Starting scheme generation and processing system, method and device based on power grid equipment, equipment, medium and program product

Abstract

The invention relates to a starting scheme generation and processing system, method and device based on power grid equipment, equipment, a medium and a program product, and relates to the technical field of power control. By adopting the system, the accuracy and reliability of the scheme can be improved. The system comprises a scheme generation unit used for generating a power grid equipment-based starting scheme based on an acquired starting step model and an acquired starting condition model; the debugging execution unit is used for carrying out equipment debugging and field verification based on the starting scheme and obtaining debugging and verification data; the automatic simulation unit is used for simulating the starting process of the power grid equipment in a virtual environment based on the starting scheme and recording current and voltage change data in the simulation process; and the comprehensive evaluation unit is used for receiving the debugging and verification data and the current and voltage change data, performing similarity calculation on the debugging and verification data and the current and voltage change data, and determining that the starting scheme passes evaluation under the condition that the similarity meets a threshold condition.

Description

Technical Field

[0001] The present application relates to the field of power control technology, and in particular to a startup plan generation and processing system, method, device, computer equipment, computer-readable storage medium and computer program product based on power grid equipment. Background Art

[0002] The startup plan is an important guarantee for the safe operation of the power system. Especially before new equipment is put into use, a detailed startup plan must be prepared to verify whether the equipment can operate safely. With the rapid development of the economy and the rapid growth of electricity demand, a large number of infrastructure projects are put into production every year, which puts higher requirements on the efficiency and quality of the startup plan preparation.

[0003] In traditional technology, the preparation and review of equipment startup plans can only rely on manual operation, which is not only inefficient, but also prone to staff errors, resulting in deficiencies in the correctness and rationality of the plan. Although some startup plan preparation systems have emerged, these systems usually simply generate startup plans, resulting in low accuracy of their output results and low flexibility in their own adjustments. Summary of the invention

[0004] Based on this, it is necessary to provide a startup plan generation and processing system, method, device, computer equipment, computer-readable storage medium and computer program product based on power grid equipment to address the above technical problems.

[0005] In a first aspect, the present application provides a startup scheme generation and processing system based on power grid equipment, the system comprising: a scheme generation unit, an execution and debugging unit, an automation simulation unit and a comprehensive evaluation unit; the scheme generation unit is respectively connected to the execution and debugging unit and the automation simulation unit in communication, and the execution and debugging unit and the automation simulation unit are respectively connected to the comprehensive evaluation unit in communication;

[0006] The scheme generating unit is used to obtain a starting step model and a starting condition model, and generate a starting scheme based on the power grid equipment based on the starting step model and the starting condition model;

[0007] The execution debugging unit is used to perform equipment debugging and on-site verification based on the startup scheme, and obtain debugging and verification data;

[0008] The automation simulation unit is used to simulate the startup process of the power grid equipment in a virtual environment based on the startup scheme, and record the current and voltage change data during the simulation process;

[0009] The comprehensive evaluation unit is used to receive the debugging and verification data and the current and voltage change data, perform similarity calculation on the debugging and verification data and the current and voltage change data, and determine that the startup scheme evaluation is passed when the similarity meets a threshold condition.

[0010] In one embodiment, the scheme generation unit includes: a word segmentation module, a model separation module, a feature extraction module, a corpus generation module and a model training module; the word segmentation module is used to use natural language processing technology to segment the historical startup steps and conditional texts of the power grid equipment to form a startup operation word segmentation text library; the model separation module is used to separate the equipment name library and the power grid topology model according to the power grid equipment model generated by the energy management system, and form a topology model within the startup range; the feature extraction module is used to extract the topological features within the startup range in the topology model using a graph attention neural network; the corpus generation module is used to form a startup step and startup condition text corpus based on the equipment name library and the startup operation word segmentation text library; the model training module is used to train the startup step statement using a sequential deep learning model, and train the startup condition statement using a non-sequential deep learning model to obtain the startup step model and the startup condition model.

[0011] In one of the embodiments, the model training module is further used to obtain standard operating steps in the historical operation data of the power grid, and convert the standard operating steps into sequence data including a command identifier and a command description; the command identifier is used as the input of the startup step model, and the command description is used as the output of the startup step model, and the startup step is trained to obtain the startup step model; the model training module is also used to obtain standard conditional statements in the historical operation data, and based on the standard conditional statements and the fully connected layer, the conditional statements are trained to obtain the startup condition model.

[0012] In one of the embodiments, the automated simulation unit is also used to establish a digital twin model of the power grid at the description subsystem layer based on the detailed parameters and historical operating data of the power grid; collect first data for adjusting the power system flow behavior, and analyze the first data to generate second data; establish a long-short-term memory network model based on the second data; generate new power grid operation flow samples based on the power grid operation status predicted by the long-short-term memory network model; perform power grid simulation calculations based on the power grid operation flow samples, and record simulation data.

[0013] In one of the embodiments, the system further includes: a user interaction unit and an adjustment feedback unit; the user interaction unit is used to provide an input window for instructions to the user and to display the acquired target data to the user; the target data includes: a power system single-line diagram, equipment status indication, real-time data chart, operation log and alarm signal; the adjustment feedback unit is used to adjust the startup scheme generation strategy of the scheme generation unit according to the difference between the debugging and verification results and the automated simulation results.

[0014] In a second aspect, the present application further provides a method for generating and processing a startup plan based on a power grid device, which is applied to a system for generating and processing a startup plan based on a power grid device, and the method includes:

[0015] Acquire a startup step model and a startup condition model, and generate a startup plan based on the power grid equipment based on the startup step model and the startup condition model;

[0016] Perform equipment debugging and on-site verification based on the startup plan, and obtain debugging and verification data;

[0017] Based on the startup scheme, simulating the startup process of the power grid equipment in a virtual environment, and recording current and voltage change data during the simulation process;

[0018] A similarity calculation is performed on the debugging and verification data and the current and voltage change data, and when the similarity meets a threshold condition, it is determined that the startup scheme evaluation has passed.

[0019] In a third aspect, the present application further provides a startup scheme generation and processing device based on a power grid device, the device comprising:

[0020] A scheme generating module, used for acquiring a starting step model and a starting condition model, and generating a starting scheme based on the power grid equipment based on the starting step model and the starting condition model;

[0021] An execution debugging module is used to perform equipment debugging and on-site verification based on the startup scheme, and obtain debugging and verification data;

[0022] An automated simulation module, used to simulate the startup process of the power grid equipment in a virtual environment based on the startup scheme, and record current and voltage change data during the simulation process;

[0023] The comprehensive evaluation module is used to calculate the similarity between the debugging and verification data and the current and voltage change data, and determine that the startup scheme evaluation has passed when the similarity meets the threshold condition.

[0024] In a fourth aspect, the present application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0025] A startup step model and a startup condition model are obtained, and a startup plan based on the power grid equipment is generated based on the startup step model and the startup condition model; equipment debugging and on-site verification are performed based on the startup plan, and debugging and verification data are obtained; based on the startup plan, the startup process of the power grid equipment is simulated in a virtual environment, and current and voltage change data including those in the simulation process are recorded; similarity is calculated between the debugging and verification data and the current and voltage change data, and when the similarity meets a threshold condition, it is determined that the startup plan has passed the evaluation.

[0026] In a fifth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0027] A startup step model and a startup condition model are obtained, and a startup plan based on the power grid equipment is generated based on the startup step model and the startup condition model; equipment debugging and on-site verification are performed based on the startup plan, and debugging and verification data are obtained; based on the startup plan, the startup process of the power grid equipment is simulated in a virtual environment, and current and voltage change data including those in the simulation process are recorded; similarity is calculated between the debugging and verification data and the current and voltage change data, and when the similarity meets a threshold condition, it is determined that the startup plan has passed the evaluation.

[0028] In a sixth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0029] A startup step model and a startup condition model are obtained, and a startup plan based on the power grid equipment is generated based on the startup step model and the startup condition model; equipment debugging and on-site verification are performed based on the startup plan, and debugging and verification data are obtained; based on the startup plan, the startup process of the power grid equipment is simulated in a virtual environment, and current and voltage change data including those in the simulation process are recorded; similarity is calculated between the debugging and verification data and the current and voltage change data, and when the similarity meets a threshold condition, it is determined that the startup plan has passed the evaluation.

[0030] The above-mentioned startup scheme generation and processing system, method, device, computer equipment, computer-readable storage medium and computer program product based on power grid equipment, by establishing a startup scheme generation and processing system for power grid equipment, using state machine principles, expert system rule bases and human-computer interaction rules, realizes the automatic, standardized and accurate compilation of startup schemes; this automated scheme generation and processing method greatly improves the efficiency of scheme compilation, reduces human errors, thereby improving the accuracy and reliability of the scheme, and this application promotes the standardization of startup scheme content and terminology through the automated startup scheme generation and verification process, forming a standardized process. This means that the preparation of the scheme is no longer dependent on personal experience, but follows unified standards and processes, which helps to improve the level of intelligence of power grid dispatching, reduce the work pressure of personnel in compiling startup schemes, and ensure the consistency and traceability of the scheme. In addition, the present application also adjusts the startup scheme generation strategy based on the simulation results, further making the generation of the startup scheme more accurate, and in a dynamically adjustable state, with the flexibility of self-adjustment. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0032] Figure 1 A structural block diagram of a system for generating and processing a startup plan based on power grid equipment in one embodiment;

[0033] Figure 2 It is a structural block diagram of a solution generating unit in an embodiment;

[0034] Figure 3 It is a structural block diagram of a system for generating and processing a startup plan based on power grid equipment in another embodiment;

[0035] Figure 4 It is a flowchart of a method for generating and processing a startup plan based on a power grid device in one embodiment;

[0036] Figure 5 It is a structural block diagram of a startup scheme generation and processing device based on power grid equipment in one embodiment;

[0037] Figure 6 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0039] In one embodiment, Figure 1 As shown, a startup scheme generation and processing system based on power grid equipment is provided, the system comprising: a scheme generation unit, an execution and debugging unit, an automation simulation unit and a comprehensive evaluation unit; the scheme generation unit is respectively connected to the execution and debugging unit and the automation simulation unit for communication, and the execution and debugging unit and the automation simulation unit are respectively connected to the comprehensive evaluation unit for communication;

[0040] A scheme generating unit, used for acquiring a starting step model and a starting condition model, and generating a starting scheme based on the power grid equipment based on the starting step model and the starting condition model;

[0041] The execution debugging unit is used to perform equipment debugging and on-site verification based on the startup plan, and obtain debugging and verification data;

[0042] An automated simulation unit, used to simulate the startup process of power grid equipment in a virtual environment based on the startup plan, and record current and voltage change data during the simulation process;

[0043] The comprehensive evaluation unit is used to receive the debugging and verification data and the current and voltage change data, calculate the similarity between the debugging and verification data and the current and voltage change data, and determine that the startup plan evaluation is passed when the similarity meets the threshold condition.

[0044] Specifically, refer to Figure 1 , a scheme generation unit is used to obtain a startup step model and a startup condition model, and automatically generate a startup scheme based on the power grid equipment based on the startup step model and the startup condition model; an execution debugging unit is used to perform equipment debugging and other on-site verification operations based on the startup scheme, and obtain debugging and verification data, including: equipment startup time and current impact response; an automated simulation unit is used to simulate the startup process of the power grid equipment in a virtual environment based on the startup scheme, and record data including current and voltage changes during the simulation process; a comprehensive evaluation unit is used to receive debugging and verification data and current and voltage change data, perform similarity calculation on the debugging and verification data and the current and voltage change data, and compare the similarity of the two output results based on the similarity calculation results. It is determined that the verification is passed only when the threshold is exceeded, otherwise an alarm is issued. The similarity calculation is as follows:

[0045]

[0046] In the above formula, A and B represent the actual result and simulation result respectively. Represents the difference measure between the two.

[0047] In the above-mentioned startup scheme generation and processing system based on power grid equipment, by establishing a startup scheme generation and processing system for power grid equipment, the state machine principle, expert system rule base and human-computer interaction rules are used to realize the automatic, standardized and accurate preparation of the startup scheme; this automated scheme generation and processing method greatly improves the efficiency of scheme preparation, reduces human errors, and thus improves the accuracy and reliability of the scheme. Moreover, this application promotes the standardization of the content and terminology of the startup scheme through the automated startup scheme generation and verification process, and forms a standardized process. This means that the preparation of the scheme is no longer dependent on personal experience, but follows unified standards and processes, which helps to improve the level of intelligence of power grid dispatching, reduce the work pressure of personnel in preparing startup schemes, and ensure the consistency and traceability of the scheme. In addition, this application also adjusts the startup scheme generation strategy based on the simulation results, which further makes the generation of the startup scheme more accurate, and is in a dynamically adjustable state, with the flexibility of self-adjustment.

[0048] In one embodiment, Figure 2 As shown, the solution generation unit includes: a word segmentation module, a model separation module, a feature extraction module, a corpus generation module and a model training module; the word segmentation module is used to use natural language processing technology to segment the historical startup steps and conditional texts of the power grid equipment to form a startup operation word segmentation text library; the model separation module is used to separate the equipment name library and the power grid topology model according to the power grid equipment model generated by the energy management system, and form a topology model within the startup range; the feature extraction module is used to use the graph attention neural network to extract the topological features within the startup range in the topology model; the corpus generation module is used to form a startup step and startup condition text corpus based on the equipment name library and the startup operation word segmentation text library; the model training module is used to train the startup step statement using a sequential deep learning model, and train the startup condition statement using a non-sequential deep learning model to obtain a startup step model and a startup condition model.

[0049] Specifically, the word segmentation module uses natural language processing technology to segment the historical startup steps and conditional texts of power grid equipment to form a startup operation word segmentation text library; the model separation module separates the equipment name library and the power grid topology model according to the power grid equipment model generated by the energy management system, and forms a topology model within the operation range; the feature extraction module uses the graph attention neural network to extract the topological features within the startup range; the corpus generation module forms a startup step and startup condition text corpus based on the equipment name library and the startup operation word segmentation text library; the model training module uses a sequential deep learning model to train the startup step statements, and uses a non-sequential deep learning model to train the startup condition statements, to obtain a startup step model and a startup condition model.

[0050] In one embodiment, the model training module is also used to obtain standard operating steps in the historical operation data of the power grid, and convert the standard operating steps into sequence data containing command identifiers and command descriptions; the command identifier is used as the input of the startup step model, and the command description is used as the output of the startup step model, and the startup step is trained to obtain the startup step model; the model training module is also used to obtain standard conditional statements in the historical operation data, and based on the standard conditional statements and the fully connected layer, the conditional statements are trained to obtain the startup condition model.

[0051] Specifically, the training process of the startup step model is as follows:

[0052] Perform word segmentation on the text of historical startup steps to form a word segmentation text library; perform feature extraction on the power grid equipment model to form a power grid topology model; define the LSTM (Long Short-Term Memory) model structure, including the input layer, LSTM layer, and output layer. Use the PyTorch framework to define the LSTM network structure, including the dimension and number of hidden layers; set hyperparameters such as learning rate, batch size, and epoch number; use MSELoss as the loss function and Adam as the optimizer. Perform forward propagation to calculate output and loss. Perform backpropagation, calculate gradients, and update model parameters. After each epoch, record and print the loss value to monitor the training process; use the test set to evaluate the model and calculate the accuracy or other performance indicators of the model; after training, save the model parameters for subsequent use or further training.

[0053] In addition, the start condition model training steps are as follows:

[0054] Perform word segmentation on the historical startup condition text to form a word segmentation text library, perform feature extraction on the power grid equipment model to form a power grid topology model; define the multi-layer perceptron (MLP) model structure, including the input layer, hidden layer, and output layer, use the PyTorch framework to define the MLP network structure, including the number of neurons in each layer; set hyperparameters such as learning rate, batch size, and epoch number; use CrossEntropyLoss as the loss function and Adam as the optimizer to perform forward propagation and calculate output and loss. Perform back propagation, calculate gradients, and update model parameters. After each epoch, record and print the loss value to monitor the training process; use the test set to evaluate the model and calculate the accuracy or other performance indicators of the model; after training, save the model parameters for subsequent use or further training.

[0055] In one embodiment, the automated simulation unit is also used to establish a digital twin model of the power grid at the description subsystem layer based on the detailed parameters and historical operating data of the power grid; collect first data for adjusting the power system flow behavior, and analyze the first data to generate second data; establish a long and short-term memory network model based on the second data; generate new power grid operation flow samples based on the power grid operation status predicted by the long and short-term memory network model; perform power grid simulation calculations based on the power grid operation flow samples, and record simulation data.

[0056] Specifically, the automated simulation unit can perform the following operations:

[0057] A digital twin model of the power grid is established at the description subsystem layer. This model can reflect the status of the primary equipment, secondary equipment and environment of the power grid. This can be achieved by collecting detailed parameters and historical operation data of the power grid, including the model, rated parameters and connection relationship of the equipment; a data parsing unit is used to collect the first data for adjusting the power system flow behavior, and these data are parsed to generate second data, which include the names of the adjusted equipment, which are the names of the first equipment; based on the second data, an LSTM model is established, which can learn the historical data of the power grid operation and predict the future power grid operation status; according to the power grid operation status predicted by the LSTM model, new power grid operation flow samples are generated, which include the equipment operation status of the power grid after different operation events; open source power grid simulation software such as PythonPower Network (Pypownet) is used for power grid simulation calculation. Pypownet can model large power grids and simulate various system operation states, and support AC and DC flow solutions; record simulation data; call the stored power grid model data snapshot and power grid equipment status snapshot according to the pre-set total simulation time and simulation clock compression ratio, and promote the simulation clock to perform power grid regulation operation simulation timing flow simulation.

[0058] For example, the automated simulation unit performs equipment simulation debugging or other simulation verification operations based on the startup plan to obtain simulation debugging or verification data. This module corresponds to the terminal execution module one by one, which is equivalent to one obtaining the actual result and the other obtaining the simulation result. The unit simulates the startup process of the power grid equipment in a virtual environment, and records the current and voltage changes in the simulation, the equipment response time, and the system stability data. The data obtained by the simulation are as follows: Simulation equipment startup time , in seconds; simulated current impulse response , in ampere (A); simulation voltage stability , the unit is volt (V); simulate the action of the protection device , binary value, 1 indicates action, 0 indicates no action.

[0059] To further illustrate, the following are the specific implementation steps for simulating the startup process of power grid equipment in a virtual environment based on the startup scheme, as well as how to record data such as current and voltage changes, equipment response time, and system stability in the simulation:

[0060] Step 1: Establish a digital twin model of the power grid at the description subsystem layer. This model can reflect the status of the primary equipment, secondary equipment and environment of the power grid. This can be achieved by collecting detailed parameters and historical operation data of the power grid, including equipment model, rated parameters, connection relationship, etc.

[0061] Step 2: Use a data analysis unit to collect first data for adjusting the power system flow behavior, and analyze these data to generate second data, which include names of adjusted devices, which are first device names.

[0062] Step 3: Based on the second data, an LSTM model is established using the LSTM algorithm. This model can learn the historical data of power grid operation and predict the future power grid operation status.

[0063] Step 4: Generate new power grid operation flow samples based on the power grid operation status predicted by the LSTM model. These samples include the power grid equipment operation status after different operation events.

[0064] Step 5: Use open source power grid simulation software such as Python Power Network (Pypownet) to perform power grid simulation calculations. Pypownet can model large power grids and simulate various system operating states, while supporting AC and DC power flow solutions.

[0065] Step 6: Record simulation data, including simulation device startup time , Simulate current impulse response , Simulation voltage stability And simulate the action of protection device .

[0066] Step 7: Call the stored power grid model data snapshot and power grid equipment status snapshot according to the preset total simulation time and simulation clock compression ratio, and advance the simulation clock to perform power grid regulation operation simulation timing flow simulation.

[0067] In one embodiment, the data obtained by the execution debugging unit includes the device startup time , Current impulse response , Voltage stability And the protection device action ; The data obtained by the automation simulation terminal unit includes the simulation device startup time , Simulate current impulse response , Simulation voltage stability , Simulate the action of protection devices .

[0068] The similarity calculation formula is as follows:

[0069]

[0070] In the above formula, w1, w2, w3, and w4 are weight coefficients used to adjust the importance of different parameters in similarity calculation. The value range of these weight coefficients is 0 to 1.

[0071] For example, the execution debugging unit performs equipment debugging or other on-site verification operations based on the startup plan, and obtains on-site debugging or verification data, which are used to calculate the comprehensive total score; the unit receives the startup plan generated by the plan generation unit, and performs on-site equipment debugging operations according to the startup plan, and records the operation results. It is used to collect key data in the equipment debugging process, including: equipment startup time, current impulse response, voltage stability, and protection device action. The collected data are as follows:

[0072] Device startup time , in seconds; current impulse response , in ampere (A); voltage stability , in volts (V); protection device action , binary value, 1 indicates action, 0 indicates no action.

[0073] In one embodiment, Figure 3As shown, the startup plan generation and processing system based on power grid equipment also includes: a user interaction unit and an adjustment feedback unit; the user interaction unit is used to provide the user with an input window for instructions and to display the acquired target data to the user; the target data includes: a power system single-line diagram, equipment status indication, real-time data chart, operation log and alarm signal; the adjustment feedback unit is used to adjust the startup plan generation strategy of the plan generation unit according to the difference between the debugging and verification results and the automation simulation results.

[0074] Specifically, the user interaction unit is used to input instructions to the user or display the acquired data. The data displayed by the visual user interaction unit includes: power system single-line diagram, equipment status indication, real-time data chart, operation log and alarm signal. The feedback adjustment unit is used to adjust the strategy of the startup scheme automatic generation module according to the difference between the actual results and the simulation results. The specific adjustment method is as follows: Optimize the atomic operation sequence: If If the preset threshold is exceeded, the operation sequence in the startup step model is adjusted to reduce the difference in startup time; the risk assessment model is adjusted: or If the preset threshold is exceeded, the risk assessment parameters in the start-up condition model are adjusted to improve the accuracy of the model; the expert system rule base is updated: When the preset threshold is exceeded, the protection device action rules in the expert system rule base are updated to improve the reliability of the model.

[0075] In one embodiment, Figure 4 As shown, a method for generating and processing a startup plan based on power grid equipment is provided, and the method is applied to Figure 1 The power grid equipment-based startup plan generation and processing system is described as an example, including the following steps:

[0076] Step S401, obtaining a startup step model and a startup condition model, and generating a startup plan based on the power grid equipment based on the startup step model and the startup condition model.

[0077] Step S402: perform equipment debugging and on-site verification based on the startup plan, and obtain debugging and verification data.

[0078] Step S403: Based on the startup plan, simulate the startup process of the power grid equipment in the virtual environment, and record the current and voltage change data during the simulation process.

[0079] Step S404, performing similarity calculation on the debugging and verification data and the current and voltage change data, and determining that the startup solution evaluation is passed when the similarity meets a threshold condition.

[0080] Specifically, a startup plan generation and processing system based on power grid equipment obtains a startup step model and a startup condition model, and generates a startup plan based on the power grid equipment based on the startup step model and the startup condition model; then, equipment debugging and on-site verification are performed based on the startup plan, and debugging and verification data are obtained; then, based on the startup plan, the startup process of the power grid equipment is simulated in a virtual environment, and current and voltage change data including those in the simulation process are recorded; finally, similarity calculation is performed on the debugging and verification data and the current and voltage change data, and when the similarity meets the threshold condition, it is determined that the startup plan evaluation has passed.

[0081] For specific definitions of the above steps, reference may be made to the relevant embodiments of the startup plan generation and processing system based on power grid equipment, which will not be described in detail here.

[0082] Compared with the traditional technology, the beneficial effects of this application are:

[0083] 1. The traditional startup plan preparation relies on manual writing, which is time-consuming, error-prone, and has low plan reliability. In contrast, this plan establishes an automatic grid startup plan preparation system, using state machine principles, expert system rule bases, and human-computer interaction rules to achieve automatic, standardized, and accurate preparation of startup plans. This automated method greatly improves the efficiency of plan preparation, reduces human errors, and thus improves the quality and reliability of the plan.

[0084] 2. This application promotes the standardization of the content and terminology of the startup plan and forms a standardized process through the automated startup plan generation and verification process. This means that the preparation of the plan no longer relies on personal experience, but follows unified standards and processes, which helps to improve the intelligence level of power grid dispatching, reduce the work pressure of personnel in compiling startup plans, and ensure the consistency and traceability of the plan.

[0085] 3. The application of terminal emulation technology gives this application a significant advantage in the field of industrial automation. Through virtual terminals, users can access and operate industrial automation systems in different locations and on different devices, no longer restricted by the location and limitations of specific physical terminal devices. This flexibility and scalability makes system deployment and maintenance more convenient and can better adapt to the changing needs and scenarios in industrial production environments. In addition, terminal emulation also helps to improve the security of the system by isolating user operations from actual production equipment and reducing potential security risks.

[0086] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0087] Based on the same inventive concept, the embodiment of the present application also provides a startup scheme generation and processing device based on power grid equipment for implementing the startup scheme generation and processing method based on power grid equipment involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of one or more startup scheme generation and processing devices based on power grid equipment provided below can refer to the limitations of the startup scheme generation and processing method based on power grid equipment above, and will not be repeated here.

[0088] In an exemplary embodiment, Figure 5 As shown, a startup scheme generation and processing device based on power grid equipment is provided, comprising:

[0089] The scheme generating module 501 is used to obtain a starting step model and a starting condition model, and generate a starting scheme based on the power grid equipment based on the starting step model and the starting condition model.

[0090] The execution debugging module 502 is used to perform device debugging and on-site verification based on the startup plan, and obtain debugging and verification data.

[0091] The automated simulation module 503 is used to simulate the startup process of the power grid equipment in a virtual environment based on the startup plan, and record the current and voltage change data during the simulation process.

[0092] The comprehensive evaluation module 504 is used to calculate the similarity between the debugging and verification data and the current and voltage change data, and determine that the startup scheme evaluation has passed when the similarity meets the threshold condition.

[0093] For the specific definition of the startup scheme generation and processing device based on the power grid equipment, please refer to the definition of the startup scheme generation and processing method based on the power grid equipment above, which will not be repeated here. Each module in the above-mentioned startup scheme generation and processing device based on the power grid equipment can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0094] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 6 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store debugging and verification data and current and voltage change data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a startup scheme generation and processing method based on a power grid device is implemented.

[0095] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0096] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0097] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0098] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0099] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0100] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0101] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0102] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A startup plan generation and processing system based on power grid equipment, characterized in that: The system comprises: a solution generation unit, an execution and debugging unit, an automatic simulation unit and a comprehensive evaluation unit; the solution generation unit is respectively connected to the execution and debugging unit and the automatic simulation unit for communication, and the execution and debugging unit and the automatic simulation unit are respectively connected to the comprehensive evaluation unit for communication; The scheme generating unit is used to obtain a starting step model and a starting condition model, and generate a starting scheme based on the power grid equipment based on the starting step model and the starting condition model; The execution debugging unit is used to perform equipment debugging and on-site verification based on the startup scheme, and obtain debugging and verification data; The automation simulation unit is used to simulate the startup process of the power grid equipment in a virtual environment based on the startup scheme, and record the current and voltage change data during the simulation process; The comprehensive evaluation unit is used to receive the debugging and verification data and the current and voltage change data, perform similarity calculation on the debugging and verification data and the current and voltage change data, and determine that the startup scheme evaluation is passed when the similarity meets a threshold condition.

2. The system according to claim 1, characterized in that The scheme generation unit includes: a word segmentation module, a model separation module, a feature extraction module, a corpus generation module and a model training module; The word segmentation module is used to segment the historical startup steps and conditional texts of the power grid equipment using natural language processing technology to form a startup operation word segmentation text library; The model separation module is used to separate the equipment name library and the power grid topology model according to the power grid equipment model generated by the energy management system, and form a topology model within the startup range; The feature extraction module is used to extract topological features within the startup range in the topological model using a graph attention neural network; The corpus generation module is used to form a startup step and startup condition text corpus based on the device name library and the startup operation word segmentation text library; The model training module is used to train the startup step statement using a sequential deep learning model, and to train the startup condition statement using a non-sequential deep learning model, so as to obtain the startup step model and the startup condition model.

3. The system according to claim 2, characterized in that The model training module is further used to obtain standard operating steps in historical operation data of the power grid, convert the standard operating steps into sequence data including command identifiers and command descriptions; use the command identifiers as inputs of the startup step model, and the command descriptions as outputs of the startup step model, train the startup steps, and obtain the startup step model; The model training module is also used to obtain standard conditional statements in the historical operation data, and train the conditional statements based on the standard conditional statements and the fully connected layer to obtain the start condition model.

4. The system according to claim 1, characterized in that The automated simulation unit is also used to establish a digital twin model of the power grid at the description subsystem layer based on the detailed parameters and historical operating data of the power grid; collect first data for adjusting the power system flow behavior, and analyze the first data to generate second data; establish a long-short-term memory network model based on the second data; generate new power grid operation flow samples based on the power grid operation status predicted by the long-short-term memory network model; perform power grid simulation calculations based on the power grid operation flow samples, and record simulation data.

5. The system according to claim 1, characterized in that The system further comprises: a user interaction unit and an adjustment feedback unit; The user interaction unit is used to provide a command input window to the user and display the acquired target data to the user; the target data includes: a power system single-line diagram, an equipment status indication, a real-time data chart, an operation log and an alarm signal; The adjustment feedback unit is used to adjust the startup solution generation strategy of the solution generation unit according to the difference between the debugging and verification results and the automatic simulation results.

6. A method for generating and processing a startup plan based on power grid equipment, characterized in that: Applied to a startup scheme generation and processing system based on power grid equipment, the method comprises: Acquire a startup step model and a startup condition model, and generate a startup plan based on the power grid equipment based on the startup step model and the startup condition model; Perform equipment debugging and on-site verification based on the startup plan, and obtain debugging and verification data; Based on the startup scheme, simulating the startup process of the power grid equipment in a virtual environment, and recording current and voltage change data during the simulation process; A similarity calculation is performed on the debugging and verification data and the current and voltage change data, and when the similarity meets a threshold condition, it is determined that the startup scheme evaluation has passed.

7. A startup plan generation and processing device based on power grid equipment, characterized in that: The device comprises: A scheme generating module, used for acquiring a starting step model and a starting condition model, and generating a starting scheme based on the power grid equipment based on the starting step model and the starting condition model; An execution debugging module is used to perform equipment debugging and on-site verification based on the startup scheme, and obtain debugging and verification data; An automated simulation module, used to simulate the startup process of the power grid equipment in a virtual environment based on the startup scheme, and record current and voltage change data during the simulation process; The comprehensive evaluation module is used to calculate the similarity between the debugging and verification data and the current and voltage change data, and determine that the startup scheme evaluation has passed when the similarity meets the threshold condition.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to claim 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to claim 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to claim 6 are implemented.

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