Substation operation and maintenance intelligent planning system based on GIM model

Abstract

The invention discloses a transformer substation operation and maintenance intelligent planning system based on a GIM model, and belongs to the technical field of transformer substation operation and maintenance. The transformer substation operation and maintenance intelligent planning system comprises a three-dimensional modeling module, a data acquisition module, an operation and maintenance analysis module and an operation and maintenance planning module; the data acquisition module is used for performing real-time data acquisition on the near-zero carbon transformer substation to obtain operation acquisition data corresponding to the near-zero carbon transformer substation; the three-dimensional modeling module is used for performing three-dimensional modeling on the near-zero carbon transformer substation based on a GIM standard to obtain a transformer substation model; acquiring operation acquisition data, and dynamically displaying the substation model according to the operation acquisition data; the operation and maintenance analysis module is used for performing real-time operation and maintenance analysis based on the substation model to obtain a corresponding operation and maintenance task; the operation and maintenance planning module is used for carrying out operation and maintenance planning and establishing and updating an operation and maintenance resource library; an operation and maintenance task is planned according to the operation and maintenance resource library, and an operation and maintenance planning result is displayed to corresponding operation and maintenance personnel; and carrying out operation and maintenance training on corresponding operation and maintenance personnel according to the operation and maintenance task.

Description

Technical Field

[0001] The present invention belongs to the technical field of substation operation and maintenance, and specifically relates to an intelligent operation and maintenance planning system for substations based on the GIM model. Background Art

[0002] As a core component of the power system, the operation and maintenance management of substations is crucial for ensuring the safe and stable operation of the power system. However, there are many deficiencies in the traditional substation operation and maintenance management methods, such as low efficiency of manual inspections, untimely fault discovery, unreasonable allocation of operation and maintenance resources, etc. With the rapid development of information technology, intelligent and automated operation and maintenance management methods have gradually become the industry trend.

[0003] The GIM model (Grid Information Model) is a power grid information modeling method based on geographic information system (GIS). It digitally processes the components of the power grid, uses the information model as a carrier, integrates the information of each element throughout its life cycle, and realizes the efficient, accurate, and comprehensive application of information.

[0004] Based on this, in order to achieve intelligent operation and maintenance processing of substations, the present invention provides an intelligent operation and maintenance planning system for substations based on the GIM model. Summary of the Invention

[0005] In order to solve the problems existing in the above solution, the present invention provides an intelligent operation and maintenance planning system for substations based on the GIM model.

[0006] The object of the present invention can be achieved through the following technical solutions:

[0007] An intelligent operation and maintenance planning system for substations based on the GIM model, including a three-dimensional modeling module, a data acquisition module, an operation and maintenance analysis module, and an operation and maintenance planning module;

[0008] The data acquisition module is used to collect real-time data of a nearly zero-carbon substation to obtain operation acquisition data corresponding to the nearly zero-carbon substation.

[0009] Further, a real-time optimization analysis is performed on the acquisition scheme of the operation acquisition data, and the optimization method includes:

[0010] Obtain the applied acquisition scheme, identify each acquisition item corresponding to the operation acquisition data according to the acquisition scheme; establish an optimization library according to the acquisition item, and the optimization library is used to store the optimization methods corresponding to the acquisition item;

[0011] Perform real-time operation and maintenance optimization analysis on the nearly zero-carbon substation according to the optimization library to obtain an optimization adjustment scheme, and the user makes an optimization adjustment according to the optimization adjustment scheme.

[0012] Further, the method for establishing the optimization library includes:

[0013] Performing feature extraction on the collection scheme according to the collection items to form a collection feature chain corresponding to the collection items, where the collection feature chain is composed of collection features, conversion features, and transmission features corresponding to the collection method, data conversion method, and transmission method respectively;

[0014] Performing a collection simulation evaluation on the collection items according to the collection feature chain to obtain the duration chain of the collection items;

[0015] Analyzing in real time the optimization methods that meet the optimization requirements according to the collection feature chain and the duration chain, and establishing an optimization library according to the optimization methods corresponding to the collection items.

[0016] Further, the method for obtaining the duration chain includes:

[0017] Obtaining historical operation collection data according to the collection feature chain of the collection items, and identifying and summarizing a number of duration analysis chains corresponding to the collection items according to the historical operation collection data;

[0018] Marking the duration analysis chain as TF(A i , B i , C i ), where i is the subscript, i = 1, 2,..., n, and n is the number of duration analysis chains; A i represents the collection duration of the corresponding duration analysis chain; B i represents the conversion duration of the corresponding duration analysis chain, and C i represents the transmission duration of the corresponding duration analysis chain;

[0019] Setting a merging formula, and the merging formula is:

[0020]

[0021] In the formula: HB is the merged value; HB1 and HB2 are the two values to be merged, respectively marked as the first value and the second value; FZ1 and FZ2 are the additional values of the first value and the second value respectively, and the additional value = the number of merges + 1;

[0022] Performing a merging analysis on the duration analysis chain TF(A i , B i , C i ) through the merging formula to obtain the duration chain of the collection items.

[0023] Further, the method for analyzing in real time the optimization methods that meet the optimization requirements according to the collection feature chain and the duration chain includes:

[0024] Screen the real-time solutions according to the acquisition feature chain, obtain several candidate methods, evaluate the duration chain of the candidate methods, calculate the cumulative duration of the duration chain, and mark it as the candidate value;

[0025] Calculate the cumulative duration of the corresponding duration chain of the acquisition item, and mark it as the application value;

[0026] Establish an optimization evaluation model. The expression of the optimization evaluation model is:

[0027]

[0028] In the formula: (DZ, YZ, YQ) are input data, DZ is the candidate value; YZ is the application value; YQ is the optimization requirement; (YZ - DZ) / YZ → YQ means that (YZ - DZ) / YZ meets the optimization requirement; the output data is the optimization evaluation value YP(DZ, YZ, YQ), and the optimization evaluation value is 1 or 0;

[0029] Analyze the candidate value and the application value through the optimization evaluation model to obtain the optimization evaluation value of the corresponding candidate method;

[0030] Mark the candidate method with an optimization evaluation value of 1 as the optimized method.

[0031] Furthermore, the method for optimizing the operation and maintenance of a nearly zero-carbon substation according to the optimization library includes:

[0032] Establish an operation and maintenance simulation model, which is used to analyze the corresponding acquisition plan and obtain the background simulation value of the acquisition plan under the corresponding operation and maintenance background;

[0033] Perform one-by-one optimization simulation according to the operation and maintenance simulation model and the optimization library to obtain the optimization simulation value of the corresponding simulation optimization plan;

[0034] Determine the optimization adjustment plan according to the optimization simulation value.

[0035] Furthermore, the method for establishing the operation and maintenance simulation model includes:

[0036] Obtain the historical operation and maintenance data of the nearly zero-carbon substation, and determine the operation and maintenance requirements of the nearly zero-carbon substation and the corresponding loss curve according to the historical operation and maintenance data. The horizontal axis of the loss curve is the duration, and the vertical axis is the economic equivalent loss value;

[0037] Set several operation and maintenance backgrounds according to the operation and maintenance requirements and historical operation and maintenance data, and set the corresponding background weights for the operation and maintenance backgrounds; integrate the operation and maintenance requirements, loss curve, operation and maintenance background, and background weights into modeling materials;

[0038] Establish an operation and maintenance simulation model according to the modeling materials.

[0039] Furthermore, the calculation formula for optimizing the simulation value is as follows:

[0040]

[0041] In the formula: YU is the optimized simulation value; j represents the corresponding operation and maintenance background, j = 1, 2,..., m, where m is the number of operation and maintenance backgrounds; λ j represents the background proportion of the corresponding operation and maintenance background; BM j represents the background simulation value of the corresponding simulation optimization scheme under the corresponding operation and maintenance background.

[0042] The three-dimensional modeling module is used to perform three-dimensional modeling on the nearly zero-carbon substation based on the GIM standard to obtain a substation model; obtain operation acquisition data, and the substation model is dynamically displayed according to the operation acquisition data.

[0043] The operation and maintenance analysis module is used to perform real-time operation and maintenance analysis based on the substation model to obtain corresponding operation and maintenance tasks.

[0044] The operation and maintenance planning module is used to carry out operation and maintenance planning, establish and update an operation and maintenance resource library, which is used to store various operation and maintenance resource information; plan operation and maintenance tasks according to the operation and maintenance resource library to obtain corresponding operation and maintenance planning results, and display the operation and maintenance planning results to corresponding operation and maintenance personnel; conduct operation and maintenance training for corresponding operation and maintenance personnel according to the operation and maintenance tasks, and update the operation and maintenance resource library according to the training results.

[0045] Furthermore, the method for conducting operation and maintenance training for corresponding operation and maintenance personnel according to the operation and maintenance tasks includes:

[0046] Identify the operation and maintenance tasks, obtain operation and maintenance analysis background data and operation and maintenance processing methods according to the operation and maintenance tasks, and integrate the operation and maintenance tasks, operation and maintenance analysis background data, and operation and maintenance processing methods into operation and maintenance training materials;

[0047] Determine the material time period according to the operation and maintenance training materials, and generate a training model according to the material time period and the substation model;

[0048] Let the user determine the training mode, and perform mode processing on the training model according to the training mode; display the training model to corresponding operation and maintenance personnel, and the operation and maintenance personnel perform operation and maintenance simulation processing according to the training model, and conduct operation and maintenance evaluation according to the simulation processing process to obtain training results.

[0049] Compared with the prior art, the beneficial effects of the present invention are:

[0050] Through the mutual cooperation among the three-dimensional modeling module, data acquisition module, operation and maintenance analysis module, and operation and maintenance planning module, the intelligent operation and maintenance planning of the near-zero-carbon substation is realized; the operation status of the near-zero-carbon substation is monitored in real time, abnormal situations are discovered and processed in a timely manner, and the frequency and time of manual inspections are reduced. Through the intelligent planning algorithm, the system can automatically allocate operation and maintenance resources, optimize operation and maintenance tasks, and improve operation and maintenance efficiency. It can provide rich operation and maintenance data and analysis results, providing scientific decision-making support for operation and maintenance personnel. Through data mining and machine learning technologies, the system can continuously optimize operation and maintenance strategies and improve the intelligent level of operation and maintenance management. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0052] Figure 1 It is a block diagram of the principle of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0053] The following will clearly and completely describe the technical solutions of the present invention in conjunction with the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0054] As Figure 1 shown, a substation operation and maintenance intelligent planning system based on the GIM model includes a three-dimensional modeling module, a data acquisition module, an operation and maintenance analysis module, and an operation and maintenance planning module;

[0055] The data acquisition module is used to collect real-time data of the near-zero-carbon substation to obtain the operation acquisition data corresponding to the near-zero-carbon substation, including equipment status, electrical parameters, environmental information, etc.; these data are the basis for subsequent analysis and planning.

[0056] In one embodiment, the operation acquisition data can be collected according to the existing data acquisition method.

[0057] In one embodiment, in order to maximize the timeliness of subsequent display and analysis of the operation acquisition data, it is necessary to analyze the applied acquisition equipment and data conversion and transmission methods. Therefore, in this embodiment, the following method is used for data acquisition, and the acquisition method includes:

[0058] Obtain the acquisition scheme of the application in real time. The acquisition scheme mainly includes the methods of data acquisition and data conversion and transmission. Since the platform will build the corresponding acquisition system during system construction, the corresponding acquisition scheme can be determined in real time;

[0059] Identify each acquisition item corresponding to the running acquisition data according to the acquisition scheme. Each acquisition item corresponds to a kind of acquisition data of a nearly zero-carbon substation, such as the current and voltage of a certain device, etc.; Extract the features of the acquisition scheme according to the acquisition items to form an acquisition feature chain corresponding to the acquisition method, data conversion method, and transmission method, that is, a feature chain corresponding to the acquisition feature, conversion feature, and transmission feature corresponding to the acquisition method, data conversion method, and transmission method respectively;

[0060] Conduct an acquisition simulation evaluation on the corresponding acquisition items according to the acquisition feature chain to obtain the duration chain corresponding to the acquisition items, that is, the durations required for acquisition according to the acquisition feature, conversion feature, and transmission feature respectively, such as acquisition duration, conversion duration, and transmission duration. The transmission duration is from the completion of conversion to the reading and display that meet the corresponding requirements; If the data is not converted, there is no conversion feature and conversion duration;

[0061] Analyze the optimization method that meets the optimization requirements in real time according to the acquisition feature chain and duration chain, that is, first determine the method that can realize data acquisition to recognition application according to the acquisition feature chain, then evaluate the duration chain of this method, and compare according to the cumulative duration to judge whether it meets the optimization requirements. The lowest optimization requirement is less than the current corresponding cumulative duration, but for considerations such as cost and expectation, a generally preset minimum ratio less than this is usually set; Establish an optimization library, store the optimization methods corresponding to the acquisition items in the optimization library, and store them classified according to the corresponding acquisition items;

[0062] Conduct real-time operation and maintenance optimization analysis on the nearly zero-carbon substation according to the optimization library to obtain an optimization adjustment plan, and display the optimization adjustment plan to the user for the user to decide whether to perform optimization adjustment.

[0063] In one embodiment, the method for obtaining the duration chain of the acquisition item includes:

[0064] Step SA1: Obtain the historical running acquisition data according to the acquisition feature chain corresponding to the acquisition item, and identify several historical duration chains corresponding to the acquisition item according to the historical running acquisition data, that is, the historical acquisition duration, historical conversion duration, and historical transmission duration corresponding to the data of the corresponding acquisition item. For the sake of distinction, mark the historical duration chain as the duration analysis chain;

[0065] Mark the obtained duration analysis chain as TF(A i ,B i ,C i), where i is a subscript representing the corresponding duration analysis chain, i = 1, 2, ……, n, and n is the number of duration analysis chains; A i represents the acquisition duration of the corresponding duration analysis chain; B i represents the conversion duration of the corresponding duration analysis chain, C i represents the transmission duration of the corresponding duration analysis chain;

[0066] Step SA2: Set the merging formula. The merging formula is:

[0067]

[0068] In the formula: HB is the merged value; HB1 and HB2 are the two values to be merged, respectively marked as the first value and the second value; FZ1 and FZ2 are the additional values of the first value and the second value respectively. The additional value = the number of merges + 1. The number of merges is the number of merges of this value, that is, after how many merges this value is obtained. If there is no merge, its additional value is 0 + 1 = 1;

[0069] Step SA3: Perform merging analysis on the duration analysis chain TF(A i , B i , C i ) through the merging formula, that is, perform sequential merging calculations on n A i , B i , C i respectively through the merging formula. For example, perform sequential merging on n A i until only one merged value remains, and obtain the acquisition representative value corresponding to this acquisition duration. And so on, obtain the conversion representative value and the transmission representative value, and integrate them into the duration chain of this acquisition item.

[0070] In one embodiment, the method for real-time analysis of the optimization method that meets the optimization requirements based on the acquisition feature chain and the duration chain includes:

[0071] Perform real-time scheme screening according to the acquisition feature chain to obtain several candidate methods, evaluate the duration chain of the candidate methods, calculate the cumulative duration of this duration chain, and mark it as the candidate value;

[0072] Identify the cumulative duration corresponding to the duration chain of the current acquisition item, and mark it as the application value;

[0073] Establish an optimization evaluation model. The expression of the optimization evaluation model is:

[0074]

[0075] Where: (DZ, YZ, YQ) are input data, DZ is the value to be selected; YZ is the applied value; YQ is the optimization requirement, which is initially set by the platform side and adjusted according to user requirements later; (YZ - DZ) / YZ → YQ means that (YZ - DZ) / YZ meets the optimization requirement; the output data is the optimization evaluation value YP(DZ, YZ, YQ), and the optimization evaluation value is 1 or 0;

[0076] Analyze the value to be selected and the applied value through the optimization evaluation model to obtain the optimization evaluation value of the corresponding selection method;

[0077] Mark the selection method with an optimization evaluation value of 1 as the optimization method.

[0078] In one embodiment, the method for performing operation and maintenance optimization analysis on a near-zero-carbon substation according to an optimization library includes:

[0079] Obtain the historical operation and maintenance data of the near-zero-carbon substation, including the historical operation and maintenance data of the same type of near-zero-carbon substation. Determine various operation and maintenance requirements of the near-zero-carbon substation according to the historical operation and maintenance data, and set corresponding loss curves for the corresponding operation and maintenance requirements according to the historical operation and maintenance data. The horizontal axis of the loss curve is the duration, and the vertical axis is the economic equivalent loss value. The duration refers to the time period from the need for operation and maintenance to the start of determining the operation and maintenance. The economic equivalent value is the economic loss corresponding to the corresponding duration, that is, the corresponding loss is transformed based on the economic loss as the benchmark. Perform statistical analysis according to the historical operation and maintenance data, and data processing can also be carried out by combining prediction, average, mode, etc., and then generate the loss curve, or the loss curve can also be set manually directly; determine the operation and maintenance background according to the operation and maintenance requirements and historical operation and maintenance data. The operation and maintenance background is the background situation of the corresponding operation and maintenance requirements of the near-zero-carbon substation. Different operation and maintenance situations are formed according to the different severity levels of the operation and maintenance requirements, and the corresponding operation and maintenance background is composed. Generally, the platform side presets several operation and maintenance backgrounds according to user requirements, and does not need to be all set, and sets the corresponding background proportion according to the occurrence probability of the corresponding operation and maintenance background. Later, the background proportion and operation and maintenance background can be adjusted according to user requirements, such as setting the near-zero-carbon substation as the operation and maintenance background for a certain period of time and setting the corresponding background proportion; integrate the operation and maintenance requirements, loss curves, operation and maintenance background, and background proportion into modeling materials;

[0080] Establish an operation and maintenance simulation model according to the modeling materials. The operation and maintenance simulation model is used to simulate the equivalent economic loss values of different operation and maintenance requirements of the corresponding acquisition plan under the preset operation and maintenance background, and summarize and output the background simulation values of the acquisition plan under different preset backgrounds, that is, the sum of the equivalent economic loss values of each operation and maintenance requirement.

[0081] Perform one-by-one optimization simulation according to the operation and maintenance simulation model and the optimization library, that is, replace the optimization methods in the optimization library one by one to form a new simulation optimization plan for simulation analysis, output the background simulation values under different operation and maintenance backgrounds, and then calculate the optimization simulation values of the corresponding acquisition plans according to the corresponding background ratios; the simulation optimization plan is the new acquisition plan formed by replacing the corresponding optimization methods; the optimization simulation value is the accumulated value after multiplying the corresponding background simulation value by the background ratio.

[0082] Determine the optimization adjustment plan according to the optimization simulation value, that is, compare the corresponding optimization simulation value with the optimization simulation value corresponding to the original acquisition plan, mark the simulation optimization plan that meets the requirements as the recommended plan, and the user determines the optimization adjustment plan according to the recommended plan.

[0083] For the simulation optimization plan that meets the requirements, generally set the recommended requirements according to the expected loss reduction preset by the user, and then judge whether it meets the requirements.

[0084] Exemplarily, the analysis method of the operation and maintenance simulation model includes:

[0085] Perform simulation according to the acquisition plan under the corresponding operation and maintenance background, identify the acquisition item data corresponding to each operation and maintenance requirement, and then determine the duration corresponding to the acquisition plan for each operation and maintenance requirement. Match the corresponding equivalent economic loss value according to the loss curve, sum the obtained equivalent economic loss values, and output the background simulation value.

[0086] The three-dimensional modeling module is used to perform three-dimensional modeling on the near-zero-carbon substation based on the GIM standard to obtain a substation model, including equipment models, connection relationships, topological structures, etc.; the substation model can intuitively display the layout and equipment status of the near-zero-carbon substation; specifically, it is modeled using the modeling method of the existing GIM model; obtain operation acquisition data, and the substation model is dynamically displayed according to the operation acquisition data.

[0087] The operation and maintenance analysis module is used to perform real-time operation and maintenance analysis based on the substation model to obtain corresponding operation and maintenance tasks.

[0088] In one embodiment, perform real-time operation and maintenance analysis based on the substation model, that is, extract the equipment health status, operation trends, etc. from the substation model. At the same time, it can also perform fault prediction and risk assessment, etc., and then determine the corresponding operation and maintenance tasks. Specifically, the operation and maintenance tasks can be determined based on the existing operation and maintenance analysis technology.

[0089] Exemplarily, establish an intelligent analysis model based on neural networks such as CNN networks or DNN networks, and then perform operation and maintenance analysis through the successfully trained intelligent analysis model.

[0090] The operation and maintenance planning module is used to carry out operation and maintenance planning, establish and update the operation and maintenance resource library. The operation and maintenance resource library is used to store various operation and maintenance resource information, including equipment information of nearly zero-carbon substations, historical operation and maintenance data, fault handling solutions, emergency plans, operation and maintenance personnel ability information and other resources; plan operation and maintenance tasks according to the operation and maintenance resource library, obtain the corresponding operation and maintenance planning results, and display the operation and maintenance planning results to the corresponding operation and maintenance personnel; conduct operation and maintenance training for the corresponding operation and maintenance personnel according to the operation and maintenance tasks, and update the operation and maintenance resource library according to the training results.

[0091] In one embodiment, planning operation and maintenance tasks according to the operation and maintenance resource library can be carried out in the following manner:

[0092] Equipment information sorting: Extract the detailed information of all equipment in the nearly zero-carbon substation from the operation and maintenance resource library, including equipment type, model, installation location, manufacturer, commissioning date, etc. Classify the equipment, such as transformers, switchgear, instrument transformers, etc., for subsequent targeted operation and maintenance planning.

[0093] Historical data analysis: Analyze the historical operation and maintenance data in the operation and maintenance resource library, including equipment fault records, maintenance records, preventive test data, etc. Identify the high-incidence period of equipment faults, common fault types and fault causes. According to the historical data, predict the operation status of the equipment and possible faults in the future period.

[0094] Operation and maintenance task formulation: Based on the results of equipment information sorting and historical data analysis, formulate specific operation and maintenance tasks. The task types include daily inspections, regular maintenance, preventive tests, fault handling, etc. Set clear time nodes, responsible persons and execution standards for each task.

[0095] Resource allocation and optimization: According to the requirements of operation and maintenance tasks, allocate corresponding resources such as personnel, tools, spare parts, etc. from the operation and maintenance resource library. Optimize the resource configuration to ensure the efficient use of resources. Develop a resource usage plan to avoid resource waste and shortages.

[0096] Risk assessment and response: Conduct a risk assessment of the operation and maintenance tasks, identify potential safety hazards and fault risks. Develop corresponding response measures and emergency plans to ensure rapid response and handling in case of faults.

[0097] Exemplarily, assume that the operation and maintenance resource library of a nearly zero-carbon substation contains the following information:

[0098] Equipment information: 2 transformers, with models S11-M-1000 / 10 and SZ11-16000 / 35 respectively; 10 sets of switchgear, including circuit breakers, disconnectors, etc.

[0099] Historical data: In the past year, the transformer S11-M-1000 / 10 has had 2 oil leakage faults, both occurring during the high-temperature periods in summer; the circuit breaker in the switchgear has had 1 refusal-to-operate fault, and the reason is a control circuit fault.

[0100] Based on the above information, the following operation and maintenance task plans are formulated:

[0101] Daily inspection: Inspect the transformer and switchgear every day, checking the appearance of the equipment, operating status, and any abnormal sounds, etc. Pay special attention to the oil level, oil temperature, and leakage situation of the transformer S11-M-1000 / 10.

[0102] Regular maintenance: Before the high-temperature period in summer every year, conduct a special maintenance on the transformer S11-M-1000 / 10, checking seals, cooling systems, etc. Conduct a comprehensive inspection of the switchgear every six months, including components such as operating mechanisms, contacts, and insulators.

[0103] Preventive tests: Conduct preventive tests on the transformer every year, including insulation resistance tests, DC resistance tests, etc. Conduct preventive tests on the switchgear every two years, including insulation resistance tests, operating tests, etc.

[0104] Fault handling: Develop emergency handling plans for the oil leakage faults of the transformer and the refusal-to-operate faults of the switchgear. Stock corresponding spare parts and tools to ensure rapid replacement and repair in case of faults.

[0105] Resource allocation and optimization: Arrange experienced operation and maintenance personnel to be responsible for the daily inspection and regular maintenance of the transformer and switchgear. Equip professional testing instruments and tools to ensure the accuracy and reliability of preventive tests. Optimize the inventory management of spare parts to ensure the timely supply and efficient utilization of spare parts.

[0106] In one embodiment, when planning operation and maintenance tasks according to the operation and maintenance resource library, intelligent analysis can be performed based on intelligent technologies;

[0107] Data collection and preprocessing: Collect operation and maintenance data of the nearly zero-carbon substation based on the operation and maintenance resource library, including equipment status monitoring data, historical fault records, preventive test data, etc.; preprocess the collected data, such as data cleaning, data conversion, and data standardization, to ensure the quality and consistency of the data.

[0108] Model training and verification: Train an intelligent model with the collected data. For example, machine learning algorithms (such as random forest, support vector machine, or neural network) can be used to train a fault prediction model. This model can learn the fault patterns of the equipment and predict the possibility of future faults based on the current equipment status. During the training process, the model also needs to be verified to ensure its accuracy and reliability.

[0109] Operation and Maintenance Task Planning: Once the model training is completed and its performance is verified, it can be applied to the planning of operation and maintenance tasks for nearly zero-carbon substations. The model can automatically generate operation and maintenance task plans based on the predicted failure rates of equipment and the availability of operation and maintenance resources. These plans can include tasks such as daily inspections, regular maintenance, preventive tests, and fault handling.

[0110] Task Allocation and Optimization: The intelligent model can also automatically allocate operation and maintenance tasks according to factors such as the skill levels of operation and maintenance personnel, task priorities, and resource availability. In addition, the model can optimize the tasks to reduce unnecessary resource consumption and improve operation and maintenance efficiency. For example, the model can plan the optimal inspection path to reduce the moving distance and time of operation and maintenance personnel.

[0111] Real-time Monitoring and Feedback: During the execution of operation and maintenance tasks, the intelligent model can monitor the operating status of equipment and the progress of operation and maintenance tasks in real time. If a fault occurs in the equipment or there are problems in task execution, the model can immediately issue an alarm and provide corresponding solutions. At the same time, the model can also collect feedback data during the operation and maintenance process for the continuous improvement and optimization of the model.

[0112] Exemplarily, assume that we have a nearly zero-carbon substation with two transformers and several switchgear. Use the intelligent model to plan the operation and maintenance tasks for these devices.

[0113] Data Collection: Collect real-time monitoring data such as the oil temperature, oil level, and load current of the transformer, as well as historical fault records and preventive test data.

[0114] Model Training: Use machine learning algorithms to train a fault prediction model that can predict the fault probability of the transformer.

[0115] Task Planning: Based on the prediction results of the model, formulate the operation and maintenance task plan for the transformer. For example, if the model predicts a high fault probability for a certain transformer, arrange more frequent inspections and preventive tests.

[0116] Task Allocation: Automatically allocate operation and maintenance tasks according to the skill levels of operation and maintenance personnel and task priorities.

[0117] Real-time Monitoring: During the execution of operation and maintenance tasks, monitor the operating status of the transformer in real time and issue an alarm immediately when a fault occurs.

[0118] In one embodiment, the method for providing operation and maintenance training to corresponding operation and maintenance personnel according to operation and maintenance tasks includes:

[0119] Identify operation and maintenance tasks, and obtain operation and maintenance analysis background data and operation and maintenance processing methods according to the operation and maintenance tasks. The operation and maintenance analysis background data is the prerequisite background data for determining the need for operation and maintenance, and is used for operation and maintenance personnel to judge whether operation and maintenance are required and analyze corresponding operation and maintenance tasks; the operation and maintenance processing method is the standard processing method for this operation and maintenance task; integrate the operation and maintenance tasks, operation and maintenance analysis background data, and operation and maintenance processing methods into operation and maintenance training materials;

[0120] Determine the material time period according to the operation and maintenance training materials. The material time period refers to the time period not lower than the time from when operation and maintenance are required to the latest operation and maintenance time. For example, if it can be determined that operation and maintenance are required for a certain operation and maintenance task at 1 o'clock and the operation and maintenance processing needs to be completed by 1:30 at the latest, then the time period from 1 o'clock to 1:30 is the minimum required material time period. Generally, in order to train operation and maintenance personnel, the corresponding time period will be extended, such as from 0:45 to 1:50; identify according to the preset material time period requirements; generate a training model according to the material time period and the substation model, which is equivalent to intercepting the substation model according to the material time period;

[0121] Let the user determine the training mode, such as virtual reality mode, direct simulation, etc. The direct mode is to directly train according to the training model; perform mode processing on the training model according to the training mode so that it trains operation and maintenance personnel according to the corresponding training mode, and specifically use the corresponding training mode technology for transformation; display the training model to the corresponding operation and maintenance personnel, and the operation and maintenance personnel perform operation and maintenance simulation processing according to the training model, and perform operation and maintenance evaluation according to the simulation processing process to obtain the training result.

[0122] Among them, the operation and maintenance personnel perform operation and maintenance simulation processing according to the training model, and determine the operation and maintenance situation and the corresponding operation and maintenance processing method according to the professional ability and experience of the operation and maintenance personnel, and can directly perform simulation operation and maintenance processing operations on the training model.

[0123] Perform operation and maintenance evaluation according to the simulation processing process, mainly to determine relevant information such as operation mistakes, errors, and hazards of the operation and maintenance personnel according to the simulation processing process, and can be evaluated in combination with the operation and maintenance training materials; and then determine the corresponding training result. The training result mainly includes the result of the operation and maintenance personnel's recognition and processing ability for the corresponding operation and maintenance problems; specifically, existing evaluation technologies or evaluation models can be applied for evaluation.

[0124] Exemplarily, clarify the evaluation objectives, such as improving operation and maintenance efficiency, reducing failure rate, optimizing service quality, etc.;

[0125] According to the evaluation objectives, select appropriate evaluation indicators. These indicators should be able to comprehensively reflect the work performance of the operation and maintenance personnel and the effect of operation and maintenance processing. Common evaluation indicators include:

[0126] Event response time: Measures the time interval from when a user reports a problem to when the operations and maintenance team starts to handle the problem. Fault recovery time: Refers to the time it takes for the system to fully recover from a failure and resume normal operation. System availability: Evaluated by statistically calculating the proportion of time the system operates normally within a certain period. Network availability: Evaluates the connectivity and stability of the network. Event resolution rate: Counts the ratio of the number of successfully resolved events to the total number of events within a certain period. Fault resolution rate: Measures the ratio of the number of successfully repaired faults to the total number of faults within a certain period. User satisfaction: Collects user feedback on the operations and maintenance services to understand the satisfaction level.

[0127] Quantify the selected evaluation indicators to ensure the comparability and computability of the data. At the same time, standardize all the data to eliminate the dimensional differences between different indicators.

[0128] Determine the weights of each indicator according to the importance of each indicator and its impact on the evaluation objective. This can be achieved through methods such as expert scoring, questionnaire surveys, and data analysis. The determination of weights should be scientific and reasonable, and be able to truly reflect the contribution degree of each indicator in the evaluation.

[0129] Based on the standardized data and the corresponding weights, establish an evaluation model. The evaluation model can use methods such as linear weighted sum, logarithmic linear weighted sum, and mixed weighted sum to calculate the evaluation results. The evaluation results should be able to intuitively reflect the work performance of the operations and maintenance personnel and the effect of operations and maintenance processing.

[0130] After establishing the evaluation model, it is necessary to conduct model verification and optimization. Through actual data testing, check the accuracy and reliability of the model. If deviations or deficiencies are found in the model, adjustments and optimizations should be made in a timely manner to ensure the accuracy and effectiveness of the evaluation results.

[0131] In one embodiment, the near-zero-carbon substation in the present invention can be replaced with other types of substations for analysis.

[0132] The above formulas are all calculated by removing the dimension and taking their numerical values. The formulas are obtained by collecting a large amount of data for software simulation to get a formula closest to the actual situation. The preset parameters and preset thresholds in the formulas are set by those skilled in the art according to the actual situation or obtained through a large amount of data simulation.

[0133] The above embodiments are only used to illustrate the technical methods of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical methods of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A substation operation and maintenance intelligent planning system based on the GIM model, characterized in that: It includes 3D modeling module, data acquisition module, operation and maintenance analysis module and operation and maintenance planning module; The data acquisition module is used to perform real-time data acquisition on the near-zero carbon substation to obtain operation acquisition data corresponding to the near-zero carbon substation; The three-dimensional modeling module is used to perform three-dimensional modeling of the near-zero carbon substation based on the GIM standard to obtain a substation model; obtain operation collection data, and the substation model is dynamically displayed according to the operation collection data; The operation and maintenance analysis module is used to perform real-time operation and maintenance analysis based on the substation model to obtain corresponding operation and maintenance tasks; The operation and maintenance planning module is used to carry out operation and maintenance planning, establish and update the operation and maintenance resource library, and the operation and maintenance resource library is used to store various operation and maintenance resource information; Plan operation and maintenance tasks according to the operation and maintenance resource library, obtain corresponding operation and maintenance planning results, and display the operation and maintenance planning results to corresponding operation and maintenance personnel; conduct operation and maintenance training for corresponding operation and maintenance personnel according to the operation and maintenance tasks, and update the operation and maintenance resource library according to the training results.

2. According to the GIM model-based intelligent planning system for substation operation and maintenance according to claim 1, it is characterized in that: Real-time optimization analysis of the collection plan for running collection data, the optimization methods include: Acquire the collection scheme of the application, and identify the collection items corresponding to the running collection data according to the collection scheme; establish an optimization library according to the collection items, and the optimization library is used to store the optimization methods corresponding to the collection items; A real-time operation and maintenance optimization analysis of the near-zero-carbon substation is performed according to the optimization library to obtain an optimization adjustment plan, and the user performs optimization adjustment according to the optimization adjustment plan.

3. According to claim 2, a substation operation and maintenance intelligent planning system based on the GIM model is characterized in that: The method for establishing the optimization library includes: Extracting features of the collection scheme according to the collection items to form a collection feature chain corresponding to the collection items, wherein the collection feature chain is composed of collection features, conversion features, and transmission features corresponding to the collection method, data conversion method, and transmission method, respectively; Performing collection simulation evaluation on the collection item according to the collection feature chain to obtain a duration chain of the collection item; According to the collection feature chain and the duration chain, an optimization method that meets the optimization requirements is analyzed in real time, and an optimization library is established according to the optimization method corresponding to the collection item.

4. According to claim 3, a substation operation and maintenance intelligent planning system based on the GIM model is characterized in that: The methods for obtaining the duration chain include: Acquire historical operation collection data according to the collection feature chain of the collection item, and identify and summarize several duration analysis chains corresponding to the collection item according to the historical operation collection data; The duration analysis chain is labeled as TF (A i , B i , C i ), i is a subscript, i = 1, 2, ..., n, n is the number of duration analysis chains; A i Indicates the collection duration of the corresponding duration analysis chain; B i Indicates the conversion duration of the corresponding duration analysis chain, C i Indicates the transmission duration of the corresponding duration analysis chain; Set the merge formula. The merge formula is: Wherein: HB is the merged value; HB1 and HB2 are two values ​​to be merged, respectively marked as the first value and the second value; FZ1 and FZ2 are the additional values ​​of the first value and the second value, respectively, and the additional value = the number of merges + 1; By combining the formula, the duration analysis chain TF(A i , B i , C i ) to perform a combined analysis to obtain the duration chain of the collection items.

5. According to claim 4, a substation operation and maintenance intelligent planning system based on the GIM model is characterized in that: The methods for optimizing the method to meet the optimization requirements by real-time analysis based on the acquisition feature chain and the duration chain include: Perform real-time solution screening according to the collected feature chain to obtain several candidate methods, evaluate the duration chain of the candidate methods, calculate the cumulative duration of the duration chain, and mark it as a candidate value; Calculate the cumulative duration of the duration chain corresponding to the collection item and mark it as the application value; An optimization evaluation model is established. The expression of the optimization evaluation model is: Where: (DZ, YZ, YQ) is the input data, DZ is the candidate value; YZ is the application value; YQ is the optimization requirement; (YZ-DZ) / YZ→YQ means (YZ-DZ) / YZ meets the optimization requirement; the output data is the optimization evaluation value YP(DZ, YZ, YQ), and the optimization evaluation value is 1 or 0; Analyze the candidate values ​​and application values ​​through the optimization evaluation model to obtain the optimization evaluation value of the corresponding candidate method; The candidate method with the optimization evaluation value of 1 is marked as the optimized method.

6. According to claim 5, a GIM model-based substation operation and maintenance intelligent planning system is characterized in that: The methods for operation and maintenance optimization analysis of near-zero carbon substations based on the optimization library include: Establishing an operation and maintenance simulation model, wherein the operation and maintenance simulation model is used to analyze the corresponding acquisition scheme and obtain background simulation values ​​of the acquisition scheme under the corresponding operation and maintenance background; Perform optimization simulation one by one according to the operation and maintenance simulation model and optimization library to obtain the optimization simulation value of the corresponding simulation optimization solution; An optimization adjustment scheme is determined according to the optimization simulation value.

7. According to claim 6, a GIM model-based substation operation and maintenance intelligent planning system is characterized in that: The method for establishing the operation and maintenance simulation model includes: Acquire historical operation and maintenance data of a near-zero-carbon substation, and determine the operation and maintenance requirements of the near-zero-carbon substation and a corresponding loss curve according to the historical operation and maintenance data, wherein the horizontal axis of the loss curve is duration and the vertical axis is an economic equivalent loss value; According to the operation and maintenance requirements and historical operation and maintenance data, several operation and maintenance backgrounds are set, and corresponding background weights are set for the operation and maintenance backgrounds; the operation and maintenance requirements, loss curves, operation and maintenance backgrounds and background weights are integrated into modeling materials; Establish an operation and maintenance simulation model based on the modeling materials.

8. According to claim 7, a GIM model-based substation operation and maintenance intelligent planning system is characterized in that: The calculation formula of the optimized simulation value is: Where: YU is the optimized simulation value; j represents the corresponding operation and maintenance background, j = 1, 2, ..., m, m is the number of operation and maintenance backgrounds; λ j Indicates the background weight of the corresponding operation and maintenance background; BM j It represents the background simulation value of the corresponding simulation optimization scheme under the corresponding operation and maintenance background.

9. The substation operation and maintenance intelligent planning system based on the GIM model according to claim 1 is characterized in that: Methods for providing operation and maintenance training to corresponding operation and maintenance personnel according to operation and maintenance tasks include: Identify operation and maintenance tasks, obtain operation and maintenance analysis background data and operation and maintenance processing methods according to the operation and maintenance tasks, and integrate the operation and maintenance tasks, operation and maintenance analysis background data and operation and maintenance processing methods into operation and maintenance training materials; Determine a material period according to the operation and maintenance training material, and generate a training model according to the material period and the substation model; The user determines the training mode, and performs mode processing on the training model according to the training mode; the training model is displayed to the corresponding operation and maintenance personnel, and the operation and maintenance personnel perform operation and maintenance simulation processing according to the training model, and perform operation and maintenance evaluation according to the simulation processing process to obtain the training results.

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