Intelligent distribution network maintenance automatic permission data model

Abstract

The invention relates to a distribution network dispatching automation technology in a power system, in particular to an intelligent distribution network maintenance automatic permission data model. The system comprises a data acquisition module, a data verification module, an automatic permission module, an equipment condition verification module before power restoration and a data backfilling module. The data acquisition module acquires related data from a distribution network OMS system and an OCS system; the data verification module carries out equipment state consistency verification, logic verification and association verification; the automatic permission module performs automatic permission and generates permission information after the verification is passed; the equipment condition verification module before power restoration performs verification before power restoration on the equipment; and the data backfilling module backfills the permission information to the distribution network OMS system. According to the method, multi-dimensional data are integrated, the accuracy, reliability and efficiency of maintenance permission are improved through hierarchical verification, and maintenance safety and stable operation of a power grid are guaranteed.

Description

Technical Field

[0001] The invention relates to a distribution network dispatching automation technology in an electric power system, and in particular to an intelligent distribution network maintenance automatic permission data model. Background Art

[0002] With the rapid growth of my country's economy, the power system continues to grow and develop, the number and scale of distribution network equipment have increased, and the workload of maintenance has increased exponentially. Traditional distribution network equipment maintenance work permits are mainly carried out by phone, which is inefficient and has many drawbacks. It can no longer meet the requirements of efficient and reliable operation of modern power systems.

[0003] Limitations of the existing system: The Guangxi Power Grid Safety Production Management System and Distribution Network OMS System were put into operation in 2015. Although the comprehensive power outage and grid connection management modules support some of the Guangxi distribution network’s businesses, such as distribution network maintenance plans, maintenance application forms, and grid connection startup plans, these functional modules only realize the circulation and approval of maintenance business forms. There are still many problems in the daily maintenance of the distribution network.

[0004] The actual distribution network maintenance faces many difficulties, such as frequent distribution network tripping and heavy maintenance tasks, and most of the execution process still relies on manual operation. The lack of effective technical means to realize the automatic execution, analysis and safety audit of the maintenance process has led to low efficiency of power grid operation and maintenance, and the reliability of distribution network power supply has also been affected, which cannot meet the current requirements of integrated control and intensive distribution network business development.

[0005] Chinese patent CN110349049A discloses an automatic work permit system for distribution network maintenance, which uses a modular design. The data reading module reads the distribution network maintenance order data in the power network and transmits the data to the distribution network maintenance order list module. The start application module submits the start application request to the start permit module; the start permit module automatically permits the start application request; the completion application module submits the completion application request to the completion termination module; the completion termination module automatically terminates the completion application request; the distribution network maintenance order list module integrates the data of the data reading module, the start application module, the start permit module, the completion application module, and the completion termination module and displays them; the data storage module is used to store the data of the data reading module, the distribution network maintenance order list module, the data storage module, the start application module, the start permit module, the completion application module, and the completion termination module; the reminder module reminds the staff of the automatic permission or termination of the distribution network maintenance order.

[0006] Today's technical requirements and limitations have promoted the development of distribution network maintenance automatic licensing technology and the birth of related data models to improve the efficiency of maintenance work and power supply reliability. Combined with the limitations of existing technologies, developing an intelligent distribution network maintenance automatic licensing data model is an inevitable trend of current development and is also the technical topic faced by this development project. Summary of the invention

[0007] The problem to be solved by the present invention is how to provide a distribution network maintenance automatic permission data model with higher efficiency, greater safety and higher intelligence.

[0008] To solve the above problems, the present invention proposes the following solutions:

[0009] An intelligent distribution network maintenance automatic permission data model includes a data acquisition module, a data verification module, an automatic permission module, a pre-power restoration equipment condition verification module, and a data backfill module.

[0010] S-1-1, data acquisition module, used to obtain distribution network maintenance order data, equipment real-time status data, dispatch operation ticket execution data and equipment fault information from the distribution network OMS system and OCS system;

[0011] S-1-2, data verification module, performs multi-source path security verification on the acquired maintenance order data;

[0012] S-1-3, automatic permission module, when the data verification module passes the verification, it automatically permits the maintenance application and generates permission information;

[0013] S-1-4, the equipment condition verification module before power restoration is used to automatically verify the equipment conditions before power restoration. The automatic verification of equipment conditions before power restoration includes four aspects: equipment electrical parameter verification, equipment protection device verification, equipment mechanical component verification and equipment line connection verification; after meeting the "five must-checks and one confirmation", it supports the dispatcher to automatically permit completion;

[0014] S-1-5, data backfill module, used to automatically backfill the license information to the distribution network OMS system.

[0015] The data verification module comprises:

[0016] S-1-2-1, Equipment status consistency check unit, used to automatically obtain the real-time status of OCS equipment and perform consistency check with the equipment status reported during the on-site start and completion application;

[0017] S-1-2-2, logic check unit, used to obtain the execution status of the associated dispatch operation ticket and the status of the related pre- and post-orders of the maintenance application form for logic check;

[0018] S-1-2-3, equipment fault information correlation verification unit, is used to obtain equipment fault information and perform correlation verification with the equipment related to the maintenance application form to determine whether there is a status conflict.

[0019] The specific steps of verifying the electrical parameters of the equipment in the automatic verification of the equipment conditions before power restoration include:

[0020] S-3-1. Check whether the rated voltage of the equipment matches the grid voltage;

[0021] S-3-2. Verify the matching between the rated current of the equipment and the actual operation requirements;

[0022] S-3-3. Verify whether the power factor of the equipment matches the grid requirements and equipment design standards.

[0023] The specific steps of verifying the equipment protection device in the automatic verification of equipment conditions before power restoration include:

[0024] S-4-1. Verify the normal working condition of the overload protection device. The overload protection device will be activated and cut off the circuit when the equipment is overloaded;

[0025] S-4-2. Verify the effectiveness of the short-circuit protection device, which quickly cuts off the circuit when a short circuit occurs in the equipment;

[0026] S-4-3. Verify the grounding protection device, which is connected to the ground to introduce leakage current into the ground.

[0027] The specific steps of verifying the mechanical parts of the equipment in the automatic verification of equipment conditions before power restoration include:

[0028] S-5-1. Verify the mechanical status of equipment with mechanical moving parts and check for any stagnation in the operation of the equipment;

[0029] S-5-2. Verify the wear of mechanical parts, observe the scratches and wear marks on the equipment, and any abnormal sounds during operation;

[0030] S-5-3. Verify the tightness of the mechanical connections of the equipment.

[0031] Preferably, the specific steps of verifying the equipment circuit in the automatic verification of equipment conditions before power restoration include:

[0032] S-6-1. Check the integrity of the connection between the equipment and the line, especially the disconnection and loose connection, observe the appearance of the connection part, and use a multimeter to measure the resistance;

[0033] S-6-2. Verify the correctness of route markings and ensure that they are clear and correct;

[0034] S-6-3. Check the insulation performance of the line and use an insulation resistance tester to measure the insulation resistance of the line. Generally, the insulation resistance is required to be greater than 0.5MΩ.

[0035] The data acquisition module and data verification module use multi-source data fusion and comprehensive safety verification technology, integrate multi-source data of the OMS system, OCS / EMS system, and DCCS system, and perform safety verification from multiple dimensions.

[0036] The multi-source data fusion module includes:

[0037] S-8-1. Multi-interface data acquisition unit, establishes stable communication interface with the power grid management platform (OMS), local energy management systems (OCS / EMS) and distribution network distributed control system (DCCS), and collects data in real time or periodically. The period of collecting maintenance order data with the OMS system is no more than 30 seconds. It maintains real-time and uninterrupted data connection with the OCS / EMS system to obtain the real-time status of the equipment, and obtains the operation ticket data in real time when the distribution network DCCS system executes the operation ticket related operations;

[0038] S-8-2, data preprocessing unit, unifies the format, performs semantic analysis and correlation matching processing on the data collected from different systems; parses the maintenance order data in the OMS system according to the predetermined semantic rules; converts the real-time status data of the equipment in the OCS / EMS system into a format compatible with the maintenance order data, and associates it with the equipment information in the maintenance order according to the equipment identification; and parses the operation steps of the operation ticket data of the distribution network DCCS system;

[0039] S-8-3, data cache and update unit, builds a high-speed cache mechanism, stores the latest data after preprocessing, and monitors the data update status of each data source in real time; when new data arrives at the data source or the data status changes, the data in the cache is updated immediately, and the data update timestamp is marked to ensure the timeliness and validity of the data, providing the latest data support for security verification and automatic licensing decisions.

[0040] The data cache and update unit uses an elimination strategy based on the comprehensive timeliness and usage frequency of the potential energy algorithm. When the cache space is insufficient, for each data x in the cache,

[0041] S-8-3-1. Calculate the timeliness potential of the data. The difference between the current time and the last update time determines the timeliness potential of the data. The smaller the time difference, the higher the potential.

[0042] S-8-3-2. Calculate the frequency potential of data usage. The more times data is used within a period of time, the higher the frequency potential of data usage.

[0043] S-8-3-3. Calculate the comprehensive potential energy of the data, set the weight coefficient to balance the timeliness potential energy and the frequency of use potential energy to determine the comprehensive potential energy of the data;

[0044] S-8-3-4. Based on the selection of weight coefficients and potential energy thresholds, construct a data benefit model for weight coefficients and conduct data analysis for the subsequent setting of potential energy thresholds;

[0045] S-8-3-5. Select to replace or retain data based on the comprehensive potential energy of the data. Set a potential energy threshold and compare the comprehensive potential energy of each data with the potential energy threshold. When the comprehensive potential energy of the data is lower than the potential energy threshold, replace the data. Otherwise, retain the data.

[0046] The comprehensive safety verification module includes:

[0047] S-10-1, the multi-dimensional real-time status verification submodule simultaneously receives the on-site reported equipment status information in the OMS system and the real-time equipment status data in the OCS / EMS system after being processed by the multi-source data fusion module, and performs accurate comparison field by field; during the verification process, the fast comparison technology is used to efficiently compare the key status parameters of the equipment. If any inconsistency is found, a high-priority alarm notification is immediately triggered, and the automatic licensing process is suspended until the inconsistency problem is resolved;

[0048] S-10-2, the logic relationship intelligent verification submodule, based on the pre-set complex logic rule base, deeply verifies the execution of the associated dispatch operation ticket and the logical relationship between the preceding and following orders of the maintenance application form. During the verification process, a path analysis algorithm based on graph theory is used to simulate the logical process of the maintenance operation. If a logical inconsistency is detected, a detailed alarm report is immediately issued. The report content includes the specific logical error points and the maintenance links that may be affected, and the automatic permission process is prevented from continuing. At the same time, logic adjustment suggestions are provided to assist operation and maintenance personnel to quickly correct the problem.

[0049] S-10-3, the fault correlation deep analysis submodule obtains the equipment fault information and the equipment information related to the maintenance application form, and then uses the fault correlation analysis technology based on the knowledge graph to explore the potential conflict relationship between the equipment fault and the maintenance plan; by constructing a knowledge graph containing multi-dimensional information such as the equipment fault type, the fault location, and the maintenance equipment scope, it quickly identifies the fault factors that may increase the risk of maintenance operations. If a status conflict is found, an accurate alarm will be issued in a timely manner. The alarm content includes the fault details, the cause of the conflict, and the recommended response measures. Automatic permission is prohibited to ensure that the maintenance work is carried out without fault interference or when the fault has been properly handled.

[0050] The beneficial effects of adopting the above technical solution are:

[0051] The data acquisition module of the present invention can comprehensively acquire various data information through the setting of the equipment status data unit, the dispatch operation ticket data unit and the equipment fault information unit, thereby providing technical support for the subsequent data verification link.

[0052] The data acquisition module in the present invention includes a multi-interface data acquisition unit, a data preprocessing unit, a data cache and update unit, which can be connected to multiple data platforms, and perform format unification, semantic analysis and association matching processing on the collected data to ensure the synergy of data in each system.

[0053] The data verification module in the present invention verifies from multiple aspects such as equipment status consistency, logical relationship and conflict of associated equipment status during the data verification process, avoiding permission errors caused by inadequate consideration of a single factor, thereby improving the accuracy and reliability of maintenance permission; and because of the strict verification of information such as equipment status, dispatch operation tickets and equipment failures, potential safety hazards can be discovered in a timely manner. Including but not limited to, when the equipment status is inconsistent, there are logical errors and conflicts in associated equipment, an alarm will be prompted, which enables maintenance personnel to deal with the problem before permission, effectively preventing maintenance work from being carried out in an unsafe state, and improving the safety of maintenance work.

[0054] The pre-power-on equipment condition verification module in the present invention verifies the electrical parameters, equipment protection devices, equipment mechanical components and equipment line connections before power-on; it collects various parameters of the equipment, which can effectively reduce the stability and safety of the equipment's power-on operation, and can also improve the equipment's operating efficiency and reduce energy consumption.

[0055] The data model in the present invention realizes the automated data processing and verification process. Compared with the traditional manual verification method, it greatly reduces the time and workload of manual operation, improves the speed of maintenance permission, and thus improves the overall efficiency of maintenance work. Fourth, accurate maintenance permission and safe maintenance work can avoid the adverse effects on the power grid caused by improper maintenance. By timely discovering and handling equipment problems, the normal operation of power grid equipment is guaranteed, thereby ensuring the stable operation of the power grid.

[0056] The data cache and update unit in the present invention uses an elimination strategy based on a potential energy algorithm that combines comprehensive timeliness and usage frequency. When the cache is insufficient, the timeliness potential and usage frequency potential of the existing data are calculated. The weight ratio between the two can be adjusted according to actual needs to determine the comprehensive potential of the data, and then the replacement or retention of the data is finally confirmed by comparing it with a manually set potential energy threshold. The elimination strategy can ensure that the data cache and update unit not only ensures that the cache space is sufficient, but also retains key data, providing data support for subsequent security verification and automatic licensing decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0058] Figure 1 A system diagram of the intelligent distribution network maintenance automatic permission data model proposed by the present invention;

[0059] Figure 2 This is a schematic diagram of a multi-source data fusion module and a comprehensive verification module in the system of the intelligent distribution network maintenance automatic permission data model proposed by the present invention. DETAILED DESCRIPTION

[0060] In order to make the features and advantages of the present invention more obvious and easy to understand, the technical solution will be clearly and completely described below in combination with the drawings and specific implementation methods. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0061] The present invention discloses an intelligent distribution network maintenance automatic permission data model.

[0062] Example 1: Distribution network maintenance order execution self-driving module

[0063] 1. Intelligent generation of operation tickets

[0064] 1) Data acquisition and analysis

[0065] like Figure 1 , establish an efficient data acquisition interface with the OMS system through the multi-interface data acquisition unit of the data acquisition module in the data model, and obtain the distribution network maintenance order data regularly (according to the set update cycle, such as ≤30S). The data preprocessing unit uses a data parsing algorithm (such as based on regular expressions or XML parsers) to parse the acquired maintenance order data and extract key information, such as maintenance object, maintenance content, planned start time, planned end time, etc.

[0066] For example, if the maintenance list is stored in XML format, use an XML parser to parse out the equipment name, maintenance item, schedule and other information.

[0067] In the acquisition phase, when the multi-interface data acquisition unit obtains the distribution network maintenance order data from the OMS system, the data cache and update unit can store this data. Since data acquisition is periodic (such as ≤30S), it can ensure that the latest data obtained is stored in time, and according to its elimination strategy based on the potential energy algorithm, it ensures that the maintenance order data in the cache is the best data in terms of timeliness and frequency of use.

[0068] The specific steps of the elimination strategy based on the potential energy algorithm include:

[0069] 1. Calculation of the timeliness potential of data. Timeliness is a key factor in data processing and management. The calculation of the timeliness potential of data aims to measure the freshness of the data and its value at the current moment. Consider the difference between the current time and the last update time of the data. If the difference is small, it means that the data is highly time-sensitive and the corresponding potential is high. A timeliness potential function can be defined. For example, let the current time be t, and the last update time of data x be t i , the update period of data x is Δt a When tt i <Δt a , the time-effect potential energy increases as the time difference decreases, which can be set as When tt i ≥Δt a When the data is updated, the timeliness potential is 0, which means that the data has exceeded its expected update cycle, its timeliness has been greatly reduced, and its value in the current decision or analysis is close to zero. For example, if the update cycle of a device status data is set to 30 seconds, and the difference between the current time and the last update time reaches or exceeds 30 seconds, the timeliness potential of the data is 0. At this time, the system may need to re-acquire the latest data to ensure the accuracy of the decision.

[0070] 2. Calculate the potential energy of data usage frequency. The more frequently used data is, the higher its potential energy should be. Suppose the number of times data x is used in n time units is n i , the usage frequency is The use frequency potential can be defined as P f (n i )=f(n i ), which means that the more frequently used data is, the higher its frequency of use potential is. In practical applications, frequently used data often has a more important reference value for system operation analysis and decision-making. For example, for the formulation of distribution network maintenance plans, the historical fault data of equipment that is frequently queried and referenced has a higher frequency of use potential, indicating that this data has a higher influence when planning maintenance work.

[0071] 3. Calculation of comprehensive potential energy of data: Considering the timeliness potential energy and the usage frequency potential energy, first set a coefficient vector (α, 1-α) and a potential energy vector (P t (t), P f (x)), where α in the coefficient vector is set manually, and the projection length of the potential energy vector on the coefficient vector can be adjusted according to on-site needs to characterize the comprehensive potential energy.

[0072] Furthermore, the key is the value of α and its optimization problem. For this purpose, a data benefit model for the value of α is constructed; the details are as follows:

[0073] First, we set the vector vector The basic characteristics of the two vectors are calculated and analyzed, including: coefficient vector The length of the potential energy vector The length of the two vectors, and the angle between the two vectors; further, it also includes the inner product of the two vectors. According to the definition of the inner product of the vector where θ is and Further consideration is based on the vector Geometric relationship is used to characterize and analyze the comprehensive potential energy; at this time, the first step is to characterize and analyze the comprehensive potential energy using vector projection, then: vector In vector The projection length on is the ratio of the inner product of the two to the coefficient vector modulus. We can represent the comprehensive potential energy P(x) as a vector In vector Upper projection length and Now we can see that, in a geometric sense, when When α=0 or α=1, the comprehensive potential energy P(x) is equal to the vector In vector When α = 1, the system is suitable for clearing outdated data and updating the system, focusing only on the timeliness of the data; when α = 0, data with high access times can be screened out, which can provide a data basis for subsequent data analysis, such as data screening based on seasonal power supply demand and fault detection.

[0074] At the same time, considering that the comprehensive potential energy is represented by the product of the projection length of the potential energy vector on the coefficient vector and the length of the coefficient vector, it can be further seen that the comprehensive potential energy is more sensitive to the potential energy data in the direction of the coefficient vector. We can determine the corresponding angle of the coefficient vector according to the required angle of the potential energy vector, which can provide a certain reference for the value of α on site.

[0075] 3. The above gives a data benefit model about the value of α. At the same time, regarding the setting of the threshold, a data process based on the trigonometric function relationship is further constructed to mine and decompose the data connotation of the above two vectors and their synergistic relationship with the comprehensive potential energy. At this time, the two variables in the potential energy vector are converted into trigonometric function forms, which are represented by the length of the potential energy vector and the angle-related quantity, respectively. From this, an expression of the variables and angle-related quantities in the coefficient vector can be obtained. Then, the variable part of the expression is derived to obtain the extreme points and change trends of the comprehensive potential energy under different data time potential energy and usage frequency potential energy proportional relationships, as follows:

[0076] First, introduce a new variable (Right now ), we can express the time-effect potential energy and the usage frequency potential energy by trigonometric functions: in is a vector The angle with a certain reference axis. Then the data instance of comprehensive potential energy is constructed and characterized as: At this point, we can further analyze the variables in the comprehensive potential energy. First, consider Take the derivative of y to find its extreme point, that is, Substituting it into y, we can get the extreme value of y, so as to analyze the comprehensive potential energy in different Through this analysis, a range reference can be provided for the later threshold selection problem.

[0077] 4. Eliminate data based on comprehensive potential energy and set a potential energy threshold Ω, which can be adjusted according to actual conditions.

[0078] For each data x in the cache, if its comprehensive potential energy P(x)≤Ω, the data can be replaced; if P(x)>Ω, the data is retained and sorted and output according to the comprehensive potential energy to facilitate subsequent data analysis.

[0079] 2) Power semantic analysis and operation ticket generation

[0080] The semantic analysis of the parsed maintenance order data is performed using the power semantic analysis algorithm and knowledge base. According to the analysis results, the structured maintenance order maintenance object and maintenance content information is automatically extracted and formed, and the associated load transfer, equipment power outage, equipment power restoration, and load recovery operation tickets are generated. For example, if the maintenance order mentions the maintenance of a transformer, the semantic analysis algorithm will identify the transformer as the maintenance object and generate the corresponding operation ticket content according to the relevant rules.

[0081] 2. Automatic execution function of dispatching operation tickets

[0082] 1) Interaction with OCS system

[0083] like Figure 2, A two-way interactive interface with the OCS system is established through the multi-interface data acquisition unit of the data acquisition module in the data model. , Through this interface, on the one hand, real-time data of power outage and power transfer execution is obtained from the OCS system, and the data cache and update unit can cache these interactive data. According to its cache strategy, the timeliness and validity of the data are guaranteed to guide the automatic execution of the operation ticket; on the other hand, the execution results of the operation ticket are pushed to the OCS system so that the OCS system can update the relevant equipment status and business records. For example, when the operation ticket is executed to the equipment power outage link, the current status of the equipment is obtained from the OCS system to ensure the safety and accuracy of the power outage operation, and then the power outage operation results are fed back to the OCS system.

[0084] At the same time, the data of the operation ticket to be executed is sent to the distribution network programmed operation module to automatically generate an operation sequence. According to the operation sequence and the real-time data fed back by the OCS system, the automatic sending and receiving of operation commands and condition confirmation of the three process links of "dispatching order", "dispatching confirmation" and "dispatching order receipt" are realized. For example, when the dispatching order is issued, the operation command is sent to the recipient's terminal or APP. After the recipient returns the execution result, the system automatically confirms and sends the result to the setting and listing module. After passing the verification, the next operation can be automatically executed.

[0085] 3. Automatic permission function for distribution network maintenance orders

[0086] In this part, the technical team built a new multi-source data verification mechanism and a pre-power-on equipment condition verification mechanism, which are detailed as follows:

[0087] 1) Multi-source data verification mechanism

[0088] Equipment status consistency check, assuming that the equipment status reported on site is vector The current status of the device obtained in real time from the OCS device is a vector The core of equipment status consistency check is to compare these two vector elements and check the consistency. Its vector form is: Indicates the key status information of the equipment to be reported on site, such as the equipment switch position, operating condition description, etc.; Corresponding to the real-time status details of the device fed back by the OCS system; the verification vector operation is:

[0089]

[0090] When all elements of this operation result are close to zero, it indicates that the status is consistent, otherwise an alarm is prompted.

[0091] Logical verification involves the execution of the dispatching operation ticket and the state of the pre- and post-orders associated with the maintenance application form. Suppose the execution progress vector of the dispatching operation ticket is The state vector of the maintenance application form before and after the completion of the order is: Specifically: Covers whether each step of the operation ticket has been executed, such as whether the circuit breaker has been closed, whether the power-off operation is in place, and other key operation execution conditions; Indicates the approval, completion and other status information of the maintenance application form and the related previous and subsequent forms; logical check vector operation, specifically: According to the established logic rules, when the product result meets specific conditions, the logic is correct, otherwise an alarm is triggered, indicating that there is a logical conflict in the process.

[0092] Equipment fault information correlation check, assuming that the equipment fault information vector is The equipment information vector related to the maintenance application form is To troubleshoot potential conflicts between the two: Contains information such as equipment fault code, fault occurrence time, fault location, etc.; vector For maintenance, the equipment model, location, current working condition and other data are involved; related verification operation: judgment When the intersection is an empty set, there is no conflict; if there are intersection elements, carefully check the conflict points and evaluate whether to issue an alarm according to the rules.

[0093] Before entering the verification process, the above multi-source data is pre-processed by the data cache and update unit to ensure the timeliness and accuracy of the data. Suppose the data state vector after the cache unit is processed is Meet the requirements of timeliness, completeness and other dimensions to avoid verification errors.

[0094] 2) Equipment condition verification mechanism before power restoration

[0095] Verify the electrical parameters, first of all, the voltage matching verification: Assume the rated voltage of the equipment is U e , the measured voltage of the power grid is U g , the lower limit of the fluctuation range is U min , the upper limit is U max , forming a vector Verification criteria: U min ≤U g ≤U max , to ensure that the device voltage is suitable. Further verification of current matching: the rated current of the device is I e , the measured operating current is I g , construct the vector When I g ≥I e When the power factor is checked, the equipment design power factor is The power factor required by the power grid is The measured power factor is The vector is represented as Ensure that the three are matched, and the inductive load also verifies the status of the power factor compensation device.

[0096] Verify the equipment protection device, considering multiple aspects, including overload protection verification: Assume the overload protection device action threshold is I th , the measured device current is I m ,vector When I m ≥I th , the device should act in time to cut off the circuit, and the overload test can be simulated on site. And verify the short-circuit protection: the short-circuit protection response time standard is t s , the measured response time is t m , the action accuracy index is A e , the measured action accuracy is A m ,vector Use professional instruments to check the response and action accuracy. Also check the grounding protection: the standard value of grounding resistance is R e , the measured ground resistance is R m The grounding line connection firmness index is C e , the measured firmness is C m ,vector Ensure grounding safety.

[0097] For the mechanical parts of the equipment, we focus on three key dimensions: mechanical status, wear and tear, and connection tightness. The first is the mechanical status verification: S is the smoothness index of the mechanical parts. e , the measured fluency is S m , whether there is a jam is marked as B (0 means no jam, 1 means jam), vector Manual operation and observation determine the equipment operating status. Then the wear condition is verified: the wear limit value of key mechanical parts is W e , the measured wear degree is W m ,vector The wear condition is judged by appearance and sound. Then the connection tightness is verified: the standard torque for connection tightness is T e , the measured torque is T m , the looseness is marked as L (0 for tight, 1 for loose), vector Check bolts, nuts and other connection parts regularly.

[0098] In terms of equipment line connection verification, we also start from the three core aspects of line integrity, line identification correctness, and line insulation performance; Line integrity verification: Assume that the standard value of line connection resistance is R c , the measured resistance is R m , disconnection and virtual connection are marked as V (0 means no abnormality, 1 means there is a problem), vector Combine appearance and multimeter measurement to judge. Line marking correctness verification: Line marking integrity standard is C e , the measured completeness is C m , the identification accuracy index is A e , the measured accuracy is A m ,vector Ensure that the marking is clear and accurate. Line insulation performance verification: The standard value of insulation resistance is R i , the measured insulation resistance is R m ,vector Measure with insulation resistance tester, R m ≥R i .

[0099] All the above verification operations are organized into the following determinant:

[0100]

[0101] Among them, “-” means that there is no directly related information at the corresponding position. This determinant system presents the entire process of multi-source data verification and equipment condition verification before power restoration. Each vector corresponding operation is checked one by one. Only when all verification results meet the standards, the equipment can automatically allow power to be restored and put into normal operation, laying a solid foundation for the stable operation and maintenance of the power system.

[0102] After the "five must-checks and one confirmation" conditions are met, the dispatcher can automatically approve the completion of the work. Verify whether the equipment is ready for power restoration, including the equipment status, the status of related protection devices, and whether there are any remaining issues.

[0103] 4. Automatic positioning and listing function of distribution network

[0104] 1) Integration with distribution network DCCS and OCS systems

[0105] Through the multi-interface data acquisition unit of the data acquisition module in the data model, an integrated interface is established with the distribution network DCCS system to automatically obtain the distribution network operation ticket data of the distribution network DCCS. At the same time, an integrated interface with the 14 local distribution network OCS systems is established to push the listing instructions to the distribution network OCS system for execution. For example, during the execution of the operation ticket, a listing instruction is generated according to the content of the operation ticket, and the listing instruction is sent to the corresponding OCS system through the integrated interface with the distribution network OCS system to implement the setting / listing operation on the OCS diagram.

[0106] After the operation is completed, OCS needs to generate a file to transmit the listing information of the operation back to the DCCS system of the ground dispatching network. At the same time, it provides a listing and delisting statistics function. The system automatically records the listing and delisting information according to the listing and delisting actions, including the listing person, listing time, type, listing equipment, delisting person, delisting time, etc. For example, after each listing or delisting operation, the system automatically records the relevant information in the database for subsequent query and statistics.

[0107] 5. Distribution network maintenance single operation self-driving intelligent log function

[0108] 1) Log information collection and synchronization

[0109] During the self-driving process of the distribution network maintenance order, the log information such as drafting, review, network command, programmed control, and anti-error verification are automatically tracked and collected. By establishing an integrated interface with the distribution network OMS system, these log information are pushed to the dispatch log module corresponding to the distribution OMS system. In this process, the data acquisition module of the data model provides a data source for the collection of log information, while the data cache and update unit ensures the integrity and accuracy of the log information during storage and transmission. For example, when a drafting operation occurs, the relevant information of the drafter and the drafting time are recorded; when an audit operation occurs, the relevant information of the auditor and the audit time are recorded, and so on. All relevant log information is synchronized to the OMS system to provide a basis for tracing and analyzing the maintenance process.

[0110] 6. Repair and execute the automatic archiving function

[0111] 1) Archiving condition verification and data synchronization

[0112] It should have an automatic archiving verification function, and the maintenance order can only be automatically archived after all power restorations are completed (or the order has been set as unexecuted by the issuing party). When archiving is completed after the power restoration, the power outage and restoration time and work delay are automatically filled back into the OMS maintenance order. For example, when the power restoration operation is completed, the system checks whether the power restoration is completely completed. If so, the power restoration time and work delay are automatically filled back into the OMS maintenance order, and the status of the maintenance order is updated to archived. This process involves the data backfill module in the data model, which ensures the closed-loop management of maintenance data. At the same time, the data verification module also guarantees the accuracy and rationality of the backfilled data to a certain extent.

[0113] Example 2: Distribution network control self-driving cockpit module

[0114] 1. Full process visualization function of distribution network maintenance list

[0115] 1) Data association and display

[0116] Based on self-driving cruise drive engine, such as Figure 1The data acquisition module in the data model is responsible for collecting data from multiple related systems. These data establish a stable connection with the maintenance business self-driving module through the multi-interface data acquisition unit to obtain maintenance business related data. In the multi-source data fusion module, the data preprocessing unit unifies the format, semantically parses and associates the collected data to ensure that the data can accurately display the various processes of maintenance execution on the cockpit interface, including load transfer, power outage, dispatch permission, permission termination, power restoration, load recovery and other processes. For example, when the mouse moves to the "power outage" link, the relevant information of the power outage operation, such as power outage equipment, power outage time, etc., is displayed. This depends on the latest data stored in the data cache and update unit. These data are cached to ensure the timeliness and validity of the data. When a maintenance order contains multiple operation items, the mouse moves to this link to display the execution status of all operation items in this link. This requires the data model to accurately integrate and process data from different data sources to fully present the execution details of the maintenance order.

[0117] 2) Display of abnormal links

[0118] The highlighting function for abnormal links, early termination, cancellation, postponement and other links in the entire maintenance process is a comprehensive safety verification mechanism based on the data model. During the data verification process, the equipment status consistency verification module, the logic verification module and the equipment fault information association verification unit perform multi-dimensional inspections on the maintenance data. When an abnormal situation occurs, this information will be marked and fed back to the cockpit interface. When the mouse moves to this link, the corresponding reason is displayed. For example, if the maintenance order is delayed during execution, it may be due to equipment failure found in the data verification (the relevant equipment failure information is detected to conflict with the maintenance plan through the equipment failure information association verification unit) or insufficient personnel (may be found in the logic verification module. Logical problems related to human resource arrangements), etc. This information is accurately displayed to the user on the cockpit interface through the processing and transmission of the data model.

[0119] 2. Function associated with safety error prevention check during the whole maintenance process

[0120] 1) Real-time monitoring and alarm

[0121] This module is similar to the data model Figure 2The comprehensive safety verification module is closely integrated to realize the safety error prevention verification function of the whole maintenance process. The multi-dimensional real-time status verification submodule, the logical relationship intelligent verification submodule and the fault correlation deep analysis submodule continuously conduct in-depth analysis of the safety error prevention verification of the whole maintenance process. In this process, the data model obtains data from multiple data sources, such as the on-site reported equipment status information in the OMS system, the real-time status data of the equipment in the OCS / EMS system, and the equipment fault information. When these data are found to be abnormal during the safety verification process, such as the multi-dimensional real-time status verification submodule finds that the real-time status of the equipment is inconsistent with the reported status, or the logical relationship intelligent verification submodule detects a logical error in the maintenance process, or the fault correlation deep analysis submodule digs out the potential conflict between the equipment failure and the maintenance plan, an abnormal alarm message will be generated. These alarm messages are displayed on the cockpit interface through the information transmission mechanism of the data model. For example, if the safety error prevention verification fails during the maintenance process, an alarm window pops up on the cockpit interface to display the reason for the failure and related operation suggestions. This is an important manifestation of the data model to ensure maintenance safety.

[0122] 3. Task query function

[0123] 1) Conditional query design

[0124] The task query function relies on the data acquisition and processing capabilities of the data model. The data acquisition module collects data from various related systems. This data covers information such as the application unit, maintenance order number, maintenance order execution status, and occurrence time. The data cache and update unit ensures the timeliness and accuracy of this data. The data stored in the cache can be quickly retrieved according to the query conditions entered by the user. For example, a maintenance order query function is provided, which can be accurately queried based on conditions such as the application unit, maintenance order number, maintenance order execution status, and occurrence time. If the user wants to query the maintenance order submitted by a certain unit, he only needs to enter the name of the application unit in the query interface, and the system can filter out the maintenance orders that meet the conditions. This process relies on the effective management and organization of data by the data model.

[0125] 4.Task overview function

[0126] 1) Default display and node distinction

[0127] The implementation of the task overview function is based on the comprehensive management of the maintenance order data by the data model. The data acquisition module in the data model obtains the full process data of the maintenance order, including the status information of each process node. After the data preprocessing unit processes the data, the data is stored and updated by the data cache and update unit. By default, the list of maintenance orders executed on the day is displayed. This is based on the filtering and presentation of time information and maintenance order execution status data by the data model. After selecting the maintenance order, the operation flow chart of the current maintenance order is displayed, and all process nodes of the maintenance order are displayed in a visual graphic, including load transfer, power outage, dispatch permission, permission termination, power restoration, load recovery, etc., and different background colors are used to distinguish between executed nodes and unexecuted nodes. For example, executed nodes are represented by green and unexecuted nodes are represented by red. This visual display is based on the node status information accurately provided by the data model, so that users can intuitively understand the execution status of the maintenance order.

[0128] 5. Quick operation function

[0129] 1) Operation interface design

[0130] The realization of quick operation functions depends on the interaction and data processing between the data model and various related systems. The cockpit interface provides quick operations such as viewing maintenance order details, manual scheduling orders, and terminating autonomous cruise. When the user clicks the button to view the details of the maintenance order, the system obtains the detailed information of the maintenance order from the relevant data source through the data acquisition module of the data model, including maintenance content, equipment information, operation records, etc., and displays it in a pop-up window. If the user wants to manually schedule and order, after clicking the corresponding button, the system enters the manual scheduling interface through the interactive interface with the OCS system and other related systems (the communication interface established by the data acquisition module in the data model) to perform related operations. This series of operations is based on the accurate acquisition of data by the data model and the effective connection between systems.

[0131] 6. One-click viewing function for original form data of core business

[0132] 1) Data acquisition and display

[0133] The one-click viewing function of the original form data of the core business of regulation utilizes the data acquisition and integration capabilities of the data model. The data acquisition module obtains data from various systems that store the original form data through the integrated interface with the relevant systems. In the multi-source data fusion module, the data can be accurately displayed on the cockpit interface after preprocessing. For example, the original approved business form can be directly opened to view. If the user wants to view the original application form of a maintenance order, after clicking the corresponding button, the original application form will be directly opened to display all relevant information. This is due to the data model's integration of data from different systems and efficient data acquisition mechanism.

[0134] 7. Business drill-down query function

[0135] 1) Multi-level query design

[0136] The business drill query function is realized on the basis of the data model's deep organization and management of data. When the data model collects and processes the maintenance order data, the detailed information of each link is recorded and stored. When the user uses the business drill query function, for example, if he wants to know the specific operation details of the "power outage" link in a maintenance order, the system first locates the relevant data of the "power outage" link through the data structure and retrieval mechanism in the data model, and then goes deep into the next level query interface to display the detailed information of the power outage operation, such as the power outage equipment, power outage time, operator, etc., providing users with detailed data query capabilities from the overall to the local, from the macro to the micro.

[0137] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0138] In various embodiments, the hardware implementation of the technology can directly adopt existing intelligent devices, including but not limited to industrial computers, PCs, smart phones, handheld stand-alone computers, floor-standing stand-alone computers, etc. Its input device preferably adopts a screen keyboard, its data storage and calculation module adopts existing memory, calculator, controller, its internal communication module adopts existing communication ports and protocols, and its remote communication adopts existing GPRS network, World Wide Internet, etc.

[0139] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0140] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are only schematic, for example, the division of modules or units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms. The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the scheme of this embodiment.

[0141] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. An intelligent distribution network maintenance automatic permission data model, characterized in that: S-1-1, data acquisition module, used to obtain distribution network maintenance order data, equipment real-time status data, dispatch operation ticket execution data and equipment fault information from the distribution network OMS system and OCS system; S-1-2, data verification module, performs multi-source path security verification on the acquired maintenance order data; S-1-3, automatic permission module, when the data verification module passes the verification, it automatically permits the maintenance application and generates permission information; S-1-4, the equipment condition verification module before power restoration is used to automatically verify the equipment conditions before power restoration. The automatic verification of equipment conditions before power restoration includes four aspects: equipment electrical parameter verification, equipment protection device verification, equipment mechanical component verification and equipment line connection verification; after meeting the "five must-check and one confirmation" requirements, it supports the dispatcher to automatically permit completion; S-1-5, data backfill module, used to automatically backfill the license information to the distribution network OMS system.

2. According to claim 1, an intelligent distribution network maintenance automatic permission data model is characterized in that The data verification module comprises: S-1-2-1, Equipment status consistency check unit, used to automatically obtain the real-time status of OCS equipment and perform consistency check with the equipment status reported during the on-site start and completion application; S-1-2-2, logic check unit, used to obtain the execution status of the associated dispatch operation ticket and the status of the related pre- and post-orders of the maintenance application form for logic check; S-1-2-3, equipment fault information correlation verification unit, is used to obtain equipment fault information and perform correlation verification with the equipment related to the maintenance application form to determine whether there is a status conflict.

3. According to claim 1, an intelligent distribution network maintenance automatic permission data model is characterized in that: The specific steps of verifying the electrical parameters of the equipment in the automatic verification of the equipment conditions before power restoration include: S-3-1. Check whether the rated voltage of the equipment matches the grid voltage; S-3-2. Verify the matching between the rated current of the equipment and the actual operation requirements; S-3-3. Verify whether the power factor of the equipment matches the grid requirements and equipment design standards.

4. According to claim 1, an intelligent distribution network maintenance automatic permission data model is characterized in that: The specific steps of verifying the equipment protection device in the automatic verification of equipment conditions before power restoration include: S-4-1. Verify the normal working condition of the overload protection device. The overload protection device will be activated and cut off the circuit when the equipment is overloaded; S-4-2. Verify the effectiveness of the short-circuit protection device, which quickly cuts off the circuit when a short circuit occurs in the equipment; S-4-3. Verify the grounding protection device, which is connected to the ground to introduce leakage current into the ground.

5. The intelligent distribution network maintenance automatic permission data model according to claim 1 is characterized in that: The specific steps of verifying the mechanical parts of the equipment in the automatic verification of equipment conditions before power restoration include: S-5-1. Verify the mechanical status of equipment with mechanical moving parts and check for any stagnation in the operation of the equipment; S-5-2. Verify the wear of mechanical parts, observe the scratches and wear marks on the equipment, and any abnormal sounds during operation; S-5-3. Verify the tightness of the mechanical connections of the equipment.

6. The intelligent distribution network maintenance automatic permission data model according to claim 1 is characterized in that: The specific steps of the device line verification in the automatic verification of device conditions before power restoration include: S-6-1. Check the integrity of the connection between the equipment and the line, especially the disconnection and loose connection, observe the appearance of the connection part, and use a multimeter to measure the resistance; S-6-2. Verify the correctness of route markings and ensure that they are clear and correct; S-6-3. Check the insulation performance of the line and use an insulation resistance tester to measure the insulation resistance of the line. Generally, the insulation resistance is required to be greater than 0.5MΩ.

7. The intelligent distribution network maintenance automatic permission data model according to claim 1 is characterized in that: Multi-source data fusion and comprehensive safety verification integrate multi-source data from the OMS system, OCS / EMS system, and DCCS system to perform safety verification from multiple dimensions.

8. The intelligent distribution network maintenance automatic permission data model according to claim 7 is characterized in that: The multi-source data fusion module includes: S-8-1. Multi-interface data acquisition unit, establishes stable communication interface with the power grid management platform (OMS), local energy management systems (OCS / EMS) and distribution network distributed control system (DCCS), and performs real-time or periodic data collection. The period of collecting maintenance order data with the OMS system is no more than 30 seconds. It maintains real-time and uninterrupted data connection with the OCS / EMS system to obtain the real-time status of the equipment, and obtains the operation ticket data in real time when the distribution network DCCS system performs operation ticket related operations; S-8-2, data preprocessing unit, unifies the format, performs semantic analysis and correlation matching processing on the data collected from different systems; parses the maintenance order data in the OMS system according to the predetermined semantic rules; converts the real-time status data of the equipment in the OCS / EMS system into a format compatible with the maintenance order data, and associates it with the equipment information in the maintenance order according to the equipment identification; parses the operation steps of the operation ticket data of the distribution network DCCS system so that it can be cross-referenced with the maintenance order process and equipment status data, ensuring the coordination of the data of each system in subsequent processing; S-8-3, data cache and update unit, builds a high-speed cache mechanism, stores the latest data after preprocessing, and monitors the data update status of each data source in real time; when new data arrives at the data source or the data status changes, the data in the cache is updated immediately, and the data update timestamp is marked to ensure the timeliness and validity of the data, providing the latest data support for security verification and automatic licensing decisions.

9. The intelligent distribution network maintenance automatic permission model according to claim 8 is characterized in that: The data cache and update unit uses a comprehensive timeliness and usage frequency elimination strategy based on the potential energy algorithm. When the cache space is insufficient, for each data x in the cache S-8-3-1. Calculate the timeliness potential of the data. The difference between the current time and the last update time determines the timeliness potential of the data. The smaller the time difference, the higher the potential. S-8-3-2. Calculate the frequency potential of data usage, and count the number of times the data is used within a certain time unit. Divide this number by the total number of time units to get the usage frequency, and then get the frequency potential of data usage; S-8-3-3. Calculate the comprehensive potential energy of the data, set the weight coefficient to balance the timeliness potential energy and the frequency of use potential energy according to the system's emphasis on timeliness and frequency of use, and determine the comprehensive potential energy of the data; S-8-3-4. Based on the selection of weight coefficients and potential energy thresholds, construct a data benefit model for weight coefficients and conduct data analysis for the subsequent setting of potential energy thresholds; S-8-3-5. Select to replace or retain data based on the comprehensive potential energy of the data. Set a potential energy threshold and compare the comprehensive potential energy of each data with the potential energy threshold. When the comprehensive potential energy of the data is lower than the potential energy threshold, replace the data. Otherwise, retain the data.

10. The intelligent distribution network maintenance automatic permission data model according to claim 7, characterized in that: The comprehensive safety verification module includes: S-10-1, the multi-dimensional real-time status verification submodule simultaneously receives the on-site reported equipment status information in the OMS system and the real-time equipment status data in the OCS / EMS system after being processed by the multi-source data fusion module, and performs accurate field-by-field comparison; during the verification process, the fast comparison technology is used to efficiently compare the key status parameters of the equipment. If any inconsistency is found, a high-priority alarm notification is immediately triggered, and the automatic licensing process is suspended until the inconsistency problem is resolved; S-10-2, the logic relationship intelligent verification submodule, based on the pre-set complex logic rule base, deeply verifies the execution of the associated dispatch operation ticket and the logical relationship between the preceding and following orders of the maintenance application form. During the verification process, a path analysis algorithm based on graph theory is used to simulate the logical process of the maintenance operation. If a logical inconsistency is detected, a detailed alarm report is immediately issued. The report content includes the specific logical error points and the maintenance links that may be affected, and the automatic permission process is prevented from continuing. At the same time, logic adjustment suggestions are provided to assist operation and maintenance personnel to quickly correct the problem. S-10-3, the fault correlation deep analysis submodule obtains the equipment fault information and the equipment information related to the maintenance application form, and then uses the fault correlation analysis technology based on the knowledge graph to explore the potential conflict relationship between the equipment fault and the maintenance plan; by constructing a knowledge graph containing multi-dimensional information such as the equipment fault type, the fault location, and the maintenance equipment scope, it quickly identifies the fault factors that may increase the risk of maintenance operations. If a status conflict is found, an accurate alarm will be issued in a timely manner. The alarm content includes the fault details, the cause of the conflict, and the recommended response measures. Automatic permission is prohibited to ensure that the maintenance work is carried out without fault interference or when the fault has been properly handled.

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