Power grid operation inspection anti-error checking method, device and equipment and storage medium

Abstract

The invention discloses a power grid operation inspection anti-error checking method, device and equipment and a storage medium, and the method comprises the steps: determining an operation task of a transformer substation, and the operation task is the control operation of primary equipment and secondary equipment during the operation inspection of the transformer substation; performing operation rehearsal on the primary equipment and the secondary equipment in the operation task, and performing anti-error checking by using an anti-error rule; after the anti-error checking is passed, sorting the primary equipment and the secondary equipment according to a preset logic, generating a corresponding switching operation sequence, and issuing the switching operation sequence to an anti-error key and a pressing plate controller; and the anti-error key performs real-time anti-error judgment based on the actual state information of the operated equipment and the rehearsal check result, and triggers the temporary control strategy of the switching operation sequence to control execution based on the anti-error judgment result. The problems that an existing power grid operation inspection anti-error scheme is not comprehensive, low in accuracy and incapable of adapting to a complex scene of cooperative operation of primary equipment and secondary equipment are solved.

Description

Technical Field

[0001] This application belongs to the field of power grid maintenance technology, and more specifically, relates to a power grid operation and maintenance error prevention verification method, device, equipment and storage medium. Background Technology

[0002] As the scale and complexity of power grids increase, the safety risks during power grid operation and maintenance also rise. Misoperation is a significant cause of power grid accidents, especially in scenarios involving the coordinated operation of primary and secondary equipment, where the risk of misoperation is even higher.

[0003] Currently, the main way to reduce misoperation is by setting constraints between primary and secondary devices. While setting constraints can prevent misoperation to some extent, they are mostly limited to single devices or simple operation scenarios, and lack the need to prevent misoperation in complex scenarios such as collaborative operation of primary and secondary devices. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this application provides a power grid operation and maintenance error prevention verification method, device, equipment, and storage medium to solve the problems that existing power grid operation and maintenance error prevention schemes are incomplete, have low accuracy, and cannot adapt to complex scenarios involving the coordinated operation of primary and secondary equipment.

[0005] The present invention adopts the following technical solution.

[0006] The first aspect of this application provides a power grid operation and maintenance error prevention verification method, applied to an error prevention host in a substation, the method comprising: Determine the operation tasks of the substation, which are the control operations of the primary and secondary equipment during the operation and maintenance of the substation. The operation rehearsals are performed on each primary and secondary device in the operation task, and the operation rehearsals are checked in a multi-dimensional collaborative manner based on the pre-built anti-misoperation rules to obtain the rehearsal check results. The anti-misoperation rules include equipment status safety rules, operation sequence compliance rules and multi-device linkage anti-misoperation rules. After the anti-misoperation verification is passed, the primary and secondary devices are sorted according to the preset logic to generate the corresponding switching operation sequence, and then sent to the anti-misoperation key and the pressure plate controller through the encrypted communication channel. The anti-misoperation key has the functions of device identification, operation permission verification and mechanical interlocking, and the pressure plate controller supports remote activation / deactivation control and status feedback. When operating equipment on-site based on the switching operation sequence, the anti-misoperation key performs real-time anti-misoperation judgment based on the actual status information of the equipment after the operation and the pre-rehearsal verification results, and obtains the real-time anti-misoperation judgment result.

[0007] Optionally, in a first implementation of the first aspect of this application, determining the substation's operational tasks includes: Receive operation instructions for primary and secondary equipment issued by the dispatching system in the substation, the operation instructions including operation type, operation object and operation time; Based on the operation type, the operation object, and the operation time, a corresponding operation task template is matched from a preset task library. The operation task template includes the operation scenario and the standard operation process of each device. Based on the current operating status of the substation and the health status of each device, the operation task template is dynamically adjusted to generate the final operation task. The dynamic adjustment includes equipment selection optimization, operation sequence adjustment, and supplementation of safety measures.

[0008] Optionally, in the second implementation of the first aspect of this application, the step of performing an operation rehearsal for each primary and secondary device in the operation task includes: The real-time operating status of primary equipment and the functional status of secondary equipment are obtained, and the real-time operating status and the functional status are mapped to obtain a joint model of primary and secondary equipment. The joint model of primary and secondary equipment includes equipment topology, electrical connection relationship and protection configuration information. Based on the operational task, the state changes of the equipment are simulated in the primary and secondary equipment joint model, wherein the simulation includes equipment switching, secondary equipment operation and circuit breaker opening and closing; Record the status data and operation steps of the equipment during the simulation process to generate a joint model of the target primary and secondary equipment corresponding to the operation task.

[0009] Optionally, in the third implementation of the first aspect of this application, the step of performing error prevention verification on the operation rehearsal based on pre-built error prevention rules includes: The device status data is extracted from the target primary and secondary device joint model and compared with the device status safety rules in the pre-built anti-misoperation rules to determine whether the device has an abnormal state. The operation steps of the target primary and secondary equipment are extracted from the joint model of the target primary and secondary equipment, and the operation steps are verified to conform to the operation sequence compliance rules in the pre-built anti-misoperation rules. The verification includes the correctness of the sequence, the reasonableness of the time interval, and the operation dependency relationship. Extract the equipment topology, electrical connection relationships, and protection configuration information from the primary and secondary equipment joint model, and determine whether there is a risk of multi-device linkage misoperation. If the equipment meets all of the following conditions, the error prevention calibration is deemed passed. These conditions include: There are no abnormal states, no risk of misoperation due to multi-device linkage, and the verification order, time interval, and operation dependencies are correct.

[0010] Optionally, in the fourth implementation of the first aspect of this application, the step of extracting the device status data from the target primary and secondary device joint model and comparing it with the device status safety rules in the pre-built anti-misoperation rules to determine whether the device has an abnormal state includes: Machine learning algorithms are introduced to deeply mine the historical operating data of the equipment and establish an equipment status prediction model; among them, the equipment status prediction model is trained based on a composite loss function to obtain a trained equipment status prediction model. The status data of the equipment is extracted from the joint model of the primary and secondary equipment of the target, and preliminary processing is performed using edge computing technology; The multi-source data fusion algorithm is used to fuse various data in the pre-processed state data. The fused data is then input into the trained equipment state prediction model for prediction to determine whether the equipment state is safe.

[0011] Optionally, a composite loss function can be constructed based on cross-entropy classification loss, temporal trend consistency loss, and multi-feature collaborative loss. Among them, the larger the prediction difference between adjacent time steps, the greater the temporal trend consistency loss, the greater the deviation between the correlation of the predicted values ​​of each feature dimension and the inherent correlation between features, and the greater the multi-feature collaborative loss.

[0012] Optionally, in the fifth implementation of the first aspect of this application, the step of extracting the operation steps of the device from the target primary and secondary device joint model and verifying whether the operation steps conform to the operation sequence compliance rules in the pre-built error prevention rules includes: Natural language processing technology is used to perform guided analysis on the target primary and secondary equipment joint model to extract the equipment operation steps; The parsed operation steps are compared with the operation sequence rules in the error prevention rules to verify whether the order, time interval, and dependency of the operation steps meet the requirements.

[0013] Optionally, in the sixth implementation of the first aspect of this application, after the anti-misoperation verification is passed, the primary and secondary devices are sorted according to preset logic to generate a corresponding switching operation sequence, including: Based on the equipment type and operation priority, the equipment sorting rules are determined, including priority for high-voltage equipment, priority for protection devices, and synchronization of associated equipment; Based on the operation sequence requirements in the operation task, the equipment sorting rules are refined to generate a switching operation sequence, which includes operation step number, equipment identifier and operation type.

[0014] Optionally, in the seventh implementation of the first aspect of this application, when operating the equipment on-site based on the switching operation sequence, the anti-misoperation key performs real-time anti-misoperation judgment based on the actual status information of the equipment after the operation and the pre-rehearsal verification result, including: Collect the actual status information of the device after the operation, including the device location, switch status and protection signals; The device location, switch status, and protection signal are compared with the device status data in the pre-run verification results to determine whether the operation was performed as expected.

[0015] A second aspect of this application provides a power grid operation and maintenance error prevention verification device for implementing the above-mentioned power grid operation and maintenance error prevention verification method, the device comprising: The operation task determination module is used to determine the operation tasks of the substation, wherein the operation tasks are the control operations of the primary and secondary equipment during the operation and maintenance of the substation; The operation pre-simulation module is used to acquire the real-time operating status of the primary equipment and the functional status of the secondary equipment, and to map the real-time operating status and the functional status to obtain a joint model of the primary and secondary equipment. Based on the joint model of the primary and secondary equipment, the operation pre-simulation is performed on each primary and secondary equipment in the operation task. The error prevention verification module is used to perform multi-dimensional collaborative error prevention verification on the operation rehearsal based on pre-built error prevention rules, and obtain the rehearsal verification result. The error prevention rules include equipment status safety rules, operation sequence compliance rules, and multi-device linkage error prevention rules. The operation sequence generation module is used to sort the primary and secondary devices according to preset logic after the anti-misoperation verification is passed, and generate the corresponding switching operation sequence. The communication module is used to send data to the anti-misoperation key and pressure plate controller via an encrypted communication channel; The real-time error prevention judgment module is used to make real-time error prevention judgments based on the actual status information of the equipment after the operation and the pre-drill verification results when the equipment is operated on-site based on the switching operation sequence.

[0016] A third aspect of this application provides an electronic device, comprising: a memory and at least one processor, wherein the memory stores a request, and the memory and the at least one processor are interconnected via a line; the at least one processor invokes the request in the memory to cause the electronic device to perform the steps of the above-described power grid operation and maintenance error prevention verification method.

[0017] A fourth aspect of this application provides a computer-readable storage medium storing a request that, when executed on a computer, causes the computer to perform the steps of the above-described power grid operation and maintenance error prevention verification method.

[0018] The method provided in this application includes determining the operation tasks of a substation, which are control operations on primary and secondary equipment during substation operation and maintenance; conducting operation rehearsals for each primary and secondary equipment in the operation tasks, and verifying the operation rehearsals based on pre-built anti-misoperation rules; after the anti-misoperation verification is passed, sorting each primary and secondary equipment according to preset logic to generate corresponding switching operation sequences, and sending them to the anti-misoperation key and pressure plate controller through an encrypted communication channel; when operating equipment on-site based on the switching operation sequences, the anti-misoperation key performs real-time anti-misoperation judgment based on the actual status information of the equipment after the operation and the rehearsal verification results, and triggers the execution of temporary control strategies for the switching operation sequences based on the results of the anti-misoperation judgment.

[0019] Compared with the prior art, the beneficial effects of the present invention include at least the following: 1. By constructing a joint model of primary and secondary equipment and combining it with an anti-misoperation rule base, we can achieve full-process and all-round anti-misoperation verification of the switching operation process of primary and secondary equipment during substation operation and maintenance. This solves the problems that existing power grid operation and maintenance anti-misoperation schemes are incomplete, have low accuracy, and cannot adapt to complex scenarios of collaborative operation of primary and secondary equipment.

[0020] 2. The operational tasks obtained through the dynamic adjustment mechanism can automatically avoid equipment with potential health hazards, optimize the operation sequence to conform to the current power grid topology, and supplement necessary safety measures, thereby reducing the risk of subsequent misoperation caused by the mismatch between the operation process and the actual situation.

[0021] 3. Incorporate the logic status of secondary equipment into the error prevention judgment system to prevent cascading risks caused by protection malfunctions or failures to operate.

[0022] 4. It solves the problem of lack of real-time dynamic control in complex collaborative operation scenarios. Through a graded response mechanism of operation interruption, equipment isolation and personnel evacuation, it effectively curbs the risk of the spread of abnormal states. At the same time, it uses structured log records to provide complete data support for accident tracing, improves the efficiency of abnormal event handling and subsequent strategy optimization capabilities.

[0023] 5. By constructing a joint model of primary and secondary equipment, operation rehearsals and error prevention verification are realized. Combined with the real-time status comparison of the error prevention key and emergency control strategies, the problems of traditional error prevention systems being unable to adapt to multi-device linkage operations, lacking automated verification and emergency response capabilities are effectively solved. It has a significant effect on improving the safety and reliability of substation operation and maintenance. Attached Figure Description

[0024] Figure 1 This is a schematic flowchart of a power grid operation and maintenance error prevention verification method provided according to an embodiment of the present invention; Figure 2 This is a schematic flowchart of another power grid operation and maintenance error prevention verification method provided according to an embodiment of the present invention; Figure 3 This is a schematic diagram of a power grid operation and maintenance error prevention and verification device provided according to an embodiment of the present invention; Figure 4 This is a schematic diagram of an electronic device provided according to an embodiment of the present invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The described embodiments are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this invention.

[0026] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar elements and are not necessarily used to describe a particular order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms “comprising” or “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] Currently, the main way to reduce misoperation is by setting constraints between primary and secondary equipment. While setting constraints can prevent misoperation to some extent, it is mostly limited to single equipment or simple operation scenarios, lacking the need to prevent misoperation in complex scenarios such as coordinated operation of primary and secondary equipment. For example, in the process of substation switching operations, if only the status of a single circuit breaker is checked, the linkage between protection devices and disconnecting switches may be overlooked, resulting in the risk of misoperation not being fully identified.

[0028] To address the aforementioned issues, existing error prevention methods cannot cover the complex scenarios of coordinated operation of primary and secondary equipment. The core problem lies in the lack of a dynamic verification mechanism for the relationships between devices. Analysis of power grid operation accident cases reveals that most erroneous operations stem from timing errors in multi-device linkage or protection configuration conflicts. Based on this, a multi-dimensional error prevention rule system covering device status, operation sequence, and linkage relationships is proposed, along with a real-time feedback control mechanism. The specific approach is as follows: First, a pre-simulation model including the joint status of primary and secondary equipment is established to identify potential risks through simulated operation processes; second, the verified schemes are transformed into executable sequences, and operation control is achieved by combining encrypted communication and physical interlocking devices; finally, real-time status comparison is introduced during the operation execution phase to form closed-loop control.

[0029] Therefore, this application proposes an anti-misoperation verification scheme that achieves operation pre-drilling and anti-misoperation verification by constructing a joint model of primary and secondary equipment, and combines real-time status comparison of anti-misoperation keys with emergency control strategies, so as to improve the safety of substation operation and maintenance and realize the collaborative anti-misoperation verification capability of primary and secondary equipment.

[0030] For ease of understanding, the specific process of the embodiments of this application is described below. Please refer to [link / reference]. Figure 1 The first embodiment of the power grid operation and maintenance error prevention verification method in this application includes: 101. Determine the operation tasks of the substation. The operation tasks are the control operations of primary and secondary equipment during the operation and maintenance of the substation. In this embodiment, the operation task is specifically an operation and maintenance operation task generated by the user on the interface of the substation's dispatch system. Specifically, the primary and secondary equipment operation tasks are created in the dispatch system, specifying the operation objectives and steps, including information such as the operation object, operation type, and operation time; for example, the primary equipment, secondary hard pressure plate, and secondary soft pressure plate elements to be operated are selected in sequence, and the system provides a graphical interface.

[0031] In practical applications, firstly, the anti-misoperation host receives operation instructions from the dispatch system via the IEC 61850 protocol. For example, the operation instruction might be "Switch the 220kV Line A from operation to maintenance," including the operation type (switching operation), the operation object (220kV Line A circuit breaker and disconnect switches on both sides), and the operation time (14:00 on June 20, 2025). Then, it retrieves a "Line Outage" template from the preset task library. This template contains standard operating procedures: disconnecting the line circuit breaker, opening and closing the disconnect switches on both sides, suspending the grounding wire, and disabling the line protection device. Finally, based on the current substation operating status (Line A load 30MW, below the rated value of 50MW) and equipment health status (circuit breaker SF6 pressure normal, disconnect switch mechanism box no condensation), the template retrieved from the task library is optimized and adjusted to generate the final operation task. This optimization includes prioritizing the disconnection of low-load lines to reduce impact, adding a pre-operation voltage verification step for the disconnect switches, and supplementing the three-dimensional coordinate verification of the grounding wire installation location.

[0032] 102. Conduct operation rehearsals for each primary and secondary device in the operation task, and verify the operation rehearsals against errors based on the pre-built error prevention rules; It should be noted that this operation rehearsal refers to simulating the operation process by establishing a joint model of primary and secondary equipment. Specifically, it can be achieved using power grid topology modeling and real-time data mapping technology, and is used to verify the impact of the operation on the overall system state.

[0033] The error prevention rules include equipment status safety rules, operation sequence compliance rules, and multi-device linkage error prevention rules. The multi-device linkage error prevention rules refer to defining the electrical connections and protection coordination relationships between devices. Specifically, they can be implemented using logical expressions or state transition matrices to prevent cross-device misoperation.

[0034] In this step, during the pre-operation rehearsal of the operation task, the real-time status of primary equipment, including but not limited to circuit breaker closed and disconnector closed, is obtained through the SCADA system. The functional status of secondary equipment, including but not limited to the normal operation of the A-line protection device, is obtained through the protection information substation. A joint model containing the following information is then generated: The equipment topology includes, but is not limited to, the connection relationship between line A, circuit breaker, disconnector, and busbar; Electrical connections include, but are not limited to, CT / PT ratio and polarity configuration; Protection configuration information includes, but is not limited to, the activation / deactivation status of longitudinal differential protection, distance protection, and zero-sequence protection.

[0035] For example, in the joint model, the operation process is simulated as follows: after the circuit breaker is disconnected, the simulated current drops from 500A to 0A; when the disconnecting switch is opened, the simulated signal change of the live display device is simulated; when the protection device is deactivated, the simulated state switching of the protection output pressure plate is simulated.

[0036] After the joint model of primary and secondary equipment is constructed in the pre-simulation, the anti-misoperation rules are used to verify the joint model. It should be noted that the verification process involves parsing the joint model, extracting the equipment status data, and then using the equipment status safety rules, operation sequence compliance rules, and multi-device linkage anti-misoperation rules within the anti-misoperation rules to verify the corresponding data in the equipment status data. Specifically: Equipment status safety rules: Verify the SF6 pressure of the circuit breaker (0.6MPa > 0.5MPa alarm value) and the contact temperature of the disconnecting switch (45℃ < 70℃ limit). Operation sequence compliance rules: Verify the sequence of "circuit breaker tripping → disconnecting switch operation" with a time interval of ≥3 seconds; Multi-device linkage rules: Check the secondary circuit of the bus differential protection CT to ensure there is no risk of open circuit.

[0037] In another implementation, when using equipment status safety rules, operation sequence compliance rules, and multi-device linkage anti-misoperation rules for error prevention verification, the verification can be implemented in three ways: secondary constraint on primary, primary constraint on secondary, and secondary constraint on secondary. These three verification logics together constitute a comprehensive error prevention system for the operation of primary and secondary equipment during power grid operation and maintenance. By reading the status data of primary and secondary equipment and verifying it in conjunction with the error prevention rule base, the system can identify and prevent potential risks of misoperation before operation. After successful simulation, the system automatically generates a switching operation sequence containing information such as operation steps, operating equipment, and operation type, ordered according to preset logic, providing operators with clear and safe operation guidance.

[0038] The system reads the status data of primary and secondary equipment from the joint model of primary and secondary equipment, and performs a complementary check on the primary, secondary, and tertiary constraints. If the rules are not met, operation is prohibited and the reason is displayed. After the simulation is passed, a switching operation sequence containing information such as operation steps, operating equipment, and operation type is automatically generated and sorted according to preset logic. Here, "not meeting" actually refers to at least one of the following: primary secondary constraint not meeting, secondary primary constraint not meeting, and tertiary secondary constraint not meeting.

[0039] During the error prevention verification, when the status of primary or secondary equipment changes, the error prevention verification is triggered to check whether the change in the operating status of primary and secondary equipment meets the error prevention rule constraints. If the operating status of the equipment does not meet the error prevention rule constraints, operation is prohibited and a corresponding prompt is given; if the operating status of the equipment meets the error prevention rule constraints, step 103 is performed.

[0040] When performing secondary constraint primary error prevention verification, the specific steps include: Read the current status information of the secondary equipment, including the status of the hard pressure plate and the soft pressure plate; Based on the constraint relationship between secondary and primary operations in the anti-misoperation rule base, determine whether the status of secondary equipment meets the requirements of complete protection function when simulating the closing of isolating disconnectors or switches. If the requirements are not met, generate detailed error messages indicating the specific reasons for not meeting the rules and the relevant secondary equipment.

[0041] When performing a second-order constraint-based error prevention check, the specific steps include: Read the current primary device status information, including the position status of switches and disconnectors; Based on the constraint relationship between primary and secondary operations in the anti-misoperation rule base, determine whether the status of the primary equipment will lead to incomplete operation of the protection function when simulating the operation of the secondary equipment; If this results in incomplete operation of the protection function, the operation will be prohibited and a corresponding prompt message will be generated, explaining the reason for prohibiting the operation and the impact on the status of the primary equipment.

[0042] When performing secondary constraint secondary error prevention verification, the specific steps include: Read the status information of all relevant secondary equipment, including the status of hard and soft pressure plates; Based on the constraint relationship between secondary and secondary operations in the anti-misoperation rule base, determine whether the status of other secondary equipment will cause the risk of malfunction or refusal to operate when simulating and rehearsing the operation of secondary equipment; If a risk exists, operation is prohibited and a detailed risk warning message is generated, indicating the secondary equipment at risk and its potential impact.

[0043] 103. After the anti-misoperation verification is passed, sort the primary and secondary devices according to the preset logic, generate the corresponding switching operation sequence, and send it to the anti-misoperation key and pressure plate controller through the encrypted communication channel. It should be noted that the anti-misoperation key has device identification, operation permission verification, and mechanical interlocking functions, and the pressure plate controller supports remote engagement / disengagement control and status feedback. Specifically, the operation sequence is transmitted to the anti-misoperation key and the pressure plate controller via wireless communication, including but not limited to Wi-Fi, Bluetooth, or wired connections, including but not limited to USB and serial port.

[0044] The preset logic of this switching operation sequence refers to the priority and correlation sorting rules of equipment operations. Specifically, it can be implemented using a decision tree algorithm based on equipment type and protection level to ensure the safety of the operation process.

[0045] It should be noted that the optimized operation sequence is obtained by dynamically adjusting the operation task template based on the operation tasks issued by the dispatcher, combined with the current operating status of the substation and the health status of the equipment. It takes into account the actual operating conditions and equipment status, and optimizes and improves the initial operation sequence.

[0046] The encrypted communication channel refers to a transmission link with data encryption and identity authentication functions. Specifically, it can be implemented using the TLS protocol combined with digital certificate technology to prevent operation instructions from being tampered with.

[0047] 104. When operating equipment on-site based on the switching operation sequence, the anti-misoperation key performs real-time anti-misoperation judgment based on the actual status information of the equipment after the operation and the pre-rehearsal verification results, and triggers the execution of the temporary control strategy of the switching operation sequence based on the result of the real-time anti-misoperation judgment.

[0048] In this embodiment, the real-time error prevention judgment refers to dynamically comparing the actual state of the device with the pre-simulation results. Specifically, edge computing devices can be used to perform millisecond-level state analysis to detect abnormal operations in a timely manner.

[0049] Specifically, after receiving operation instructions through a standardized interface, they are parsed into key information such as operation type, operation object, and time node. The templates stored in the task library cover standard procedures for scenarios such as switching operations and equipment maintenance. Operation instructions are mapped to corresponding templates using keyword or pattern matching algorithms. Subsequently, combined with real-time operational data collected from the substation, such as circuit breaker status and protection device signals, as well as indicators like remaining lifespan and failure rate from equipment health assessment reports, the equipment selection in the templates is optimized, for example, replacing equipment with potential failure risks. Simultaneously, the operation sequence is adjusted according to the current power grid topology, for example, prioritizing the operation of isolation equipment when the busbar is energized. The safety measures supplementary section includes pre-set emergency response plans for abnormal equipment states, such as adding a grounding operation step when an insulation abnormality is detected.

[0050] This embodiment uses a dynamic adjustment mechanism to automatically avoid equipment with potential health hazards, optimize the operation sequence to conform to the current power grid topology, and supplement necessary safety measures, thereby reducing the risk of misoperation caused by the mismatch between the operation process and the actual situation.

[0051] Please see Figure 2 The second embodiment of the power grid operation and maintenance error prevention verification method in this application includes: 201. Determine the operation tasks of the substation. The operation tasks are the control operations of primary and secondary equipment during the operation and maintenance of the substation. Specifically, the system receives operation instructions for primary and secondary equipment issued by the substation dispatch system. These instructions include the operation type, the operation object, and the operation time. Based on the operation type, the operation object, and the operation time, a corresponding operation task template is matched from a preset task library. The operation task template includes the operation scenario and the standard operation procedure for each device. The operation task template is dynamically adjusted based on the current operating status of the substation and the health status of each device to generate the final operation task. The dynamic adjustment includes equipment selection optimization, operation sequence adjustment, and supplementation of safety measures.

[0052] The operation instruction refers to the structured instruction issued by the scheduling system, which includes the operation type, operation object, and operation time. Specifically, it can be received in real time through the IEC 61850, DNP3, or Modbus interface of the scheduling automation system. Its function is to ensure the standardization and traceability of the source of the operation task.

[0053] The task library refers to a pre-built database containing common operation scenarios and standard operation procedures. Specifically, it can use keyword retrieval or pattern recognition algorithms for template matching. Its purpose is to inherit historical operation experience and maintain operational standardization.

[0054] The dynamic adjustment refers to optimizing the standard template based on real-time operating status and equipment health data. Specifically, the equipment health assessment results can be used as the basis for equipment selection and optimization, and the operating status monitoring data can be used as the constraint condition for adjusting the operation sequence. Its purpose is to make the operation task adapt to the dynamic working conditions on site.

[0055] In practical applications, after receiving operation instructions through a standardized interface, the instructions are parsed into key information such as operation type, operation object, and time node. A task library stores templates of standard procedures covering scenarios such as switching operations and equipment maintenance. Key information parsed from the operation instructions is mapped to corresponding templates using keyword or pattern matching algorithms. Subsequently, combined with real-time operational data collected from the substation, such as circuit breaker status and protection device signals, as well as indicators like remaining lifespan and failure rate from equipment health assessment reports, the equipment selection in the templates is optimized, for example, replacing equipment with potential failure risks. Simultaneously, the operation sequence is adjusted according to the current power grid topology to obtain the operation tasks; for example, prioritizing the operation of isolation equipment when the busbar is energized. The safety measures supplementary stage includes pre-set emergency response plans for abnormal equipment states, such as adding a grounding operation step when an insulation abnormality is detected.

[0056] This embodiment can automatically avoid equipment with potential health hazards by dynamically adjusting the operation tasks obtained, optimize the operation sequence to conform to the current power grid topology, and supplement necessary safety measures, thereby reducing the risk of subsequent misoperation caused by the mismatch between the operation process and the actual situation.

[0057] In this embodiment, receiving operation instructions for primary and secondary equipment issued by the dispatch system in the substation includes: Through the interface of the scheduling automation system, the system receives operation instructions for primary and secondary equipment issued by the scheduling system in real time. The interface includes IEC 61850, DNP3 and Modbus. The operation instructions are parsed to extract key information such as operation type, operation object, and operation time. The parsing is performed in XML or JSON format. The parsed operation instructions are stored in the operation task queue for subsequent processing. The queue adopts the first-in, first-out (FIFO) principle.

[0058] The interface of the scheduling automation system refers to the standardized protocol channel used to realize data communication between the scheduling system and the anti-misoperation host. Specifically, it can be implemented by a communication module that supports IEC 61850, DNP3 and Modbus protocols. The heterogeneous communication problem between different scheduling systems is solved through multi-protocol compatibility design.

[0059] When parsing operation instructions, unstructured instructions are converted into structured data. Specifically, XML or JSON parsers can be used for semantic recognition and field extraction, and standardized data formats can eliminate semantic biases caused by manual parsing.

[0060] The operation task queue refers to a caching mechanism used to temporarily store instructions to be processed. Specifically, it can be implemented using a queue management system based on an in-memory database. The first-in, first-out principle is used to maintain the timing of operation instructions and prevent disorder in the order of instruction processing.

[0061] Specifically, the multi-protocol interface module of the scheduling automation system continuously listens for communication requests from different scheduling systems. When it detects an operation command conforming to the IEC 61850, DNP3, or Modbus protocol format, it automatically establishes a secure connection and receives the command data. The received raw command is transmitted to the parsing module, which performs field matching using a pre-set XML or JSON format template to accurately extract key parameters such as operation type, operation object identifier, and operation timestamp. The parsed structured data is encapsulated into operation task objects in a unified format and stored in the operation task queue according to the order of receipt. The queue management system retrieves the task objects sequentially according to the first-in, first-out principle and passes them to the subsequent error prevention and verification module for processing, ensuring the timeliness and integrity of the operation commands.

[0062] Furthermore, the step of matching a corresponding operation task template from a preset task library according to the operation instruction includes: A pre-defined task library is constructed, which covers common operation scenarios and standard operation procedures. The scenarios include switching operations, equipment maintenance, and protection device activation / deactivation. If a relational database or graph database is used, it can be used to store standard process templates for scenarios such as switching operations, equipment maintenance, and protection device activation / deactivation, providing structured data support for rapid matching. Based on the operation type and operation object in the operation instruction, the corresponding operation task template is matched from the task library. The matching adopts keyword retrieval or pattern recognition algorithm. Keyword retrieval refers to template matching by extracting keywords in the operation instruction. Specifically, it can be implemented by combining word segmentation algorithm with index query. For example, "circuit breaker tripping" in the operation type is used as the keyword to retrieve the corresponding operation step template in the task library. Pattern recognition algorithm refers to template matching by analyzing the implicit features in the operation instruction. Specifically, it can be implemented by natural language processing technology or machine learning model. For example, semantic analysis is used to identify the correlation between operation objects, thereby matching templates for multi-device collaborative operation. If no matching template is found, a new operation task template is generated and stored in the task library. The generation is based on the operation instruction content and the power grid safety regulations. A rule engine is used in conjunction with the provisions of the power grid safety regulations. For example, based on the equipment type and operation target in the operation instruction, a new template containing the operation sequence, safety measures and verification steps is automatically generated.

[0063] Specifically, the task library integrates historical operation records and power grid regulations to form a set of standard procedures covering scenarios such as switching operations and equipment maintenance. When an operation instruction is received, the system first extracts the operation type and operation object as matching criteria, for example, the operation type is "line power outage maintenance" and the operation object is "circuit breaker A and disconnector B". Then, it searches the task library for templates containing the same operation type and equipment through keyword search. If found, it is directly called; if not found, a pattern recognition algorithm is used to analyze the equipment correlation in the instruction. For example, after identifying the linkage relationship between the circuit breaker and the protection device, it matches multiple equipment operation templates. When no available template is available in the task library, the system generates a new template containing operation steps, safety verification, and anomaly handling based on the equipment parameters in the operation instruction and the interlocking logic in the power grid safety regulations, and stores it in the task library for subsequent use.

[0064] 202. Obtain the real-time operating status of the primary equipment and the functional status of the secondary equipment, and map the real-time operating status to the functional status to obtain a joint model of the primary and secondary equipment; It should be noted that the primary and secondary equipment joint model refers to an integrated model formed by mapping the real-time operating status of primary equipment with the functional status of secondary equipment. Specifically, it can be implemented using data mapping or object relationship mapping technology to integrate the physical connection and logical association of primary and secondary equipment. The primary and secondary equipment joint model here includes equipment topology, electrical connection relationship and protection configuration information.

[0065] In this embodiment, basic information of power grid equipment is collected, including equipment type, equipment parameters, and equipment location; a power grid topology model is constructed, which covers the electrical connection relationships between equipment and protection configuration information; the basic information and the topology model are fused to generate a joint model of primary and secondary equipment, and the fusion adopts data mapping or ORM (Object Relational Mapping) technology.

[0066] The basic information refers to the fundamental attribute data of power grid equipment. Specifically, this can be achieved by collecting equipment type, rated parameters, and installation location information through an equipment ledger management system, providing static data support for the joint model. The power grid topology model refers to the network structure reflecting the electrical connections between equipment. This can be achieved by constructing the connection relationships between nodes and edges using graph databases or relational databases, used to describe the dynamic operational relationships of equipment. Data mapping or object-relational mapping techniques refer to methods for associating heterogeneous data sources. This can be achieved using database table associations or entity-relational mapping frameworks, ensuring data consistency between the basic information and the topology model.

[0067] Specifically, the system first collects the type, voltage level parameters, and physical location of primary equipment such as circuit breakers and disconnectors within the substation through an equipment ledger system. Simultaneously, it acquires the model, functional parameters, and installation location of secondary equipment such as protection devices and monitoring and control devices. Next, a topology model is constructed based on the main electrical wiring diagram, defining the connection relationships between circuit breakers and busbars, and the configuration relationships between protection devices and primary equipment. Finally, an ORM framework is used to map the parameters in the equipment ledger to the nodes in the topology model, for example, associating circuit breaker model parameters with topology node attributes, forming a joint model that includes equipment attributes, connection relationships, and protection configurations. This provides an accurate joint data foundation for primary and secondary equipment in complex collaborative operation scenarios, solving the verification blind spot problem caused by isolated equipment information in traditional anti-misoperation systems.

[0068] 203. Based on the operation task, simulate the state changes of the equipment in the joint model of primary and secondary equipment. The simulation includes equipment switching, secondary equipment operation and circuit breaker opening and closing. In this step, the equipment switching refers to the simulated operation of putting primary equipment into or taking it out of operation. This can be implemented using the topology analysis module in power grid simulation software to predict the impact of equipment status changes on the power grid structure. The secondary equipment operation refers to the simulation of the logic response of protection devices or automatic control equipment. This can be implemented using a protection logic simulator to verify whether the linkage behavior of secondary equipment during operation meets preset conditions. The circuit breaker opening and closing refers to the simulation of the circuit breaker's open or closed state. This can be implemented using a switch quantity simulator to analyze the impact of circuit breaker operation on electrical connection relationships.

[0069] 204. Record the status data and operation steps of the equipment during the simulation process, and generate a joint model of the target primary and secondary equipment corresponding to the operation task; During the operational rehearsal, real-time operating parameters of primary equipment, such as circuit breaker position signals and disconnector status, are first acquired through data acquisition interfaces. Simultaneously, the protection function activation / deactivation status and setting parameters of secondary equipment are also acquired. This data is mapped into a joint model, forming a digital mirror image that includes equipment topology connections and protection configuration associations. Subsequently, based on the equipment control requirements of the operational task, state change simulations are performed in the model: for example, when a circuit breaker on a certain line is tripped, the model synchronously updates the circuit breaker's opening / closing status and triggers the reset logic of the associated line protection devices. During this process, equipment switching operations change the power grid topology, the actions of secondary equipment update the protection function status, and the opening and closing of circuit breakers affect electrical connections. All state change data generated by the simulated operations are recorded in real time, forming a target joint model that includes operation step numbers, equipment identifiers, and state parameters.

[0070] This embodiment achieves full-coverage verification of complex collaborative operation scenarios through the construction and operation simulation of a joint model of primary and secondary equipment. For example, during the switching operation of primary equipment, it simultaneously verifies whether the activation and deactivation states of the secondary protection pressure plates match, avoiding misjudgments caused by fragmented analysis of equipment states in traditional methods. Simultaneously, the structured operation data generated during the dynamic simulation provides accurate input for subsequent error prevention rule verification. For instance, it automatically detects the risk of misoperation by closing the grounding switch while the circuit breaker is in operation based on the topology changes after the circuit breaker is opened or closed.

[0071] 205. Extract the status data of the equipment from the joint model of the primary and secondary equipment, and compare it with the equipment status safety rules in the pre-built anti-misoperation rules to determine whether the equipment has an abnormal status. The device state safety rules refer to the constraints used to check whether the device is in a permissible operating state. Specifically, they can be implemented using a state machine model. By comparing the current state of the device with the set of permissible states in the rule base in real time, it is ensured that the device does not have the risk of operating with defects.

[0072] In this embodiment, equipment status safety rules are defined, which cover equipment overload, short circuit, grounding abnormality and other states; equipment status data is extracted from the joint model, which includes current, voltage, temperature and pressure; the extracted equipment status data is compared with the equipment status safety rules to determine whether the equipment has an abnormal state, and the comparison adopts threshold comparison or pattern recognition algorithm.

[0073] Optionally, the step of extracting the device status data from the target primary and secondary device joint model and comparing it with the device status safety rules in the pre-built anti-misoperation rules to determine whether the device has an abnormal state includes: Machine learning algorithms are introduced to deeply mine the historical operating data of the equipment and establish a predictive model for the equipment status. The status data of the equipment is extracted from the joint model of the primary and secondary equipment of the target, and preliminary processing is performed using edge computing technology; A multi-source data fusion algorithm is used to fuse various data in the pre-processed state data. The fused data is then input into the equipment state prediction model for prediction to determine whether the equipment state is safe.

[0074] Among them, the equipment state prediction model is trained based on the composite loss function to obtain the trained equipment state prediction model.

[0075] Specifically, a device state prediction model can be established based on a bidirectional long short-term memory network and an attention mechanism. This model incorporates historical operating data of the device, including but not limited to time-series physical quantities, status switching quantities, and operational switching quantities. Time-series physical quantities include voltage, current, temperature, and pressure. Status switching quantities include device opening and closing status, protection plate activation / deactivation status, and alarm signals. Operational switching quantities include historical operation timestamps, operation types, and post-operation state change magnitudes. Operation types include switching and maintenance. The device state prediction model is trained using a composite loss function to obtain the optimal model.

[0076] Specifically, a composite loss function is constructed based on cross-entropy classification loss, temporal trend consistency loss, and multi-feature collaborative loss. Among them, the larger the prediction difference between adjacent time steps, the greater the temporal trend consistency loss, the greater the deviation between the correlation of the predicted values ​​of each feature dimension and the inherent correlation between features, and the greater the multi-feature collaborative loss.

[0077] The composite loss function is expressed as follows:

[0078] in, This represents the total loss value of the composite loss function. Represents the cross-entropy classification loss. This represents the time-series trend consistency loss. This represents multi-feature collaborative loss. The weights representing the cross-entropy classification loss are... The weights representing the time-series trend consistency loss The weights represent the multi-feature collaborative loss.

[0079] It should be noted that the cross-entropy classification loss is an existing function, which will not be elaborated here.

[0080] Specifically, the time-series trend consistency loss is expressed by the following formula:

[0081] Where T represents a short period of time. This represents the predicted probability of safety at time t. This represents the predicted probability of safety at time t-1. This indicates a preset reasonable threshold range.

[0082] When the difference between predictions at adjacent time steps exceeds a preset reasonable threshold, a penalty is applied, resulting in a larger loss, so that the model's predicted trend is consistent with the actual gradual characteristics of the device.

[0083] Specifically, the multi-feature collaborative loss is expressed as follows:

[0084] in, This indicates the correlation between the predicted values ​​of features fi and fj. represents the normal correlation degree between features fi and fj in the feature correlation matrix, and K represents the number of independent feature dimensions, which is the total number of multi-dimensional features extracted from the joint model of the target primary and secondary equipment.

[0085] The correlation between the predicted values ​​of each feature dimension and the feature correlation matrix is ​​calculated. The feature correlation matrix is ​​the inherent correlation between features obtained through historical data mining. When the absolute value of the difference is greater than the preset difference threshold, it indicates a greater degree of violation of the feature linkage law, resulting in loss, which causes the model to correct the prediction according to the feature linkage law.

[0086] In this embodiment, a composite loss function is constructed by combining temporal consistency loss and multi-feature collaborative loss, enabling the model to determine whether the device status is safe in complex scenarios such as collaborative operation of primary and secondary devices, thereby improving accuracy.

[0087] 206. Extract the operation steps of the equipment from the joint model of the primary and secondary equipment, and verify whether the operation steps comply with the operation sequence compliance rules in the pre-built anti-misoperation rules. The verification includes the correctness of the sequence, the reasonableness of the time interval, and the operation dependency relationship. Specifically, a directed graph model is used to describe the dependencies between operation steps. By verifying whether the execution order of operation steps conforms to the preset path, system disorder caused by incorrect order can be avoided.

[0088] In this embodiment, the step of extracting the operation steps from the target primary and secondary equipment joint model and verifying whether the operation steps conform to the operation sequence compliance rules in the pre-built error prevention rules includes: Natural language processing technology is used to perform guided analysis on the target primary and secondary equipment joint model to extract the equipment operation steps; The parsed operation steps are compared with the operation sequence rules in the error prevention rules to verify whether the order, time interval, and dependency of the operation steps meet the requirements.

[0089] Furthermore, after extracting the operation steps of the equipment from the target primary and secondary equipment joint model and verifying whether the operation steps conform to the operation sequence compliance rules in the pre-built error prevention rules, the process also includes: A risk assessment model is introduced to evaluate the risk level of each operational step. This model considers various factors such as equipment condition, operating environment, and operator skill level, providing operators with more comprehensive risk information.

[0090] Based on the risk assessment results, the order or method of operation can be dynamically adjusted to reduce operational risks. For example, for high-risk operations, a confirmation step can be added or two people can be required to operate the operation; for low-risk operations, the process can be simplified or the degree of automation can be increased.

[0091] 207. Extract the equipment topology, electrical connection relationship and protection configuration information from the target primary and secondary equipment joint model, and determine whether there is a risk of multi-equipment linkage misoperation; Specifically, a dynamic model of equipment linkage relationships is first constructed. This model can reflect the linkage relationships and influence paths between equipment in real time. The model considers various factors such as the physical connections, logical associations, and protection configurations of the equipment to ensure the accuracy and completeness of the linkage relationships. Then, simulation technology is used to simulate and test the equipment linkage relationships. By simulating the equipment linkage process under different operating scenarios, it is possible to check for any violations of linkage error prevention rules. Simulation testing can identify potential linkage misoperation risks in advance, providing operators with early warnings and preventive measures.

[0092] Furthermore, considering the interconnectedness of the power system with external systems such as the dispatch management system, equipment management system, and security system, a cross-system linkage anti-misoperation verification mechanism is constructed. Data interaction and sharing with external systems are achieved through interface technology, ensuring real-time acquisition of external system status information and operational instructions during operation rehearsals. This cross-system linkage anti-misoperation verification can prevent equipment malfunctions or failures to operate due to external system manipulation, thereby improving the overall safety of the power system.

[0093] 208. If it is determined that the equipment is not in an abnormal state, there is no risk of misoperation due to multi-device linkage, and the verification sequence, time interval, and operation dependency are correct, then the misoperation prevention verification is deemed to have passed. Specifically, topology analysis algorithms are used to detect the electrical connections between devices, and combined with protection configuration information, it is determined whether there is a possibility of falsely triggering the action of other devices.

[0094] In practical applications, during the operation rehearsal phase, the real-time status of the equipment is first matched against the permitted statuses in the safety rule base using a status data comparison module. For example, when a circuit breaker is detected to be under maintenance, a status anomaly alarm is triggered. Subsequently, the operation step verification module parses the rehearsal operation sequence, using a timestamp verification method to ensure that the time interval between adjacent operation steps meets the minimum safety threshold, and verifying the logical order of operation steps through a dependency graph. Finally, the topology analysis engine traverses the electrical connections between devices, and combined with the setting parameters of the protection devices, identifies potential risk points where the operation of one device might cause other devices to malfunction. For example, when a line switch is disconnected, a risk of overcurrent protection malfunction in an adjacent protection device is detected.

[0095] In this embodiment, after performing multi-dimensional collaborative error prevention verification on the operation rehearsal based on pre-built error prevention rules and obtaining the rehearsal verification result, the method further includes: Environmental monitoring equipment is deployed at the operation site to collect environmental parameters such as temperature, humidity, wind speed, and rainfall in real time; The collected environmental parameters are compared with the environmental safety standards in the anti-misoperation rule base. When the environmental parameters exceed the safe range, an early warning message is generated in a timely manner to prompt the operator to suspend operation or take corresponding preventive measures. Develop environmentally adaptive operation strategies based on the changing trends of environmental parameters and historical data; By embedding environmentally adaptable operational strategies into the operational rehearsal and verification process, operational tasks can be executed under different environmental conditions.

[0096] 209. After the anti-misoperation verification is passed, sort the primary and secondary equipment according to the preset logic to generate the corresponding switching operation sequence; In this step, the equipment sorting rules are determined based on the equipment type and operation priority. The equipment sorting rules include priority for high-voltage equipment, priority for protection devices, and synchronization of associated equipment. Based on the operation sequence requirements in the operation task, the equipment sorting rules are refined to generate a switching operation sequence. The switching operation sequence includes operation step number, equipment identifier, and operation type.

[0097] The equipment sorting rules refer to a sorting logic based on equipment type and operation priority, which can be implemented using a rule engine or decision tree algorithm to solve the inefficiency problem caused by chaotic equipment operation sequences in complex scenarios. The high-voltage equipment priority principle prioritizes high-voltage equipment operation steps by identifying equipment voltage level parameters, avoiding system instability caused by delayed operations. The protection device priority principle prioritizes protection device activation / deactivation operations before related primary equipment operations by analyzing the functional attributes of secondary equipment, preventing malfunctions or failures to operate. The related equipment synchronization principle ensures that related equipment operation steps are executed synchronously in time or space by analyzing the electrical connections or logical control relationships between devices.

[0098] Specifically, the equipment sorting rules first establish a basic sorting framework based on equipment type and operation priority. For example, high-voltage circuit breaker operation steps take precedence over low-voltage disconnector operation, and relay protection device activation / deactivation operations take precedence over corresponding line switch operations. Then, the sorting rules are refined based on the specific sequence requirements of the operation tasks. For instance, in switching operations, the operation area is divided according to the power outage range, and the equipment operation steps within the same area are arranged in descending order of voltage level. Simultaneously, protection device activation / deactivation steps are inserted between the corresponding primary equipment operation steps. The final generated switching operation sequence achieves process standardization through operation step numbering, equipment identification uses QR codes or RFID tags for precise positioning, and the operation type field clearly indicates specific actions such as opening, closing, or parameter setting.

[0099] In this embodiment, the step of formulating device sorting rules based on device type and operation priority includes: Define equipment type classifications, which include high-voltage equipment, low-voltage equipment, protection devices, and measuring devices; Based on the type of equipment and the degree of impact of the operation on power grid security, operation priorities are established, including emergency operations, important operations, and general operations. Based on the operational sequence requirements in the operational tasks, the equipment sorting rules are refined to generate a switching operation sequence. The refinement adopts weighted sorting or AHP (Analytic Hierarchy Process).

[0100] After the anti-misoperation verification is passed, and the primary and secondary devices are sorted according to preset logic to generate the corresponding switching operation sequence, the method further includes: The legality of the switching operation sequence is verified to ensure that the sequence complies with the power grid safety regulations and equipment operation requirements. The legality verification includes operation conflict detection, equipment status consistency check and operation time window verification.

[0101] 210. The data is sent to the anti-misoperation key and pressure plate controller via an encrypted communication channel; Specifically, the switching operation sequence is encrypted using either a symmetric or asymmetric encryption algorithm to ensure data transmission security. The encrypted switching operation sequence is then sent to the anti-misoperation key and pressure plate controller via wireless or wired communication, including 4G / 5G, Wi-Fi, and fiber optic communication. Feedback information from the anti-misoperation key and pressure plate controller is received to confirm successful data reception; this feedback information includes a reception timestamp, device identifier, and verification result.

[0102] The step of encrypting the switching operation sequence includes: Select an encryption algorithm, the algorithm including symmetric encryption algorithms including but not limited to AES or asymmetric encryption algorithms including but not limited to RSA; Generate an encryption key, which may include a symmetric key or an asymmetric key pair; The switching operation sequence is encrypted using an encryption key to generate encrypted data. The processing employs either block encryption or stream encryption.

[0103] 211. When operating equipment on-site based on the switching operation sequence, the anti-misoperation key makes real-time anti-misoperation judgments based on the actual status information of the equipment after the operation and the pre-rehearsal verification results. In this embodiment, the actual status information of the device after the operation is collected through built-in sensors or external interfaces. The actual status information includes the device location, switch status, and protection signal. The device location, switch status, and protection signal are compared with the device status data in the pre-operation verification results to determine whether the operation was performed as expected.

[0104] The built-in sensor refers to the status detection device integrated into the anti-misoperation key. Specifically, it can be implemented using a photoelectric sensor or a Hall effect sensor to directly measure the mechanical position of the equipment or the physical state of the switch contacts. This feature ensures the real-time and accuracy of status information through hardware-level data acquisition, avoiding errors from manual recording.

[0105] The external interface refers to the communication channel between the anti-misoperation key and the secondary equipment. Specifically, it can be implemented using an RS-485 or Ethernet interface to acquire the action signals of the protection device and the activation / deactivation status of the pressure plate. This feature expands the data sources for anti-misoperation judgment, enabling collaborative verification of the mechanical status of the primary equipment and the protection signals of the secondary equipment.

[0106] The device position refers to the mechanical open / closed state of primary equipment such as circuit breakers and disconnectors, which can be determined by measuring the contact position using limit switches or encoders. This feature provides a physical basis for the operation results of primary equipment to prevent misjudgments.

[0107] The protection signal refers to the action signal or alarm information output by the relay protection device, which can be transmitted through GOOSE messages or hard contact signals. This feature incorporates the logic state of secondary equipment into the anti-misoperation judgment system, preventing cascading risks caused by protection maloperation or failure to operate.

[0108] Specifically, after executing each step of the switching operation sequence, the anti-misoperation key collects the mechanical position information of the primary equipment through built-in sensors, and simultaneously acquires the protection signals of the secondary equipment through an external interface. For example, after disconnecting the circuit breaker, the built-in sensor detects its contact separation state, and the external interface synchronously reads the interlocking signal of the protection device. The collected equipment position, switch status, and protection signals are encapsulated into structured data packets and compared with the equipment status data in the pre-performance verification results. The comparison process not only verifies numerical consistency but also checks the logical timing matching based on the topological connection relationship between the equipment. For example, if the associated line protection pressure plate does not exit as predicted after the circuit breaker tripping operation is completed, it is determined to be an operation anomaly. The anti-misoperation key uploads the anomaly result to the anti-misoperation host, triggering a temporary control strategy to suspend subsequent operations.

[0109] It is understood that the step of collecting the actual status information of the device after operation through built-in sensors or external interfaces includes: The anti-misoperation key incorporates sensors, including a position sensor, a switch status sensor, and a current sensor. Connect to the device status monitoring system via an external interface, such as RS485, CAN or Ethernet, to obtain the actual status information of the device; The collected actual status information is preprocessed, including data filtering, data calibration, and data format conversion.

[0110] 212. The temporary control strategy for triggering the switching operation sequence based on the result of the anti-misjudgment is executed.

[0111] In this embodiment, if the result of the anti-misoperation judgment is that the operation is performed as expected, the next operation in the switching operation sequence is continued; if the result of the anti-misoperation judgment is that the operation is not performed as expected, the current operation is paused and a temporary control strategy is triggered. The temporary control strategy includes operation interruption, equipment isolation, and personnel evacuation. Abnormal operation information and the execution status of the temporary control strategy are recorded, and an abnormality handling log is generated. The abnormality handling log includes the abnormal time, equipment identification, and handling result.

[0112] If the error prevention judgment results in non-performance as expected, the current operation is suspended, and temporary control strategies are triggered, including: Define a temporary control strategy library, which covers strategies such as operation interruption, equipment isolation, and personnel evacuation; Based on the anomaly type and risk level in the error prevention judgment results, the corresponding strategy is matched from the temporary control strategy library; The matched temporary control strategy is executed, and control instructions are sent to the operator via the anti-misoperation key or the dispatch system. These instructions include operation interruption signals, equipment isolation commands, and evacuation routes.

[0113] The above technical solutions solve the problem of lack of real-time dynamic control in complex collaborative operation scenarios. Through the hierarchical response mechanism of operation interruption, equipment isolation and personnel evacuation, the risk of the spread of abnormal states is effectively curbed. At the same time, structured log records provide complete data support for accident tracing, improving the efficiency of abnormal event handling and subsequent strategy optimization capabilities.

[0114] This embodiment realizes operation rehearsal and error prevention verification by constructing a joint model of primary and secondary equipment. Combined with the real-time status comparison of the error prevention key and emergency control strategy, it effectively solves the problems of traditional error prevention systems being unable to adapt to multi-device linkage operation, lacking automated verification and emergency response capabilities. It has a significant effect on improving the safety and reliability of substation operation and maintenance.

[0115] The above describes the power grid operation and maintenance error prevention verification method in the embodiments of this application. The following describes the power grid operation and maintenance error prevention verification device in the embodiments of this application. Please refer to [link / reference]. Figure 3 One embodiment of the power grid operation and maintenance error prevention verification device in this application includes: The operation task determination module 310 is used to determine the operation task of the substation, wherein the operation task is the control operation of the primary and secondary equipment during the operation and maintenance of the substation. The operation pre-simulation module 320 is used to acquire the real-time operating status of the primary equipment and the functional status of the secondary equipment, and to map the real-time operating status and the functional status to obtain a joint model of the primary and secondary equipment. Based on the joint model of the primary and secondary equipment, the operation pre-simulation is performed on each primary and secondary equipment in the operation task. The error prevention verification module 330 is used to perform multi-dimensional collaborative error prevention verification on the operation rehearsal based on the pre-built error prevention rules to obtain the rehearsal verification result. The error prevention rules include equipment status safety rules, operation sequence compliance rules and multi-device linkage error prevention rules. The operation sequence generation module 340 is used to sort each primary and secondary device according to preset logic after the anti-misoperation verification is passed, and generate the corresponding switching operation sequence. Communication module 350 is used to send data to the anti-misoperation key and the pressure plate controller through an encrypted communication channel. The anti-misoperation key has the functions of device identification, operation permission verification and mechanical locking. The pressure plate controller supports remote engagement / disengagement control and status feedback. The real-time error prevention judgment module 360 ​​is used to make real-time error prevention judgments based on the actual status information of the equipment after the operation and the pre-drill verification results when the equipment is operated on-site based on the switching operation sequence.

[0116] The device further includes: The control strategy execution module 370 is used to trigger the execution of a temporary control strategy for the switching operation sequence based on the result of the anti-misjudgment. The temporary control strategy includes operation interruption, equipment isolation, and personnel evacuation.

[0117] In this embodiment, the operation task determination module 310 is specifically used for: Receive operation instructions for primary and secondary equipment issued by the dispatching system in the substation, the operation instructions including operation type, operation object and operation time; Based on the operation type, the operation object, and the operation time, a corresponding operation task template is matched from a preset task library. The operation task template includes the operation scenario and the standard operation process of each device. Based on the current operating status of the substation and the health status of each device, the operation task template is dynamically adjusted to generate the final operation task. The dynamic adjustment includes equipment selection optimization, operation sequence adjustment, and supplementation of safety measures.

[0118] In this embodiment, the operation pre-simulation module 320 is specifically used for: The real-time operating status of primary equipment and the functional status of secondary equipment are obtained, and the real-time operating status and the functional status are mapped to obtain a joint model of primary and secondary equipment. The joint model of primary and secondary equipment includes equipment topology, electrical connection relationship and protection configuration information. Based on the operational task, the state changes of the equipment are simulated in the primary and secondary equipment joint model, wherein the simulation includes equipment switching, secondary equipment operation and circuit breaker opening and closing. Record the status data and operation steps of the equipment during the simulation process to generate a joint model of the target primary and secondary equipment corresponding to the operation task.

[0119] In this embodiment, the error prevention verification module 330 is specifically used for: The device status data is extracted from the primary and secondary device joint model and compared with the device status safety rules in the pre-built anti-misoperation rules to determine whether the device has an abnormal state. The operation steps of the equipment are extracted from the primary and secondary equipment joint model, and the operation steps are verified to conform to the operation sequence compliance rules in the pre-built anti-misoperation rules. The verification includes the correctness of the sequence, the reasonableness of the time interval, and the operation dependency relationship. Extract the equipment topology, electrical connection relationships, and protection configuration information from the primary and secondary equipment joint model, and determine whether there is a risk of multi-device linkage misoperation. If it is determined that the equipment is not in an abnormal state, there is no risk of misoperation due to multi-device linkage, and the verification order, time interval, and operation dependency are correct, then the misoperation prevention verification is deemed to have passed.

[0120] In this embodiment, the operation sequence generation module 340 is specifically used for: Based on the equipment type and operation priority, the equipment sorting rules are determined, including priority for high-voltage equipment, priority for protection devices, and synchronization of associated equipment; Based on the operation sequence requirements in the operation task, the equipment sorting rules are refined to generate a switching operation sequence, which includes operation step number, equipment identifier and operation type.

[0121] In this embodiment, the real-time error prevention judgment module 360 ​​is specifically used for: The actual status information of the device after operation is collected through built-in sensors or external interfaces. The actual status information includes the device location, switch status and protection signals. The device location, switch status, and protection signal are compared with the device status data in the pre-run verification results to determine whether the operation was performed as expected.

[0122] In this embodiment, the control strategy execution module 370 is specifically used for: If the result of the error prevention judgment is that the operation is performed as expected, then continue to execute the next operation in the switching operation sequence; If the result of the error prevention judgment is that the operation is not performed as expected, the current operation is suspended and a temporary control strategy is triggered. The temporary control strategy includes operation interruption, equipment isolation and personnel evacuation. Record abnormal operation information and the execution status of temporary control strategies, and generate an abnormality handling log, which includes the abnormal time, device identifier and handling result.

[0123] Based on the previous embodiment, this embodiment describes in detail the specific functions of each module and the unit composition of some modules. Through the above modules, the specific functions of the original modules are refined, the operation of the power grid operation and maintenance error prevention and verification device is improved, its operational reliability is enhanced, and the actual logic between each step is clarified, thereby improving the practicality of the device.

[0124] This application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is loaded onto the processor, it implements the power grid operation and maintenance error prevention verification method according to Embodiment 1.

[0125] Figure 4 This is a schematic diagram of the structure of an electronic device 400 provided in an embodiment of this application. The electronic device 400 can vary significantly due to different configurations or performance characteristics. It may include one or more central processing units (CPUs) 410 (e.g., one or more processors) and a memory 420, and one or more storage media 430 (e.g., one or more mass storage devices) for storing application programs 433 or data 432. The memory 420 and storage media 430 can be temporary or persistent storage. The program stored in the storage media 430 may include one or more modules (not shown in the diagram), each module including a series of request operations on the electronic device 400. Furthermore, the processor 410 may be configured to communicate with the storage media 430 and execute the series of request operations in the storage media 430 on the electronic device 400 to implement the steps of the aforementioned power grid operation and maintenance error prevention verification method.

[0126] Electronic device 400 may also include one or more power supplies 440, one or more wired or wireless network interfaces 450, one or more input / output interfaces 460, and / or one or more operating systems 431, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, etc. Those skilled in the art will understand that... Figure 4 The illustrated electronic device structure does not constitute a limitation on the electronic device provided in this application. It may include more or fewer components than illustrated, or combine certain components, or have different component arrangements.

[0127] This application also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium, wherein the computer-readable storage medium stores a request that, when the request is executed on a computer, causes the computer to perform the steps of the power grid operation and maintenance error prevention verification method.

[0128] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system, device, or unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0129] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several requests to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0130] It is worth noting that in the embodiments of the present invention, "steps + numbers" is only an expression for clearly describing a specific implementation method of a power grid operation and maintenance error prevention verification method, and is not an absolute restriction on the order of each step. Under the guidance of the core concept of the present invention, changing the order of these steps to obtain the same or similar technical effects all fall within the scope of the present invention.

[0131] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A method for verifying the prevention of malfunctions in power grid operation and maintenance, applied to the malfunction prevention host in a substation, characterized in that, The method includes: Determine the operation tasks of the substation, which are the control operations of the primary and secondary equipment during the operation and maintenance of the substation. The real-time operating status of the primary equipment and the functional status of the secondary equipment are obtained, and the real-time operating status and the functional status are mapped to obtain a joint model of primary and secondary equipment. Based on the joint model of primary and secondary equipment, the operation of each primary and secondary equipment in the operation task is rehearsed, and the operation rehearsal is checked in a multi-dimensional collaborative manner based on the pre-built anti-misoperation rules to obtain the rehearsal check result. The anti-misoperation rules include equipment status safety rules, operation sequence compliance rules and multi-device linkage anti-misoperation rules. After the anti-misoperation verification is passed, the primary and secondary devices are sorted according to the preset logic to generate the corresponding switching operation sequence, and then sent to the anti-misoperation key and pressure plate controller through the encrypted communication channel. When operating equipment on-site based on the switching operation sequence, the anti-misoperation key performs real-time anti-misoperation judgment based on the actual status information of the equipment after the operation and the pre-rehearsal verification results, and obtains the real-time anti-misoperation judgment result.

2. The power grid operation and maintenance error prevention verification method according to claim 1, characterized in that, The anti-misoperation key has the functions of device identification, operation permission verification and mechanical locking, and the pressure plate controller supports remote engagement / disengagement control and status feedback.

3. The power grid operation and maintenance error prevention verification method according to claim 1, characterized in that, The determination of the substation's operational tasks includes: Receive operation instructions for primary and secondary equipment issued by the dispatching system in the substation, the operation instructions including operation type, operation object and operation time; Based on the operation type, the operation object, and the operation time, a corresponding operation task template is matched from a preset task library. The operation task template includes the operation scenario and the standard operation process of each device. Based on the current operating status of the substation and the health status of each device, the operation task template is dynamically adjusted to generate the final operation task. The dynamic adjustment includes equipment selection optimization, operation sequence adjustment, and supplementation of safety measures.

4. The power grid operation and maintenance error prevention verification method according to claim 1, characterized in that, The operation rehearsal based on the joint model of primary and secondary equipment for each primary and secondary equipment in the operation task includes: The primary and secondary equipment joint model includes equipment topology, electrical connection relationships, and protection configuration information; Based on the operational task, the state changes of the equipment are simulated in the primary and secondary equipment joint model, wherein the simulation includes equipment switching, secondary equipment operation and circuit breaker opening and closing; Record the status data and operation steps of the equipment during the simulation process, and generate a joint model of the target primary and secondary equipment corresponding to the operation task. The joint model of the target primary and secondary equipment is used for each primary and secondary equipment to perform operation rehearsals according to the operation steps.

5. The power grid operation and maintenance error prevention verification method according to claim 4, characterized in that, The pre-built error prevention rules are used to perform multi-dimensional collaborative error prevention verification of the operation rehearsal, resulting in rehearsal verification results, including: The device status data is extracted from the target primary and secondary device joint model and compared with the device status safety rules in the pre-built anti-misoperation rules to determine whether the device has an abnormal state. The operation steps of the target primary and secondary equipment are extracted from the joint model of the target primary and secondary equipment, and the operation steps are verified to conform to the operation sequence compliance rules in the pre-built anti-misoperation rules. The verification includes the correctness of the sequence, the reasonableness of the time interval, and the operation dependency relationship. Extract the equipment topology, electrical connection relationships, and protection configuration information from the target primary and secondary equipment joint model, and determine whether there is a risk of multi-device linkage misoperation; If the equipment meets all of the following conditions, the error prevention calibration is deemed passed. These conditions include: There are no abnormal states, no risk of misoperation due to multi-device linkage, and the verification order, time interval, and operation dependencies are correct.

6. The power grid operation and maintenance error prevention verification method according to claim 5, characterized in that, The step of extracting device status data from the target primary and secondary device joint model and comparing it with the device status safety rules in the pre-built anti-misoperation rules to determine whether the device has an abnormal state includes: Machine learning algorithms are introduced to deeply mine the historical operating data of the equipment and establish an equipment status prediction model; among them, the equipment status prediction model is trained based on a composite loss function to obtain a trained equipment status prediction model. The status data of the equipment is extracted from the joint model of the primary and secondary equipment of the target, and preliminary processing is performed using edge computing technology; The multi-source data fusion algorithm is used to fuse various data in the pre-processed state data. The fused data is then input into the trained equipment state prediction model for prediction to determine whether the equipment state is safe.

7. The power grid operation and maintenance error prevention verification method according to claim 6, characterized in that, A composite loss function is constructed based on cross-entropy classification loss, temporal trend consistency loss, and multi-feature collaborative loss. Among them, the larger the prediction difference between adjacent time steps, the greater the temporal trend consistency loss, the greater the deviation between the correlation of the predicted values ​​of each feature dimension and the inherent correlation between features, and the greater the multi-feature collaborative loss.

8. The power grid operation and maintenance error prevention verification method according to claim 5, characterized in that, The steps for extracting equipment from the target primary and secondary equipment joint model, and verifying whether the operation steps conform to the operation sequence compliance rules in the pre-built error prevention rules, include: Natural language processing technology is used to perform guided analysis on the target primary and secondary equipment joint model to extract the equipment operation steps; The parsed operation steps are compared with the operation sequence rules in the error prevention rules to verify whether the order, time interval, and dependency of the operation steps meet the requirements.

9. The power grid operation and maintenance error prevention verification method according to claim 1, characterized in that, After the anti-misoperation verification is passed, the primary and secondary devices are sorted according to preset logic to generate corresponding switching operation sequences, including: Based on the equipment type and operation priority, the equipment sorting rules are determined, including priority for high-voltage equipment, priority for protection devices, and synchronization of associated equipment; Based on the operation sequence requirements in the operation task, the equipment sorting rules are refined to generate a switching operation sequence, which includes operation step number, equipment identifier and operation type.

10. The power grid operation and maintenance error prevention verification method according to claim 1, characterized in that, When operating equipment on-site based on the switching operation sequence, the anti-misoperation key performs real-time anti-misoperation judgment based on the actual status information of the equipment after the operation and the pre-rehearsal verification results, including: Collect the actual status information of the device after the operation, including the device location, switch status and protection signals; The device location, switch status, and protection signal are compared with the device status data in the pre-run verification results to determine whether the operation was performed as expected.

11. A power grid operation and maintenance error prevention verification device, used to implement the power grid operation and maintenance error prevention verification method according to any one of claims 1 to 10, characterized in that, The device includes: The operation task determination module is used to determine the operation tasks of the substation, wherein the operation tasks are the control operations of the primary and secondary equipment during the operation and maintenance of the substation; The operation pre-simulation module is used to acquire the real-time operating status of the primary equipment and the functional status of the secondary equipment, and to map the real-time operating status and the functional status to obtain a joint model of the primary and secondary equipment. Based on the joint model of the primary and secondary equipment, the operation pre-simulation is performed on each primary and secondary equipment in the operation task. The error prevention verification module is used to perform multi-dimensional collaborative error prevention verification on the operation rehearsal based on pre-built error prevention rules, and obtain the rehearsal verification result. The error prevention rules include equipment status safety rules, operation sequence compliance rules, and multi-device linkage error prevention rules. The operation sequence generation module is used to sort the primary and secondary devices according to preset logic after the anti-misoperation verification is passed, and generate the corresponding switching operation sequence. The communication module is used to send data to the anti-misoperation key and pressure plate controller via an encrypted communication channel; The real-time error prevention judgment module is used to make real-time error prevention judgments based on the actual status information of the equipment after the operation and the pre-drill verification results when the equipment is operated on-site based on the switching operation sequence.

12. An electronic device, characterized in that, The electronic device includes: A memory and at least one processor, wherein the memory stores requests, and the memory and the at least one processor are interconnected via lines; The at least one processor invokes the request in the memory to cause the electronic positioning device to perform the steps of the power grid operation and maintenance error prevention verification method as described in any one of claims 1 to 10.

13. A computer-readable storage medium storing a computer program thereon, characterized in that: When the computer program is executed by the processor, it implements each step of the power grid operation and maintenance error prevention verification method as described in any one of claims 1 to 10.

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