Safe operation measure generation method and system for power transformation secondary screen

Abstract

The invention relates to the technical field of information, and discloses a safety operation measure generation method and system for a power transformation secondary screen, and the method comprises the steps: collecting historical typical layout cases of all power transformation secondary screens in a transformer substation, and formulating an importance degree evaluation rule; the importance degree and the operation sequence of each power transformation secondary screen are determined through a rule reasoning algorithm and a case reasoning algorithm, a dynamically updated priority list is generated, real-time screen cabinet layout data are combined, a graphical human-computer interface is designed, the screen cabinet layout is displayed in a clear and visual mode, and when a target screen cabinet is selected through a human-computer interaction interface, the target screen cabinet can be selected through the human-computer interaction interface. The operation compliance is judged in real time by adopting a rule engine based on a decision-making tree, and then when the operation compliance is met, according to the operation history and the current selection, an important screen cabinet possibly operated in the next step is recommended by adopting a collaborative filtering algorithm, and a safe operation measure scheme is generated, so that the accuracy, the safety and the efficiency of the secondary screen cabinet operation scheme of the transformer substation are effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of information technology, and in particular to a method and system for generating safety operation measures for a secondary panel of a transformer substation. Background Art

[0002] In the method of generating safe operation measures for the secondary panel of a substation, how to achieve efficient interaction between the current staff and the secondary circuit system (hereinafter referred to as the secondary system) of the secondary panel of the substation that can control all substations is a key technical issue.

[0003] The traditional human-computer interaction method is to use keyboard and mouse for operation. However, in the special working environment of substations, current staff often need to frequently switch between different cabinets. Under this premise, using keyboard and mouse for selection operation is inefficient and prone to errors.

[0004] It can be seen that how to design a more intuitive and convenient human-computer interaction method to improve the work efficiency and accuracy of the substation secondary panel safety operation measures generation process has become a technical problem that technical personnel in this field need to solve urgently. Summary of the invention

[0005] The present invention provides a method and system for generating safety operation measures for a substation secondary panel, which solves the problem of how to design a more intuitive and convenient human-computer interaction mode to improve the work efficiency and accuracy of the process of generating safety operation measures for a substation secondary panel.

[0006] In order to solve the above technical problems, the first aspect of the present invention provides a method for generating safe operation measures for a substation secondary panel, which is applied to a secondary system connected to each substation secondary panel in a substation, and the method comprises: Obtaining real-time panel cabinet layout data of all substation secondary panels in the substation and historical typical panel cabinet layout cases of each substation secondary panel; Constructing the importance evaluation rules of each substation secondary panel, and combining them with the historical typical panel cabinet layout cases, determining the importance and operation sequence of each substation secondary panel through rule reasoning algorithm and case reasoning algorithm, and generating a panel cabinet priority operation list; Based on the real-time panel layout data and the panel priority operation list, and in combination with the screen size of the secondary system and the logical relationship and business process between the substation secondary panels, a human-computer interaction interface of the secondary system is constructed; In response to the target substation secondary panel selected by the current staff through the human-computer interaction interface, the attribute information of the target substation secondary panel is obtained to be input into the pre-built panel cabinet selection rule decision tree model for processing to obtain a compliance result; If the compliance result meets the preset rules, the target substation secondary panel is updated using a collaborative filtering algorithm based on the received historical operation data and current selection of the current staff member to generate a safe operation measure plan.

[0007] As one of the preferred solutions, the step of obtaining the real-time panel cabinet layout data of all substation secondary panels in the substation includes: Receiving the panel cabinet layout diagram transmitted by all substation secondary panels in the substation for compression processing, obtaining compressed layout data, and storing the compressed layout data in a data table of a relational database based on a predefined table structure; A multi-level index structure is constructed for the fields of the relational database using a B+ tree, so that when the secondary system is initialized, the target compressed layout data that matches the current system version is retrieved and extracted from the relational database based on the multi-level index structure and decompressed to obtain the original cabinet layout diagram and its location information; The layout coordinate information and relative position information of each substation secondary panel are determined according to the position information of the original panel cabinet layout diagram, and cached through the LRU cache strategy to obtain the real-time panel cabinet layout data of each substation secondary panel.

[0008] As one of the preferred solutions, the importance evaluation rules of each substation secondary panel are constructed, and combined with the historical typical panel cabinet layout cases, the importance and operation sequence of each substation secondary panel are determined by rule reasoning algorithm and case reasoning algorithm, and a panel cabinet priority operation list is generated, including: The importance evaluation rules are constructed based on the functions, locations and usage frequencies of each substation secondary panel, and are combined with each of the historical typical panel cabinet layout cases to convert them into rule sets and input them into a Drools-based rule reasoning engine, so as to perform rule matching and reasoning through a decision tree algorithm to determine the importance scores of each substation secondary panel; According to the importance scores of the substation secondary panels and the layout methods of the historical typical panel cabinet layout cases and the location information of the substation secondary panels contained therein, a secondary panel cabinet layout knowledge base is constructed; The nearest neighbor algorithm is used to calculate and match the similarity of each real-time screen cabinet layout data with the typical screen cabinet layout case, so as to extract the target layout case and its importance score and operation sequence information from the secondary screen cabinet layout knowledge base, and process it through a quick sorting algorithm to obtain the screen cabinet priority operation list.

[0009] As one of the preferred solutions, based on the real-time panel layout data and the panel priority operation list, combined with the screen size of the secondary system and the logical relationship and business process between the substation secondary panels, the human-computer interaction interface of the secondary system is constructed, including: Using a responsive layout design method based on a grid system to divide each of the real-time screen cabinet layout data into a number of grid units, and adjusting the size and number of each of the grid units according to the screen size of the secondary system; Taking the priority operation list of the panel cabinet as a constraint condition, and according to the importance and operation frequency of each substation secondary panel in the secondary panel cabinet layout knowledge base, the initial layout of each substation secondary panel is performed on the screen interface of the secondary system; The initial layout result is adjusted according to the logical relationship and business process between the substation secondary screens to configure the color and structure of the interface of the secondary system, the element arrangement of the interface is optimized through the layout algorithm, and the touch or click interaction method is integrated on the interface to generate the human-computer interaction interface of the secondary system for display.

[0010] As one of the preferred solutions, the acquisition of the attribute information of the target substation secondary panel and inputting it into a pre-built panel cabinet selection rule decision tree model for processing before obtaining the compliance result includes: Acquire the unique identification information corresponding to the target substation secondary panel, and extract the target location information of the target substation secondary panel and its related location information with other substation secondary panels from the secondary panel cabinet layout knowledge base according to the unique identification information; Based on the target location information and the related location information, a spatial index algorithm is used to retrieve adjacent cabinets within a preset range from the target substation secondary cabinet, and an importance score of each adjacent cabinet is extracted from the secondary cabinet layout knowledge base; The importance scores and power-on status data of each adjacent screen cabinet are traversed to compare with the preset importance threshold and the preset power-on status respectively, and according to the comparison result, the adjacent screen cabinet whose score exceeds the preset importance threshold and is in the power-on state is taken as the target adjacent screen cabinet to be marked as a warning on the human-computer interaction interface.

[0011] As one of the preferred solutions, the property information of the target substation secondary panel is obtained and input into a pre-built panel cabinet selection rule decision tree model for processing to obtain a compliance result, including: Based on the location information, size information and importance score of the substation secondary panels contained in each of the historical typical panel cabinet layout cases, a decision tree algorithm is used to convert the panel cabinet selection rules and safety specifications into nodes and edges of the decision tree to construct the panel cabinet selection rule decision tree model; The attribute information of the target substation secondary panel is extracted and converted into an input feature vector, which is input into the panel cabinet selection rule decision tree model for real-time analysis and rule matching, so as to determine whether the current selection complies with the preset panel cabinet selection rules and preset safety specifications based on the analysis and matching results, and obtain the compliance result of the operation.

[0012] As one of the preferred solutions, if the compliance result meets the preset rules, the target substation secondary panel is updated using a collaborative filtering algorithm based on the received historical operation data and current selection of the current staff to generate a safe operation measure plan, including: In the priority list generation step, if the compliance result meets the preset rules, the importance and access frequency of each substation secondary panel are weighted averaged to quantify the comprehensive score of each substation secondary panel and sort them from high to low to generate a panel cabinet priority list; In the target panel cabinet update step, the target position information of the target substation secondary panel currently selected is used to determine a plurality of adjacent panel cabinets of the target substation secondary panel and their relative position information set, and the target position information of the target substation secondary panel is combined with the historical operation data of the current staff member obtained, the panel cabinet priority list and the target substation secondary panel as the input of the collaborative filtering algorithm, and the updated target substation secondary panel is output; Based on the updated target substation secondary panel, the priority list generation step and the target panel cabinet update step are repeatedly executed until a preset number of repetitions is reached, and the updated target substation secondary panels obtained in each iteration are combined to generate a safe operation measure plan.

[0013] As one of the preferred solutions, the target screen cabinet updating step further includes: Acquire historical operation record data of several staff members, and extract historical access to the cabinets of each staff member from the historical operation record data to construct a user-cabinet rating matrix; Based on the user-panel cabinet rating matrix, the similarity between the staff is quantified to obtain a user similarity matrix, which is combined with the target substation secondary panel currently selected by the current staff, and the interest of the current staff in each substation secondary panel is predicted through a collaborative filtering algorithm model to obtain a recommended panel cabinet ranking list; The top N substation secondary panels with the highest recommendation are selected from the recommended panel cabinet ranking list, weighted by their own importance scores, and the substation secondary panel with the highest weighted score is output as the updated target substation secondary panel.

[0014] As one of the preferred solutions, if the compliance result meets the preset rules, the target substation secondary panel is updated by using a collaborative filtering algorithm according to the received historical operation data and current selection of the current staff to generate a safe operation measure plan, which includes: Acquire the real-time behavior data of the current staff for preprocessing, use an incremental learning algorithm to perform online learning on the preprocessed real-time behavior data, so as to capture the dynamic change trend of the operation behavior of the current staff in real time, and perform initial optimization of the safety operation measure plan based on the dynamic change trend; Obtain the panel cabinet ID, operation type and operation time in the historical operation data of the current staff member, and use the panel cabinet ID and the operation type as the item set, and the operation time as the transaction ID to mine the association rules between different substation secondary panels and operations of the current staff member through the association rule mining algorithm; The historical operation data is classified by using a classification algorithm, and potential risk operations are identified to add risk labels to each substation secondary panel, and the safety operation measures plan that has been initially optimized is secondary optimized based on the association rules and the risk labels to generate a final safety operation measures plan.

[0015] A second aspect of the present invention provides a safety operation measure generation system for a substation secondary panel, which is applied to a secondary system connected to each substation secondary panel in a substation, and the safety operation measure generation system includes: A data acquisition module, used to acquire real-time panel cabinet layout data of all substation secondary panels in the substation and historical typical panel cabinet layout cases of each substation secondary panel; A list generation module is used to construct the importance evaluation rules of each substation secondary panel, and combine them with the historical typical panel cabinet layout cases to determine the importance and operation sequence of each substation secondary panel through rule reasoning algorithm and case reasoning algorithm, and generate a panel cabinet priority operation list; An interface construction module, for constructing a human-computer interaction interface of the secondary system based on the real-time panel layout data and the panel priority operation list, in combination with the screen size of the secondary system and the logical relationship and business process between the substation secondary panels; A result acquisition module is used to respond to the target substation secondary panel selected by the current staff through the human-computer interaction interface, and obtain the attribute information of the target substation secondary panel to input it into the pre-built panel cabinet selection rule decision tree model for processing to obtain the compliance result; The solution generation module is used to update the target substation secondary panel using a collaborative filtering algorithm based on the received historical operation data and current selection of the current staff if the compliance result meets the preset rules, so as to generate a safe operation measure plan.

[0016] Compared with the prior art, the embodiments of the present invention have the following advantages: (1) By evaluating the importance and determining the order of operations, staff can perform operations according to priority, avoiding blind and repetitive work and improving operational efficiency. Combining historical cases and real-time data, as well as compliance judgment, it ensures the safety and accuracy of operations and reduces the risk of operational errors. (2) The human-computer interaction interface is intuitive and easy to use, allowing staff to quickly get started and complete operational tasks efficiently. The use of intelligent technologies such as rule reasoning, case reasoning, and collaborative filtering algorithms enables the secondary system to make reasonable decisions based on historical data and current conditions, providing scientific operational guidance for staff. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solution of the present invention, the drawings required for use in the implementation mode will be briefly introduced below. Obviously, the drawings described below are only some implementation modes of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 It is a flow chart of a method for generating safety operation measures for a substation secondary panel provided by a certain embodiment of the present invention; Figure 2 It is a structural diagram of a safety operation measure generation system for a substation secondary panel provided by a certain embodiment of the present invention. DETAILED DESCRIPTION

[0019] The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings and embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. The purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] In the description of this application, the terms "first", "second", "third", etc. are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first", "second", "third", etc. may explicitly or implicitly include one or more of the feature. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0021] In the description of the present application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be a connection between the two components. The terms "vertical", "horizontal", "left", "right", "upper", "lower" and similar expressions used herein are for illustrative purposes only, and do not indicate or imply that the system or component referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0022] In the description of this application, it should be noted that, unless otherwise defined, all technical and scientific terms used in the present invention have the same meaning as those commonly understood by those skilled in the art. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood by specific circumstances.

[0023] In one embodiment, if Figure 1 As shown, the first aspect of the present invention provides a method for generating safety operation measures for a substation secondary panel, which is applied to a secondary system connected to each substation secondary panel in a substation, and the method comprises: S1. Obtaining real-time panel cabinet layout data of all substation secondary panels in the substation and historical typical panel cabinet layout cases of each substation secondary panel; Specifically, the substation secondary panel in the present invention refers to a cabinet-like device used to carry secondary equipment in the substation, which can also be called a panel, a cabinet, a panel cabinet, etc. In the substation, there are many types of panels, mainly including protection panels (cabinets), measurement and control panels (cabinets), communication panel cabinets, video cabinets, clock panels, battery panels, DC panels, AC panels, meter panels, etc. Each panel cabinet has its specific purpose. Some can collect and process the operation data of the primary equipment to determine whether it is in a normal working state. Some can monitor various parameters of the power system in real time, such as voltage, current, power, etc., and upload these data to the secondary circuit system (or secondary system) connected to each substation secondary panel in the substation for efficient interaction. Some can even integrate functions such as remote operation, reliable locking and real-time monitoring to further improve the safety and reliability of the power system; among them, the acquisition of real-time panel cabinet layout data can be obtained by accessing the computer monitoring system equipped with the substation, and the historical typical panel cabinet layout cases of each substation secondary panel can be obtained by accessing the database storing the design scheme and historical records of the panel cabinet layout.

[0024] In one embodiment, the step of obtaining real-time panel cabinet layout data of all substation secondary panels in the substation includes: Receiving the panel cabinet layout diagram transmitted by all substation secondary panels in the substation for compression processing, obtaining compressed layout data, and storing the compressed layout data in a data table of a relational database based on a predefined table structure; A multi-level index structure is constructed for the fields of the relational database using a B+ tree, so that when the secondary system is initialized, the target compressed layout data that matches the current system version is retrieved and extracted from the relational database based on the multi-level index structure and decompressed to obtain the original cabinet layout diagram and its location information; The layout coordinate information and relative position information of each substation secondary panel are determined according to the position information of the original panel cabinet layout diagram, and cached through the LRU cache strategy to obtain the real-time panel cabinet layout data of each substation secondary panel.

[0025] In addition, the present invention can also compress the layout diagram of the panel cabinet sent by each substation secondary panel to obtain compressed layout data; wherein the compressed layout data includes compressed image data and related location information; then store it in a data table based on a predefined table structure to efficiently store and query layout diagram data; wherein the table structure should include information such as compressed image data field, location information field and version information field. Taking a 500kV substation as an example, the original size of the layout diagram of its substation secondary panel is 5000x3000 pixels, and the file size is about 45MB. It can be compressed to about 10% of the original size, i.e. 4.5MB, using the JPEG2000 compression algorithm, while keeping the image quality loss within an acceptable range. The compressed image data can be converted into binary format for storage to facilitate database operations. When designing the relational database table structure, a table named "Screen Cabinet Layout Diagram" can be created, which contains the following fields: ID (primary key, auto-increment integer), station name (variable-length string), compressed image data (binary large object BLOB), location information (JSON format string), version number (integer), update time (date time) and other predefined structures. Among them, the location information field stores the coordinate data of each screen cabinet, such as {"Screen Cabinet 1": [100, 200], "Screen Cabinet 2": [300, 200]}, which is convenient for subsequent parsing and rendering.

[0026] For the layout diagram data stored in the data table, a B+ tree is used to establish a multi-level index, and appropriate index types and index fields are used to improve the efficiency of data retrieval and query. When the secondary system is initialized, the latest screen cabinet layout diagram data that matches the current system version is loaded from the data table, and the compressed data and related location information of each screen cabinet layout diagram are obtained and decompressed to restore the original screen cabinet layout diagram for visual display and operation in the system. To improve query efficiency, a composite index can be established on the "station name" and "version number" fields, using a B+ tree index structure to quickly locate the latest version of the layout diagram of a specific substation, and a separate index can be established for the "update time" field, thereby forming a multi-level index structure, so that when the secondary system is initialized, the latest version of the layout diagram data can be retrieved from the database through an SQL query statement: For example, SELECT compressed image data, location information FROM panel cabinet layout diagram WHERE station name = `XXX 500kV substation' ORDER BY version number DESCLIMIT1 The compressed data obtained is then decompressed. Assuming that the JPEG2000 decoder is used, the binary data can be restored to the original image format. The decompressed layout diagram needs to be rendered according to the location information. Taking Web applications as an example, the HTML5Canvas element can be used to draw the layout diagram: first, the image is drawn as the background, and then the location information JSON data is parsed, and the interactive area or mark is drawn at the corresponding coordinate position, so as to ensure the accuracy of the layout and realize the user interaction function.

[0027] Finally, the layout coordinate information and relative position information of each substation secondary panel are determined according to the location information of the original panel layout diagram, and cached through the LRU cache strategy to improve the access and call efficiency of the layout diagram when the secondary system is running, reduce frequent database query operations, and dynamically load and update the panel layout diagram data as needed during the system operation. By comparing the data version and the system version, ensure that the layout diagram data used is consistent with the system version, and then obtain the real-time panel layout data of each substation secondary panel that can ensure the accuracy and reliability of the data. When the LRU (least recently used) cache strategy is adopted, it is assumed that the secondary system memory allows the layout diagram data of 10 panels in the substation to be cached. Whenever a site is visited, its data is loaded to the top of the cache. When the cache reaches the upper limit, the longest unused data is deleted, which can significantly reduce the number of database queries and improve the response speed; and during the system operation, the version number in the database is checked through regular polling or push mechanism to dynamically update the layout diagram data. If a new version is found, the local cache is updated to ensure that the system always uses the latest layout data.

[0028] The present invention significantly reduces the data storage space and transmission bandwidth requirements through compression processing, while the use of relational databases provides powerful data management and query capabilities; at the same time, the establishment of multi-level indexes optimizes data retrieval efficiency, and the introduction of a cache mechanism balances performance and real-time requirements. This complete solution is not only applicable to substation secondary panel layout diagrams, but can also be extended to other similar large-scale graphic data management scenarios, such as factory layout diagrams, building floor plans, etc. In this way, substation operation and maintenance staff can quickly and accurately obtain and operate secondary panel layout information, improving work efficiency and accuracy. At the same time, the scalability and performance of the secondary system are also guaranteed, providing a good foundation for future functional expansion and data scale growth.

[0029] In addition, for the historical typical cabinet layout cases of each substation secondary panel, we can start from substations of different voltage levels, such as 500kV, 220kV, 110kV, etc., and analyze the functional configuration and spatial layout characteristics of its secondary cabinet. For example, the secondary equipment room of a 500kV substation may contain multiple types of cabinets such as protection panels, measurement and control panels, and communication panels. Its layout needs to consider the logical relationship and operational convenience between the equipment. Each classic case contains the basic information of the substation, the operation sequence of the cabinet, the location coordinate information of the cabinet involved, the layout method, the importance score and other fields. The relevant data in these cases are stored in the database after the case is generated, so as to facilitate retrieval, and the selection of typical cases is determined based on the relationship between the score after the case is run and the preset score. The running time, error rate, etc. are involved in the scoring, which will not be elaborated here. Only cases with scores exceeding the preset score can be stored in the database as typical cases.

[0030] S2. Construct the importance evaluation rules of each substation secondary panel, and combine them with the historical typical panel cabinet layout cases, determine the importance and operation sequence of each substation secondary panel through rule reasoning algorithm and case reasoning algorithm, and generate a panel cabinet priority operation list; In one embodiment, step S2 includes: The importance evaluation rules are constructed based on the functions, locations and usage frequencies of each substation secondary panel, and are combined with each of the historical typical panel cabinet layout cases to convert them into rule sets and input them into a Drools-based rule reasoning engine, so as to perform rule matching and reasoning through a decision tree algorithm to determine the importance scores of each substation secondary panel; According to the importance scores of the substation secondary panels and the layout methods of the historical typical panel cabinet layout cases and the location information of the substation secondary panels contained therein, a secondary panel cabinet layout knowledge base is constructed; The nearest neighbor algorithm is used to calculate and match the similarity of each real-time screen cabinet layout data with the typical screen cabinet layout case, so as to extract the target layout case and its importance score and operation sequence information from the secondary screen cabinet layout knowledge base, and process it through a quick sorting algorithm to obtain the screen cabinet priority operation list.

[0031] Specifically, when collecting typical layout cases of each panel cabinet contained in each substation in the power system, the function, location, frequency of use, fault impact and other factors of each panel cabinet are comprehensively considered, and a set of perfect importance evaluation rules are formulated to quantitatively score the importance of the panel cabinet. For example, the main transformer protection panel is given the highest score of 10 points due to its criticality, while the ordinary measurement and control panel is only 5 points. This scoring mechanism can intuitively reflect the importance of each panel cabinet in the entire system; and the collected typical layout cases and the formulated importance evaluation rules are converted into a rule set, input into the Drools-based rule reasoning engine, and the decision tree algorithm is used for rule matching and reasoning to determine the importance score of each panel cabinet. The application of the rule reasoning engine enables the system to automatically determine the importance of the panel cabinet according to the preset rules. For example, the rule "If the panel cabinet type is main transformer protection and is located in the center, the importance score is 10" can be set. The Drools engine can efficiently process such complex rule sets and provide a basis for subsequent layout optimization.

[0032] Then, a secondary cabinet layout knowledge base is constructed based on the importance score of each cabinet and historical typical cabinet layout cases. The knowledge base should contain rich layout cases, corresponding importance scores, and operation sequence information.

[0033] Finally, based on rule reasoning, the KNN (K-NearestNeighbor) algorithm is introduced for case reasoning. The Euclidean distance between the current real-time screen cabinet layout data and the typical screen cabinet layout cases in the knowledge base is calculated, and the most similar K layout cases are found to obtain the operation sequence information and importance score of the screen cabinets. The quick sorting algorithm is used to process them to generate a dynamically updated screen cabinet priority operation list. The screen cabinets in the list are sorted according to importance and operation order. The generation of the priority list integrates the results of rule reasoning and case reasoning, which not only ensures the rationality of the layout, but also draws on historical experience.

[0034] By constructing importance assessment rules and rule reasoning engines, the present invention can more accurately assess the importance of each substation secondary panel, providing strong support for layout optimization; by utilizing the secondary panel cabinet layout knowledge base and the nearest neighbor algorithm, it can quickly match typical cases similar to the target layout, thereby greatly shortening the layout design time; the panel cabinet priority operation list obtained by the quick sorting algorithm can provide operation and maintenance personnel with a clear operation order and priority, thereby improving operation and maintenance efficiency and safety.

[0035] S3, based on the real-time panel layout data and the panel priority operation list, and in combination with the screen size of the secondary system and the logical relationship and business process between the substation secondary panels, construct the human-computer interaction interface of the secondary system; In one embodiment, step S3 includes: Using a responsive layout design method based on a grid system to divide each of the real-time screen cabinet layout data into a number of grid units, and adjusting the size and number of each of the grid units according to the screen size of the secondary system; Taking the priority operation list of the panel cabinet as a constraint condition, and according to the importance and operation frequency of each substation secondary panel in the secondary panel cabinet layout knowledge base, the initial layout of each substation secondary panel is performed on the screen interface of the secondary system; The initial layout result is adjusted according to the logical relationship and business process between the substation secondary screens to configure the color and structure of the interface of the secondary system, the element arrangement of the interface is optimized through the layout algorithm, and the touch or click interaction method is integrated on the interface to generate the human-computer interaction interface of the secondary system for display.

[0036] Specifically, the present invention converts the real-time panel cabinet layout data and the panel cabinet priority operation list into a standardized JSON format, providing a structured input for interface design. For example, a typical panel cabinet data may contain the following fields: {"id":"CB001","type":"main transformer protection","priority":10,"position":{"x":100,"y":200},"size":{"width":80,"height":120}}, so that the front-end framework can perform data parsing and rendering, and according to the characteristics of the touch screen or large-screen display, a responsive layout design method based on a grid system is adopted, and according to the complexity of the real-time panel cabinet layout data and the screen size, the interface screen of the entire secondary system is divided into several grid units. These grid units are the basic units of layout design, which are used to accommodate and arrange elements such as substation secondary screens. In addition, in the process of dividing the grid units, the adaptability of different screen sizes should be considered to ensure that a good layout effect can be presented on different devices. Suppose there is a large screen with a width of 1920 pixels, which can be divided into a grid of 12 columns and 6 rows. The size of each grid unit is 160 pixels wide and 180 pixels high. When the screen size changes, the grid unit will automatically resize to maintain the coordination of the overall layout and ensure the consistency and usability of the interface on different devices.

[0037] Then, the order in the priority operation list of the cabinets is used as a constraint condition to ensure that the cabinets with higher importance and frequent operation are placed in more conspicuous and easy-to-operate positions. Taking into account the importance and operation frequency of each cabinet, the cabinets ranked higher in the priority list are placed in a prominent position on the interface, such as the center or top area of ​​the screen. For example, the main transformer protection panel may be placed in the upper center of the screen, occupying a 2x2 grid unit, while the secondary measurement and control panel may be arranged in the edge area, occupying a 1x1 grid unit, to highlight key information and improve operation efficiency. For each cabinet, a concise and clear graphical icon is designed to greatly reduce the user's cognitive load. For example, the main transformer protection panel can use a transformer-shaped icon with a red border to indicate its importance, and the line protection panel can be represented by a line icon with a lightning symbol. However, these icon designs must follow the principle of consistency and use similar line thickness and color schemes to ensure the harmony of the overall visual effect and achieve the initial layout.

[0038] Finally, the initial layout results are adjusted according to the logical relationship and business process between each cabinet, and appropriate alignment, grouping, spacing and other methods are used to improve the orderliness and readability of information presentation. Soft and bright color matching is adopted to avoid using overly bright or contrasting colors to reduce the user's visual fatigue, so as to realize the configuration of the color matching and structure of the interface of the secondary system. The layout algorithm is used to optimize the arrangement of elements of the interface to avoid overly dense or loose visual effects, and the touch or click interaction method is integrated on the interface to generate the human-computer interaction interface of the secondary system for display, so that users can select the target cabinet with their fingers or mice, and the secondary system dynamically updates the interface content according to the selected cabinet information. At the same time, necessary feedback mechanisms are provided, such as button highlighting and click sound effects, to enhance the certainty and comfort of operation. Among them, when adjusting the initial layout results, related protective screen cabinets can also be combined together to form a visual whole to reflect the actual connection relationship between the equipment, which helps operators quickly understand the system structure; and use a soft blue-gray as the background color, and use different shades of blue to indicate the importance of the screen cabinet. For example, the most important screen cabinet can use dark blue, and the secondary one can use light blue. Warning messages can be expressed in yellow or orange to attract attention but not too glaring. This color scheme is both beautiful and ergonomic, and can reduce visual fatigue caused by long-term operation.

[0039] The present invention realizes the optimization design and improvement of the human-computer interaction interface of the secondary system through multiple steps such as a responsive layout design method based on a grid system, initial layout, layout adjustment and interface configuration, layout optimization and integrated interaction mode, and generation and display of a human-computer interaction interface. The method of comprehensively using multiple technologies and design principles not only improves the operating efficiency of the secondary equipment of the substation, but also lays the foundation for intelligent operation and maintenance.

[0040] S4, in response to the target substation secondary panel selected by the current staff through the human-computer interaction interface, and obtaining the attribute information of the target substation secondary panel, so as to input it into the pre-built panel cabinet selection rule decision tree model for processing, and obtain the compliance result; Specifically, after the human-computer interaction interface is generated, the current staff can use the interface to determine the target substation secondary panel and send it to the secondary system. The secondary system responds to the received target substation secondary panel and obtains the coordinate position, size, relative position relationship and other position information of the panel cabinet to determine whether there are important and energized panel cabinets in the adjacent area of ​​the selected panel cabinet and whether the current operation complies with the preset rules.

[0041] In one embodiment, the acquisition of the attribute information of the target substation secondary panel, and inputting it into a pre-built panel cabinet selection rule decision tree model for processing, before obtaining the compliance result, includes: Acquire the unique identification information corresponding to the target substation secondary panel, and extract the target location information of the target substation secondary panel and its related location information with other substation secondary panels from the secondary panel cabinet layout knowledge base according to the unique identification information; Based on the target location information and the related location information, a spatial index algorithm is used to retrieve adjacent cabinets within a preset range from the target substation secondary cabinet, and an importance score of each adjacent cabinet is extracted from the secondary cabinet layout knowledge base; The importance scores and power-on status data of each adjacent screen cabinet are traversed to compare with the preset importance threshold and the preset power-on status respectively, and according to the comparison result, the adjacent screen cabinet whose score exceeds the preset importance threshold and is in the power-on state is taken as the target adjacent screen cabinet to be marked as a warning on the human-computer interaction interface.

[0042] Specifically, the target substation secondary panel received by the secondary system generally contains its corresponding unique identification information, such as the panel cabinet number "CB001", so that the system can quickly retrieve the location coordinates, length, width, height and other dimension information of the panel cabinet and the position information relative to other panel cabinets from the pre-stored data or knowledge base. For example, the location coordinates of the target panel cabinet "CB001" are (100, 200), and the dimensions are 80cm wide, 120cm high, and 60cm deep. It is located in the northwest corner of the substation main control room. These precise data lay the foundation for subsequent safety analysis.

[0043] Then, based on the extracted location information, a spatial index algorithm such as R-tree is used to quickly retrieve the adjacent cabinets within a certain range of the target cabinet, and obtain the location information and importance scores of these adjacent cabinets. Assuming that the search range is set to 3 meters around the target cabinet, the R-tree algorithm can return all cabinet information within this range within milliseconds. This efficient retrieval is crucial for real-time safety monitoring, especially in large substations where there may be hundreds of cabinets.

[0044] Finally, the importance scores and live status data of the adjacent cabinets are traversed to determine whether their importance exceeds the preset importance threshold and whether they are currently in a live state. If both conditions are met (i.e., whether there is a cabinet that is both important and in a live state), the adjacent cabinet is determined to be an important and live target adjacent cabinet, and according to the location information of the important and live adjacent cabinets obtained in the previous step, the locations of these cabinets are dynamically marked on the interface, and eye-catching warning icons and text messages are displayed to remind the staff to keep a safe distance from these cabinets. The importance threshold can be set to 8 (out of 10 points), and any cabinet that exceeds this threshold and is in a live state is considered a high-risk object. For example, a main transformer protection panel with an importance of 9 points and in operation belongs to this type of high-risk cabinet, which helps staff quickly identify potential danger areas. On the human-computer interaction interface, high-risk cabinets can be marked with red flashing icons, and warning texts such as "Attention: High-voltage equipment, keep a safe distance" can be displayed at the same time. This intuitive visual reminder can effectively reduce the risk of misoperation.

[0045] The present invention uses a spatial index algorithm to quickly retrieve adjacent cabinets, and screens based on importance scores and live status, so that the cabinets that need attention can be quickly located, thereby improving the work efficiency of operation and maintenance personnel; warning marks are made for adjacent cabinets that are in a live state and have a high degree of importance, which helps operation and maintenance personnel to promptly discover potential safety hazards and take corresponding measures, thereby enhancing the safety of the power system; intuitive warning marks are made on the human-computer interaction interface, so that operation and maintenance personnel can understand the information of the cabinets that need attention at a glance, thereby optimizing the human-computer interaction experience; the scheme combines multiple technical means such as spatial index algorithm, importance assessment and live status monitoring, realizes intelligent management and early warning of substation secondary panels, and improves the intelligence level of the power system.

[0046] In one embodiment, the acquisition of the attribute information of the target substation secondary panel is input into a pre-built panel cabinet selection rule decision tree model for processing to obtain a compliance result, including: Based on the location information, size information and importance score of the substation secondary panels contained in each of the historical typical panel cabinet layout cases, a decision tree algorithm is used to convert the panel cabinet selection rules and safety specifications into nodes and edges of the decision tree to construct the panel cabinet selection rule decision tree model; The attribute information of the target substation secondary panel is extracted and converted into an input feature vector, which is input into the panel cabinet selection rule decision tree model for real-time analysis and rule matching, so as to determine whether the current selection complies with the preset panel cabinet selection rules and preset safety specifications based on the analysis and matching results, and obtain the compliance result of the operation.

[0047] Specifically, the present invention is based on the location information, size information, importance score and other attribute information of the substation secondary screen contained in each historical typical screen cabinet layout case, adopts a decision tree algorithm, pre-constructs a screen cabinet selection rule decision tree model, and converts the screen cabinet selection rules and safety specifications (the rules and specifications here can be summarized and extracted from the historical typical screen cabinet layout cases through data statistics and analysis methods, etc.) into nodes and edges of the decision tree; and inputs the attribute information of the target substation secondary screen into the constructed model for real-time analysis and rule matching, and judges whether the current selection operation complies with the preset screen cabinet selection rules and safety specifications (the preset rules and specifications can be summarized in actual work or according to industry standards), and obtains the compliance result of the operation. If the compliance result of the operation does not comply with the preset rules, then according to the matching results of the decision tree model, the corresponding prompt information and warning information are obtained, and displayed to the staff in real time on the interface in the form of pop-up windows, voice, etc. If the current selection operation complies with the preset rules, then according to the matching results of the decision tree model, the prompt information of the next optional operation is obtained to guide the staff to perform subsequent operations.

[0048] For example, in a substation environment, a simple decision tree node may be "Is the importance of the cabinet greater than 8?" If so, it will enter the sub-node of "Check whether there are any live devices within 3 meters around." This hierarchical structure enables the system to quickly evaluate the safety and compliance of operations. In actual applications, the staff may select a cabinet numbered "CB005", then the secondary system will immediately retrieve detailed information about the cabinet from the knowledge base, such as the location coordinates (150, 300), the size of 100cm×150cm×70cm, and the importance of 9. These attribute information are converted into the input feature vector of the decision tree, such as [9,150,300,100,150,70]. The decision tree model will then analyze this vector to determine whether it meets the preset rules. Assume that a rule of the decision tree is "no other equipment can be operated within 2 meters around a cabinet with an importance greater than 8". If the system detects that another cabinet being operated by the staff is within 1.5 meters of "CB005", the decision tree will immediately determine that this is an illegal operation and generate a warning message: "Warning: You are operating two cabinets with high importance at the same time, which may cause safety hazards. Please maintain an operating distance of at least 2 meters". This real-time feedback mechanism can effectively prevent potential dangerous operations. When the system determines that an operation is illegal, it can not only give a warning but also explain the reason. For example, the operation is illegal: Reason 1) The importance of the selected cabinet is 9, which exceeds the safety threshold of 8; Reason 2) There are other important equipment being operated within 1.5 meters. This detailed explanation helps the staff understand the safety rules and improve the standardization of the operation. In the case of compliant operation, the decision tree model can also provide suggestions for the next operation. For example, when the staff successfully selects a cabinet with low importance, the secondary system may prompt: "The current operation is compliant. It is recommended to check whether the internal connection of the cabinet is normal and record the operating parameters next." This guided operation process can significantly improve work efficiency and safety.

[0049] The present invention realizes rapid parsing and matching of panel cabinet selection rules by constructing a panel cabinet selection rule decision tree model, thereby improving decision-making efficiency; the decision tree model constructed based on historical typical panel cabinet layout cases and clear rules and safety specifications can accurately judge whether the current selection meets the requirements, thereby enhancing the accuracy of compliance judgment; the complex panel cabinet selection rules and safety specifications are converted into nodes and edges of the decision tree, thereby realizing automatic parsing and matching of rules, improving the intelligence level of the power system, and providing an intelligent, flexible and sustainable optimization solution for the safe operation of the substation, which can not only guide the staff's operation in real time, but also improve its own accuracy and applicability through continuous learning, thereby improving work efficiency while maximizing operational safety.

[0050] S5. If the compliance result meets the preset rules, the target substation secondary panel is updated using a collaborative filtering algorithm based on the received historical operation data and current selection of the current staff member to generate a safe operation measure plan; In one embodiment, step S5 includes: In the priority list generation step, if the compliance result meets the preset rules, the importance and access frequency of each substation secondary panel are weighted averaged to quantify the comprehensive score of each substation secondary panel and sort them from high to low to generate a panel cabinet priority list; In the target panel cabinet update step, the target position information of the target substation secondary panel currently selected is used to determine a plurality of adjacent panel cabinets of the target substation secondary panel and their relative position information set, and the target position information of the target substation secondary panel is combined with the historical operation data of the current staff member obtained, the panel cabinet priority list and the target substation secondary panel as the input of the collaborative filtering algorithm, and the updated target substation secondary panel is output; Based on the updated target substation secondary panel, the priority list generation step and the target panel cabinet update step are repeatedly executed until a preset number of repetitions is reached, and the updated target substation secondary panels obtained in each iteration are combined to generate a safe operation measure plan.

[0051] Specifically, in the priority list generation step, if the compliance result meets the preset rules, the comprehensive score of each screen cabinet is calculated by weighted average based on the attributes such as the importance of the screen cabinet and the access frequency preset in the screen cabinet layout diagram database, where the importance weight is 0.6 and the access frequency weight is 0.4. The calculated comprehensive scores of the screen cabinets are sorted from high to low to generate a screen cabinet priority list and store it in the priority list database.

[0052] In the target cabinet update step, the position coordinates of the target cabinet selected by the current staff are obtained, and the adjacent cabinet information of the cabinet is queried from the cabinet layout diagram database or knowledge base through the coordinates to obtain a set of position coordinates of adjacent cabinets. These are combined with the staff's historical operation records, the position coordinates of the currently selected cabinet, the position coordinate set of adjacent cabinets, and the cabinet priority list as the input of the collaborative filtering recommendation algorithm. The user-item collaborative filtering algorithm is used to calculate the next operation cabinet that the current staff may be interested in, so as to update the target cabinet.

[0053] Based on the updated target cabinet, the priority list generation step and the target cabinet update step are repeatedly executed until a preset number of repetitions is reached, and the updated target cabinets obtained in each iteration process are combined to generate a safe operation measure plan.

[0054] For example, the secondary system may record that the current staff has visited the cabinets numbered CB001, CB003, and CB005 multiple times in the past week. These data are stored in the operation history database to provide a basis for subsequent analysis. The calculation of the comprehensive score of the cabinet involves multiple factors. Assuming that the importance of the CB001 cabinet is 9 points (out of 10 points), the average monthly access frequency is 20 times, and the importance of the CB002 cabinet is 7 points, and the average monthly access frequency is 30 times, then according to the weighted average formula, the comprehensive score of CB001 is 9×0.6+20×0.4÷50=7.4, and the comprehensive score of CB002 is 7×0.6+30×0.4÷50=6.6. This calculation method takes into account the inherent properties of the cabinet and reflects its actual usage, which helps to generate a more reasonable priority list. The acquisition of adjacent cabinet information is crucial for the recommendation algorithm. Assuming that the cabinet CB003 currently selected by the staff is located at the coordinates (100, 200), the secondary system will query the layout map database to find all cabinets within a 2-meter range, such as CB004 (110, 210), CB005 (90, 195), etc. This information helps the algorithm consider spatial correlation and avoid recommending cabinets that are too far apart. The core of the collaborative filtering algorithm is to discover similarities between users. For example, the secondary system may find that staff A and B often operate high-voltage distribution cabinets, but rarely contact low-voltage control cabinets. Based on this similarity, when A selects a new high-voltage cabinet, the secondary system may recommend several high-voltage cabinets that B has recently used.

[0055] The present invention can quickly determine the priority of the panel cabinet through the priority list generation step, so as to optimize the layout and operation process; through compliance inspection and rule judgment, ensure that the selection and operation of each substation secondary panel comply with the preset panel cabinet selection rules and safety specifications; use collaborative filtering algorithm, combined with the historical operation data and preferences of the staff, to achieve personalized panel cabinet recommendations, improve the convenience and comfort of operation; through the iteration and optimization process, comprehensively consider multiple factors, generate a comprehensive safety operation measure plan, and improve the safety and reliability of the entire power system.

[0056] In one embodiment, the target screen cabinet updating step further includes: Acquire historical operation record data of several staff members, and extract historical access to the cabinets of each staff member from the historical operation record data to construct a user-cabinet rating matrix; Based on the user-panel cabinet rating matrix, the similarity between the staff is quantified to obtain a user similarity matrix, which is combined with the target substation secondary panel currently selected by the current staff, and the interest of the current staff in each substation secondary panel is predicted through a collaborative filtering algorithm model to obtain a recommended panel cabinet ranking list; The top N substation secondary panels with the highest recommendation are selected from the recommended panel cabinet ranking list, weighted by their own importance scores, and the substation secondary panel with the highest weighted score is output as the updated target substation secondary panel.

[0057] Specifically, the present invention can also analyze the historical behaviors of multiple users to discover users with similar screen cabinet access behaviors, and then make recommendations to the current user based on the choices of similar users to update the target screen cabinet, specifically: extract the screen cabinets visited by each staff member from the historical operation record data of several staff members, generate a user-screen cabinet rating matrix, and then calculate the similarity between users, and then predict the current user's interest in each screen cabinet through a collaborative filtering algorithm model based on the screen cabinet scores of similar users, and obtain a ranked list of recommended screen cabinets, and finally, based on the ranked list of recommended screen cabinets, obtain the top N screen cabinets with the highest recommendation degree and weight them by their own importance scores, and use the substation secondary screen with the highest weighted score as the updated target substation secondary screen, and highlight it in a striking manner such as highlighting and flashing in the screen cabinet selection interface to guide the staff to perform subsequent operations.

[0058] In addition, after the staff completes the operation of recommending the cabinet, the feedback data on the recommendation result is recorded, including whether the recommended cabinet is selected, the time efficiency of the operation, etc. The feedback data is stored in the recommendation feedback database, and the feedback data is regularly extracted from the recommendation feedback database. The adoption rate of the recommended cabinets is counted, that is, what proportion of the recommended cabinets are selected by the staff, and the evaluation indicators such as accuracy and recall rate are used to evaluate the effect of the recommendation algorithm. The optimization algorithms such as gradient descent are used to adjust the parameters of the collaborative filtering model to continuously improve the accuracy and practicality of the recommendation. If the adoption rate is low, it is necessary to analyze the reasons and consider optimizing the similarity calculation method of the collaborative filtering algorithm or adjusting the number of recommended cabinets to improve the practicality of the recommendation.

[0059] The present invention realizes personalized panel cabinet recommendation for current staff members through collaborative filtering algorithm model, combined with historical operation record data and user similarity matrix, and improves the accuracy and practicality of recommendation. In the recommendation process, not only the historical access behavior of staff members is taken into account, but also the importance score of the panel cabinet itself is combined, so that the recommendation result is more comprehensive and reasonable. By constructing a user-panel cabinet scoring matrix and a user similarity matrix, and using a collaborative filtering algorithm model for prediction, a recommended panel cabinet ranking list can be quickly generated, thereby improving decision-making efficiency. Updating the target substation secondary panel according to the recommendation results is helpful to optimize the panel cabinet layout and operation process, and improve the safety and reliability of the power system.

[0060] In one embodiment, after step S5, the method further includes: Acquire the real-time behavior data of the current staff for preprocessing, use an incremental learning algorithm to perform online learning on the preprocessed real-time behavior data, so as to capture the dynamic change trend of the operation behavior of the current staff in real time, and perform initial optimization of the safety operation measure plan based on the dynamic change trend; Obtain the panel cabinet ID, operation type and operation time in the historical operation data of the current staff member, and use the panel cabinet ID and the operation type as the item set, and the operation time as the transaction ID to mine the association rules between different substation secondary panels and operations of the current staff member through the association rule mining algorithm; The historical operation data is classified by using a classification algorithm, and potential risk operations are identified to add risk labels to each substation secondary panel, and the safety operation measures plan that has been initially optimized is secondary optimized based on the association rules and the risk labels to generate a final safety operation measures plan.

[0061] Specifically, the present invention pre-processes the actual operation behavior data such as the screen cabinet position, operation time, and operation type selected by the current staff in the manual interaction interface to convert these time fields into timestamp format, and inputs them into the incremental learning algorithm (such as Hoeffding Tree) for online learning, so as to update the model parameters in real time, capture the dynamic change trend of the staff's operation behavior, and perform initial optimization of the safety operation measures based on the dynamic change trend. Assuming that the secondary system finds that the staff has frequently checked the status of the two screen cabinets CB001 and CB002 recently, the HoeffdingTree algorithm will dynamically adjust the model parameters and increase the weight of these two screen cabinets in the recommendation list to quickly adapt to the changes in the staff's operating habits and improve the accuracy of the recommendation.

[0062] Obtain the current staff's panel ID, operation type and operation time in their own historical operation data, and use the panel ID and the operation type as the item set, and the operation time as the transaction ID. Use the association rule mining algorithm (such as FP-Growth) to mine the association rules between the current staff in different substation secondary panels and operations, and discover the staff's operation habits and potential risks. Association rule mining helps to discover potential operation patterns. Through FP-Growth algorithm analysis, the secondary system may find a rule: after operating CB001, there is an 80% probability of operating CB003 within 10 minutes. This association information can be used to predict the next possible operation, thereby optimizing the interface display and prompt strategy. For example, there may be a "related operation" edge between CB001 and CB003, with a weight of 0.8. When CB001 is found to have safety hazards, the secondary system will update the node attributes through Cypher statements, such as increasing the risk level of CB001 to "high" and reducing its importance from 9 to 7. Dynamically adjusting the display order of the cabinets can effectively guide the staff's operations. For example, the cabinet list originally sorted by number may be adjusted to be sorted in descending order of importance. Important and safe cabinets (such as CB002) may be given a striking green background, while risky cabinets (such as CB001) may be displayed in yellow or red, intuitively reminding operators to pay attention to potential risks. Using the Jinja2 template engine to generate interactive prompts can greatly improve the flexibility of the system. When the staff selects CB001, the secondary system may generate the following prompt based on its "high risk" label: "Note: This cabinet has had three abnormalities recently, please check the switch status carefully" to effectively reduce operational risks.

[0063] Finally, classification algorithms such as decision trees, support vector machines, and random forests are used to classify historical operation data, identify potential risk operations, and add risk labels to each substation secondary panel, so as to perform secondary optimization on the initially optimized safety operation measures based on association rules and risk labels, and generate the final safety operation measures. That is, if a certain panel cabinet is found to have a high selection frequency but has safety hazards, a risk label is added to the corresponding panel cabinet node, and its importance attribute value is reduced. In the manual interaction interface, the importance attribute of each panel cabinet node is obtained through Neo4j database query, and the display order and CSS style of the panel cabinet are dynamically adjusted according to the importance value, highlighting the important and safe panel cabinets, and guiding the staff to give priority to selection. When the staff selects a panel cabinet, the secondary system uses the Jinja2 template engine to dynamically generate the corresponding interactive prompts in HTML format according to the risk label and association rules of the panel cabinet node, such as operation precautions, potential risk warnings, etc., and displays them to the staff in a friendly way through the Web page.

[0064] In addition, after the staff completes the screen cabinet operation, the feedback data on the system prompt strategy is recorded, such as whether the risk is effectively avoided and whether the operation efficiency is improved. The feedback data is stored in the feedback log collection of the MongoDB database, and the feedback log collection is regularly queried from the MongoDB database to extract features and convert labels for the feedback data to generate a data set for training the decision tree model. Then, the Decision TreeClassifier in the scikit-learn library is used to evaluate the effectiveness of the prompt strategy, and the hyperparameters of the decision tree are optimized through grid search to improve the accuracy of the strategy evaluation. According to the evaluation results of the decision tree, the generation rules of the prompt strategy are dynamically adjusted, such as modifying the conditional judgment statement in the Jinja2 template, updating the case library collection stored in the MongoDB database, and applying the optimized prompt strategy to subsequent screen cabinet operations, continuously improving the security protection capabilities of the system. In order to protect the privacy and sensitive data of the staff, when storing the operation log and feedback data, the user ID is one-way hashed using SHA-256 to replace the original user identifier. At the same time, sensitive fields (such as cabinet location, operation time, etc.) stored in MySQL, Neo4j and MongoDB databases are encrypted with AES symmetric encryption to ensure data confidentiality. In the process of data analysis and mining, only desensitized data is used to avoid the leakage of private information.

[0065] The present invention conducts online learning of real-time behavior data through an incremental learning algorithm, can capture the dynamic change trend of the current staff's operating behavior in real time, and dynamically adjust the safety operation measures plan, thereby improving the real-time adaptability and personalization of the plan; through the association rule mining algorithm, the association rules between the current staff in different substation secondary panels and operations are mined, which is helpful to understand the staff's operating habits and needs, and provide strong support for the optimization plan; the classification algorithm is used to identify potential risk operations, and risk labels are added to each substation secondary panel, which is helpful to discover and prevent safety risks in advance and improve the safety and reliability of the power system; the safety operation measures plan is comprehensively optimized by combining real-time behavior data, association rules and risk factors, making the plan more comprehensive, reasonable and effective; the optimized safety operation measures plan can better adapt to the current staff's operating habits and needs, reduce misoperation and risk events, and improve operating efficiency and safety.

[0066] In the embodiment of the present application, based on the problem of how to design a more intuitive and convenient human-computer interaction method to improve the work efficiency and accuracy of the process of generating safety operation measures for substation secondary panels, a method for generating safety operation measures for substation secondary panels is designed, which is applied to the secondary system connected to each substation secondary panel in the substation, and realizes the construction of substation secondary panel importance evaluation rules by collecting real-time panel cabinet layout data of all substation secondary panels in the substation and historical typical panel cabinet layout cases, and determines the importance and operation sequence of each substation secondary panel through rule reasoning and case reasoning algorithms, thereby generating a panel cabinet priority operation list; based on real-time panel cabinet layout, the panel cabinet layout is used to evaluate the importance of the substation secondary panel. The bureau data and the priority operation list of the panel cabinet are combined with the screen size of the secondary system, the logical relationship between the substation secondary panels and the business process to build an easy-to-operate human-computer interaction interface; when the target substation secondary panel selected by the staff through the human-computer interaction interface is received, the attribute information of the panel is obtained, and the compliance judgment is made through the pre-built panel cabinet selection rule decision tree model; if the compliance result meets the preset rules, the secondary system will use the collaborative filtering algorithm to update the target substation secondary panel according to the historical operation data and current selection of the staff, and finally generate a technical solution for the safe operation measures plan to effectively improve the accuracy, safety and efficiency of the substation secondary panel cabinet operation plan.

[0067] It should be noted that although the steps in the above flowchart are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders.

[0068] In another embodiment, if Figure 2 As shown, the second aspect of the present invention provides a safety operation measure generation system for a substation secondary panel, which is applied to a secondary system connected to each substation secondary panel in a substation, and the safety operation measure generation system includes: The data acquisition module 10 is used to acquire the real-time panel cabinet layout data of all substation secondary panels in the substation and the historical typical panel cabinet layout cases of each substation secondary panel; The list generation module 20 is used to construct the importance evaluation rules of each substation secondary panel, and combine them with the historical typical panel cabinet layout cases to determine the importance and operation sequence of each substation secondary panel through rule reasoning algorithm and case reasoning algorithm, and generate a panel cabinet priority operation list; An interface construction module 30 is used to construct a human-computer interaction interface of the secondary system based on the real-time panel layout data and the panel priority operation list, and in combination with the screen size of the secondary system and the logical relationship and business process between the substation secondary panels; The result acquisition module 40 is used to respond to the target substation secondary panel selected by the current staff through the human-computer interaction interface and obtain the attribute information of the target substation secondary panel to input it into the pre-built panel cabinet selection rule decision tree model for processing to obtain the compliance result; The solution generation module 50 is used to update the target substation secondary panel using a collaborative filtering algorithm based on the received historical operation data and current selection of the current staff if the compliance result meets the preset rules, so as to generate a safe operation measure plan.

[0069] It should be noted that each module in the above-mentioned system for generating safety operating measures for a secondary substation can be fully or partially implemented through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules. For the specific definition of a system for generating safety operating measures for a secondary substation, please refer to the definition of a method for generating safety operating measures for a secondary substation in the above text. The two have the same functions and effects and will not be repeated here.

[0070] In summary, the present invention relates to the field of information technology, and discloses a method and system for generating safe operating measures for substation secondary panels. By collecting historical typical layout cases of all substation secondary panels in the substation and formulating importance evaluation rules, the importance and operation order of each substation secondary panel are determined through rule reasoning algorithms and case reasoning algorithms, and a dynamically updated priority list is generated. Combined with real-time panel cabinet layout data, a graphical human-computer interface is designed to display the panel cabinet layout in a clear and intuitive manner. When selecting the target panel cabinet through the human-computer interaction interface, a decision tree-based rule engine is used to judge the compliance of the operation in real time. When it is compliant, a collaborative filtering algorithm is used to recommend important panel cabinets that may be operated in the next step based on the operation history and current selection, and a safe operating measures plan is generated to effectively improve the accuracy, safety and efficiency of the substation secondary panel cabinet operation plan.

[0071] Each embodiment in this specification is described in a progressive manner, and the same or similar parts of each embodiment can be directly referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. It should be noted that the technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above-mentioned embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0072] The above-mentioned embodiments only express several preferred implementation modes of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in the technical field, several improvements and substitutions can be made without departing from the technical principles of the present invention, and these improvements and substitutions should also be regarded as the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be based on the protection scope of the claims.

Claims

1. A method for generating safety operation measures for a substation secondary panel, characterized in that: Applied to a secondary system connected to each substation secondary panel in a substation, the method comprises: Obtaining real-time panel cabinet layout data of all substation secondary panels in the substation and historical typical panel cabinet layout cases of each substation secondary panel; Constructing the importance evaluation rules of each substation secondary panel, and combining them with the historical typical panel cabinet layout cases, determining the importance and operation sequence of each substation secondary panel through rule reasoning algorithm and case reasoning algorithm, and generating a panel cabinet priority operation list; Based on the real-time panel layout data and the panel priority operation list, and in combination with the screen size of the secondary system and the logical relationship and business process between the substation secondary panels, a human-computer interaction interface of the secondary system is constructed; In response to the target substation secondary panel selected by the current staff through the human-computer interaction interface, the attribute information of the target substation secondary panel is obtained to be input into the pre-built panel cabinet selection rule decision tree model for processing to obtain a compliance result; If the compliance result meets the preset rules, the target substation secondary panel is updated using a collaborative filtering algorithm based on the received historical operation data and current selection of the current staff member to generate a safe operation measure plan.

2. A method for generating safety operation measures for a substation secondary panel according to claim 1, characterized in that: The step of obtaining the real-time panel cabinet layout data of all substation secondary panels in the substation includes: Receiving the panel cabinet layout diagram transmitted by all substation secondary panels in the substation for compression processing, obtaining compressed layout data, and storing the compressed layout data in a data table of a relational database based on a predefined table structure; A multi-level index structure is constructed for the fields of the relational database using a B+ tree, so that when the secondary system is initialized, the target compressed layout data that matches the current system version is retrieved and extracted from the relational database based on the multi-level index structure and decompressed to obtain the original cabinet layout diagram and its location information; The layout coordinate information and relative position information of each substation secondary panel are determined according to the position information of the original panel cabinet layout diagram, and cached through the LRU cache strategy to obtain the real-time panel cabinet layout data of each substation secondary panel.

3. A method for generating safety operation measures for a substation secondary panel according to claim 1, characterized in that: The importance evaluation rules of each substation secondary panel are constructed and combined with the historical typical panel cabinet layout cases, the importance and operation sequence of each substation secondary panel are determined through rule reasoning algorithm and case reasoning algorithm, and a panel cabinet priority operation list is generated, including: The importance evaluation rules are constructed based on the functions, locations and usage frequencies of each substation secondary panel, and are combined with each of the historical typical panel cabinet layout cases to convert them into rule sets and input them into a Drools-based rule reasoning engine, so as to perform rule matching and reasoning through a decision tree algorithm to determine the importance scores of each substation secondary panel; According to the importance scores of the substation secondary panels and the layout methods of the historical typical panel cabinet layout cases and the location information of the substation secondary panels contained therein, a secondary panel cabinet layout knowledge base is constructed; The nearest neighbor algorithm is used to calculate and match the similarity of each real-time screen cabinet layout data with the typical screen cabinet layout case, so as to extract the target layout case and its importance score and operation sequence information from the secondary screen cabinet layout knowledge base, and process it through a quick sorting algorithm to obtain the screen cabinet priority operation list.

4. A method for generating safety operation measures for a substation secondary panel according to claim 3, characterized in that: The human-computer interaction interface of the secondary system is constructed based on the real-time panel layout data and the panel priority operation list, and in combination with the screen size of the secondary system and the logical relationship and business process between the substation secondary panels, including: Using a responsive layout design method based on a grid system to divide each of the real-time screen cabinet layout data into a number of grid units, and adjusting the size and number of each of the grid units according to the screen size of the secondary system; Taking the priority operation list of the panel cabinet as a constraint condition, and according to the importance and operation frequency of each substation secondary panel in the secondary panel cabinet layout knowledge base, the initial layout of each substation secondary panel is performed on the screen interface of the secondary system; The initial layout result is adjusted according to the logical relationship and business process between the substation secondary screens to configure the color and structure of the interface of the secondary system, the element arrangement of the interface is optimized through the layout algorithm, and the touch or click interaction method is integrated on the interface to generate the human-computer interaction interface of the secondary system for display.

5. A method for generating safety operation measures for a substation secondary panel according to claim 3, characterized in that: The acquisition of the attribute information of the target substation secondary panel, and inputting it into the pre-built panel cabinet selection rule decision tree model for processing, before obtaining the compliance result, includes: Acquire the unique identification information corresponding to the target substation secondary panel, and extract the target location information of the target substation secondary panel and its related location information with other substation secondary panels from the secondary panel cabinet layout knowledge base according to the unique identification information; Based on the target location information and the related location information, a spatial index algorithm is used to retrieve adjacent cabinets within a preset range from the target substation secondary cabinet, and an importance score of each adjacent cabinet is extracted from the secondary cabinet layout knowledge base; The importance scores and power-on status data of each adjacent screen cabinet are traversed to compare with the preset importance threshold and the preset power-on status respectively, and according to the comparison result, the adjacent screen cabinet whose score exceeds the preset importance threshold and is in the power-on state is taken as the target adjacent screen cabinet to be marked as a warning on the human-computer interaction interface.

6. A method for generating safety operation measures for a substation secondary panel according to claim 5, characterized in that: The acquisition of the attribute information of the target substation secondary panel is input into the pre-built panel cabinet selection rule decision tree model for processing to obtain the compliance result, including: Based on the location information, size information and importance score of the substation secondary panels contained in each of the historical typical panel cabinet layout cases, a decision tree algorithm is used to convert the panel cabinet selection rules and safety specifications into nodes and edges of the decision tree to construct the panel cabinet selection rule decision tree model; The attribute information of the target substation secondary panel is extracted and converted into an input feature vector, which is input into the panel cabinet selection rule decision tree model for real-time analysis and rule matching, so as to determine whether the current selection complies with the preset panel cabinet selection rules and preset safety specifications based on the analysis and matching results, and obtain the compliance result of the operation.

7. A method for generating safety operation measures for a substation secondary panel according to claim 5, characterized in that: If the compliance result meets the preset rules, the target substation secondary panel is updated using a collaborative filtering algorithm based on the received historical operation data and current selection of the current staff member to generate a safe operation measure plan, including: In the priority list generation step, if the compliance result meets the preset rules, the importance and access frequency of each substation secondary panel are weighted averaged to quantify the comprehensive score of each substation secondary panel and sort them from high to low to generate a panel cabinet priority list; In the target panel cabinet update step, the target position information of the target substation secondary panel currently selected is used to determine a plurality of adjacent panel cabinets of the target substation secondary panel and their relative position information set, and the target position information of the target substation secondary panel is combined with the historical operation data of the current staff member obtained, the panel cabinet priority list and the target substation secondary panel as the input of the collaborative filtering algorithm, and the updated target substation secondary panel is output; Based on the updated target substation secondary panel, the priority list generation step and the target panel cabinet update step are repeatedly executed until a preset number of repetitions is reached, and the updated target substation secondary panels obtained in each iteration are combined to generate a safe operation measure plan.

8. A method for generating safety operation measures for a substation secondary panel according to claim 7, characterized in that: The target screen cabinet updating step further includes: Acquire historical operation record data of several staff members, and extract historical access to the cabinets of each staff member from the historical operation record data to construct a user-cabinet rating matrix; Based on the user-panel cabinet rating matrix, the similarity between the staff is quantified to obtain a user similarity matrix, which is combined with the target substation secondary panel determined by the current staff member in the current selection, and the current staff member's interest in each substation secondary panel is predicted through a collaborative filtering algorithm model to obtain a recommended panel cabinet ranking list; The top N substation secondary panels with the highest recommendation are selected from the recommended panel cabinet ranking list, weighted by their own importance scores, and the substation secondary panel with the highest weighted score is output as the updated target substation secondary panel.

9. A method for generating safety operation measures for a substation secondary panel according to claim 6, characterized in that: If the compliance result meets the preset rules, the target substation secondary panel is updated by using a collaborative filtering algorithm according to the received historical operation data and current selection of the current staff to generate a safe operation measure plan, including: Acquire the real-time behavior data of the current staff for preprocessing, use an incremental learning algorithm to perform online learning on the preprocessed real-time behavior data, so as to capture the dynamic change trend of the operation behavior of the current staff in real time, and perform initial optimization of the safety operation measure plan based on the dynamic change trend; Obtain the panel cabinet ID, operation type and operation time in the historical operation data of the current staff member, and use the panel cabinet ID and the operation type as the item set, and the operation time as the transaction ID to mine the association rules between different substation secondary panels and operations of the current staff member through the association rule mining algorithm; The historical operation data is classified by using a classification algorithm, and potential risk operations are identified to add risk labels to each substation secondary panel, and the safety operation measures plan that has been initially optimized is secondary optimized based on the association rules and the risk labels to generate a final safety operation measures plan.

10. A system for generating safe operation measures for a secondary substation, characterized in that: Applied to the secondary system connected to each substation secondary panel in the substation, the safety operation measure generation system includes: A data acquisition module, used to acquire real-time panel cabinet layout data of all substation secondary panels in the substation and historical typical panel cabinet layout cases of each substation secondary panel; A list generation module is used to construct the importance evaluation rules of each substation secondary panel, and combine them with the historical typical panel cabinet layout cases to determine the importance and operation sequence of each substation secondary panel through rule reasoning algorithm and case reasoning algorithm, and generate a panel cabinet priority operation list; An interface construction module, for constructing a human-computer interaction interface of the secondary system based on the real-time panel layout data and the panel priority operation list, in combination with the screen size of the secondary system and the logical relationship and business process between the substation secondary panels; A result acquisition module is used to respond to the target substation secondary panel selected by the current staff through the human-computer interaction interface, and obtain the attribute information of the target substation secondary panel to input it into the pre-built panel cabinet selection rule decision tree model for processing to obtain the compliance result; The solution generation module is used to update the target substation secondary panel using a collaborative filtering algorithm based on the received historical operation data and current selection of the current staff if the compliance result meets the preset rules, so as to generate a safe operation measure plan.

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