An intelligent power equipment operation and maintenance method and system

Abstract

The present invention discloses an intelligent power equipment operation and maintenance method and system, belonging to the field of power equipment management, wherein the method comprises: collecting historical operating status data of the power equipment; performing a safe operation cycle attenuation analysis on the power equipment based on the historical operating status data; analyzing the power equipment according to a safe cycle instant trend set; generating an operation and maintenance plan for the power equipment based on the operation and maintenance level cycle analysis results; simulating the power equipment based on the power equipment operation and maintenance plan; optimizing the power equipment operation and maintenance plan according to the simulation results of the power equipment to generate multiple power equipment operation and maintenance optimization plans, wherein the power equipment operation and maintenance optimization plans correspond to the power equipment; executing the power equipment operation and maintenance optimization plans to perform intelligent operation and maintenance on the power equipment. This application solves the problems of low efficiency, high cost, high safety risk, inaccurate fault diagnosis, and irregular maintenance management in the power operation and maintenance in the prior art.

Description

Technical Field

[0001] The present invention relates to the field of power equipment management, and in particular to an intelligent power equipment operation and maintenance method and system. Background Art

[0002] With the continuous advancement of communications and computer network technologies, power grids are moving towards automation and intelligence. Smart grids, with their advantages such as efficient energy utilization, strong defense capabilities, self-healing capabilities, and reduced operating costs, are gradually becoming a core development direction for the power industry. Smart grids are composed of a variety of power equipment, such as power transformers, transmission and distribution networks, and control and relay protection devices. The stable operation of these devices is crucial to ensuring the security and reliability of smart grids.

[0003] Traditional power operation and maintenance methods, such as incident repairs and scheduled maintenance, are no longer able to meet the needs of modern smart grids. Incident repairs often result in troubleshooting after a fault has occurred, while scheduled maintenance can cause equipment to be shut down for repairs at unnecessary times, resulting in wasted resources.

[0004] In summary, this application aims to solve the problems of low efficiency, high cost, high safety risks, inaccurate fault diagnosis and irregular maintenance management in traditional power operation and maintenance. Summary of the Invention

[0005] This application provides an intelligent power equipment operation and maintenance method and system, aiming to solve the problems of low efficiency, high cost, high safety risk, inaccurate fault diagnosis and irregular maintenance management in the existing power operation and maintenance technology.

[0006] In view of the above problems, the present application provides an intelligent power equipment operation and maintenance method and system.

[0007] The first aspect disclosed in the present application provides an intelligent power equipment operation and maintenance method, which includes collecting historical operating status data of multiple power equipment in a target area; performing a safe operation cycle attenuation analysis on the multiple power equipment based on the historical operating status data to obtain a safe cycle instantaneous trend set; analyzing the multiple power equipment according to the safe cycle instantaneous trend set to determine an operation and maintenance level cycle analysis result; generating operation and maintenance plans for multiple power equipment based on the operation and maintenance level cycle analysis result; simulating the multiple power equipment based on the multiple power equipment operation and maintenance plans to generate simulation results for multiple power equipment; optimizing the multiple power equipment operation and maintenance plans according to the simulation results of the multiple power equipment to generate multiple power equipment operation and maintenance optimization plans, and the multiple power equipment operation and maintenance optimization plans have a corresponding relationship with the multiple power equipment; executing the multiple power equipment operation and maintenance optimization plans to perform intelligent operation and maintenance on the multiple power equipment.

[0008] Another aspect disclosed in the present application provides an intelligent power equipment operation and maintenance system, which includes a historical data acquisition module: used to collect historical operating status data of multiple power equipment in a target area; a periodic decay analysis module: used to perform safe operation periodic decay analysis on multiple power equipment based on the historical operating status data, and obtain a safe period instantaneous trend set; a periodic analysis result determination module: used to analyze multiple power equipment according to the safe period instantaneous trend set, and determine the operation and maintenance level periodic analysis result; an operation and maintenance plan generation module: used to generate operation and maintenance plans for multiple power equipment based on the operation and maintenance level periodic analysis result; a simulation result generation module: used to simulate multiple power equipment based on the multiple power equipment operation and maintenance plans, and generate simulation results for multiple power equipment; an operation and maintenance optimization plan generation module: used to optimize multiple power equipment operation and maintenance plans according to the simulation results of multiple power equipment, and generate multiple power equipment operation and maintenance optimization plans, and the multiple power equipment operation and maintenance optimization plans have a corresponding relationship with the multiple power equipment; an intelligent operation and maintenance module: used to execute the multiple power equipment operation and maintenance optimization plans, and perform intelligent operation and maintenance on multiple power equipment.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] By collecting historical operating status data of multiple power equipment in the target area, a safe operation cycle attenuation analysis is performed to obtain a safe cycle instant trend set. Based on these trend sets, the operation and maintenance level cycle of the power equipment is analyzed to determine the operation and maintenance priority. According to the analysis results, a corresponding operation and maintenance plan is generated, and the feasibility of the plan is verified through simulation. According to the simulation results, the operation and maintenance plan is optimized to form an operation and maintenance optimization plan corresponding to the power equipment, and these optimization plans are executed to realize the intelligent operation and maintenance of the power equipment. It solves the problems of low efficiency, high cost, high safety risk, inaccurate fault diagnosis and irregular maintenance management in the existing power operation and maintenance technology, achieves the goal of improving the operating efficiency, reliability and safety of power equipment, reducing operation and maintenance costs, and providing strong support for the development of smart grids.

[0011] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 A flowchart of an intelligent power equipment operation and maintenance method is provided for an embodiment of the present application;

[0013] Figure 2 A structural diagram of an intelligent power equipment operation and maintenance system is provided for an embodiment of the present application.

[0014] Explanation of the accompanying symbols: historical data collection module 11, periodic attenuation analysis module 12, periodic analysis result determination module 13, operation and maintenance plan generation module 14, simulation result generation module 15, operation and maintenance optimization plan generation module 16, intelligent operation and maintenance module 17. DETAILED DESCRIPTION

[0015] The overall idea of ​​the technical solution provided by this application is as follows:

[0016] The embodiment of the present application provides an intelligent power equipment operation and maintenance method and system. By collecting the historical operating status data of multiple power equipment in the target area, analyzing the attenuation of the safe operation cycle of these equipment, and obtaining the instantaneous trend set of the safe cycle. Subsequently, based on these trend sets, a detailed operation and maintenance level cycle analysis is performed on each power equipment to clarify the operation and maintenance priority of each equipment. Then, based on the analysis results, a targeted operation and maintenance plan is formulated. In order to verify the effectiveness of the operation and maintenance plan, the present application uses simulation technology to simulate the operation of multiple power equipment and generate simulation results. Based on these simulation results, the operation and maintenance plan is optimized to form a more optimized operation and maintenance plan to ensure that the plan matches the specific power equipment. Finally, these optimized operation and maintenance plans are executed to realize intelligent operation and maintenance management of power equipment and ensure the stable operation of the equipment.

[0017] After introducing the basic principles of the present application, various non-limiting implementation methods of the present application will be specifically introduced in conjunction with the drawings in the specification.

[0018] Example 1

[0019] like Figure 1 As shown, an embodiment of the present application provides an intelligent power equipment operation and maintenance method, the method comprising:

[0020] Step S100: Collect historical operating status data of multiple power equipment in a target area.

[0021] Specifically: collect historical operating data of all power equipment (such as transformers, circuit breakers, cables, etc.) in the target area. The historical operating status data includes parameters such as voltage, current, temperature, humidity, vibration, as well as equipment operation logs and fault records. Among them, the target area usually refers to a specific geographical range or area where intelligent power equipment operation and maintenance management is required. This area can be a city, an industrial area, a power grid subnet, or any area with clear boundaries and a specific collection of power equipment.

[0022] This step can provide strong data support for subsequent operation and maintenance management by collecting historical operating status data of multiple power equipment in the target area.

[0023] Step S200: performing a safety operation cycle attenuation analysis on a plurality of power equipment based on the historical operation status data to obtain a safety cycle instant trend set.

[0024] Specifically: using the historical operating status data, an in-depth analysis of the operating status of the power equipment is conducted, including steps such as data preprocessing, feature extraction, data grouping and division, model construction and training, model verification and optimization, performance degradation prediction, and construction of a safety cycle instant trend set. Among them, the degradation analysis refers to an evaluation process for the gradual decline in the performance of power equipment over time. Its goal is to identify patterns in the performance of power equipment over time by analyzing historical data. This includes a gradual decline in performance indicators, an increase in failure frequency, or other trends related to equipment aging. The safety cycle instant trend set contains information such as the performance degradation trend and remaining safe operating time of each power device to provide support for subsequent operation and maintenance decisions.

[0025] This step analyzes the safe operation cycle decay of multiple power equipment based on historical operating status data, obtaining a set of instantaneous safe cycle trends to provide strong support for subsequent operation and maintenance decisions. This helps to identify potential safety hazards in advance, optimize operation and maintenance plans, and improve the reliability and operational efficiency of power equipment.

[0026] Step S300: Analyze multiple power equipment according to the safety cycle instant trend set to determine an operation and maintenance level cycle analysis result.

[0027] Specifically: First, interpret the instantaneous trend set of the safety cycle to understand the trend, speed, and possible turning points or mutation points of the performance degradation of each power equipment.

[0028] Based on the performance degradation trends of power equipment, a series of safety level standards are established. These standards are based on the rate of performance degradation, remaining safe operating time, or other key performance indicators. O&M levels include "Normal," "Attention," and "Emergency," reflecting the current status of the equipment and expected maintenance needs. Based on the equipment's O&M level and current operating status, an appropriate O&M cycle is established for each device. Different O&M levels have different requirements. For example, "Normal"-level equipment may only require routine inspections and maintenance, while "Emergency"-level equipment requires immediate action to avoid safety incidents.

[0029] The O&M cycle refers to the frequency or time interval for O&M operations on power equipment. O&M personnel determine an appropriate O&M cycle based on the equipment's O&M level and performance degradation trends. For equipment with a higher O&M level, the O&M cycle may be shortened to ensure timely detection and resolution of potential safety issues. For equipment with a lower O&M level, the O&M cycle may be extended to reduce unnecessary O&M costs.

[0030] This step analyzes multiple power equipment based on the safety cycle instant trend set to determine the O&M level cycle analysis results. This has significant technical benefits, including accurate prediction and risk assessment, optimized O&M planning, improved O&M efficiency, reduced safety risks, and enhanced O&M management. This helps ensure the safety and stability of the power system and improve the efficiency and quality of O&M work.

[0031] Step S400: generating operation and maintenance plans for a plurality of power equipment based on the operation and maintenance level cycle analysis results.

[0032] Specifically: Based on the overall strategy of the power company and the actual status of the power equipment, clarify the goals of the operation and maintenance plan, such as ensuring stable operation of equipment, reducing failure rates, and optimizing operation and maintenance costs.

[0033] For each power equipment, a corresponding operation and maintenance plan is developed based on the analysis results of its operation and maintenance level cycle. The maintenance plan should include maintenance content, maintenance cycle, maintenance methods (such as preventive maintenance and post-failure maintenance), and required resources (such as manpower, materials, tools, etc.). The goal is to ensure that the equipment operates in optimal condition.

[0034] This step generates multiple O&M plans for power equipment based on the O&M level cycle analysis results. This helps improve the O&M management of power equipment, ensure stable operation of equipment, and optimize the use of O&M resources.

[0035] Step S500: simulating a plurality of power equipment based on the plurality of power equipment operation and maintenance plans to generate simulation results of the plurality of power equipment.

[0036] Specifically: Before the operation and maintenance plan is officially implemented, simulation technology is used to test and verify the plan.

[0037] Select appropriate simulation software or tools based on the characteristics and O&M requirements of the power equipment. Build a simulation model of the power equipment, including its physical model, control logic, and failure modes. Input parameters such as the maintenance plan and monitoring strategy from the O&M plan into the simulation model.

[0038] According to the actual situation, set the simulation conditions, such as running time, load changes, environmental conditions, etc. Consider the impact of different operation and maintenance plans on equipment performance and set different simulation scenarios.

[0039] Run the established simulation model in simulation software to simulate the actual operation of power equipment. Monitor changes in equipment performance parameters such as voltage, current, temperature, and failure rate during the simulation. Record simulation results, including equipment operating status, performance changes, and failure occurrences.

[0040] This step simulates the operation and maintenance plans for multiple power equipment, accurately predicting performance changes under different operation and maintenance strategies. This not only improves the efficiency of O&M plan formulation but also optimizes resource allocation, ensuring efficient and stable operation of power equipment. Simulations can also identify potential problems in advance, reduce the risk of equipment failure, and improve the safety and reliability of the power system.

[0041] Step S600: Optimizing multiple power equipment operation and maintenance plans according to the simulation results of the multiple power equipment to generate multiple power equipment operation and maintenance optimization plans, wherein the multiple power equipment operation and maintenance optimization plans correspond to the multiple power equipment.

[0042] Specifically: First, collect detailed data generated by simulations, including the operating status, performance changes, and fault conditions of each power device. Conduct in-depth analysis of this data to understand the impact of different operation and maintenance solutions on device performance.

[0043] Based on the simulation results, the performance of power equipment under each O&M scenario is evaluated. For example, this may include cost, efficiency, reliability, and safety. Optimization algorithms (such as the taboo search algorithm) are used to optimize the O&M scenarios. The optimal O&M scenario can be automatically searched for based on pre-set objective functions (such as minimizing failure rate or maximizing equipment lifespan). This optimization algorithm generates a corresponding O&M optimization plan for each power equipment. This O&M optimization plan fully considers the equipment's performance characteristics, operating environment, and O&M requirements to ensure optimal equipment operation.

[0044] This step optimizes the operation and maintenance solutions based on the simulation results of multiple power equipment, and generates multiple operation and maintenance optimization solutions corresponding to the power equipment, thereby realizing intelligent and efficient operation and maintenance management of power equipment.

[0045] Step S700: executing the plurality of power equipment operation and maintenance optimization schemes to perform intelligent operation and maintenance on the plurality of power equipment.

[0046] Specifically: Confirm the O&M optimization plan for each power equipment, ensuring all details are consistent with the actual equipment conditions and business needs. Prepare the necessary tools, equipment, and human resources to ensure that all O&M tasks can be executed according to the plan.

[0047] Assign O&M tasks to appropriate staff members based on the specific content of the O&M optimization plan and their skills. Clarify the goals, requirements, and completion deadlines for each task, ensuring each staff member is fully aware of their responsibilities and tasks.

[0048] Staff members began executing various O&M tasks according to assigned tasks and the specific steps of the O&M optimization plan. During the execution process, they maintained communication and collaboration with the team to promptly resolve any issues or difficulties encountered. They also monitored the equipment's operating status and performance data to ensure stable operation within the control of the optimization plan.

[0049] During the O&M process, real-time equipment operating data, performance data, and fault information are collected. This collected data is analyzed to evaluate the effectiveness of the O&M optimization plan and identify potential issues and areas for improvement. Based on the results of this data analysis, necessary adjustments and optimizations are made to the O&M optimization plan. Based on the identified issues and areas for improvement, corresponding improvement measures and plans are developed. The adjusted O&M optimization plan is then reapplied to equipment O&M to continuously improve the equipment's operating status and performance.

[0050] Utilize intelligent monitoring systems to monitor equipment operating status and performance data in real time. Establish early warning and alarm mechanisms to promptly notify personnel and address any equipment anomalies or failures. Use intelligent analysis systems to conduct in-depth analysis of equipment operating data to predict future operating status and potential risks. Record all data and events during the operation and maintenance process to create a complete operation and maintenance record. Summarize and evaluate operation and maintenance work, analyzing effectiveness and areas for improvement. Incorporate operation and maintenance experiences and lessons learned into the company's operation and maintenance management knowledge and database to provide reference for subsequent work.

[0051] This step ensures the effective implementation of O&M optimization plans for multiple power equipment, achieving the goal of intelligent O&M. It not only improves equipment operating efficiency and reliability but also reduces O&M costs and risks.

[0052] Furthermore, the method described in this application also includes:

[0053] Based on the historical operating status data, multiple operating times, multiple equipment performance parameters, and multiple fault maintenance records of multiple electrical equipment are extracted, and data of the multiple equipment performance parameters and the multiple fault maintenance records are divided into training set, supervision set, and test set according to the multiple operating times; a safe operation cycle attenuation model is constructed based on the training set and the supervision set, and when the test set passes the verification, the safe operation cycle attenuation model is output; multiple electrical equipment are analyzed through the safe operation cycle attenuation model to generate multiple performance attenuation speeds, multiple remaining safe operation times, and multiple operation fault prediction information; the safe cycle instantaneous trend set is drawn based on the multiple performance attenuation speeds, the multiple remaining safe operation times, and the multiple operation fault prediction information.

[0054] Specifically, the system extracts the operating time, performance parameters (such as voltage, current, and temperature) and fault repair records of multiple power devices from historical operating status data. Operating time refers to the total time elapsed from the start-up of a power device to its shutdown. Fault repair records detail the repair process, results, and related information associated with the equipment when it fails. Examples include the date, device name, device number, fault description, repair process, and repair results.

[0055] The extracted equipment performance parameters and fault repair records are divided into training, supervision, and test sets based on various operating periods. Typically, the training set is used for model training, the supervision set is used for model validation and adjustment, and the test set is used to evaluate the model's generalization capabilities.

[0056] Based on the training and supervision sets, a safe operation cycle degradation model is constructed using machine learning or statistical methods. This model should be able to describe the performance degradation of power equipment over time and predict potential failures. The constructed safe operation cycle degradation model is validated using a test set. If the model's performance on the test set meets the predetermined requirements, it demonstrates generalizability and can be used for practical analysis. Once the test set passes validation, the safe operation cycle degradation model is output.

[0057] The validated safe operation cycle decay model was used to analyze the performance of multiple power equipment. This included calculating the performance decay rate (i.e., how quickly performance degrades over time), multiple remaining safe operation times (i.e., the remaining time the equipment can maintain a safe operating state), and multiple operational failure predictions (i.e., predicting the type and time of possible future equipment failures).

[0058] Based on the calculated performance degradation rates, remaining safe operating times, and operational failure predictions, a safety cycle instantaneous trend set is drawn. This trend set can intuitively display the performance degradation trend, remaining safe operating time, and potential failure risks of each power device, providing decision support for operations and maintenance personnel.

[0059] This step achieves quantitative analysis and prediction of the performance degradation trends of multiple power equipment by constructing and running a safe operation cycle attenuation model, providing a scientific basis for preventive maintenance and fault warning of power equipment.

[0060] Furthermore, the method described in this application also includes:

[0061] Based on the multiple performance decay rates, the multiple remaining safe operating times, and the multiple operation fault prediction information, a first performance decay rate, a first remaining safe operating time, and a first operation fault prediction information are extracted; based on the first performance decay rate, the first remaining safe operating time, and the first operation fault prediction information, a first comprehensive evaluation index is established for the first power equipment; the operating time of the first power equipment is used as the first coordinate axis, and the first comprehensive evaluation index is used as the second coordinate axis; a first safety cycle instantaneous coordinate system is constructed based on the first coordinate axis and the second coordinate axis; the first historical operating state of the first power equipment is synchronized to the first safety cycle instantaneous coordinate system, and a first safety cycle instantaneous trend is determined; and the first safety cycle instantaneous trend is added to the safety cycle instantaneous trend set.

[0062] Specifically: from the performance degradation rates, remaining safe operating time and operation failure prediction information of multiple power devices, the first performance degradation rate, the first remaining safe operating time and the first operation failure prediction information of the first power device are extracted.

[0063] The first performance decay rate refers to the rate at which the performance parameters of a first power device (i.e., a device selected from multiple power devices) decline over time. This rate is typically determined by comparing the rate of change of the device's performance parameters (such as voltage, current, power, efficiency, etc.) at different time points. A faster performance decay rate indicates a more rapid decline in device performance, potentially requiring more frequent maintenance or earlier replacement.

[0064] The first remaining safe operating time is a prediction of the remaining time the first power equipment can maintain safe operation based on current performance parameters and the expected rate of performance degradation. This time is typically estimated based on the equipment's performance degradation model, historical data, and current operating status. A shorter remaining safe operating time indicates that the equipment is likely nearing the end of its life or requires more urgent maintenance.

[0065] The first operational fault prediction information refers to information about the type, timing, and probability of future equipment failures, derived using machine learning, statistical analysis, or other predictive methods based on the first power equipment's historical operational status data, performance parameters, and fault repair records. This information helps operations and maintenance personnel understand potential equipment issues in advance, enabling them to perform preventative maintenance or develop response strategies.

[0066] Based on the extracted first performance degradation rate, the first remaining safe operation time, and the first operational failure prediction information, a first comprehensive evaluation index is established for the first power equipment. The first comprehensive evaluation index is a comprehensive score, index, or other form that can reflect the overall safe operation status and trend of the power equipment.

[0067] The operating time of the first power equipment is used as the first coordinate axis (X-axis), representing changes over time. The first comprehensive evaluation indicator is used as the second coordinate axis (Y-axis), representing the overall level of the equipment's safe operating status. Using these first and second coordinate axes, a first safety cycle instantaneous coordinate system for the first power equipment is constructed. This coordinate system will be used to display the instantaneous trend of the equipment's safety cycle.

[0068] The first historical operating state of the first power device is synchronized to the first safety period instantaneous coordinate system, that is, historical data points (ie, comprehensive evaluation index values ​​at different time points) are marked on the coordinate system.

[0069] Based on the historical operating status data points of the first power device in the first safety cycle instantaneous coordinate system, a trend line, fitting curve, or other visualization method is used to determine its safety cycle instantaneous trend. This trend reflects the change in device performance over time, including possible attenuation, stability, or improvement trends.

[0070] For other power equipment, repeat the above steps (from extracting key information to adding to the trend set) to construct and display their respective safety cycle instantaneous trends, and add these trends to the safety cycle instantaneous trend set.

[0071] Based on this step, a comprehensive safety cycle instant trend set can be constructed. This trend set can be used to analyze the safety operation status and trends of multiple power equipment, helping operation and maintenance personnel identify potential problems, develop maintenance plans, and optimize resource allocation.

[0072] Furthermore, the method described in this application also includes:

[0073] Based on the instantaneous trend of the first safety cycle, the first power equipment is evaluated to generate a first evaluation result; based on the first evaluation result, first safety status information and a first operation development trend of the first power equipment are generated; based on the first safety status information, safety identification is performed, and the operation and maintenance level of the first power equipment is determined according to the safety identification result; according to the operation and maintenance level of the first power equipment and in combination with the first operation development trend, a first operation and maintenance cycle is formulated; based on the operation and maintenance level of the first power equipment, a dynamic analysis is performed within the first operation and maintenance cycle to determine a first operation and maintenance level cycle analysis result; and the first operation and maintenance level cycle analysis result is added to the operation and maintenance level cycle analysis result.

[0074] Specifically, based on the constructed instantaneous trend of the first safety cycle, a comprehensive analysis is conducted on the performance degradation, remaining safe operating time, and operational failure prediction information of the first power equipment. By comparing historical data, industry standards, and expert experience, the current safety status and future development trends of the first power equipment are evaluated, generating a first assessment result for the first power equipment. This first assessment result should include information such as the equipment's performance status, potential risks, and expected lifespan.

[0075] Based on the assessment results, the current safety status information of the first power device is extracted, such as status labels such as "safe," "warning," and "danger." Simultaneously, based on the assessment results and prediction information, the device's future operational trends are generated, such as the expected time of failure and possible failure types.

[0076] Based on the first safety status information, a safety identification is performed. This includes determining whether the equipment is in a normal, abnormal, or dangerous state. Based on the safety identification results, an operation and maintenance level is determined for the first power equipment. The operation and maintenance level can be classified based on factors such as the risk level and urgency of the equipment, such as "normal," "concern," or "emergency."

[0077] Based on the O&M level of the first power equipment and its operational development trends, a targeted O&M cycle is developed. This O&M cycle includes inspection frequency, maintenance intervals, and replacement cycles. During this defined O&M cycle, the operating status of the first power equipment is continuously monitored and dynamically analyzed. This includes collecting real-time operating data, analyzing performance indicator changes, and predicting potential failures.

[0078] Based on the dynamic analysis results, the operation and maintenance level cycle of the first power equipment is evaluated. This may include adjusting the operation and maintenance level, modifying the operation and maintenance cycle, and proposing a new maintenance strategy.

[0079] Furthermore, the method described in this application also includes:

[0080] Based on the operation and maintenance level of the first power equipment and the first operation and maintenance cycle, multiple simulation operation and maintenance data are set; based on the multiple power equipment operation and maintenance plans, the first power equipment is simulated in combination with the multiple simulation operation and maintenance data to generate an equipment operation and maintenance simulation data set; based on the equipment operation and maintenance simulation data set, the operation simulation data, performance simulation data, and fault simulation data of the first power equipment are determined; based on the operation simulation data, the performance simulation data, and the fault simulation data, the operation and maintenance evaluation of the multiple power equipment operation and maintenance plans is performed to generate multiple operation and maintenance evaluation results; and the multiple operation and maintenance evaluation results are added to the simulation results of the first power equipment.

[0081] Specifically, based on the operation and maintenance level and first operation and maintenance cycle of the first power equipment, multiple simulated operation and maintenance data are set. The simulated operation and maintenance data covers various factors such as the equipment's operating time, load changes, environmental conditions (such as temperature, humidity, pressure, etc.), and operating mode. This data is used to simulate the equipment's operation under different operation and maintenance conditions.

[0082] Using multiple power equipment operation and maintenance plans, combined with pre-defined simulation operation and maintenance data, a simulation is performed on the first power equipment. This process simulates the actual operation of the equipment under different operation and maintenance plans, including its operating status, performance, and potential failures. After the simulation is complete, a device operation and maintenance simulation dataset is generated, containing various simulated data for the equipment under different operation and maintenance plans, such as operating parameters, performance indicators, and failure records. Based on the device operation and maintenance simulation dataset, the operation simulation data, performance simulation data, and failure simulation data for the first power equipment are analyzed and determined. This data details the equipment's performance in the simulation, including its operating efficiency, performance stability, and the frequency and type of failures.

[0083] Based on operational simulation data, performance simulation data, and fault simulation data, multiple power equipment O&M plans are evaluated. The evaluation process considers multiple indicators, such as equipment reliability, cost-effectiveness, and safety, to comprehensively assess the effectiveness of different O&M plans. Multiple O&M evaluation results are generated. Each O&M plan receives one or more evaluation results, which quantify the plan's performance in the simulation.

[0084] Finally, the generated multiple O&M evaluation results are added to the simulation results of the first power equipment. O&M managers can easily view the evaluation results of each O&M solution, compare the advantages and disadvantages of different solutions, and select the O&M solution that best suits the current equipment and O&M environment.

[0085] Through the above steps, operation and maintenance managers can formulate more scientific and reasonable operation and maintenance plans based on the results of simulation and operation and maintenance evaluation, thereby improving the operation and maintenance efficiency and safety of power equipment.

[0086] Furthermore, the method described in this application also includes:

[0087] A taboo table is constructed using a taboo optimization algorithm; the first power equipment operation and maintenance plan is used as an initial solution, and a first operation and maintenance fitness value is calculated based on the simulation results of the first power equipment, and there is a one-to-one correspondence between the first operation and maintenance fitness value and the first power equipment operation and maintenance plan; cross-validation is performed based on the initial solution to generate a candidate solution, and the candidate solution includes the fitness value of the candidate solution; the taboo table is traversed to match the candidate solution, and whether the candidate solution is in the taboo table is determined according to the matching result; if the candidate solution is not in the taboo table, the candidate solution is added to the candidate solution set, and the initial solution is updated with the candidate solution with the largest fitness value based on the candidate solution set to generate an updated solution; the updated solution is added to the taboo table for updating, and it is iterated until the change in fitness value is less than a preset threshold; an updated value of the taboo table is obtained, and the first power equipment operation and maintenance optimization plan is output according to the updated value of the taboo table.

[0088] Specifically, a taboo table is constructed using a taboo optimization algorithm (such as the Tabu Search algorithm). The taboo table is used to record the solutions that have been searched to prevent the algorithm from falling into a local optimal solution and guide the search process to explore new areas.

[0089] The first power equipment operation and maintenance plan is used as the initial solution, and a first operation and maintenance fitness value is calculated based on the simulation results of the first power equipment. This fitness value reflects the performance of the operation and maintenance plan in the simulation and has a one-to-one correspondence with the initial solution (i.e., the first power equipment operation and maintenance plan).

[0090] Cross-validation is performed based on the initial solution to generate multiple candidate solutions. These candidate solutions represent new O&M solutions that have been modified or adjusted from the initial solution. Each candidate solution includes a corresponding fitness value, which is also calculated based on the simulation results.

[0091] The tabu table is traversed to match candidate solutions, and each candidate solution is checked to see if it already exists in the tabu table. The purpose of the tabu table is to prevent the algorithm from repeatedly searching for solutions that have already been evaluated, thereby improving search efficiency.

[0092] If the candidate solution is not in the taboo table (i.e., the solution is new or has not been evaluated), it is added to the candidate solution set. Then, the candidate solution with the largest fitness value is selected from the candidate solution set and used to update the initial solution (i.e., the current optimal solution) to generate a new updated solution.

[0093] The updated solution is added to the tabu table for updating. When updating the tabu table, the length of the tabu table and the update strategy need to be considered to ensure that the algorithm can effectively move in the search space while avoiding falling into local optimal solutions.

[0094] Repeat the above steps to perform an iterative search. During the iteration process, the algorithm continuously generates new candidate solutions, updates the candidate solution set and the initial solution, and updates the tabu table. When the change in fitness value is less than a preset threshold, the algorithm is considered to have converged to a sufficiently good solution and the iteration stops.

[0095] Finally, based on the updated value of the taboo table (i.e., the state of the taboo table when the algorithm stops), an operation and maintenance optimization plan for the first power equipment is output. The operation and maintenance optimization plan is the optimal or nearly optimal operation and maintenance plan found under given conditions, which can help operation and maintenance managers develop more scientific and reasonable operation and maintenance plans, thereby improving the safe and stable operation of the equipment.

[0096] Furthermore, the method described in this application also includes:

[0097] According to the taboo table, extract the initial value of the taboo table, wherein the initial value of the taboo table has a taboo initial fitness; determine whether the fitness value of the candidate solution is greater than or equal to the taboo initial fitness; if the fitness value of the candidate solution is greater than or equal to the taboo initial fitness, replace the initial value of the taboo table with the candidate solution corresponding to the fitness value of the candidate solution, and set it as the updated value of the taboo table; if it is less than, set the initial value of the taboo table to the updated value of the taboo table.

[0098] Specifically: First, based on the current state of the taboo table, the initial value of the taboo table is extracted. The initial value is usually an evaluated solution recorded in the taboo table and its corresponding taboo initial fitness.

[0099] Next, determine whether the fitness value of the candidate solution currently generated is greater than or equal to the taboo initial fitness. This step is to evaluate whether the candidate solution is better than the solution recorded in the taboo table.

[0100] If the candidate solution's fitness is greater than or equal to the initial tabu fitness, it indicates that the candidate solution is a better solution. At this point, the initial tabu table value is replaced with the candidate solution corresponding to the candidate solution's fitness value, and this value is set as the updated tabu table value. The purpose of this step is to update the tabu table with a better solution so that subsequent searches can be based on this better solution.

[0101] Case 2: If the candidate solution's fitness is less than the initial tabu fitness, it indicates that the candidate solution is not as good as the solution recorded in the tabu table. In this case, the tabu table remains unchanged, and the initial tabu table value is directly set to the updated tabu table value. This step is to avoid adding poorly performing solutions to the tabu table and ensure that the tabu table always records the best performing solutions.

[0102] Based on this step, the tabu table can be dynamically updated, always recording the best solutions encountered during the search process. This helps the algorithm avoid repeatedly evaluating poor solutions in subsequent searches, improves search efficiency, and helps find the global optimal solution or a near-optimal solution.

[0103] In summary, the intelligent power equipment operation and maintenance method provided by the embodiments of the present application has the following technical effects:

[0104] 1. By deeply analyzing the historical operating data of power equipment, we accurately predict the decline in its safe operating cycle and develop targeted O&M plans. The application of simulation technology effectively verifies the feasibility of the O&M plans and generates optimized O&M plans through optimization. Ultimately, implementing these optimized plans enables intelligent O&M of power equipment, significantly improving O&M efficiency and equipment operational stability.

[0105] 2. By constructing and operating a safe operation cycle attenuation model, we have achieved quantitative analysis and prediction of the performance attenuation trends of multiple power equipment, providing a scientific basis for preventive maintenance and fault warning of power equipment.

[0106] 3. By setting multiple simulation operation and maintenance data sets and combining them with specific operation and maintenance plans, the first power equipment was simulated, generating a comprehensive dataset containing operation, performance, and fault simulation data. Based on these datasets, the operation and maintenance plans were accurately evaluated, generating multiple operation and maintenance evaluation results, providing strong support for the intelligent operation and maintenance of power equipment and improving the scientific nature and accuracy of operation and maintenance decision-making.

[0107] Example 2

[0108] Based on the same inventive concept as the intelligent power equipment operation and maintenance method in the above embodiment, Figure 2 As shown, an embodiment of the present application provides an intelligent power equipment operation and maintenance system, which includes:

[0109] Historical data collection module 11: used to collect historical operating status data of multiple power equipment in the target area;

[0110] The cycle decay analysis module 12 is configured to perform a safety cycle decay analysis on a plurality of power devices based on the historical operation status data to obtain a safety cycle instant trend set;

[0111] The cycle analysis result determination module 13 is used to analyze multiple power equipment according to the safety cycle instant trend set to determine the operation and maintenance level cycle analysis result;

[0112] An operation and maintenance plan generating module 14 is configured to generate operation and maintenance plans for a plurality of power equipment based on the operation and maintenance level cycle analysis result;

[0113] Simulation result generation module 15: used to simulate multiple power equipment based on the multiple power equipment operation and maintenance plans, and generate simulation results for multiple power equipment

[0114] An operation and maintenance optimization solution generating module 16 is configured to optimize a plurality of operation and maintenance solutions for power equipment according to the simulation results of the plurality of power equipment, and generate a plurality of operation and maintenance optimization solutions for power equipment, wherein the plurality of operation and maintenance optimization solutions for power equipment correspond to the plurality of power equipment;

[0115] The intelligent operation and maintenance module 17 is used to execute the multiple power equipment operation and maintenance optimization plans and perform intelligent operation and maintenance on the multiple power equipment.

[0116] Furthermore, the system is also used for:

[0117] Extract multiple operating times, multiple equipment performance parameters, and multiple fault maintenance records of multiple power equipment based on the historical operating status data

[0118] Dividing the plurality of equipment performance parameters and the plurality of fault maintenance records into a training set, a supervision set, and a test set according to the plurality of operating times;

[0119] Building a safe operation cycle attenuation model based on the training set and the supervision set, and outputting the safe operation cycle attenuation model when the test set passes verification;

[0120] Analyze multiple power equipment using the safe operation cycle attenuation model to generate multiple performance attenuation rates, multiple remaining safe operation times, and multiple operation fault prediction information;

[0121] The safety period instant trend set is drawn based on the multiple performance decay rates, the multiple remaining safe operation times, and the multiple operation failure prediction information.

[0122] Furthermore, the system is also used for:

[0123] Extracting a first performance degradation rate, a first remaining safe operation time, and first operation failure prediction information based on the multiple performance degradation rates, the multiple remaining safe operation time, and the multiple operation failure prediction information;

[0124] Establishing a first comprehensive evaluation index for the first power equipment based on the first performance degradation rate, the first remaining safe operation time, and the first operation fault prediction information;

[0125] The operating time of the first power equipment is used as a first coordinate axis, and the first comprehensive evaluation index is used as a second coordinate axis;

[0126] Constructing a first safety period instantaneous coordinate system according to the first coordinate axis and the second coordinate axis;

[0127] Synchronizing a first historical operating state of the first power device to the first safety period instantaneous coordinate system to determine the first safety period instantaneous trend;

[0128] The first safety period instantaneous trend is added to the safety period instantaneous trend set.

[0129] Furthermore, the system is also used for:

[0130] Evaluate the first power equipment based on the instantaneous trend of the first safety period to generate a first evaluation result;

[0131] generating first safety status information and a first operation development trend of the first power equipment according to the first evaluation result;

[0132] performing safety identification based on the first safety status information, and determining an operation and maintenance level of the first power equipment according to a safety identification result;

[0133] Formulate a first operation and maintenance cycle according to the operation and maintenance level of the first power equipment and in combination with the first operation development trend;

[0134] Performing a dynamic analysis within the first operation and maintenance cycle according to the operation and maintenance level of the first power equipment to determine a first operation and maintenance level cycle analysis result;

[0135] The first operation and maintenance level cycle analysis result is added to the operation and maintenance level cycle analysis result.

[0136] Furthermore, the system is also used for:

[0137] Setting a plurality of simulation operation and maintenance data based on the operation and maintenance level of the first power equipment and the first operation and maintenance cycle;

[0138] Based on the multiple power equipment operation and maintenance plans, and in combination with the multiple simulation operation and maintenance data, simulate the first power equipment to generate an equipment operation and maintenance simulation data set;

[0139] Determining operation simulation data, performance simulation data, and fault simulation data of the first power equipment based on the equipment operation and maintenance simulation data set;

[0140] Performing operation and maintenance evaluation on the plurality of power equipment operation and maintenance plans based on the operation simulation data, the performance simulation data, and the fault simulation data, and generating a plurality of operation and maintenance evaluation results;

[0141] The multiple operation and maintenance evaluation results are added to the simulation results of the first power equipment.

[0142] Furthermore, the system is also used for:

[0143] Use the tabu optimization algorithm to build a tabu table;

[0144] Taking the first power equipment operation and maintenance plan as an initial solution, and calculating a first operation and maintenance fitness value based on the simulation result of the first power equipment, wherein the first operation and maintenance fitness value has a one-to-one correspondence with the first power equipment operation and maintenance plan;

[0145] Performing cross-validation based on the initial solution to generate a candidate solution, wherein the candidate solution includes a fitness value of the candidate solution;

[0146] Traversing the taboo table to match the candidate solution, and determining whether the candidate solution is in the taboo table according to the matching result;

[0147] If the candidate solution is not in the taboo table, the candidate solution is added to a candidate solution set, and the initial solution is updated based on the candidate solution with the largest fitness value in the candidate solution set to generate an updated solution;

[0148] Adding the updated solution to the taboo table for updating, thereby iterating until the change in fitness value is less than a preset threshold;

[0149] Obtaining an updated value of the taboo table, and outputting a first power equipment operation and maintenance optimization plan according to the updated value of the taboo table.

[0150] Furthermore, the system is also used for:

[0151] Extracting a taboo table initial value according to the taboo table, wherein the taboo table initial value has a taboo initial fitness;

[0152] Determining whether the fitness value of the candidate solution is greater than or equal to the taboo initial fitness;

[0153] If the fitness value of the candidate solution is greater than or equal to the taboo initial fitness, the initial value of the taboo table is replaced according to the candidate solution corresponding to the fitness value of the candidate solution and set as the updated value of the taboo table;

[0154] If it is less than, the initial value of the taboo table is set as the updated value of the taboo table.

[0155] Any step of the method described above can be stored as a computer instruction or program in an unlimited computer memory, and can be called and recognized by an unlimited computer processor to implement any method in the embodiments of the present application, without any unnecessary restrictions.

[0156] Furthermore, the terms "first" or "second" as described above may not only represent an order relationship but may also represent a specific concept and / or refer to the selection of multiple elements individually or collectively. Obviously, those skilled in the art may make various modifications and variations to this application without departing from the scope of this application. Thus, if such modifications and variations fall within the scope of this application and its equivalents, this application is intended to include such modifications and variations.

Claims

1. An intelligent power equipment operation and maintenance method, characterized in that: The method comprises: Collect historical operating status data of multiple power equipment in the target area; Performing a safety operation cycle attenuation analysis on a plurality of power equipment based on the historical operation status data to obtain a safety cycle instant trend set; Analyze multiple power equipment according to the safety cycle instant trend set to determine the operation and maintenance level cycle analysis results; generating an operation and maintenance plan for a plurality of power equipment based on the operation and maintenance level cycle analysis result; Performing simulations on multiple power equipment based on the multiple power equipment operation and maintenance plans to generate simulation results for the multiple power equipment; Optimizing multiple power equipment operation and maintenance plans according to the simulation results of the multiple power equipment to generate multiple power equipment operation and maintenance optimization plans, wherein the multiple power equipment operation and maintenance optimization plans correspond to the multiple power equipment; Executing the plurality of power equipment operation and maintenance optimization plans to perform intelligent operation and maintenance on the plurality of power equipment; The method of performing a safe operation cycle attenuation analysis on a plurality of power equipment based on the historical operation status data to obtain a safe cycle instant trend set includes: Extracting multiple operating times, multiple equipment performance parameters, and multiple fault maintenance records of multiple power equipment based on the historical operating status data; Dividing the plurality of equipment performance parameters and the plurality of fault maintenance records into a training set, a supervision set, and a test set according to the plurality of operating times; Building a safe operation cycle attenuation model based on the training set and the supervision set, and outputting the safe operation cycle attenuation model when the test set passes verification; Analyze multiple power equipment using the safe operation cycle attenuation model to generate multiple performance attenuation rates, multiple remaining safe operation times, and multiple operation fault prediction information; The safety period instant trend set is drawn based on the multiple performance decay rates, the multiple remaining safe operation times, and the multiple operation failure prediction information.

2. The method according to claim 1, wherein The method includes: drawing the safety period instant trend set based on the multiple performance decay rates, the multiple remaining safe operation times, and the multiple operation failure prediction information; Extracting a first performance degradation rate, a first remaining safe operation time, and first operation failure prediction information based on the multiple performance degradation rates, the multiple remaining safe operation time, and the multiple operation failure prediction information; Establishing a first comprehensive evaluation index for the first power equipment based on the first performance degradation rate, the first remaining safe operation time, and the first operation fault prediction information; The operating time of the first power equipment is used as a first coordinate axis, and the first comprehensive evaluation index is used as a second coordinate axis; Constructing a first safety period instantaneous coordinate system according to the first coordinate axis and the second coordinate axis; Synchronizing a first historical operating state of the first power device to the first safety period instantaneous coordinate system to determine the first safety period instantaneous trend; The first safety period instantaneous trend is added to the safety period instantaneous trend set.

3. The method according to claim 2, wherein Analyzing multiple power equipment according to the safety cycle instant trend set to determine an operation and maintenance level cycle analysis result, the method includes: Evaluate the first power equipment based on the instantaneous trend of the first safety period to generate a first evaluation result; generating first safety status information and a first operation development trend of the first power equipment according to the first evaluation result; performing safety identification based on the first safety status information, and determining an operation and maintenance level of the first power equipment according to a safety identification result; Formulate a first operation and maintenance cycle according to the operation and maintenance level of the first power equipment and in combination with the first operation development trend; Performing a dynamic analysis within the first operation and maintenance cycle according to the operation and maintenance level of the first power equipment to determine a first operation and maintenance level cycle analysis result; The first operation and maintenance level cycle analysis result is added to the operation and maintenance level cycle analysis result.

4. The method according to claim 3, wherein Simulating multiple power equipment based on the multiple power equipment operation and maintenance plans to generate simulation results for the multiple equipment includes: Setting a plurality of simulation operation and maintenance data based on the operation and maintenance level of the first power equipment and the first operation and maintenance cycle; Based on the multiple power equipment operation and maintenance plans, and in combination with the multiple simulation operation and maintenance data, simulate the first power equipment to generate an equipment operation and maintenance simulation data set; Determining operation simulation data, performance simulation data, and fault simulation data of the first power equipment based on the equipment operation and maintenance simulation data set; Performing operation and maintenance evaluation on the plurality of power equipment operation and maintenance plans based on the operation simulation data, the performance simulation data, and the fault simulation data, and generating a plurality of operation and maintenance evaluation results; The multiple operation and maintenance evaluation results are added to the simulation results of the first power equipment.

5. The method according to claim 4, wherein Optimizing the multiple power equipment operation and maintenance plans according to the simulation results of the multiple power equipment to generate multiple power equipment operation and maintenance optimization plans, the method comprising: Use the tabu optimization algorithm to build a tabu table; Taking the first power equipment operation and maintenance plan as an initial solution, and calculating a first operation and maintenance fitness value based on the simulation result of the first power equipment, wherein the first operation and maintenance fitness value has a one-to-one correspondence with the first power equipment operation and maintenance plan; Performing cross-validation based on the initial solution to generate a candidate solution, wherein the candidate solution includes a fitness value of the candidate solution; Traversing the taboo table to match the candidate solution, and determining whether the candidate solution is in the taboo table according to the matching result; If the candidate solution is not in the taboo table, the candidate solution is added to a candidate solution set, and the initial solution is updated based on the candidate solution with the largest fitness value in the candidate solution set to generate an updated solution; Adding the updated solution to the taboo table for updating, thereby iterating until the change in fitness value is less than a preset threshold; Obtaining an updated value of the taboo table, and outputting a first power equipment operation and maintenance optimization plan according to the updated value of the taboo table.

6. The method according to claim 5, wherein The method for updating the taboo table value includes: Extracting a taboo table initial value according to the taboo table, wherein the taboo table initial value has a taboo initial fitness; Determining whether the fitness value of the candidate solution is greater than or equal to the taboo initial fitness; If the fitness value of the candidate solution is greater than or equal to the taboo initial fitness, the initial value of the taboo table is replaced according to the candidate solution corresponding to the fitness value of the candidate solution and set as the updated value of the taboo table; If it is less than, the initial value of the taboo table is set as the updated value of the taboo table.

7. An intelligent power equipment operation and maintenance system, characterized in that: For executing the method according to any one of claims 1 to 6, the system comprises: Historical data collection module: used to collect historical operating status data of multiple power equipment in the target area; A cycle decay analysis module is configured to perform a safe operation cycle decay analysis on a plurality of power devices based on the historical operation status data to obtain a safe cycle instant trend set, wherein the safe cycle instant trend set includes the performance decay trend and the remaining safe operation time information of each power device; A cycle analysis result determination module is used to analyze multiple power equipment according to the safety cycle instant trend set and determine the operation and maintenance level cycle analysis result; An operation and maintenance plan generating module is configured to generate operation and maintenance plans for a plurality of power equipment based on the operation and maintenance level cycle analysis results; Simulation result generation module: used to simulate multiple power equipment based on the multiple power equipment operation and maintenance plans, and generate simulation results for multiple power equipment An operation and maintenance optimization plan generation module is configured to optimize a plurality of operation and maintenance plans for power equipment according to the simulation results of the plurality of power equipment, and generate a plurality of operation and maintenance optimization plans for power equipment, wherein the plurality of operation and maintenance optimization plans for power equipment correspond to the plurality of power equipment; Intelligent operation and maintenance module: used to execute the multiple power equipment operation and maintenance optimization plans and perform intelligent operation and maintenance on multiple power equipment.

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