A main and micro integrated regulation and multi-scenario training method and system

Abstract

The application discloses a kind of micro-integrated control and multi-scenario training method oriented main distribution system, method includes: obtaining the training data of simulation training input parameter;Set the initial environment of simulation training, including according to the training role and teaching plan information, according to the training range, the loading of simulation initial section data of control operation is carried out;Different scene, scene instance and the running mode of sub-scene are established, multi-person joint training simulation or multi-person independent training simulation is carried out, and the training process is scored, and evaluation report is generated.The application provides simulation training scene management, starts the simulation environment of specified scene, provides fault and abnormal setting function for instructor, provides two training modes of joint training and independent training for student, automatically records important information of student operation, carries out evaluation, realizes the control operation simulation of micro-integrated main distribution and multi-scenario training of distribution network, improves the ability of staff to quickly analyze and handle fault, improves the ability of power supply recovery.

Description

Technical Field

[0001] This invention relates to the field of power distribution network technology, and in particular to a method and system for integrated control of main distribution and micro-distribution systems and multi-scenario training. Background Technology

[0002] With the guidance of national policies and the continuous investment of power companies, the application of integrated dispatching and distribution systems in the power grid is becoming more and more widespread. However, the differences between the main and distribution networks in terms of voltage levels, service targets, and application focus have brought about significant changes in traditional power grid technologies and operation methods, placing higher demands on the professional skills and teamwork of main and distribution network production personnel.

[0003] Currently, there are few environments suitable for multi-level grid boundary equipment joint simulation training that integrates main, distribution, and micro-level systems. As a result, the ability of staff to quickly analyze and handle faults and restore power supply is low. However, research on simulation of control and operation strategies for main, distribution, and micro-level systems and multi-scenario training technology for distribution networks can help improve the ability to handle faults quickly by constructing a simulation operation environment that integrates main and distribution systems and studying joint training of main and distribution personnel in such an environment. Summary of the Invention

[0004] The purpose of this section is to outline some aspects of embodiments of the present invention and to briefly describe some preferred embodiments. Simplifications or omissions may be made in this section, as well as in the abstract and title of this application, to avoid obscuring the purpose of these documents; however, such simplifications or omissions should not be construed as limiting the scope of the invention.

[0005] In view of the aforementioned existing problems, this invention is proposed. Therefore, this invention provides a method for integrated control and multi-scenario training of main-distribution-micro-control systems, addressing the problem of joint simulation training of multi-level grid boundary equipment in integrated main-distribution-micro-control simulation training.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] In a first aspect, the present invention provides a method for integrated control of main and auxiliary systems and multi-scenario training, including:

[0008] Obtain training data for simulation training input parameters;

[0009] The training data is input into the simulation training to set up the initial environment of the simulation training, including loading the initial cross-sectional data of the simulation to be adjusted and run according to the training scope based on the training roles and lesson plan information.

[0010] Based on the initial environment, different scenarios, scenario instances, and sub-scenario operation modes are established to conduct multi-person joint training simulation or multi-person independent training simulation, and the training process is scored to generate evaluation reports.

[0011] As a preferred embodiment of the integrated control and multi-scenario training method for main and auxiliary systems described in this invention, the training data includes:

[0012] Training users are the usernames of the users who will be operating the system.

[0013] Training roles include instructor roles and trainee roles;

[0014] The training scope includes the main network, distribution network, microgrid, main distribution, distribution microgrid, and integrated main distribution microgrid. The training scope of the instructors or trainees is set according to the responsibility area of ​​the dispatchers.

[0015] Training lesson plan information, including lesson plan title, relevant sections, and relevant events.

[0016] As a preferred embodiment of the integrated control and multi-scenario training method for main and auxiliary components described in this invention, the initial environment for the simulation training includes:

[0017] Based on the instructor role, a multi-instructor collaborative lesson plan creation system is provided, integrating main, auxiliary, and micro-instructor functions. The system automatically generates lesson plans based on the fault location, lesson plan type, and duration, and analyzes, processes, and inputs them into the evaluation system. At the same time, a training mode is provided for the instructor role to supervise the training process of trainees.

[0018] Based on the student's role, the lesson plan section is loaded. Based on the relative time of the lesson plan, the fault or abnormal operation mode is triggered at regular intervals, waiting for the student to process the simulation environment for operation. The student's operation information is recorded and synchronized to the instructor's role.

[0019] As a preferred embodiment of the integrated control and multi-scenario training method for main and auxiliary components described in this invention, the lesson plan preparation includes:

[0020] Acquire primary and secondary models of the main distribution network, state estimation section data, dispatching plan data, and load forecasting data, and generate training sections through section adjustment and remote sensing data adjustment;

[0021] The lesson plan is created through graphical operations, a set of graphics is created, and the primary and secondary model framework of the main distribution network is set in the first layer.

[0022] The state estimation section data, scheduling plan data, and load forecast data are converted into visual graphics and set in the second layer;

[0023] Based on the lesson plan information and training scope, design the graphic layout and style, highlight the key points of the graphics through different graphic elements, text, colors and label combinations, and display and adjust them on the second layer;

[0024] Data conforming to the primary and secondary models of the main distribution network are processed and analyzed, and data is filtered, sorted or aggregated. Calculations and inferences are performed based on the data, and the data is set in the third layer.

[0025] Drag the second and third layers into the first layer to associate them, and arrange them according to the model field parameters and the teaching logic of the lesson plan to create an interactive graphic collection. Add interactive functions, including hovering to display data values ​​or clicking to switch different graphic data views.

[0026] Save the training lesson plan's graphic set, operation events, fault events, lesson plan name, and lesson plan type to complete the lesson plan information creation.

[0027] As a preferred embodiment of the integrated control and multi-scenario training method for main and auxiliary components described in this invention, the teaching plan is initiated in the following ways:

[0028] Acquire real-time state estimation data of the online system, use the real-time state estimation results as the online lesson plan, use them as the initial power flow, and start the simulation.

[0029] Obtain any saved lesson plan data section as the initial flow and start the simulation;

[0030] Obtain the flow profile of the scheduler as the initial flow profile, and start the simulation;

[0031] The cross section obtained from the accident inversion is subjected to state estimation, which serves as the initial power flow cross section for the dispatcher training simulation, and the simulation is started.

[0032] Retrieve the stored cross-sections, and based on the network cross-sections saved at any stage of training, use them as the initial power flow to start the simulation;

[0033] The simulation starts by resetting the lesson plan and retrieving data from the offline original database to generate offline lesson plans as the initial flow.

[0034] As a preferred embodiment of the integrated control and multi-scenario training method for main and auxiliary systems described in this invention, the scenario includes:

[0035] Scenario creation includes creating simulation scenario instances based on user training needs, selecting the simulation scope and simulation users, dynamically allocating resources based on the simulation scope, isolating scenario instances from each other, and having access permission management for scenario instances.

[0036] Scenario monitoring includes monitoring the status of training system resources and the usage of scenario instances;

[0037] Scenario release includes dynamically recycling scenario instances, supporting manual recycling and custom recycling time.

[0038] As a preferred embodiment of the integrated control and multi-scenario training method for main and auxiliary systems described in this invention, wherein:

[0039] The operation simulation includes,

[0040] Normal operation simulation, which simulates the normal operation of primary and secondary equipment in the power system, and supports the simulation of power grid dispatching operation commands;

[0041] The simulation of incorrect operations automatically identifies incorrect operations during the training process and provides prompts.

[0042] Dispatch order simulation, simulating the execution process of special dispatch orders and integrated dispatch orders;

[0043] Abnormal fault simulation includes simulation of faults and abnormalities in lines, equipment, and secondary protection automatic devices, as well as simulation of compound faults formed by the superposition of faults and abnormalities. It also includes simulation of new energy grid disconnection and setting of faults and abnormalities in feeder equipment.

[0044] Secondly, this invention provides a system for integrated control of main and auxiliary components and multi-scenario training, including:

[0045] The data acquisition module is used to acquire data from the simulation training.

[0046] The training environment management module is used to maintain and monitor the entire lifecycle of simulated training scenarios. This includes scenario creation, instance monitoring, and scenario release.

[0047] The lesson plan management module is used to acquire main and auxiliary micro-models, state estimation section data, scheduling plan data, and load forecast data on demand, and to perform simulations.

[0048] The multi-person simulation training module is used for joint training of multiple people on the same lesson plan, or for independent training of multiple people on the same lesson plan.

[0049] The simulation result evaluation module is used to evaluate and score the training process according to the evaluation rules set in the lesson plan, automatically identify the wrong operation in the training process, provide online auxiliary prompts, record and save important training information events of trainees in the training process, and generate evaluation reports.

[0050] Thirdly, the present invention provides an electronic device, comprising:

[0051] Memory and processor;

[0052] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of the main-component-micro integrated control and multi-scenario training method.

[0053] Fourthly, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the method for integrated control of main and auxiliary micro-systems and multi-scenario training.

[0054] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention manages simulation training scenarios, sets corresponding training start-up parameters, starts the simulation environment of specified scenarios, provides instructors with fault and anomaly setting functions, provides an integrated operating environment covering main and distribution micro-models, provides trainees with two training modes: joint training and independent training, automatically records important information of trainees' operations, and automatically evaluates trainees' operations based on simulation result evaluation functions. It realizes integrated control and operation simulation of main and distribution micro-models and multi-scenario training of distribution networks, studies joint training of main and distribution personnel in an integrated dispatching environment, improves staff's ability to quickly analyze and handle faults, and enhances the ability to restore power supply. Attached Figure Description

[0055] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0056] Figure 1 This is a schematic diagram of the overall process of the integrated control and multi-scenario training method for main and auxiliary micro-control as described in one embodiment of the present invention. Detailed Implementation

[0057] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0058] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0059] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0060] This invention is described in detail with reference to the schematic diagrams. When detailing the embodiments of this invention, for ease of explanation, the cross-sectional views illustrating the device structure may be partially enlarged, not adhering to the usual scale. Furthermore, the schematic diagrams are merely examples and should not be construed as limiting the scope of protection of this invention. In actual fabrication, the three-dimensional spatial dimensions of length, width, and depth should be included.

[0061] Furthermore, in the description of this invention, it should be noted that the terms "upper," "lower," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are used solely for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. In addition, the terms "first," "second," or "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0062] Unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" in this invention should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; similarly, they can refer to mechanical connections, electrical connections, or direct connections, or indirect connections through an intermediate medium, or internal connections between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0063] Example 1

[0064] Reference Figure 1 As an embodiment of the present invention, a method for integrated control of main and auxiliary components and multi-scenario training is provided, comprising:

[0065] S1, acquire data on simulation training input parameters, including training users, training roles, training scope, and training lesson plan information;

[0066] Furthermore, train users on the user names for operation;

[0067] Training roles include instructor roles and trainee roles;

[0068] The training scope includes multiple options such as main network, distribution network, microgrid, main distribution, distribution microgrid, and integrated main distribution microgrid. The corresponding teaching plan scope for instructors or the training scope for trainees are set according to the responsibility area of ​​the dispatcher.

[0069] Training lesson plan information, including lesson plan title, relevant sections, and relevant events.

[0070] S2, in the simulation training based on the data input, set up the initial environment of the simulation training, including loading the initial cross-sectional data of the simulation to be adjusted and run according to the training scope based on the training roles and lesson plan information;

[0071] Specifically, for the same training user, only one training session is allowed, and the user cannot be assigned both instructor and trainee roles at the same time.

[0072] Furthermore, based on the instructor's role, it provides a multi-instructor collaborative lesson plan creation service that integrates main, supplementary, and micro-instructor functions. The service automatically generates lesson plans based on the location of the fault, the type of lesson plan, and the duration, and analyzes and inputs the processing strategies into the evaluation system. At the same time, it provides a training model for instructors to supervise the processing of trainees.

[0073] Based on the student's role, the lesson plan section is loaded. Based on the relative time of the lesson plan, the fault or abnormal operation mode is triggered at regular intervals, waiting for the student to process the simulation environment for operation. The student's operation information is recorded and synchronized to the instructor's role.

[0074] Specifically, the instructor role can set the location of the fault and the type of fault. Based on the location of the fault and the type of fault, it can automatically analyze the action logic of the primary and secondary equipment and simulate and analyze the action sequence at the time of the fault.

[0075] Furthermore, lesson plan preparation includes,

[0076] Acquire primary and secondary models of the main distribution network, state estimation section data, dispatching plan data, and load forecasting data, and generate training sections through section adjustment and remote sensing data adjustment;

[0077] Lesson plans can be created through graphical manipulation or manual editing.

[0078] Preferably, lesson plans are created through graphical operations, which are faster and more efficient, and the resulting lesson plans are more in line with requirements, thus improving work efficiency compared to manual editing.

[0079] The lesson plan is created through graphical operations, a set of graphics is created, and the primary and secondary model framework of the main distribution network is set in the first layer.

[0080] The state estimation section data, scheduling plan data, and load forecast data are converted into visual graphics and set in the second layer;

[0081] Based on the lesson plan information and training scope, design the graphic layout and style, highlight the key points of the graphics through different graphic elements, text, colors and label combinations, and display and adjust them on the second layer to convey information;

[0082] Data conforming to the primary and secondary models of the main distribution network are processed and analyzed, and data is filtered, sorted or aggregated. Calculations and inferences are performed based on the data, and the data is set in the third layer.

[0083] Drag the second and third layers into the first layer to associate them, and arrange them according to the model field parameters and the teaching logic of the lesson plan to create an interactive graphic collection. Add interactive functions, including hovering to display data values ​​or clicking to switch different graphic data views.

[0084] Save the training lesson plan's graphic set, operation events, fault events, lesson plan name, and lesson plan type to complete the lesson plan information creation.

[0085] It should be noted that the training plan creation, saving, and loading functions provide instructors with lesson preparation capabilities, including the establishment of initial training scenarios and the setting of events. Multiple methods for setting initial conditions are available, offering various means to control the training process. Instructors can easily set up the scenarios required for training and create event-based training plans. The instructor console control provides instructors with control and monitoring of the training process, supporting operation settings and fault / anomaly settings for main and distribution micro-equipment. Event settings can be performed in multiple ways, such as on the plant wiring diagram, on the power flow wiring diagram, or on the event list.

[0086] It offers a wealth of lesson plan settings to meet different needs. Furthermore, the methods for initiating lesson plans include...

[0087] Acquire real-time state estimation data of the online system, use the real-time state estimation results as the online lesson plan, use them as the initial power flow, and start the simulation.

[0088] The simulation can be started by acquiring any saved lesson plan data section as the initial power flow. The simulation can be started from any saved case, and various different cases can be studied. The start can be from the most recent case to the required system state, and changes can be made as needed. The saved network wiring method, operation mode, secondary system configuration, etc. can all be modified. The modified lesson plan can be saved as another or overwritten. The initial power flow section can be bundled with event cases as a whole case for saving and use, or it can be saved separately and used in combination.

[0089] Obtain a cross-section of the Dispatcher Power Flow (DPF) as the initial power flow, and start the simulation. Since dispatcher power flow can be studied in various ways, including real-time, historical, and future modes, it can be selected as the basic case for Dispatcher Training Simulation (DTS) as needed.

[0090] The section obtained from the incident reversal (PDR) is estimated through state and used as the initial power flow section for dispatcher training simulation (DTS). Once the simulation is started, dispatcher training simulation (DTS) can be performed on historical incidents.

[0091] Obtain the stored cross-section, save the network cross-section at any stage of training as the initial power flow, and start the simulation, such as saving the end state of the post-fault transition process as the initial condition.

[0092] The simulation starts by resetting the lesson plan and retrieving data from the offline original database to generate offline lesson plans as the initial flow.

[0093] Furthermore, after selecting the desired initial cross-section, users can edit, save, and retrieve it. The lesson plan maintenance function allows users to save the obtained power flow pattern from any startup method; upon the next startup, simply enter the corresponding name to obtain the desired initial power flow. All initial cross-section power flows can be modified as needed, and the system also provides functions for retrieving, saving, deleting, and categorizing lesson plans. Each lesson plan has detailed prompts available for querying, including the lesson plan creator, creation time, modification time, source of the lesson plan, total system output, total load, and a brief description. These prompts can be expanded according to user needs.

[0094] The verification of the lesson plan includes initial condition verification and event table verification. Initial power flow verification involves calculating the initial power flow based on the starting values ​​in the initial conditions, observing whether there is a solution for the initial power flow, whether the calculation results are similar to the expectations, whether there are any abnormal phenomena, and whether the tie-line power is correct. If the initial power flow results are not satisfactory, the initial conditions are adjusted and verification is repeated. If the results are satisfactory, the training begins with the initial power flow. The effectiveness, usability, and suitability of the events set in the event table are observed and verified by the instructor through a training simulation system.

[0095] S3, based on the initial environment, establishes different scenarios, scenario instances and sub-scenario operation modes, conducts multi-person joint training simulation or multi-person independent training simulation, scores the training process, and generates evaluation reports.

[0096] It should be noted that scene isolation is used to isolate real-time running data from simulation data; instructor / student training roles are isolated through sub-scenes; independent simulations of multiple instructors / students are isolated through scene instances; and joint simulations of multiple instructors / students are connected through the same scene instance.

[0097] Furthermore, the establishment of scenarios includes,

[0098] Scenario creation includes creating simulation scenario instances based on user training needs, selecting the simulation scope and simulation users, dynamically allocating resources based on the simulation scope, isolating scenario instances from each other, and having access permission management for scenario instances.

[0099] Scenario monitoring includes monitoring the status of training system resources and the usage of scenario instances;

[0100] Scenario release includes dynamically recycling scenario instances, supporting manual recycling and custom recycling time.

[0101] It should be noted that the multi-student practical assessment in the simulation scenario supports joint training of multiple students using the same simulation lesson plan, as well as independent training of multiple students using different simulation lesson plans. Based on the user-submitted scenario type, model scope, and participating personnel, simulation resources are organized on demand, enabling flexible creation and dynamic recycling of simulation scenarios and flexible deployment of simulation environments. This provides simulation environments for training and joint exercises for ground and dispatching personnel, meeting the needs of multi-level, multi-person simultaneous online training and improving the utilization rate of training resources.

[0102] It can also start, terminate, pause, and resume training, and monitor the status and event execution during the training process.

[0103] Furthermore, operational simulation includes,

[0104] Normal operation simulation, which simulates the normal operation of primary and secondary equipment in the power system, and supports the simulation of power grid dispatching operation commands;

[0105] The simulation of incorrect operations automatically identifies incorrect operations during the training process and provides prompts.

[0106] Dispatch order simulation, simulating the execution process of special dispatch orders and integrated dispatch orders;

[0107] Abnormal fault simulation includes simulation of faults and abnormalities in lines, equipment, and secondary protection automatic devices, as well as simulation of compound faults formed by the superposition of faults and abnormalities. It also includes simulation of new energy grid disconnection and setting of faults and abnormalities in feeder equipment.

[0108] Specifically, normal operation simulation includes circuit breaker opening and closing, disconnector opening and closing, transformer tap changer and neutral grounding adjustment, shunt capacitor, shunt reactor and series compensator connection and disconnection operations, generator active power output, reactive power output and terminal voltage adjustment, equipment tagging and tag removal operations, support for plant / region / system load regulation, simulation and execution of dispatching orders, alarm confirmation, reset, suppression, blocking and other operations, remote control unlocking and locking operations, synchronization operations, parsing and execution of operation ticket operation sequences, and other normal operations.

[0109] The simulation of misoperation includes opening and closing disconnect switches under load, closing grounding switches (with grounding wires) while energized, energizing grounding switches (with grounding wires), closing switches at non-equipotential locations, energizing fault areas, closing loops on feeders with inconsistent wiring groups, and misoperation during training. Based on the equipment and type of misoperation, the simulation automatically triggers the generation of fault information for that equipment and drives the secondary protection action.

[0110] The dispatch order simulation includes specific dispatch orders and comprehensive operation instructions. Specific dispatch orders include switch operations, capacitor switching, reactor switching, generator start-up and shutdown, generator and load active / reactive power output adjustment, transformer tap adjustment, neutral point grounding switch (grounding switch) operation, fault handling and recovery operations, distributed power grid connection / off-grid operation, energy storage start-up control, active / reactive power output adjustment of adjustable resources in the distribution network, and start-up and shutdown of secondary equipment (including automatic transfer switch, feeder automation, and reclosing). Comprehensive operation instructions include: busbar bypass switch replacement, transformer, line, and busbar power outage / maintenance, and distribution network feeder operation mode adjustment. It can simulate dispatch operation terminology at all levels based on the network topology, parse comprehensive instructions, perform security checks on the execution of comprehensive orders, and provide relevant safety operation prompts, serving a self-training function.

[0111] Abnormal fault simulations include power distribution line short-circuit fault simulation, grounding fault simulation, and busbar undervoltage fault simulation.

[0112] It should be noted that the student simulation operation is primarily designed to help trainees familiarize themselves with daily dispatching operations and respond to power system regulation under abnormal operating conditions set by instructors. Through simulating various dispatching operations and post-fault system conditions, trainees perform dispatching operations, switching operations, fault handling, and source-grid-load-storage coordinated control, improving dispatchers' basic skills and accident response capabilities; conducting joint provincial, regional, and distribution fault response drills to enhance multi-level fault coordination capabilities; and conducting research and analysis on the operation of main and distribution microgrids to improve operators' grid awareness and analytical capabilities. The trainees' operation process is simultaneously recorded to the instructors, enabling real-time monitoring of the trainees.

[0113] Furthermore, simulation training evaluation can score the training process based on aspects such as operational safety, power grid safety, power supply reliability, and power supply economy during training exercises.

[0114] The evaluation reports can record and save various events and key states during the training of control personnel, and generate corresponding evaluation reports. The evaluation reports should include system power, voltage, current, and frequency exceeding limits, load loss, power loss, and misoperation situations. Records should also include student scheduling operations, instructor operations, misoperation records, bus power outage records, automatic device action records, and relay protection action records during the simulation.

[0115] This invention manages simulation training scenarios, sets corresponding training start-up parameters, launches the simulation environment for specified scenarios, provides instructors with fault and anomaly setting functions, offers an integrated operating environment covering main and distribution micro-models, and provides trainees with two training modes: joint training and independent training. It automatically records important information of trainees' operations and automatically evaluates trainees' operations based on simulation results. This enables integrated control and operation simulation of main, distribution, and micro-models and multi-scenario training for distribution networks. It also studies joint training of main and distribution personnel in an integrated dispatching environment, improving staff's ability to quickly analyze and handle faults and enhance power restoration capabilities.

[0116] The above is an illustrative scheme of a main-distribution-micro-integrated control and multi-scenario training method according to this embodiment. It should be noted that the technical solution of this main-distribution-micro-integrated control and multi-scenario training system belongs to the same concept as the technical solution of the above-described main-distribution-micro-integrated control and multi-scenario training method. Details not described in detail in this embodiment can be found in the description of the above-described main-distribution-micro-integrated control and multi-scenario training method.

[0117] This embodiment is for a main-distribution-micro integrated control and multi-scenario training system, including:

[0118] The data acquisition module is used to acquire data from the simulation training.

[0119] The training environment management module is used to maintain and monitor the entire lifecycle of simulated training scenarios. This includes scenario creation, instance monitoring, and scenario release.

[0120] The lesson plan management module is used to acquire main and auxiliary micro-models, state estimation section data, scheduling plan data, and load forecast data on demand, and to perform simulations.

[0121] The multi-person simulation training module is used for joint training of multiple people on the same lesson plan, or for multiple people to train independently on the same lesson plan.

[0122] The simulation result evaluation module is used to evaluate and score the training process according to the evaluation rules set in the lesson plan, automatically identify the wrong operation in the training process, provide online auxiliary prompts, record and save important training information events of trainees in the training process, and generate evaluation reports.

[0123] This embodiment also provides an electronic device suitable for integrated control of main and auxiliary components and multi-scenario training, including:

[0124] The system includes a memory and a processor. The memory stores computer-executable instructions, and the processor executes these instructions to implement the integrated control and multi-scenario training method for main and auxiliary micro-control systems as proposed in the above embodiments.

[0125] This embodiment also provides a storage medium storing a computer program, which, when executed by a processor, implements the method for integrated control of main and auxiliary micro-systems and multi-scenario training as proposed in the above embodiments.

[0126] The storage medium proposed in this embodiment belongs to the same inventive concept as the method for implementing integrated control of master and slave micro-systems and multi-scenario training proposed in the above embodiments. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0127] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0128] Example 2

[0129] Referring to Table 1, an embodiment of the present invention provides a method for integrated control of main and auxiliary micro-systems and multi-scenario training. To verify its beneficial effects, it is scientifically demonstrated through economic benefit calculations and simulation experiments.

[0130] Taking the actual operation data of a provincial power grid company as an example, historical cross-sectional operation data from the past week was used for control operation simulation testing. Considering the large amount of data in the distribution network model, to improve testing efficiency, the distribution network and microgrid models were trimmed according to feeders in the training course materials. Four feeders with interconnections and related microgrid models were selected for loading the training model cross-section. Three scenario examples were started for the training simulation. The instructor set up simulations of short-circuit faults, ground faults, and bus undervoltage faults. Trainees performed corresponding actions according to different faults. The simulation system automatically calculated the system power flow after the operation and automatically scored the trainees based on their actions. Refer to Table 1 for the simulation calculation reaction time results.

[0131] Method of the present invention Single power flow core calculation time ≤1s Fault response time ≤5s Operation control response time ≤5s

[0132] Table 1. Simulation results of reaction time calculation

[0133] According to the results in Table 1, during the simulation calculation, the time for a single power flow core calculation is ≤1 second, the fault and abnormal response time is ≤5 seconds, and the operation control response time is ≤5 seconds. A convenient and efficient integrated operation environment of main and auxiliary micro-models has been constructed, which significantly improves the ability of staff to quickly analyze and handle faults.

[0134] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for integrated control of main and auxiliary systems and multi-scenario training, characterized in that, include: Obtain training data for simulation training input parameters; The training data is input into the simulation training to set up the initial environment of the simulation training, including loading the initial cross-sectional data of the simulation to be adjusted and run according to the training scope based on the training roles and lesson plan information. Based on the initial environment, different scenarios, scenario instances, and sub-scenario operation modes are established to conduct multi-person joint training simulation or multi-person independent training simulation, and the training process is scored to generate an evaluation report. Setting up the initial environment for the simulation training includes providing multi-instructor collaborative lesson plan creation, which integrates main, supplementary, and micro-teacher roles. The lesson plan creation includes... Acquire primary and secondary models of the main distribution network, state estimation section data, dispatching plan data, and load forecasting data, and generate training sections through section adjustment and remote sensing data adjustment; The lesson plan is created through graphical operations, a set of graphics is created, and the primary and secondary model framework of the main distribution network is set in the first layer. The state estimation section data, scheduling plan data, and load forecast data are converted into visual graphics and set in the second layer; Based on the lesson plan information and training scope, design the graphic layout and style, highlight the key points of the graphics through different graphic elements, text, colors and label combinations, and display and adjust them on the second layer; Data conforming to the primary and secondary models of the main distribution network are processed and analyzed, and data is filtered, sorted or aggregated. Calculations and inferences are performed based on the data, and the data is set in the third layer. Drag the second and third layers into the first layer to associate them, and arrange them according to the model field parameters and the teaching logic of the lesson plan to create an interactive graphic collection. Add interactive functions, including hovering to display data values ​​or clicking to switch different graphic data views. Save the training lesson plan's graphic set, operation events, fault events, lesson plan name, and lesson plan type to complete the lesson plan information creation.

2. The method for integrated control and multi-scenario training of main and auxiliary components as described in claim 1, characterized in that, The training data includes, Training users are the usernames of the users who will be operating the system. Training roles include instructor roles and trainee roles; The training scope includes the main network, distribution network, microgrid, main distribution, distribution microgrid, and integrated main distribution microgrid. The training scope of the instructors or trainees is set according to the responsibility area of ​​the dispatchers. Training lesson plan information, including lesson plan title, relevant sections, and relevant events.

3. The method for integrated control and multi-scenario training of main and auxiliary components as described in claim 1 or 2, characterized in that, Setting up the initial environment for the simulation training includes, The system integrates multiple instructors to create collaborative lesson plans, automatically generating lesson plans based on the location of the fault, the type of lesson plan, and the duration. It also analyzes, processes, and inputs the lessons into the evaluation system. Simultaneously, it provides training models for instructors and monitors the training process of trainees. Based on the student's role, the lesson plan section is loaded. Based on the relative time of the lesson plan, the fault or abnormal operation mode is triggered at regular intervals, waiting for the student to process the simulation environment for operation. The student's operation information is recorded and synchronized to the instructor's role.

4. The method for integrated control and multi-scenario training of main and auxiliary systems as described in claim 1, characterized in that, The methods for initiating the lesson plan include: Acquire real-time state estimation data of the online system, use the real-time state estimation results as the online lesson plan, use them as the initial power flow, and start the simulation. Obtain any saved lesson plan data section as the initial flow and start the simulation; Obtain the flow profile of the scheduler as the initial flow profile, and start the simulation; The cross section obtained from the accident inversion is subjected to state estimation, which serves as the initial power flow cross section for the dispatcher training simulation, and the simulation is started. Retrieve the stored cross-sections, and based on the network cross-sections saved at any stage of training, use them as the initial power flow to start the simulation; The simulation starts by resetting the lesson plan and retrieving data from the offline original database to generate offline lesson plans as the initial flow.

5. The method for integrated control and multi-scenario training of main and auxiliary components as described in claim 1 or 4, characterized in that, Establishing the scenario includes, Scenario creation includes creating simulation scenario instances based on user training needs, selecting the simulation scope and simulation users, dynamically allocating resources based on the simulation scope, isolating scenario instances from each other, and having access permission management for scenario instances. Scenario monitoring includes monitoring the status of training system resources and the usage of scenario instances; Scenario release includes dynamically recycling scenario instances, supporting manual recycling and custom recycling time.

6. The method for integrated control and multi-scenario training of main and auxiliary systems as described in claim 5, characterized in that, Operational simulation includes, Normal operation simulation, which simulates the normal operation of primary and secondary equipment in the power system, and supports the simulation of power grid dispatching operation commands; The simulation of incorrect operations automatically identifies incorrect operations during the training process and provides prompts. Dispatch order simulation, simulating the execution process of special dispatch orders and integrated dispatch orders; Abnormal fault simulation includes simulation of faults and abnormalities in lines, equipment, and secondary protection automatic devices, as well as simulation of compound faults formed by the superposition of faults and abnormalities. It also includes simulation of new energy grid disconnection and setting of faults and abnormalities in feeder equipment.

7. A system for integrated control and multi-scenario training of main and auxiliary equipment, characterized in that: include, The data acquisition module is used to acquire data from the simulation training. The training environment management module is used to maintain and monitor the entire lifecycle of simulation training scenarios, including scenario creation, instance monitoring, and scenario release. The lesson plan management module is used to acquire and simulate the main and auxiliary micro-models, state estimation section data, scheduling plan data, and load forecast data. The multi-person simulation training module is used for joint training of multiple people on the same lesson plan, or for independent training of multiple people on the same lesson plan. The simulation result evaluation module is used to evaluate and score the training process according to the evaluation rules set in the lesson plan, automatically identify the wrong operation in the training process, provide online auxiliary prompts, record and save important training information events of trainees in the training process, and generate evaluation reports. Setting up the initial environment for the simulation training includes providing multi-instructor collaborative lesson plan creation, which integrates main, supplementary, and micro-teacher roles. The lesson plan creation includes... Acquire primary and secondary models of the main distribution network, state estimation section data, dispatching plan data, and load forecasting data, and generate training sections through section adjustment and remote sensing data adjustment; The lesson plan is created through graphical operations, a set of graphics is created, and the primary and secondary model framework of the main distribution network is set in the first layer. The state estimation section data, scheduling plan data, and load forecast data are converted into visual graphics and set in the second layer; Based on the lesson plan information and training scope, design the graphic layout and style, highlight the key points of the graphics through different graphic elements, text, colors and label combinations, and display and adjust them on the second layer; Data conforming to the primary and secondary models of the main distribution network are processed and analyzed, and data is filtered, sorted or aggregated. Calculations and inferences are performed based on the data, and the data is set in the third layer. Drag the second and third layers into the first layer to associate them, and arrange them according to the model field parameters and the teaching logic of the lesson plan to create an interactive graphic collection. Add interactive functions, including hovering to display data values ​​or clicking to switch different graphic data views. Save the training lesson plan's graphic set, operation events, fault events, lesson plan name, and lesson plan type to complete the lesson plan information creation.

8. An electronic device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of the main-component-micro integrated control and multi-scenario training method according to any one of claims 1 to 6.

9. A computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the integrated control and multi-scenario training method for main-component micro-control as described in any one of claims 1 to 6.

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