Power supply line control method, device, equipment, medium and program for power system

Abstract

The invention relates to the technical field of artificial intelligence, in particular to a power supply line control method and device of a power system, equipment, a medium and a program, and the method comprises the steps: obtaining operation state parameters of a main power supply line in the power system; determining a fault type and a fault position of the main supply line according to the operation state parameters; if the fault type is a first type of fault, screening an optimal standby line associated with the main power supply line, and executing a corresponding power supply switching action according to the optimal standby line and the fault position; and if the fault type is a second type of fault, executing a corresponding target operation according to the recovery state of the main power supply line within the delay protection duration. Therefore, the problems that in the related technology, the standby circuit switching technology mostly depends on fixed voltage / current detection logic, or simple interlocking judgment is achieved through a programmable logic controller, the risks of misoperation, operation refusal and the like exist, the multivariable combination situation is difficult to process, and the power supply safety margin cannot be dynamically evaluated are solved.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence technology, and in particular to a method, device, equipment, medium and program for controlling power supply lines of an electric power system. Background Art

[0002] Critical power supply loads such as hospitals, rail transit control rooms, and communication hubs require extremely high power continuity and are typically supplied by two or more power sources. If the primary power supply fails, switching to the backup line must be performed within a very short time to prevent equipment power outages, data loss, and potential safety incidents.

[0003] In related technologies, traditional backup line switching technologies mostly rely on fixed voltage / current detection logic or use PLC to implement simple interlocking judgment. Such methods have certain limitations, such as the risks of false operation and refusal to operate, and are difficult to handle multi-variable combinations and cannot dynamically evaluate the power supply safety margin. Summary of the Invention

[0004] The present application provides a power supply line control method, device, equipment, medium and program for an electric power system to solve the problems in related technologies such as backup line switching technology relying on fixed voltage / current detection logic or using programmable logic controllers to implement simple interlocking judgment, which have risks such as false operation and refusal to operate, difficulty in handling multi-variable combinations, and inability to dynamically evaluate power supply safety margins.

[0005] A first aspect embodiment of the present application provides a power supply line control method for an electric power system, comprising the following steps: obtaining operating status parameters of a main power supply line in the electric power system; determining a fault type and a fault location of the main power supply line based on the operating status parameters; if the fault type is a first type fault, screening an optimal backup line associated with the main power supply line, and performing a corresponding power supply switching action based on the optimal backup line and the fault location; if the fault type is a second type fault, performing a corresponding target operation based on the recovery status of the main power supply line within a delayed protection period.

[0006] Optionally, the screening of the best backup path associated with the main power supply line includes: identifying all available backup lines associated with the main power supply line; scoring the parameter indicators of each available backup line using a target algorithm to generate a corresponding scoring result; and screening the best backup path according to priority based on the scoring result.

[0007] Optionally, before executing the corresponding power supply switching action according to the optimal backup line and the fault location, it includes: calculating the importance level of the power supply point corresponding to the fault location of the main supply line according to the operating status parameters; if the importance level is greater than a preset level threshold, executing the corresponding power supply switching action according to the optimal backup line, otherwise the power supply switching action is not executed, and a warning message is generated to the control center according to the fault type and fault location.

[0008] Optionally, after executing the corresponding power supply switching action according to the optimal backup line, it includes: identifying the operating status parameters after switching to the optimal backup line; determining the power supply switching status according to the operating status parameters; if the power supply switching status is a failure or an abnormal state, switching to the backup line of the next priority.

[0009] Optionally, within the delayed protection period, the corresponding target operation is performed according to the recovery status of the main power supply line, including: if the recovery status of the main power supply line has not returned to normal within the delayed protection period, then the corresponding power supply switching action is performed according to the optimal backup line and the fault location.

[0010] Optionally, determining the fault type and fault location of the main supply line based on the operating status parameters includes: inputting the operating status parameters into a target neural network model, and the target neural network model outputs the fault type and fault location of the main supply line, wherein the target neural network model includes a convolutional neural network and a self-attention mechanism layer, the convolutional neural network is used to extract fault features from the operating status parameters, and the self-attention mechanism layer is used to generate a fault type according to the fault feature weights, and generate a fault location according to the global dependency of the fault features.

[0011] The second aspect of the present application provides a power supply line control device for an electric power system, including: an acquisition module for acquiring operating status parameters of a main power supply line in the electric power system; a processing module for determining the fault type and fault location of the main power supply line based on the operating status parameters; a switching module for screening the best backup line associated with the main power supply line if the fault type is a permanent fault, and performing a corresponding power supply switching action based on the best backup line and the fault location; and an execution module for performing a corresponding target operation based on the recovery status of the main power supply line within a delayed protection period if the fault type is a temporary fault.

[0012] An embodiment of the third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to execute the power supply line control method of the power system as described in the above embodiment.

[0013] A fourth aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to perform the power supply line control method of the power system as described in the above embodiment.

[0014] The fifth aspect of the present application provides a computer program product, including a computer program or instructions, which, when executed, implements the power supply line control method of the power system as described in the above embodiment.

[0015] Therefore, this application has at least the following beneficial effects:

[0016] The embodiment of the present application monitors the status parameters of the main power supply line in real time, so as to promptly discover potential problems or existing faults and ensure continuous power supply to important load points. By using artificial intelligence algorithms to analyze the collected data, it is possible to more accurately distinguish different types of faults, so as to adopt the most appropriate response strategy. For the first type of fault, the system will automatically evaluate all available backup lines and select the best backup line based on a multi-factor scoring mechanism to ensure stability and safety during the switching process; for the second type of fault, a reasonable delay protection time is set to allow the system to attempt self-recovery, avoid unnecessary switching operations, and reduce equipment wear and maintenance costs.

[0017] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0019] Figure 1 This is a flow chart of a power supply line control method for a power system provided according to an embodiment of the present application;

[0020] Figure 2 A flowchart of a work flow according to an embodiment of the present application is provided;

[0021] Figure 3 This is an example diagram of a power supply line control device for a power system provided according to an embodiment of the present application;

[0022] Figure 4 A schematic diagram of the overall structure of a system according to an embodiment of the present application;

[0023] Figure 5 A schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0024] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0025] The following describes a power supply line control method, device, vehicle, storage medium, and program for a power system according to an embodiment of the present application with reference to the accompanying drawings.

[0026] Specifically, Figure 1 A flowchart of a power supply line control method for a power system provided in an embodiment of the present application.

[0027] like Figure 1 As shown, the power supply line control method of the power system includes the following steps:

[0028] In step S101 , operating status parameters of a main power supply line in a power system are obtained.

[0029] It is understandable that the embodiments of the present application can obtain the operating status parameters of the main power supply line in the power system, so as to subsequently determine the fault type and fault location of the main power supply line based on the operating status parameters.

[0030] It should be noted that the operating status parameters of the main power supply line include voltage, current, frequency, active power, load change rate, switch status and other electrical parameters, without specific limitation.

[0031] In step S102, the fault type and fault location of the main power supply line are determined according to the operating status parameters.

[0032] It can be understood that the embodiments of the present application can quickly identify potential fault signs by real-time analysis of operating status parameters such as voltage, current, and frequency, accurately determine the fault type and locate the specific location of the fault, improve response speed, enhance system stability, and thus improve user experience.

[0033] In an embodiment of the present application, the fault type and fault location of the main supply line are determined according to the operating status parameters, including: inputting the operating status parameters into a target neural network model, and the target neural network model outputting the fault type and fault location of the main supply line, wherein the target neural network model includes a convolutional neural network and a self-attention mechanism layer, the convolutional neural network is used to extract fault features from the operating status parameters, and the self-attention mechanism layer is used to generate a fault type according to the fault feature weight, and generate a fault location according to the global dependency of the fault features.

[0034] It can be understood that the embodiments of the present application utilize the self-attention mechanism layer to better understand the global dependencies between fault features, thereby accurately determining the fault location and fault type, improving fault detection accuracy, reducing the misjudgment rate and increasing the response speed.

[0035] It should be noted that a state recognition framework is constructed based on the convolutional neural network and Transformer fusion model, and the prediction and diagnosis of potential faults, power quality degradation and impact characteristics of the main supply line are achieved through training the model.

[0036] Specifically, this application uses convolutional neural networks (CNNs), support vector machines (SVMs), or random forest algorithms to build fault identification models. Model training is based on historical substation fault samples and real-time simulation data. Real-time current waveform eigenvalues ​​are used as input vectors, and voltage disturbance patterns and circuit breaker response signals are combined for joint modeling.

[0037] In step S103, if the fault type is a first type fault, the best backup line associated with the main power supply line is selected, and a corresponding power supply switching action is performed according to the best backup line and the fault location.

[0038] It can be understood that the embodiments of the present application can screen the best backup line associated with the main power supply line when the fault type is a first type fault, and perform corresponding power supply switching actions according to the best backup line and the fault location to achieve disturbance-free switching. Selecting the optimal backup line can maximize resource utilization while ensuring the stability and security of the system. The automated process reduces the need for human intervention, improves the speed and accuracy of the entire switching process, and reduces the risk of misoperation.

[0039] It should be noted that the first type of fault is a permanent fault, and the switching verification uses the frequency fluctuation, voltage recovery time, and load current change within the "10-second window before and after switching" as the switching success judgment criteria.

[0040] Permanent faults are those that, once they occur, cannot be restored through simple reclosing or other temporary measures. These faults typically involve hardware damage or irreversible problems in the power system, requiring actual repair or replacement of equipment to restore normal operation.

[0041] Specifically, a permanent fault will not resolve on its own within a short period of time (e.g., seconds to minutes) or be automatically restored through automatic reclosing. Common causes include, but are not limited to, broken wires, burnt transformers, ground faults caused by damaged cable insulation, and switchgear failures. To resolve a permanent fault, a technician must be dispatched to the site for inspection and repair, which may involve replacing damaged components and repairing line connections.

[0042] In an embodiment of the present application, screening the best backup path associated with the main power supply line includes: identifying all available backup lines associated with the main power supply line; scoring the parameter indicators of each available backup line using a target algorithm to generate a corresponding scoring result; and screening the best backup path according to the priority based on the scoring result.

[0043] It can be understood that the embodiment of the present application can use a target algorithm to quantitatively score the key parameters of each available backup line, and sort them by priority based on the scoring results, ensuring that the optimal backup path can be quickly found even in a complex power grid environment, so as to accurately match the best backup path, maximize resource utilization, enhance the adaptability and flexibility of the overall system, and improve the reliability and intelligence level of the power system.

[0044] It should be noted that this application can score each alternative line through a multi-factor weighted scoring method, and the weight factors include but are not limited to: load margin, voltage compliance, response speed, historical reliability and failure rate; the backup line evaluation includes the line no-load voltage, historical tripping times, terminal load stability, etc. as scoring parameters.

[0045] In an embodiment of the present application, before executing the corresponding power supply switching action according to the optimal backup line and the fault location, it includes: calculating the importance level of the power supply point corresponding to the fault location of the main supply line according to the operating status parameters; if the importance level is greater than the preset level threshold, executing the corresponding power supply switching action according to the optimal backup line, otherwise the power supply switching action is not executed, and a warning message is generated to the control center according to the fault type and fault location.

[0046] Among them, the preset level threshold can be set according to actual needs without specific limitation.

[0047] It is understandable that different power supply points in the embodiments of the present application have different sensitivities to power outages. Through the importance level evaluation mechanism, on-demand response can be achieved, resource waste or insufficient response can be avoided, and unnecessary initiation of backup power switching processes at non-critical load points can be avoided. Limited backup resources can be reserved for more urgent and more important scenarios, and power supply resource scheduling can be optimized. While ensuring continuous power supply to critical loads, unnecessary switching operations can be reduced, equipment losses and operation and maintenance costs can be reduced, and the safety and economy of the system can be enhanced.

[0048] It should be noted that the power supply point importance assessment module makes weighted judgments based on different load levels and key objects (such as hospitals, airports, and data centers) in the preset database. The assessment results are divided into three levels: core, important, and general.

[0049] In an embodiment of the present application, after executing the corresponding power supply switching action according to the best backup line, it includes: identifying the operating status parameters after switching to the best backup line; determining the power supply switching state according to the operating status parameters; if the power supply switching state is a failure or an abnormal state, switching to the backup line of the next priority.

[0050] It is understandable that after switching to the backup line, the embodiment of the present application must verify whether stable power supply is truly achieved. If the switching fails or an abnormality occurs after the switching, the system can quickly identify and take remedial measures to prevent the critical load from losing power. It no longer relies on a single backup line, but instead builds a multi-level switching strategy to improve the overall power supply security level.

[0051] It should be noted that the switching decision execution has the functions of timeout detection and redundant channel judgment. When the first backup line fails to switch, it will automatically switch to the second priority line for re-switching and generate an alarm record.

[0052] In step S104 , if the fault type is a second type fault, a corresponding target operation is performed according to the recovery state of the main power supply line within the delay protection time.

[0053] Among them, the delay protection duration can be set according to actual needs and is not specifically limited.

[0054] It can be understood that when the fault type is a second type fault, the embodiment of the present application performs the corresponding target operation according to the recovery status of the main power supply line within the delayed protection period. By setting the delayed protection period, unnecessary backup line switching caused by short-term disturbances can be avoided, equipment wear and maintenance costs can be reduced, and system stability can be improved.

[0055] It should be noted that the second type of fault is a temporary fault, also known as a transient fault or a recoverable fault. These faults occur briefly but can be self-recovered or restored to normal operation through simple repair measures (such as automatic reclosing). These faults typically do not have a long-term impact on the power grid and do not require complex repair operations.

[0056] Specifically, many temporary faults can recover on their own without human intervention, such as instantaneous voltage fluctuations caused by lightning strikes and bird short-circuits. After the interference source disappears, the power grid can return to normal. Although it may cause momentary power outages or deterioration in power quality, it usually does not cause long-term power outages.

[0057] In an embodiment of the present application, during the delayed protection period, the corresponding target operation is performed according to the recovery status of the main power supply line, including: if the recovery status of the main power supply line has not returned to normal within the delayed protection period, the corresponding power supply switching action is performed according to the optimal backup line and the fault location.

[0058] It can be understood that the embodiments of the present application can give the main power supply line a chance to recover by itself by setting a delayed protection time, reduce unnecessary backup power switching triggered by short-term disturbances, and thus maintain the overall stability of the power grid. If the main power supply line fails to return to normal within the delayed protection time, it will quickly switch to the best backup line to ensure that key load points will not be affected by long-term power outages, improve system stability, and enhance fault tolerance.

[0059] For example, suppose a critical operating room in a hospital experiences a temporary voltage dip:

[0060] Step 1: The system detects a voltage drop and identifies it as a second type of fault (temporary fault), immediately activating a delayed protection mechanism and setting a certain time (e.g., a few seconds) to observe whether the main power supply line can recover on its own.

[0061] Step 2: Within the delay protection period, if the voltage returns to normal, the system remains in its original state and continues to be powered by the main power supply line, avoiding unnecessary backup switching.

[0062] Step 3: If the voltage does not return to normal within the delay protection period, the system will quickly switch to the backup power supply based on the previously evaluated best backup line information to ensure the continuous power supply to the operating room is not affected.

[0063] According to the power supply line control method of the power system proposed in the embodiment of the present application, by real-time monitoring of the status parameters of the main power supply line, potential problems or existing faults can be discovered in a timely manner to ensure continuous power supply to important load points. By using artificial intelligence algorithms to analyze the collected data, different types of faults can be distinguished more accurately, so as to adopt the most appropriate response strategy. For the first type of fault, the system will automatically evaluate all available backup lines and select the best backup line based on a multi-factor scoring mechanism to ensure stability and safety during the switching process; for the second type of fault, a reasonable delay protection time is set to allow the system to attempt self-recovery, avoid unnecessary switching operations, and reduce equipment wear and maintenance costs.

[0064] The following will be combined Figure 2The power supply line control method of the power system of the present application is described in detail. All steps of the present application can be deployed in the dispatching automation system, protection terminal or substation background server, and synchronized with the SCADA (Supervisory Control and Data Acquisition) system to achieve synchronization. The details are as follows:

[0065] Step 1: Fault identification and power supply point importance determination

[0066] The monitoring system continuously collects the operating status parameters of the main power supply line (such as current, voltage, frequency, etc.); the artificial intelligence model embedded in the system uses fault identification algorithms (such as convolutional neural networks (CNN), support vector machines (SVM), etc.) to perform real-time analysis of the collected parameters; once an abnormal fluctuation is detected, the system immediately makes a preliminary determination of the fault type and its possible location; the system automatically determines whether it is an important power supply point based on the historical load data of the power supply point, the level of access equipment, the importance rating and other information.

[0067] Step 2: Intelligent identification of fault attributes

[0068] The artificial intelligence module further analyzes the fault waveform and time characteristics, and uses the trained classification model to classify the fault attributes (such as permanent fault or temporary fault); for temporary faults, the system sets time delay protection and waits for the reclosing processing results; if it is judged to be a permanent fault, the switching plan preparation process is immediately started.

[0069] Step 3: Backup line status assessment

[0070] The system retrieves data such as the real-time operating status, load capacity, and protection configuration of alternative lines; the artificial intelligence model conducts multi-dimensional assessments (such as power supply path reliability, voltage stability, current operating margin, etc.); and prioritizes each alternative path according to a preset algorithm to determine the optimal backup switching plan.

[0071] Step 4: Switching between decision making and execution

[0072] If the evaluation results meet the switching conditions, the system generates a switching instruction and sends a remote control command to the dispatching system or protection device to block the main line and put the backup line into operation. The switching process is fully automatic closed-loop control and the entire process data is recorded.

[0073] Step 5: Status Verification and Alarm After Switching

[0074] The system performs stability analysis and confirmation on the power supply status after switching; if the switching is successful, it enters the new operating state and issues a "fault switching successful" signal; if the switching fails, the system will enter the fault-tolerant processing process, such as skipping switching, alarm reporting, and manual intervention prompts.

[0075] Step 6: Record the entire process and retrain the model

[0076] The key data and results of the entire fault detection, analysis, judgment, switching, and verification process will be automatically recorded; the recorded data will be used for the continuous training and optimization of subsequent artificial intelligence models; the artificial intelligence model weights can be updated remotely and regularly to improve recognition and decision-making accuracy.

[0077] Example 1:

[0078] The system is deployed within the main substation of a large hospital. The primary power supply is drawn from a 10kV municipal power line, with backup lines consisting of an emergency diesel generator and a regional backup power grid. The data acquisition module monitors the three-phase voltage, current, and power quality factors of the main power supply circuit in real time. When the AI-assisted judgment module identifies a main circuit voltage fluctuation exceeding 5% for 300ms, combined with current load trends, it determines a voltage sag and predicts a power outage within three seconds.

[0079] At this point, the backup path assessment module estimates that the diesel generator will take 8 seconds to start, while the grid backup path can be activated within 1 second. Therefore, the intelligent switching execution module executes the grid backup activation logic. After a successful switchover, the event log is stored in the local model training library, and the AI ​​judgment weights are updated.

[0080] Example 2:

[0081] The system, deployed in the data center's substation, utilizes a dual-busbar structure with three incoming lines. When a fault occurs on main power supply A, the AI ​​model identifies fault characteristics (waveform distortion, zero-sequence current fluctuations, and power dips) within 500ms. The switching module quickly switches power to bus B, preventing any load loss. The self-learning module feeds pre- and post-fault waveform characteristics into the model for backtracking, enhancing pre-fault detection capabilities.

[0082] In summary, this application has the following beneficial effects:

[0083] (1) Fault type determination mechanism integrating artificial intelligence (AI) intelligent identification: AI technologies (such as convolutional neural networks (CNN), support vector machines (SVM), and random forests) are embedded in the power backup switching process to achieve multi-dimensional feature extraction and classification of fault characteristics (such as short-circuit current waveforms, frequency anomalies, and voltage drops). Different from the traditional fixed threshold judgment method, this method can effectively distinguish between transient and permanent faults, improve the accuracy and rationality of switching, and avoid erroneous switching or switching rejection.

[0084] (2) Introducing a dynamic evaluation mechanism for the importance of power supply points: A scenario-oriented "power supply point importance level model" is proposed. According to multi-dimensional parameters such as the load level of the power supply point, the user type (such as airports, hospitals, data centers), and historical operation records, the "core", "important", and "general" levels are dynamically assigned to guide whether to start artificial intelligence-assisted switching decisions, thus realizing for the first time "importance-based classification" intelligent power supply guarantee.

[0085] (3) Multi-factor scoring and ranking mechanism for backup lines: An innovative backup line evaluation model has been constructed, which uses weighted scoring and ranking based on factors such as power supply reliability, voltage level matching, current operating status, response speed, and historical failure rate. The system can adaptively select the optimal path to achieve accurate, rapid, and sustainable backup line switching, significantly improving the switching success rate and stability.

[0086] (4) Introducing a "self-learning and feedback closed-loop" mechanism into the switching strategy: By introducing a state feedback and AI model self-learning mechanism, the system collects and analyzes the operational data of each successful and failed switch and uses it to optimize the AI ​​model parameters, achieving a system that becomes more accurate with use. This mechanism has the ability to continuously evolve, addressing the shortcomings of traditional expert rule systems, which are "rigid, slow, and poorly adaptable."

[0087] (5) Multi-module decoupling combined architecture design: adopting a modular structure, each module including fault detection, assessment and judgment, artificial intelligence identification, backup route selection, switching execution, communication interface and other functional units can be independently deployed and interconnected, supporting flexible integration into existing dispatching automation systems, protection terminals, background control platforms, etc., with good compatibility and engineering feasibility.

[0088] (6) Switching fault tolerance with redundant safety mechanism: The system has built-in switching failure detection and multi-path fallback mechanism. After the first switching failure, it can automatically select the suboptimal path to continue switching and report the fault information to avoid a complete power outage caused by a single failure, thereby enhancing the power supply guarantee capability of important loads.

[0089] (7) Realize the integrated deployment of "artificial intelligence + power backup switching": The overall architecture realizes a complete closed loop from perception-analysis-evaluation-decision-making-control, and truly applies artificial intelligence technology to the intelligent backup switching of power systems, with significant advantages of scalability, replicability and high adaptability.

[0090] Next, a power supply line control device for a power system proposed according to an embodiment of the present application will be described with reference to the accompanying drawings.

[0091] Figure 3 It is a block diagram of a power supply line control device of an electric power system according to an embodiment of the present application.

[0092] like Figure 3 As shown, the power supply line control device 10 of the power system includes: an acquisition module 100 , a processing module 200 , a switching module 300 and an execution module 400 .

[0093] Among them, the acquisition module 100 is used to obtain the operating status parameters of the main power supply line in the power system; the processing module 200 is used to determine the fault type and fault location of the main power supply line based on the operating status parameters; the switching module 300 is used to screen the best backup line associated with the main power supply line if the fault type is a permanent fault, and perform the corresponding power supply switching action according to the best backup line and the fault location; the execution module 400 is used to perform the corresponding target operation according to the recovery status of the main power supply line within the delay protection time if the fault type is a temporary fault.

[0094] Specifically, if Figure 4 As shown in FIG, the artificial intelligence-assisted intelligent backup switching system includes:

[0095] (1) Data acquisition module: including primary equipment measurement devices, communication interfaces, data gateways, etc., which collect parameters such as voltage, current, frequency, active power, load change rate, etc. of the main supply and backup supply circuits in real time and upload them to the artificial intelligence judgment module.

[0096] (2) The fault detection module is used to preliminarily determine whether a fault has occurred based on the real-time acquisition of the operating status parameters of the main power supply line, including voltage, current, frequency, switch status, etc.

[0097] (3) The power supply point importance assessment module is used to dynamically assess the importance level of the power supply point based on the load level, power supply type, power supply object and power supply sensitivity of the power supply point, and output the importance assessment result.

[0098] (4) Artificial Intelligence-Assisted Judgment Module: This module builds a state recognition framework based on a convolutional neural network (CNN) and Transformer fusion model. This module uses a training model to predict and diagnose potential faults, power quality degradation, and impact characteristics of the main power supply line. It uses machine learning or deep learning models to classify faults based on historical fault data and online real-time data, determine whether the fault type is permanent or temporary, and assist in the decision-making process of whether to perform a switchover.

[0099] (5) Backup path evaluation module: Based on the topology, power on / off status, short-circuit capacity, cable length, maximum load capacity and other indicators, combined with the current load conditions, it outputs the priority matrix of the backup power supply path; it is used to obtain the status of all backup lines associated with the main power supply line, evaluate the availability, load capacity, voltage level, switching success rate, etc. of each line, and form a candidate backup path list.

[0100] (6) Intelligent switching execution module: automatically generates switching instructions based on the evaluation results, and controls the switch action through the remote control device or PLC to execute the main disconnect and backup input logic to complete the "disturbance-free" switching. Specifically: when it is judged that the main power supply line fails and the importance of the power supply point reaches the set threshold, the optimal backup line switching operation is executed based on the artificial intelligence judgment result and the backup line evaluation result, and a switching command is issued to the protection device and circuit breaker.

[0101] (7) Communication interface module, used to realize high-speed data communication between this system and the dispatching master station, telecontrol device, and protection equipment, to ensure information synchronization and the issuance of control instructions.

[0102] (8) Experience-Based Self-Learning Module: This module traces the switching event results back to the model training, dynamically adjusts the model weights and parameters based on the reinforcement learning method, and improves the fault prediction and backup path optimization capabilities. It collects the system operation data after the switching to determine whether the switching is successful, and performs parameter callback and training optimization on the artificial intelligence model to improve the accuracy of subsequent judgments.

[0103] It should be noted that the above explanation of the embodiment of the power supply line control method of the power system is also applicable to the power supply line control device of the power system of this embodiment, and will not be repeated here.

[0104] According to the power supply line control device of the power system proposed in the embodiment of the present application, by real-time monitoring of the status parameters of the main power supply line, potential problems or existing faults can be discovered in a timely manner to ensure continuous power supply to important load points. By using artificial intelligence algorithms to analyze the collected data, different types of faults can be distinguished more accurately, so as to adopt the most appropriate response strategy. For the first type of fault, the system will automatically evaluate all available backup lines and select the best backup line based on a multi-factor scoring mechanism to ensure stability and safety during the switching process; for the second type of fault, a reasonable delay protection time is set to allow the system to attempt self-recovery, avoid unnecessary switching operations, and reduce equipment wear and maintenance costs.

[0105] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0106] Memory 501 , processor 502 , and computer programs stored in the memory 501 and executable on the processor 502 .

[0107] When the processor 502 executes the program, the power supply line control method of the power system provided in the above embodiment is implemented.

[0108] Furthermore, the electronic device further includes:

[0109] The communication interface 503 is used for communication between the memory 501 and the processor 502 .

[0110] The memory 501 is used to store computer programs that can be run on the processor 502 .

[0111] The memory 501 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0112] If the memory 501, the processor 502, and the communication interface 503 are implemented independently, the communication interface 503, the memory 501, and the processor 502 can be connected to each other via a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0113] Optionally, in a specific implementation, if the memory 501, the processor 502 and the communication interface 503 are integrated on a chip, the memory 501, the processor 502 and the communication interface 503 can communicate with each other through an internal interface.

[0114] The processor 502 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0115] An embodiment of the present application further provides a computer-readable storage medium having a computer program or instruction stored thereon. When the computer program or instruction is executed by a processor, the power supply line control method of the power system as described above is implemented.

[0116] An embodiment of the present application further provides a computer program product, including a computer program or instructions, which, when executed, implements the above power supply line control method for the power system.

[0117] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0118] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of technical features indicated. Thus, a feature specified as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of this application, "N" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0119] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing a custom logical function or process step, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed in a different order than shown or discussed, including performing functions in a substantially simultaneous manner or in a reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application pertain.

[0120] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiment, the N steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, it can be implemented using any one or a combination of the following technologies known in the art: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0121] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

Claims

1. A power supply line control method for an electric power system, characterized in that: The following steps are involved: Obtaining operating status parameters of the main power supply line in the power system; determining a fault type and a fault location of the main power supply line according to the operating status parameters; If the fault type is a first type fault, selecting the best backup line associated with the main power supply line, and performing a corresponding power supply switching action according to the best backup line and the fault location; If the fault type is a second type fault, a corresponding target operation is performed according to the recovery state of the main power supply line within the delay protection time.

2. The power supply line control method of the power system according to claim 1, characterized in that: The screening of the best backup path associated with the main power supply line includes: Identify all available backup lines associated with the main power supply line; Using the target algorithm to score the parameter indicators of each available backup line to generate corresponding scoring results; The best backup path is selected according to the priority based on the scoring result.

3. The power supply line control method of the power system according to claim 2, characterized in that: Before performing a corresponding power supply switching action according to the optimal backup line and the fault location, the method includes: Calculating the importance level of the power supply point corresponding to the fault location of the main power supply line according to the operating status parameters; If the importance level is greater than the preset level threshold, the corresponding power supply switching action is performed according to the optimal backup line; otherwise, the power supply switching action is not performed, and an alarm message is generated to the control center according to the fault type and fault location.

4. The power supply line control method of the power system according to claim 1, characterized in that: After performing the corresponding power supply switching action according to the optimal backup line, the method includes: Identify the operating status parameters after switching to the best backup line; determining a power supply switching state according to the operating state parameters; If the power supply switching state is a failure or an abnormal state, the power supply is switched to a backup line of the next priority.

5. The power supply line control method of the power system according to claim 1, characterized in that: The performing of a corresponding target operation according to the recovery state of the main power supply line within the delay protection time includes: If the recovery state of the main power supply line does not return to normal within the delayed protection time, a corresponding power supply switching action is performed according to the optimal backup line and the fault location.

6. The power supply line control method of the power system according to claim 1, characterized in that: Determining the fault type and fault location of the main power supply line according to the operating status parameters includes: The operating status parameters are input into a target neural network model, and the target neural network model outputs the fault type and fault location of the main supply line, wherein the target neural network model includes a convolutional neural network and a self-attention mechanism layer, the convolutional neural network is used to extract fault features from the operating status parameters, and the self-attention mechanism layer is used to generate a fault type according to the fault feature weights, and generate a fault location according to the global dependency of the fault features.

7. A power supply line control device for an electric power system, characterized in that: include: An acquisition module, used to obtain operating status parameters of the main power supply line in the power system; a processing module, configured to determine a fault type and a fault location of the main power supply line according to the operating status parameters; a switching module configured to select the best backup line associated with the main power supply line if the fault type is a permanent fault, and perform a corresponding power supply switching action according to the best backup line and the fault location; An execution module is used to execute a corresponding target operation according to the recovery state of the main power supply line within the delay protection time if the fault type is a temporary fault.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the power supply line control method for the power system according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the power supply line control method of the power system according to any one of claims 1 to 6.

10. A computer program product, characterized in that The method comprises a computer program, which, when executed by a processor, is used to implement the power supply line control method of the power system according to any one of claims 1 to 6.

Images