues sequentially. That is, the smaller the digital number, the closer the corresponding branch node is to the starting point of the line branch; The branch monitoring unit collects the monitoring information of the corresponding line branch in real time and transmits it to the fault determination unit. The monitoring information contains the parameter information of all branch nodes within the line branch. The parameter information of one branch node includes the monitoring values of a number of monitoring parameters collected at the branch node; In this application, the monitoring parameters include the effective value (amplitude) of three-phase current, zero-sequence current (neutral line current), current mutation rate (current change rate per unit time), amplitude and phase angle of three-phase voltage, zero-sequence voltage (neutral point voltage offset), voltage sag depth and duration, harmonic parameters, total harmonic distortion rate, harmonic content, power parameters, active power, reactive power, power factor, wire temperature, real-time cable temperature, discharge pulse amplitude, discharge frequency, vibration frequency, vibration acceleration, arrival time of the traveling wave head, traveling wave polarity and amplitude, traveling wave propagation speed, dynamic impedance amplitude, impedance angle, R-X plane trajectory offset, high-frequency transient current, voltage sag recovery time, harmonic current content, transient zero-sequence power direction, high-frequency pulse count, arc reignition time interval, current unbalance, abnormal minimum load at night, equipment clock synchronization error, breaker opening and closing status; It should be noted here that the selection of monitoring parameters is determined by the monitoring personnel according to the fault location method adopted by the cloud positioning platform; A number of threshold values of monitoring parameters are pre-stored in the fault determination unit. After receiving the monitoring information of the line branch transmitted, the fault determination unit extracts the parameter information of all branch nodes contained therein, and sequentially performs fault determination on the parameter information of the corresponding branch nodes in ascending order of digital number. Based on the fault determination results, the fault reference data of the line branch is selected and generated, and the fault reference data is transmitted to the branch interaction module; The fault determination steps are as follows: Perform fault determination on the parameter information of the branch node with digital number 1: Extract the monitoring values of all monitoring parameters contained in the parameter information of the branch node with digital number 1, and compare the extracted monitoring values of all monitoring parameters with their corresponding threshold values: If there is at least one monitored value of the monitored parameter greater than or equal to its corresponding threshold value, it is determined that there is a fault in the line branch. At this time, obtain the parameter information of all branch nodes with digital numbers greater than or equal to 1 in the monitoring information of the line branch and generate the fault reference data of the line branch based on it; If there is no monitored value of any of the monitored parameters greater than or equal to its corresponding threshold value, at this time, in the order of increasing digital numbers, the parameter information of branch nodes with digital numbers 2, 3,..., z is sequentially subjected to fault determination. It should be noted here that if the monitored values of all monitored parameters included in the parameter information of the branch node with digital number z are less than their corresponding threshold values, it is determined that the line branch is normal and no processing is performed. z represents the total number of parameter information included in the monitoring information; The branch interaction module is used to perform branch transmission on the fault reference data of each received line branch; Before the branch interaction module receives the conversion evaluation table of several monitored parameters to be transmitted, after receiving the fault reference data of each line branch, it transmits it to the cloud positioning platform; After the branch interaction module receives the conversion evaluation table of several monitored parameters to be transmitted, after receiving the fault reference data of each line branch, the branch interaction module performs branch transmission on it according to the preset branch transmission rules, specifically as follows: S21: Mark the parameter information of all branch nodes included in the fault reference data in the order of increasing digital numbers as H1, H2,..., Hh, H≥1; S22: According to the data format of the monitored value of monitored parameter A1 in parameter information H1, obtain the conversion complexity I1 of this data format in the conversion evaluation table of monitored parameter A1 stored in the branch interaction module; S23: Use the formula K1 = I1×J1×λ1 to calculate and obtain the conversion time-consuming index K1 of monitored parameter A1 in parameter information H1. In the formula, λ1 is a preset equal-ratio resource conversion score, and J1 is the data capacity size of the monitored value of monitored parameter A1 in parameter information H1; S24: Calculate and obtain the conversion time-consuming indexes of monitored parameters A2, A3,..., Aa in parameter information H1 in sequence according to S23 and use the formula to calculate and obtain their sum, and calibrate the sum as the total conversion time-consuming index L1 of the branch node corresponding to parameter information H1; S25: Calculate and obtain the total conversion time-consuming indexes L2, L3,..., Lh of the branch nodes corresponding to parameter information H2, H3,..., Hh in sequence according to S21 to S24; S26: Compare the total conversion time-consuming metric L1 with Pmin and Pmax, where Pmin and Pmax are the preset minimum and maximum boundary values of the branch respectively. Based on the comparison result, transfer the parameter information H1 of the branch node corresponding to the total conversion time-consuming metric L1 according to the preset branch transfer rule, as follows: S261: If the total conversion time-consuming metric L1 meets the first branch condition: L1 < Pmin, then take the parameter information H1 of the branch node corresponding to the total conversion time-consuming metric L1 as the first branch data of the branch node; The branch transfer module transfers the first branch data of the branch node corresponding to the total conversion time-consuming metric L1 to the branch monitoring unit corresponding to the branch node. The branch monitoring unit performs data format conversion on the monitoring values of all monitoring parameters in the first branch data to obtain the transient ready data of the line branch based on the branch node, and transfers the transient ready data to the fault location unit of the cloud positioning platform for temporary storage; S262: If the total conversion time-consuming metric L1 meets the second branch condition: Pmin ≤ L1 ≤ Pmax, then obtain all the monitoring parameters corresponding to the conversion time-consuming metrics less than or equal to P1 from all the conversion time-consuming metrics used to calculate the total conversion time-consuming metric L1, and extract the monitoring values of all the obtained monitoring parameters from the parameter information H1 as the first branch data of the branch node for temporary storage, and take the monitoring values of all the remaining unextracted monitoring parameters in the parameter information H1 as the second branch data of the branch node for temporary storage, where P1 is the preset first branch quantization screening index; The branch transfer module transfers the first branch data of the branch node corresponding to the total conversion time-consuming metric L1 to the branch monitoring unit corresponding to the branch node. The branch monitoring unit performs data format conversion on the monitoring values of all monitoring parameters in the first branch data to obtain the branch conversion data of the line branch based on the branch node, and transfers the branch conversion data to the fault location unit of the cloud positioning platform for temporary storage; The branch monitoring unit transfers the second branch data of the branch node corresponding to the total conversion time-consuming metric L1 to the preprocessing unit of the cloud positioning platform. After receiving the transmitted second branch data, the preprocessing unit performs data format conversion on the monitoring values of all monitoring parameters included in the parameter information of all branch nodes included therein to obtain the branch conversion data of the line branch based on the branch node, and transfers the branch conversion data to the fault location unit; After receiving the two branch conversion data of the line branch based on the branch node transmitted, the fault location unit temporarily stores them as the transient ready data of the line branch based on the branch node; S263: If the total conversion time indicator L1 satisfies the third branch condition: L1 > Pmax, then the parameter information H1 of the branch node corresponding to the total conversion time indicator L1 is used as the second branch data of the line branch based on the branch node. The branch monitoring unit transmits the second branch data of the branch node corresponding to the total conversion time indicator L1 to the preprocessing unit of the cloud positioning platform. After receiving the transmitted second branch data, the preprocessing unit performs data format conversion on the monitoring values of all monitoring parameters included in the parameter information of all branch nodes included therein to obtain the transient ready data of the line branch based on the branch node, and transmits the transient ready data to the fault location unit for temporary storage. S27: Perform branch transmission on the parameter information of the branch nodes corresponding to the total conversion time indicators L2, L3,..., Lh according to S26. It should be noted here that the process of branch transmission of the parameter information of the branch nodes corresponding to the total conversion time indicators L1, L2,..., Lh is carried out synchronously. After storing the transient ready data of the line branch based on the branch nodes corresponding to the total conversion time indicators L1, L2,..., Lh, the fault location unit uses it as the fault ready data of the line branch, and uses the fault location method to perform fault location on the line branch to obtain the fault location information of the line branch. It should be noted here that no fault processing information is generated during the preprocessing of the second branch data by the preprocessing unit at this time. The cloud positioning platform is used to perform fault location on the line branch in the cloud. The cloud positioning platform includes a preprocessing unit, a fault location unit, and an information analysis unit. After receiving the transmitted fault reference data of the line branch, the cloud positioning platform transmits it to the preprocessing unit, and the preprocessing unit stores the standard formats of several monitoring parameters preset by the monitoring personnel. After receiving the transmitted fault reference data of the line branch, the preprocessing unit preprocesses the fault reference data, generates the fault ready data of the line branch based on the preprocessing result, and records the fault processing information of the line branch during the preprocessing process. The steps for generating the fault ready data are as follows: Extract the parameter information of all branch nodes from the fault reference data. For the parameter information of any one branch node, obtain the standard formats of all monitoring parameters included in the parameter information, perform data format conversion on the monitoring values of the corresponding monitoring parameters in the parameter information according to the standard formats, and generate the transient ready data of the corresponding branch node according to the monitoring values of all the monitoring parameters after the data format conversion is completed. Generate the fault readiness data of the line branch according to the transient readiness data of all the branch nodes; During the generation of the transient readiness data of any one of the branch nodes, the preprocessing unit records the original format, data capacity size, conversion duration, progress start duration, and start and end duration of all monitoring parameters in the parameter information of the branch node and generates the transient record information of the branch node based on them; Generate the fault handling information of the line branch according to the transient record information of all the branch nodes; For any one monitoring parameter, its original format refers to the data format before the monitoring value of the monitoring parameter is not subjected to data format conversion, and the standard format is the standard format of the monitoring parameter preset by the monitoring personnel stored in the preprocessing unit; Its data capacity size refers to the data capacity size before the monitoring value is not subjected to data format conversion, and the conversion duration refers to the duration consumed for the monitoring value to be converted into the corresponding standard format; Its progress start duration refers to the difference between the moment when the monitoring value of the monitoring parameter starts format conversion and the moment when the monitoring value of the first monitoring parameter in the fault reference information starts data format conversion, and its progress end duration refers to the difference between the moment when the data format conversion of the monitoring value of the monitoring parameter is completed and the moment when the format conversion of the monitoring value of the last monitoring parameter in the fault reference information is completed; The preprocessing unit transmits the fault readiness data of the line branch to the fault location unit, and the preprocessing unit synchronously transmits the fault handling information of the line branch to the information analysis unit for storage; After receiving the transmitted fault readiness data of the line branch, the fault location unit uses the fault location method to perform fault location on the line branch to obtain the fault location information of the line branch, displays the fault location information and the fault type of the fault point to the monitoring personnel for viewing, and synchronously uses sound to alarm the monitoring personnel; The monitoring personnel formulate a corresponding maintenance plan for the fault point according to the fault location information and the fault type, and the corresponding maintenance personnel repair the fault point according to the maintenance plan; The fault location information at least includes the location information of the fault point, and the location information refers to any data that can clearly define the actual location of the fault point; In this application, the location information includes the digital number of the line branch closest to the fault point, the actual path distance from the fault point, and the node section. The node section is two digital numbers, which are used to indicate that the fault point is between the branch nodes corresponding to these two digital numbers; In this application, the fault location method is selected from the impedance method and the traveling wave method; The information analysis unit analyzes all the fault processing information stored therein within a preset analysis duration, and the analysis steps are as follows: S11: Mark all the monitoring parameters selected by the monitoring personnel for monitoring as A1, A2,..., Aa, where a ≥ 1; S12: Obtain all the original formats containing the monitoring parameter A1 from all the fault processing information stored in the information analysis unit and remove duplicates therefrom, and mark all the remaining original formats after duplicate removal as B1, B2,..., Bb, where b ≥ 1; S13: Extract from all the fault processing information all the fault processing information with the original format B1 of the monitoring parameter A1 contained therein according to the original format B1, and mark them as C1, C2,..., Cc, where c ≥ 1; S14: Use the formula F1 = D1×ɑ1 + D2×ɑ2 + (D3×β1 + D4×β2)×ɑ3 to calculate and obtain the conversion evaluation complexity F1 of the monitoring parameter A1 in a branch node contained in the fault processing information C1. In the formula, D1, D2, D3, and D4 are the data capacity size, conversion duration, progress start duration, and progress end duration of the monitoring parameter A1 in the record information data of the branch node in the fault processing information C1 in sequence, ɑ1, ɑ2, ɑ3 are the preset first, second, and third dimension evaluation weights in sequence, used to adjust the dimensions of these four different dimensions of data capacity size, conversion duration, progress start duration, and progress end duration to a unified dimension for conversion evaluation, and β1, β2 are the preset progress ratio weights, and β1 and β2 satisfy β1 + β2 = 1 numerically; It should be noted here that the conversion evaluation complexity is defined artificially and is used to characterize the conversion complexity of the monitoring parameter A1 from the original format B1 to the standard format. When constructing this complexity calculation formula, the purpose of introducing (D3×β1 + D4×β2) is to introduce the evaluation logic of the processing order of each monitoring parameter during the data format conversion process of the system, making the conversion evaluation complexity more accurate; In the prior art, the system will perform a priority evaluation on the numerical values of each monitoring parameter in the fault processing information C1 according to the current available computing resources and the complex characteristics of the data conversion task itself, and then determine the sequence of data format conversion of the monitoring numerical values of all monitoring parameters; S15: Sequentially calculate according to S14 to obtain the conversion evaluation complexity of the monitoring parameter A1 in all branch nodes within the fault handling information C1, then use the discrete point filtering algorithm to process the obtained conversion evaluation complexities, and calculate the average value of all the remaining conversion evaluation complexities after data processing. Calibrate the average value as the conversion complex feature G1 of the monitoring parameter A1 based on the fault handling information C1; In this application, the discrete point filtering algorithm can be any one of the Z-score filtering algorithm, the IQR filtering algorithm, and the density filtering algorithm; S16: Sequentially calculate according to S13 to S15 to obtain the conversion complex features G2, G3,..., Gc of the monitoring parameter A1 based on the fault handling information C2, C3,..., Cc; Similarly, use the discrete point filtering algorithm to process the obtained conversion complex features G1, G2,..., Gc, and calculate the average value of all the remaining conversion complex features after data processing. Calibrate the average value as the conversion complexity of the monitoring parameter A1 relative to the original format B1; S17: Sequentially obtain the conversion complexities of the monitoring parameter A1 relative to the original formats B2, B3,..., Bb according to S12 to S16, and generate a conversion evaluation table for the monitoring parameter A1 based on them. The conversion evaluation table contains the conversion complexities of the original formats B1, B2,..., Bb; S18: Sequentially generate conversion evaluation tables for the monitoring parameters A2, A3,..., Aa according to S11 to S17; The information analysis unit transmits the generated conversion evaluation tables of the monitoring parameters A1, A2,..., Aa to the branch interaction module and the branch line monitoring module respectively; After receiving the transmitted conversion evaluation tables of the monitoring parameters A1, A2,..., Aa, the branch interaction module stores them; After receiving the transmitted conversion evaluation tables of the monitoring parameters A1, A2,..., Aa, the branch line monitoring module transmits them to all branch monitoring units for storage.

[0012] For some data in the above formulas, numerical calculations are performed after removing their dimensions. At the same time, the content not described in detail in this specification belongs to the prior art well-known to those skilled in the art.

[0013] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A line branch identification system for a distribution substation area, characterized in that, Including: A branch line monitoring module for real-time monitoring of all line branches branched from a target main line. Any line branch branched from the target main line contains several branch nodes. For any line branch, all branch nodes contained therein correspond to a digital number, and the digital numbers are sequentially arranged starting from 1; The branch line monitoring module includes a fault determination unit. After receiving the monitoring information of a line branch transmitted each time, the fault determination unit extracts the parameter information of all branch nodes contained therein, and sequentially performs fault determination on the parameter information of the corresponding branch nodes in ascending order of the digital numbers, and selects and generates the fault reference data of the line branch based on the fault determination result; The branch interaction module is used for: when there is no conversion evaluation table of several monitoring parameters stored in the module, each time it receives the fault reference data of a line branch, it transmits it to the preprocessing unit for preprocessing, generates the fault ready data of the line branch based on the preprocessing result, and records the fault processing information of the line branch during the preprocessing process; The branch interaction module is also used for: when there is already a conversion evaluation table of several monitoring parameters stored in the module, each time it receives the fault reference data of a line branch, it performs branch transmission on it according to the preset branch transmission rules; An information analysis unit for extracting all original formats of each monitoring parameter from all fault processing information stored therein according to each monitoring parameter selected by the monitoring personnel; For any one monitoring parameter, according to each original format of the extracted monitoring parameter, several corresponding fault processing information are extracted from all fault processing information, and the conversion complexity of the monitoring parameter relative to each extracted original format is obtained according to the data capacity size, conversion duration, progress start duration, and progress end duration contained in each extracted fault processing information; The information analysis unit generates a conversion evaluation table of all monitoring parameters based on the conversion complexity of all monitoring parameters relative to each extracted original format; 2. The line branch identification system for a distribution substation area according to claim 1, characterized in that, The steps for the information analysis unit to analyze all fault processing information stored therein to obtain a conversion evaluation table of several monitoring parameters are as follows: S11: Mark all monitoring parameters selected by the monitoring personnel for monitoring as A1, A2,..., Aa, where a≥1; S12: Obtain all original formats of the monitoring parameter A1 contained in all fault processing information stored in the information analysis unit and remove duplicates therefrom, and mark the remaining original formats after deduplication as B1, B2,..., Bb, where b≥1; S13: Extract all fault processing information with the original format of the monitoring parameter A1 being B1 from all the fault processing information according to the original format B1, and mark them as C1, C2,..., Cc, where c≥1; S14: Calculate and obtain the conversion evaluation complexity F1 of the monitoring parameter A1 in a branch node included in the fault handling information C1 by using the formula F1 = D1×ɑ1 + D2×ɑ2 + (D3×β1 + D4×β2)×ɑ3. In the formula, D1, D2, D3, and D4 are the data volume size, conversion duration, progress start duration, and progress end duration of the monitoring parameter A1 in the record information data of the branch node in the fault handling information C1 in sequence. ɑ1, ɑ2, and ɑ3 are the preset first, second, and third dimension evaluation weights in sequence. β1 and β2 are the preset progress proportion weights, and β1 and β2 satisfy β1 + β2 = 1 numerically. S15: Calculate and obtain the conversion evaluation complexity of the monitoring parameter A1 in all branch nodes in the fault handling information C1 in sequence according to S14, then use the discrete point filtering algorithm to process the data of all obtained conversion evaluation complexities, and calculate the average value of all remaining conversion evaluation complexities after data processing. Calibrate the average value as the conversion complex feature G1 of the monitoring parameter A1 based on the fault handling information C1. S16: Calculate and obtain the conversion complex features G2, G3,..., Gc of the monitoring parameter A1 based on the fault handling information C2, C3,..., Cc in sequence according to S13 to S15. Use the discrete point filtering algorithm to process the conversion complex features G1, G2,..., Gc obtained, and calculate the average value of all remaining conversion complex features after data processing. Calibrate the average value as the conversion complexity of the monitoring parameter A1 relative to the original format B1. S17: Obtain the conversion complexities of the monitoring parameter A1 relative to the original formats B2, B3,..., Bb in sequence according to S12 to S16 and generate a conversion evaluation table of the monitoring parameter A1 based on them. The conversion evaluation table contains the conversion complexities of the original formats B1, B2,..., Bb. S18: Generate the conversion evaluation tables of the monitoring parameters A2, A3,..., Aa in sequence according to S11 to S17.

3. The line branch identification system for a distribution substation area according to claim 2, characterized in that, The branch transfer rules for branch transfer of the fault reference data of a line branch are as follows: S21: Mark the parameter information of all branch nodes included in the fault reference data as H1, H2,..., Hh in ascending order of digital numbers, where h ≥ 1. S22: Obtain the conversion complexity I1 of the data format in the conversion evaluation table of the monitoring parameter A1 stored in the branch interaction module according to the data format of the monitoring value of the monitoring parameter A1 in the parameter information H1. S23: Calculate and obtain the conversion time-consuming index K1 of the monitoring parameter A1 in the parameter information H1 by using the formula K1 = I1×J1×λ1. In the formula, λ1 is the preset equal ratio resource conversion fraction, and J1 is the data volume size of the monitoring value of the monitoring parameter A1 in the parameter information H1. S24: Calculate and obtain the conversion time-consuming indexes of the monitoring parameters A2, A3,..., Aa in the parameter information H1 in sequence according to S23 and calculate the sum by using the formula. Calibrate the sum as the total conversion time-consuming index L1 of the branch node corresponding to the parameter information H1. S25: according to S21 to S24, the total conversion time consumption indicators L2, L3, ..., Lh of the branch nodes corresponding to the acquired parameter information H2, H3, ..., Hh are calculated in sequence; S26: Compare the total conversion time consumption index L1 with Pmin and Pmax, where Pmin and Pmax are respectively the preset branch minimum and maximum limit values, and perform branch transmission on the parameter information H1 of the branch node corresponding to the total conversion time consumption index L1 based on the size comparison result, as follows: S261: If the total conversion time indicator L1 satisfies the first branch condition: L1 <Pmin则将转换耗时总指标L1对应的分支节点的参数信息H1作为所述分支节点的第一分支数据,将所述第一分支数据传输到所述分支节点对应的分支监测单元; S262: If the total conversion time index L1 satisfies the second branch condition: Pmin≤L1≤Pmax, then all monitoring parameters corresponding to the conversion time indexes less than or equal to P1 are obtained from all conversion time indexes calculated to obtain the total conversion time index L1, and the monitoring values ​​of all the acquired monitoring parameters are extracted from the parameter information H1 as the first branch data of the branch node for temporary storage, and the monitoring values ​​of all the remaining monitoring parameters that have not been extracted in the parameter information H1 are temporarily stored as the second branch data of the branch node, and P1 is the preset first branch quantitative screening index; The branch transmission module transmits the first branch data to the branch monitoring unit corresponding to the branch node, and the branch monitoring unit transmits the second branch data to the preprocessing unit; S263: If the total conversion time consumption index L1 satisfies the third branch condition: L1>Pmax, the parameter information H1 of the branch node corresponding to the total conversion time consumption index L1 is used as the second branch number of the line branch based on the branch node, and the second branch data is transmitted to the preprocessing unit; S27: According to S26, the parameter information of the branch nodes corresponding to the total conversion time consumption indicators L2, L3, ..., Lh are branched and transmitted.

4. The line branch identification system for a distribution substation area according to claim 3, characterized in that, In S261, the branch monitoring unit performs data format conversion on the monitoring values ​​of all monitoring parameters in the first branch data to obtain transient ready data of the line branch based on the branch node, and transmits the transient ready data to the fault location unit for temporary storage.

5. The line branch identification system for a distribution substation area according to claim 3, characterized in that, S262, the branch monitoring unit performs data format conversion on the monitoring values ​​of all monitoring parameters in the first branch data to obtain branch conversion data of the line branch based on the branch node, and transmits the branch conversion data to the fault location unit for temporary storage; After receiving the transmitted second branch data, the preprocessing unit performs data format conversion on the monitoring values ​​of all monitoring parameters contained in the parameter information of all branch nodes contained therein to obtain the branch conversion data of the line branch based on the branch node, and transmits the branch conversion data to the fault location unit.

6. A line branch identification system for a distribution substation area according to claim 1, characterized in that, The steps for generating fault-ready data for a line branch are as follows: Extract the parameter information of all branch nodes from the fault reference data. For the parameter information of any one branch node, obtain the standard format of all monitored parameters included in the parameter information, and perform data format conversion on the monitored values of the corresponding monitored parameters in the parameter information according to the standard format. After the data format conversion of the monitored values of all monitored parameters is completed, generate the transient ready data of the corresponding branch node according to the monitored values of all monitored parameters after conversion; Generate the fault ready data of the line branch according to the transient ready data of all branch nodes.

7. A line branch identification system for a distribution substation area according to claim 6, characterized in that, During the generation of the transient ready data of any one of the branch nodes, the preprocessing unit records the original format, data capacity size, conversion duration, progress start duration, and start and end duration of all monitored parameters in the parameter information of the branch node and generates the transient record information of the branch node based on it. Generate the fault processing information of the line branch according to the transient record information of all branch nodes.

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