Intelligent monitoring method and system for switching operation of transformer substation

Abstract

The invention provides an intelligent monitoring method and system for switching operation of a transformer substation, and relates to the technical field of power grids. Multi-source sensing data such as SCADA signals, video data, temperature data, vibration data and environment data are collected in real time, a global rule engine and a process state engine are adopted for parallel study and judgment, switching operation is subjected to real-time multi-dimensional cross validation and deep analysis from the two dimensions of a macroscopic safety rule and a microcosmic operation process, and the real-time multi-dimensional cross validation and deep analysis are achieved. And the comprehensiveness and accuracy of risk identification are improved. And then strategy fusion is carried out based on a security priority principle, and an intelligent monitoring instruction including graded early warning and equipment locking is generated, so that differentiated and precise countermeasures are implemented for risks of different grades. By constructing an intelligent monitoring process integrating real-time sensing, intelligent analysis, strategy decision and accurate execution, the problem of safety risk existing in manual switching operation is solved, and the safety and intelligent level of switching operation of the transformer substation are improved.

Description

Technical Field

[0001] This invention relates to the field of power grid technology, and in particular to an intelligent monitoring method and system for switching operations in substations. Background Technology

[0002] Substations are the core hubs of the power grid, and their safe and stable operation is directly related to the reliability of power supply. Switching operations are among the most frequent and critical operations in substations. Their purpose is to change the electrical wiring methods, operating modes, or equipment states by altering the operating states of equipment such as circuit breakers and disconnectors. Currently, traditional switching operations mainly rely on the "operation ticket" system, the "one person operating, one person monitoring" model, and the "manual monitoring by a supervisor."

[0003] Manual switching operations are affected by the technical skills, sense of responsibility, and mental state of the operators, supervisors, and monitors. The safety and correctness of switching operations are potentially compromised. Human negligence, lack of experience, or fatigue can easily lead to misoperation, resulting in significant safety risks. Summary of the Invention

[0004] This invention provides an intelligent monitoring method and system for substation switching operations, which solves the safety risks associated with manual switching operations and improves the safety of substation switching operations.

[0005] In a first aspect, the present invention provides an intelligent monitoring method for substation switching operations. The method includes: real-time acquisition of multi-source sensor data from substation equipment, including SCADA signals, video data, temperature data, vibration data, and environmental data; based on the multi-source sensor data, parallel analysis is performed using a global rule engine and a process status engine to obtain rule analysis results and process analysis results; based on the rule analysis results and process analysis results, strategy fusion is performed according to the safety priority principle to obtain intelligent monitoring instructions for switching operations; the intelligent monitoring instructions include tiered early warning instructions and equipment interlocking instructions; and intelligent monitoring of substation switching operations is performed based on the intelligent monitoring instructions.

[0006] In one possible implementation, the step of performing parallel analysis based on the multi-source sensor data through a global rule engine and a process state engine to obtain rule analysis results and process analysis results includes: performing rule matching based on the multi-source sensor data and an improved Rete algorithm to obtain rule analysis results; and performing state monitoring of the operation process based on the multi-source sensor data and an embedded state machine to obtain process analysis results.

[0007] In one possible implementation, the step of performing rule matching based on the multi-source sensor data and the improved Rete algorithm to obtain rule judgment results includes: encapsulating the multi-source sensor data into working memory elements; the working memory elements are standardized fact objects corresponding to the error prevention rules; inputting the working memory elements into a pre-compiled Rete network, filtering them through the root node and type node of the Rete network, and distributing them to Alpha nodes for single-condition matching to obtain successfully matched working memory elements; in the Beta nodes of the Rete network, performing multi-condition and time-series logic association matching based on the successfully matched working memory elements and historical signal data stored in the time-series context buffer to determine the matching result; the matching result includes whether the matching is successful or unsuccessful, and the terminal node corresponding to the successful matching; if the matching result is successful, activating the rules of the terminal node and generating the rule judgment result, which is used to characterize whether the current operation has a risk of violating global security rules.

[0008] In one possible implementation, before obtaining the rule judgment result and process judgment result by parallel analysis based on the multi-source sensor data through a global rule engine and a process state engine, the method further includes: constructing an expert knowledge base based on anti-error rules formed by substation safety regulations and operational experience; compiling a Rete network based on the expert knowledge base; the Rete network includes a root node, type node, Alpha node, Beta node, and terminal node; wherein, the condition part of the anti-error rule is decomposed into independent modes, the Alpha node stores the single-condition mapping relationship between the independent modes of the anti-error rule and the working memory element, the Beta node stores the association logic of different independent modes of the anti-error rule, and the multi-condition mapping relationship between different independent modes and the working memory element, and the terminal node binds the rule conclusion part of the anti-error rule; a time-series context buffer is constructed, and an association relationship is established between the time-series context buffer and the Beta node of the Rete network, the association relationship being used to provide historical signal data query support for the multi-condition matching.

[0009] In one possible implementation, the step of monitoring the operation process based on the multi-source sensor data and the embedded state machine to obtain a process judgment result includes: determining the currently executed standard operation ticket and the current operation step based on the multi-source sensor data; instantiating the embedded state machine based on the currently executed standard operation ticket and the current operation step; the state of the embedded state machine corresponds to the current operation step, and the state transition condition of the embedded state machine is triggered by the expected real-time signal of the current operation step; comparing the multi-source sensor data with the state transition condition of the embedded state machine to determine the comparison result; if the comparison result is consistent with the state transition condition, the embedded state machine transitions to the next state; if the comparison result is inconsistent with the state transition condition, the process judgment result is generated; the process judgment result includes a process sequence error alarm.

[0010] In one possible implementation, before obtaining the rule judgment result and process judgment result by performing parallel analysis based on the multi-source sensor data through a global rule engine and a process state engine, the method further includes: constructing a standard operation ticket library based on the audited standardized switching operation step sequence; pre-compiling state machine templates for various operation tickets based on the standard operation ticket library; the state machine templates define the state sequences of various operation tickets and the transition conditions between states; wherein, each state in the state sequence corresponds to an operation step in the operation ticket, and the transition condition is the expected equipment signal that should be generated after the operation step is successfully executed; and determining the embedded state machine based on the state machine templates of various operation tickets.

[0011] In one possible implementation, the step of fusing strategies based on the rule-based judgment results and process-based judgment results, and prioritizing safety, to obtain intelligent monitoring instructions for switching operations includes: identifying whether the rule-based judgment results contain high-risk alarms; the high-risk alarms are used to indicate violations that directly lead to equipment damage or personal injury; if the rule-based judgment results include high-risk alarms, then the intelligent monitoring instruction is determined to be the highest-level equipment interlocking instruction; if the rule-based judgment results do not include high-risk alarms, then the process-based judgment results are judged; if the process-based judgment results include process sequence error alarms, then the intelligent monitoring instruction is determined to be an error alarm instruction, which indicates an abnormal operation sequence; if the rule-based judgment results do not include process sequence error alarms but include low-to-medium risk alarms, then the intelligent monitoring instruction is determined to be an alarm notification instruction, which alerts attention to non-emergency anomalies; if the process-based judgment results are normal, then the intelligent monitoring instruction is determined to be a normal monitoring instruction.

[0012] In one possible implementation, the intelligent monitoring of substation switching operations based on the intelligent monitoring command includes: if the intelligent monitoring command is an equipment interlock command, sending a hard contact interlock signal or a soft message interlock command to the equipment control system corresponding to the current operation step to forcibly interrupt the ongoing switching operation; if the intelligent monitoring command is an error alarm command or an alarm prompt command, pushing alarm information and handling suggestions to the monitoring terminal in the form of sound, light, and electricity; receiving feedback information from operators on alarm information; and associating and storing the multi-source sensor data, intelligent monitoring commands, and feedback information of the entire process from the beginning to the end of the current operation step to form a structured case.

[0013] In one possible implementation, after intelligently monitoring the substation switching operations based on the intelligent monitoring instructions, the method further includes: classifying the structured cases to determine confirmed valid alarm cases, system false alarm cases, and newly added valid anomaly handling procedures; increasing the weight or confidence of the rules corresponding to the confirmed valid alarm cases for each case; correcting the rule triggering conditions for system false alarm cases for each case; and generating new rules for newly added valid anomaly handling procedures and storing them in the expert knowledge base to optimize the expert knowledge base.

[0014] Secondly, embodiments of the present invention provide an intelligent monitoring device for substation switching operations. This intelligent monitoring device includes a communication module and a processing module. The communication module is used to collect multi-source sensor data from substation equipment in real time, including SCADA signals, video data, temperature data, vibration data, and environmental data. The processing module is used to perform parallel analysis based on the multi-source sensor data using a global rule engine and a process status engine to obtain rule analysis results and process analysis results. Based on the rule analysis results and process analysis results, and according to the safety priority principle, strategy fusion is performed to obtain intelligent monitoring instructions for switching operations. The intelligent monitoring instructions include tiered early warning instructions and equipment interlocking instructions. Based on the intelligent monitoring instructions, intelligent monitoring of substation switching operations is performed.

[0015] Thirdly, embodiments of the present invention provide an electronic device including a memory and a processor. The memory stores a computer program, and the processor is configured to call and run the computer program stored in the memory to perform the steps of the method as described in the first aspect and any possible implementation thereof.

[0016] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program, characterized in that, when the computer program is executed by a processor, it implements the steps of the method as described in the first aspect and any possible implementation thereof.

[0017] This invention provides an intelligent monitoring method and system for substation switching operations. By real-time acquisition of multi-source sensor data, including SCADA signals, video data, temperature data, vibration data, and environmental data, and employing a global rule engine and a process status engine for parallel analysis, this invention enables real-time, multi-dimensional cross-validation and in-depth analysis of switching operations from both macro-level safety rules and micro-level operational processes, improving the comprehensiveness and accuracy of risk identification. Subsequently, based on the principle of safety priority, strategy fusion is performed to generate intelligent monitoring instructions, including tiered early warning and equipment interlocking, enabling differentiated and precise response measures for different levels of risk. This invention solves the safety risks associated with manual switching operations by constructing an intelligent monitoring process integrating real-time perception, intelligent analysis, strategy decision-making, and precise execution, improving the safety and intelligence level of substation switching operations, and effectively preventing operational risks caused by human error or monitoring lag. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating an intelligent monitoring method for switching operations in a substation, provided in an embodiment of the present invention. Figure 2 This is a schematic diagram of the structure of an intelligent monitoring device for switching operations in a substation, provided in an embodiment of the present invention. Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0020] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of the invention. However, those skilled in the art will understand that the invention can be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods are omitted so as not to obscure the description of the invention with unnecessary detail.

[0021] In the description of this invention, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The term "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone. Furthermore, "at least one" and "more than one" refer to two or more. The terms "first," "second," etc., do not limit the quantity or order of execution, and "first," "second," etc., do not necessarily imply differences.

[0022] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner to facilitate understanding.

[0023] Furthermore, the terms "comprising" and "having," and any variations thereof, used in the description of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or modules is not limited to the steps or modules listed, but may optionally include other steps or modules not listed, or may optionally include other steps or modules inherent to such process, method, product, or device.

[0024] To make the objectives, technical solutions, and advantages of the present invention clearer, the following description will be provided in conjunction with the accompanying drawings and specific embodiments.

[0025] As described in the background section, manual switching operations have the following drawbacks.

[0026] 1. High dependence on subjective judgment of personnel: The technical level, sense of responsibility and mental state of operators, supervisors and monitors directly affect the safety and correctness of operations. Human negligence, lack of experience or fatigue can easily lead to misoperation and bring huge safety risks.

[0027] 2. Isolated and Delayed Monitoring Methods: Existing monitoring systems, such as Supervisory Control and Data Acquisition (SCADA) systems and video surveillance systems, are usually independent of each other, forming information silos. Operators, supervisors, and monitors find it difficult to conduct real-time, comprehensive correlation analysis and judgment of the mechanical status of equipment, changes in electrical quantities, and personnel behavior throughout the entire operation process, resulting in strong monitoring lag.

[0028] 3. Lack of intelligent proactive early warning: Existing technologies cannot proactively predict and intervene in potential risks during operation. For complex abnormal operating conditions, such as "closing or disconnecting disconnect switches under load," "equipment not in place," or "protective circuit breakers not closed," the system lacks in-depth fusion analysis and intelligent interpretation capabilities, and cannot provide effective early warnings before accidents occur.

[0029] 4. Insufficient operational efficiency and traceability: Manual operation is inefficient and lacks objective and continuous digital records, resulting in a lack of data support for post-event analysis, responsibility determination, and operational optimization.

[0030] As the construction of smart grids deepens, many existing monitoring solutions are improved from a single dimension. For example, some solutions use rule bases for simple error prevention logic verification, but rule bases are usually rigid and cannot handle complex, time-series multi-source information fusion scenarios; some solutions introduce video analysis technology, but it is susceptible to environmental interference and it is difficult to directly and accurately judge the subtle mechanical state changes of equipment; and some solutions attempt to integrate SCADA with video information, but these mostly remain at the level of information linkage and lack an intelligent decision-making core capable of deep reasoning and closed-loop control.

[0031] Therefore, there is an urgent need for a substation switching operation intelligent monitoring solution that can deeply integrate multi-source information, has real-time intelligent analysis and proactive early warning capabilities, and is applicable to actual production environments, so as to fundamentally improve the safety, standardization and intelligence of switching operations.

[0032] This invention aims to overcome the shortcomings of existing technologies and provide a method and system capable of comprehensive, intelligent, and closed-loop monitoring of substation switching operations. The core objective is to achieve real-time, proactive, and precise early warning and intervention for operational risks through deep fusion of multi-source information and a hybrid intelligent matching strategy, significantly improving the safety and intelligence level of switching operations.

[0033] The overall concept of this invention is to construct an intelligent closed-loop system encompassing "perception-analysis-decision-execution-learning". The core technology lies in employing a hybrid matching strategy combining an improved Rete algorithm and an embedded state machine, with a central arbitrator making the final decision.

[0034] The intelligent monitoring system of this invention comprises four main modules: a multi-source data perception module, an intelligent analysis engine module, a central arbitration and decision-making module, and an early warning execution and feedback learning module. The multi-source data perception module is responsible for real-time acquisition and standardization of SCADA signals, video streams, sensor data (temperature, vibration, etc.), environmental data, etc. The intelligent analysis engine module is the core processing unit, integrating a global rule engine based on an improved Rete algorithm and a process state engine based on an embedded state machine, used for parallel analysis of input data. The central arbitration and decision-making module receives the output results of the global rule engine and the process state engine, performs fusion decision-making based on preset strategies such as "safety priority," and generates the final monitoring command. The early warning execution and feedback learning module executes the final monitoring command, performs tiered alarms, and feeds back the handling results to the case library and model library, enabling system self-learning and self-evolution.

[0035] like Figure 1 As shown, this embodiment of the invention provides an intelligent monitoring method for substation switching operations. The method includes steps S101-S104.

[0036] S101. Real-time acquisition of multi-source sensor data from substation equipment.

[0037] In this embodiment of the application, the multi-source sensor data includes SCADA signals, video data, temperature data, vibration data, and environmental data.

[0038] For example, embodiments of the present invention can construct a multi-source data perception layer to collect heterogeneous data streams from SCADA systems, high-definition video surveillance, IoT sensors, and environmental monitoring equipment in real time.

[0039] S102. Based on the multi-source sensor data, parallel analysis is performed through the global rule engine and the process status engine to obtain the rule analysis results and the process analysis results.

[0040] In some embodiments, the present invention can construct an intelligent analysis engine with a hybrid matching strategy based on an improved Rete algorithm and an embedded state machine; wherein, the improved Rete algorithm, by introducing a time-series context buffer, endows the rule base with the ability to interpret historical sequences of signals; the embedded state machine instantiates a process monitoring model for each operation ticket being executed, for strictly verifying the sequentiality of operation steps.

[0041] As one possible implementation, step S102 can be specifically implemented as steps S1021-S1022.

[0042] S1021. Based on the multi-source sensor data and the improved Rete algorithm, perform rule matching to obtain the rule judgment result.

[0043] For example, step S1021 can be specifically implemented as steps A1-A4.

[0044] A1. Encapsulate the multi-source sensor data into working memory elements.

[0045] In some embodiments, the working memory element is a standardized fact object corresponding to the error prevention rule.

[0046] A2. Input the working memory element into the pre-compiled Rete network. After being filtered by the root node and type node of the Rete network, it is distributed to the Alpha node for single-condition matching to obtain the successfully matched working memory element.

[0047] A3. In the Beta node of the Rete network, based on the successfully matched working memory element, perform multi-condition and time-series logic association matching with the historical signal data stored in the timing context buffer to determine the matching result.

[0048] In some embodiments, the matching result includes whether the match was successful or failed, and the corresponding terminal node when the match was successful.

[0049] For example, the matching process of the improved Rete algorithm includes: 1. Encapsulating the real-time data stream into working memory elements and inputting them into the pre-compiled Rete network; 2. After being filtered by the root node and type node, the working memory elements are distributed to the corresponding Alpha node for single-condition matching; 3. The successfully matched elements are matched in the Beta node with the historical signal data stored in the time-series context buffer for multi-condition and time-series logic association matching; 4. If the matching is successful and reaches the terminal node, the corresponding rule is activated and a global security assessment conclusion is generated.

[0050] A4. If the matching result is successful, the rules of the terminal node are activated, and the rule judgment result is generated.

[0051] In some embodiments, the rule assessment results are used to characterize whether the current operation carries the risk of violating global security rules.

[0052] For example, traditional rule engines can only judge instantaneous states and cannot understand time-sequential violations such as "there was current in the line in the past 10 seconds, and now the isolating switch is activated". This invention uses an improved Rete algorithm (global rule engine) with time-sequential context caching to solve this problem, as shown in the following process.

[0053] 1. Rule compilation: Compile expert knowledge (such as the five-defense rules) into a Rete network (including root node, Alpha node, Beta node, etc.).

[0054] 2. Timing Context Buffer (TCC): Adds a buffer to the system to store the historical sequence of key signals in a recent period.

[0055] 3. Matching Process: When a real-time signal (such as "disconnect switch tripping") is input, the Beta node will simultaneously query historical data in the TCC while performing conditional association. For example, it will check whether "the current of this line is greater than 0 within 10 seconds before the tripping operation", thus accurately determining the serious violation of "tripping under load", even if the current happens to be 0 at the moment of tripping.

[0056] S1022. Based on the multi-source sensor data and the embedded state machine, the operation process is monitored to obtain the process judgment result.

[0057] For example, step S1022 can be specifically implemented as steps B1-B5.

[0058] B1. Based on the multi-source sensor data, determine the standard operating ticket to be executed and the current operating steps.

[0059] B2. Instantiate the embedded state machine based on the currently executed standard operation ticket and the current operation steps.

[0060] In some embodiments, the state of the embedded state machine corresponds to the current operation step, and the state transition condition of the embedded state machine is triggered by the expected real-time signal of the current operation step.

[0061] B3. Compare the multi-source sensor data with the state transition conditions of the embedded state machine to determine the comparison result.

[0062] For example, the operation process of an embedded state machine includes: 1. Pre-compiling a state machine template according to a standard operation ticket, wherein the state of the template corresponds to the operation step, and the transition condition is triggered by a real-time signal and manual confirmation information; 2. Instantiating a state machine for the currently executed operation ticket, which strictly follows the principle of "only being in one state at a time"; 3. When a real-time signal is received, the state machine determines whether it is the expected transition condition for the current state; if so, it transitions to the next state; if not, it generates a process sequence error alarm.

[0063] B4. If the comparison result is consistent with the state transition condition, the embedded state machine will transition to the next state.

[0064] B5. If the comparison result is inconsistent with the state transition conditions, then the process judgment result is generated.

[0065] In some embodiments, the process analysis results include a process sequence error alarm.

[0066] For example, in order to ensure the strict sequence of the operation process and prevent sequential errors such as skipping or missing steps, the present invention can be implemented using the following process.

[0067] 1. One task, one state machine: Dynamically instantiate a state machine for each operation ticket being executed.

[0068] 2. States and Transitions: Each "state" of the state machine corresponds to a step of the operation ticket (such as "waiting for the circuit breaker to open"), and the "transition condition" is the expected correct signal (such as "receiving the circuit breaker opening signal").

[0069] 3. Strict verification: The state machine is in only one state at any given time. If an unexpected signal is received (such as receiving a "disconnect switch tripped" signal while in the "waiting for circuit breaker to trip" state), it is immediately determined to be an "incorrect operation sequence".

[0070] S103. Based on the rule analysis results and process analysis results, and in accordance with the safety priority principle, strategy fusion is performed to obtain intelligent monitoring instructions for switching operations.

[0071] In some embodiments, the present invention can use a central arbitrator to receive and fuse the global rule matching result output by the improved Rete algorithm with the process sequence verification result output by the embedded state machine, make a comprehensive decision based on a preset priority strategy, and generate the final monitoring instruction.

[0072] In this embodiment, the intelligent monitoring instructions include tiered early warning instructions and equipment lockout instructions.

[0073] As one possible implementation, step S103 can be specifically implemented as steps S1031-S1036.

[0074] S1031. Identify whether the rule analysis results contain high-risk alarms.

[0075] In some embodiments, the high-risk alarm is used to indicate violations that directly lead to equipment damage or personal injury.

[0076] S1032. If the rule analysis result includes a high-risk alarm, then the intelligent monitoring instruction is determined to be the highest-level device interlock instruction.

[0077] S1033. If the rule analysis result does not include high-risk alarms, then the process analysis result shall be judged.

[0078] S1034. However, if the process analysis result includes a process sequence error alarm, then the intelligent monitoring instruction is determined to be an error alarm instruction.

[0079] In some embodiments, the error alarm instruction is used to indicate an abnormal operation sequence; S1035. If the rule analysis result does not include process sequence error alarms, but includes low-to-medium risk alarms, then the intelligent monitoring instruction is determined to be an alarm prompt instruction.

[0080] In some embodiments, the alarm notification instruction is used to draw attention to non-urgent anomalies.

[0081] S1036. If the process analysis result is normal, then the intelligent monitoring instruction is determined to be a normal monitoring instruction.

[0082] For example, the decision logic of the central arbitrator includes: 1. The central arbitrator receives the results from both engines. It first determines whether the global rules engine outputs a "high-risk" alarm (such as "triggering under load"). If so, regardless of the state machine result, the arbitrator issues the highest-level "blocking" command and may trigger the control system to lock out the system. 2. If the global rules engine does not have a high-risk alarm, the arbitrator determines whether the process state engine reports an "incorrect sequence". If so, the arbitrator issues an "error" alarm command, prompting the operator to correct the steps. 3. If the global rules engine only has a "medium-risk" alarm (such as "equipment temperature too high"), and the process is correct, the arbitrator issues a "warning" command, reminding personnel to pay attention. 4. If neither is abnormal, the arbitration result is "normal", and the system records and continues to monitor.

[0083] For example, when the conclusions of two engines conflict, the present invention can make the final and safest decision through the following process, defining a clear decision logic tree.

[0084] 1. First priority (safety blocking): As long as the global rule engine issues a high-risk alarm (such as "triggering under load"), regardless of the state machine result, the arbitrator will immediately issue the highest level "blocking" command and can lock related equipment.

[0085] 2. Second priority (process error correction): If there is no high risk to overall security, but the process status engine reports an incorrect sequence, the arbitrator will issue an "error" alarm to prompt the operator to correct the steps.

[0086] 3. Third priority (warning prompt): If there are only low to medium risk warnings from the global rule engine (such as "device temperature is too high"), then issue a "warning" prompt.

[0087] 4. Normal Pass: If neither is abnormal, the instruction is "Normal".

[0088] S104. Based on the intelligent monitoring instructions, perform intelligent monitoring of the substation switching operations.

[0089] In some embodiments, the present invention can execute tiered early warnings based on the final monitoring instructions and push alarm information containing handling suggestions to the monitoring terminal. At the same time, the event and handling results are self-learned and updated to the case library and model library to achieve continuous optimization of the system.

[0090] As one possible implementation, step S104 can be specifically implemented as steps S1041-S1044.

[0091] S1041. If the intelligent monitoring instruction is a device interlocking instruction, a hard contact interlocking signal or a soft message interlocking command is sent to the device control system corresponding to the current operation step to forcibly interrupt the switching operation being executed.

[0092] S1042. If the intelligent monitoring instruction is an error alarm instruction or an alarm prompt instruction, then the alarm information and handling suggestions are pushed to the monitoring terminal in the form of sound, light, and electricity.

[0093] S1043. Receive feedback information from operators regarding alarm information.

[0094] S1044. Link and store the multi-source sensor data, intelligent monitoring instructions, and feedback information of the entire process from start to finish of the current operation step to form a structured case.

[0095] This invention provides an intelligent monitoring method for substation switching operations. By real-time acquisition of multi-source sensor data, including SCADA signals, video data, temperature data, vibration data, and environmental data, and employing a global rule engine and a process status engine for parallel analysis, it can perform real-time, multi-dimensional cross-validation and in-depth analysis of switching operations from both macro-level safety rules and micro-level operational processes, improving the comprehensiveness and accuracy of risk identification. Subsequently, based on the principle of safety priority, strategy fusion is performed to generate intelligent monitoring instructions, including tiered early warning and equipment interlocking, enabling differentiated and precise response measures for different levels of risk. This invention solves the safety risks associated with manual switching operations by constructing an intelligent monitoring process integrating real-time perception, intelligent analysis, strategy decision-making, and precise execution, improving the safety and intelligence level of substation switching operations, and effectively preventing operational risks caused by human error or monitoring lag.

[0096] Optionally, the intelligent monitoring method for substation switching operations provided in this embodiment of the invention further includes steps S201-S204 after step S104.

[0097] S201. Based on the structured cases, divide them to determine the confirmed valid alarm cases, system false alarm cases, and newly added valid exception handling procedures.

[0098] S202. For confirmed valid alarm cases, increase the weight or confidence of the rules corresponding to the valid alarm cases.

[0099] S203. For false alarm cases in the system, correct the rule triggering conditions corresponding to the false alarm cases in the system.

[0100] S204. For newly added and effective exception handling procedures, generate new rules and store them in the expert knowledge base to optimize the expert knowledge base.

[0101] In this way, the present invention stores each anomaly and the finally confirmed effective handling solution as a new case in the "historical case library". The confidence level of the rule engine and the transition conditions of the state machine are fine-tuned and optimized periodically using this new data, making the system "smarter" with use.

[0102] This invention achieves comprehensive and in-depth intelligent monitoring. By integrating multi-dimensional information such as SCADA electrical quantities, video images, equipment mechanical status, and personnel behavior, it constructs a three-dimensional perception system, overcoming the limitations of traditional single-system monitoring.

[0103] This invention enhances the proactive early warning and real-time intervention capabilities of monitoring systems. The hybrid matching strategy adopted in this invention can discover complex, cross-device global security risks through the improved Rete algorithm, and can strictly ensure the correctness of the operation sequence through the state machine, thus realizing the leap from passive alarm to proactive early warning, and from post-analysis to in-process intervention.

[0104] This invention constructs a closed-loop control and self-evolution mechanism. The system can not only detect problems and issue alarms, but also provide handling suggestions and store the processed results as new knowledge. Through machine learning, the rule base and model are continuously optimized, making the system more and more intelligent with use.

[0105] This invention significantly enhances security and reliability. The dual-engine parallel analysis and central arbitration architecture provides redundant judgments, forming a defense-in-depth system. Even if one engine fails, the other engine can still provide effective protection, greatly reducing the risk of misoperation and missed judgments.

[0106] Optionally, the intelligent monitoring method for substation switching operations provided in this embodiment of the invention further includes steps S301-S303 before step S102.

[0107] S301. Based on the safety regulations and operational experience of substations, establish an expert knowledge base to prevent errors.

[0108] S302. Based on the expert knowledge base, the Rete network is compiled.

[0109] In some embodiments, the Rete network includes a root node, type nodes, Alpha nodes, Beta nodes, and terminal nodes. Specifically, the conditional portion of the error prevention rule is decomposed into independent modes. The Alpha node stores the single-condition mapping relationship between the independent modes of the error prevention rule and working memory elements. The Beta node stores the association logic of different independent modes of the error prevention rule, as well as the multi-condition mapping relationship between different independent modes and working memory elements. The terminal node binds the rule conclusion portion of the error prevention rule.

[0110] S303. Construct a time-series context buffer and establish an association between the time-series context buffer and the Beta node of the Rete network. The association is used to provide query support for historical signal data for the multi-condition matching.

[0111] Thus, this invention, by pre-building an expert knowledge base and compiling it into a Rete network, systematizes and structures the dispersed anti-misoperation rules, providing a reliable basis for the rule engine's judgment. This invention, by constructing a temporal context cache and associating it with Beta nodes, enables rule matching to understand the temporal context of operations, accurately identifying complex violations that depend on historical states, such as "closing and reconnecting a disconnect switch under load." This fundamentally solves the deficiency of traditional rule engines that can only judge instantaneous states, greatly improving the depth and accuracy of global security assessment.

[0112] Optionally, the intelligent monitoring method for substation switching operations provided in this embodiment of the invention further includes steps S401-S403 before step S102.

[0113] S401. Construct a standard operation ticket library based on the audited standardized switching operation procedure sequence.

[0114] S402. Based on the standard operation ticket library, pre-compile state machine templates for various operation tickets.

[0115] In some embodiments, the state machine template defines various operation ticket state sequences and transition conditions between states; wherein each state in the state sequence corresponds to an operation step in the operation ticket, and the transition condition is the expected device signal that should be generated after the operation step is successfully executed.

[0116] S403. Based on the state machine templates of various operation tickets, determine the embedded state machine.

[0117] Thus, by establishing a standard operation ticket library and pre-compiling state machine templates, this invention transforms standardized operation procedures into a strictly logical model that can be executed by machines. This enables the system to instantiate a monitoring model with a clear state sequence and transition conditions for each actual operation, thereby achieving rigid constraints and automated verification of the execution order of operation steps, effectively eliminating sequential errors such as skipping steps and missing steps, and ensuring the standardization and consistency of the switching operation process.

[0118] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0119] The following are device embodiments of the present invention. For details not described in detail, please refer to the corresponding method embodiments described above.

[0120] Figure 2 A schematic diagram of a substation switching operation intelligent monitoring device 500 provided in an embodiment of the present invention is shown. The intelligent monitoring device 500 includes a communication module 501 and a processing module 502.

[0121] The communication module 501 is used to collect multi-source sensor data from substation equipment in real time. The multi-source sensor data includes SCADA signals, video data, temperature data, vibration data, and environmental data.

[0122] The processing module 502 is used to perform parallel analysis based on the multi-source sensor data through a global rule engine and a process status engine to obtain rule analysis results and process analysis results; based on the rule analysis results and process analysis results, and according to the safety priority principle, perform strategy fusion to obtain intelligent monitoring instructions for switching operations; the intelligent monitoring instructions include hierarchical early warning instructions and equipment interlocking instructions; and perform intelligent monitoring of substation switching operations based on the intelligent monitoring instructions.

[0123] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. The electronic device 600 includes: a processor 601, a memory 602, and a computer program 603 stored in the memory 602 and executable on the processor 601. When the processor 601 executes the computer program 603, it implements the steps in the above-described method embodiments. Alternatively, when the processor 601 executes the computer program 603, it implements the functions of each module / unit in the above-described device embodiments.

[0124] For example, the computer program 603 may be divided into one or more modules / units, which are stored in the memory 602 and executed by the processor 601 to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program 603 in the electronic device 600.

[0125] The processor 601 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0126] The memory 602 can be an internal storage unit of the electronic device 600, such as a hard disk or memory of the electronic device 600. The memory 602 can also be an external storage device of the electronic device 600, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD) card, flash card, etc., equipped on the electronic device 600. Furthermore, the memory 602 can include both internal and external storage units of the electronic device 600. The memory 602 is used to store the computer program and other programs and data required by the terminal. The memory 602 can also be used to temporarily store data that has been output or will be output.

[0127] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A substation switching operation intelligent monitoring method, characterized in that, The method comprises the following steps: real-time acquisition of multi-source sensing data of substation equipment, wherein the multi-source sensing data comprises SCADA signals, video data, temperature data, vibration data and environmental data; parallel research and judgment based on the multi-source sensing data through a global rule engine and a process state engine, to obtain rule research results and process research results; strategy fusion based on the rule research results and the process research results according to a safety priority principle, to obtain intelligent monitoring instructions for switching operations; the intelligent monitoring instructions comprise hierarchical early warning instructions and equipment locking instructions; intelligent monitoring of substation switching operations based on the intelligent monitoring instructions.

2. The substation switching operation intelligent monitoring method according to claim 1, characterized in that, The parallel research and judgment based on the multi-source sensing data through the global rule engine and the process state engine to obtain the rule research results and the process research results comprises: rule matching based on the multi-source sensing data and an improved Rete algorithm, to obtain the rule research results; state monitoring of operation processes based on the multi-source sensing data and an embedded state machine, to obtain the process research results.

3. The method of substation switching operation intelligent monitoring according to claim 2, characterized in that, The rule matching based on the multi-source sensing data and the improved Rete algorithm to obtain the rule research results comprises: encapsulation of the multi-source sensing data into working memory elements; the working memory elements are standardized fact objects corresponding to anti-misoperation rules; input of the working memory elements into a pre-compiled Rete network, filtering through root nodes and type nodes of the Rete network, and then distribution to Alpha nodes for single-condition matching, to obtain working memory elements with successful matching; multi-condition and time sequence logic association matching between the working memory elements with successful matching and historical signal data stored in a time sequence context buffer in Beta nodes of the Rete network, to determine matching results; the matching results comprise successful matching or failed matching, and a corresponding terminal node in case of successful matching; if the matching result is successful matching, a rule of the terminal node is activated, to generate the rule research results, which are used to represent whether there is a risk of violating global safety rules in current operations.

4. The method of substation switching operation intelligent monitoring according to claim 3, characterized in that, Before the parallel research and judgment based on the multi-source sensing data through the global rule engine and the process state engine to obtain the rule research results and the process research results, the method further comprises the following steps: construction of an expert knowledge base based on anti-misoperation rules formed according to substation safety regulations and operation experience; compilation of the Rete network based on the expert knowledge base; the Rete network comprises root nodes, type nodes, Alpha nodes, Beta nodes and terminal nodes; wherein, condition parts of the anti-misoperation rules are decomposed into independent modes, single-condition mapping relationships between the independent modes of the anti-misoperation rules and working memory elements are stored in the Alpha nodes, associated logics of different independent modes of the anti-misoperation rules and multi-condition mapping relationships between different independent modes and working memory elements are stored in the Beta nodes, and rule conclusion parts of the anti-misoperation rules are bound in the terminal nodes. A timing context buffer is constructed, and an association between the timing context buffer and a Beta node of the Rete network is established, the association being used to provide query support for the historical signal data of the multi-condition matching.

5. The method of substation switching operation intelligent monitoring according to claim 2, characterized in that, The operation flow is monitored based on the multi-source sensing data and the embedded state machine, and a flow analysis result is obtained, including: Based on the multi-source sensing data, a currently executed standard operation order and a current operation step are determined; An embedded state machine is instantiated based on the currently executed standard operation order and the current operation step; a state of the embedded state machine corresponds to the current operation step, and a state transition condition of the embedded state machine is triggered by an expected real-time signal of the current operation step; The multi-source sensing data is compared with the state transition condition of the embedded state machine to determine a comparison result; If the comparison result is consistent with the state transition condition, the embedded state machine is transferred to a next state; If the comparison result is inconsistent with the state transition condition, the flow analysis result is generated; the flow analysis result includes a flow sequence error alarm.

6. The method of intelligent monitoring of substation switching operation according to claim 5, characterized in that, Before the rule analysis result and the flow analysis result are obtained based on the multi-source sensing data by using the global rule engine and the flow state engine, the following steps are further included: A standard operation order library is constructed based on an audited standardized switching operation step sequence; State machine templates of various operation orders are pre-compiled based on the standard operation order library; the state machine templates define state sequences of various operation orders and transition conditions between the states; each state in the state sequence corresponds to an operation step in the operation order, and the transition condition is an expected device signal that should be generated after the operation step is successfully executed; The embedded state machine is determined based on the state machine templates of various operation orders.

7. The method of substation switching operation intelligent monitoring according to claim 1, characterized in that, Based on the rule analysis result and the flow analysis result, policy fusion is performed according to a safety priority principle to obtain an intelligent monitoring instruction for switching operation, including: It is determined whether the rule analysis result includes a high-risk alarm; the high-risk alarm is used to indicate a rule violation operation that directly leads to device damage or personal accidents; If the rule analysis result includes the high-risk alarm, it is determined that the intelligent monitoring instruction is a highest-level device locking instruction; If the rule analysis result does not include the high-risk alarm, the flow analysis result is judged; If the flow analysis result includes a flow sequence error alarm, it is determined that the intelligent monitoring instruction is an error alarm instruction, which is used to indicate an abnormal operation sequence; If the rule analysis result does not include the flow sequence error alarm and includes a medium-low risk alarm, it is determined that the intelligent monitoring instruction is an alarm prompt instruction, which is used to remind attention to non-urgent abnormalities; If the flow analysis result is normal, it is determined that the intelligent monitoring instruction is a normal monitoring instruction.

8. The method of substation switching operation intelligent monitoring according to any one of claims 1 to 7, characterized in that, Based on the intelligent monitoring instruction, intelligent monitoring is performed on the switching operation of the substation, including: If the intelligent monitoring instruction is a device lock instruction, a hard contact lock signal or a soft message lock command is sent to a device control system corresponding to the current operation step, and an ongoing switching operation is forcibly interrupted; If the intelligent monitoring instruction is an error alarm instruction or an alarm prompt instruction, alarm information and disposal suggestions are pushed to a monitoring terminal in the form of sound, light and electricity; Feedback information of the operation personnel on the alarm information is received; Full-process multi-source sensing data, intelligent monitoring instructions and feedback information of the operation personnel from the beginning to the end of the current operation step are associated and stored to form a structured case.

9. The method of substation switching operation intelligent monitoring according to any one of claims 1 to 7, characterized in that, After the intelligent monitoring of the substation switching operation based on the intelligent monitoring instruction, the method further includes: Based on the structured case, the method further includes: For the confirmed effective alarm case, the weight or confidence of the effective alarm case corresponding rule is improved; For the system false alarm case, the rule triggering condition corresponding to the system false alarm case is corrected; For the newly added effective abnormal disposal process, a new rule is generated and stored in the expert knowledge base to optimize the expert knowledge base.

10. A substation switching operation intelligent monitoring system, characterized in that, The intelligent monitoring system includes an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor is used to call and run the computer program stored in the memory to execute the method in any one of claims 1 to 9.

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