A method and system for generating lesson plans for training virtual instructors in power grid dispatching

Abstract

The present invention discloses a method and system for generating a lesson plan for training a virtual instructor for power grid dispatching, and belongs to the technical field of power grid simulation. The method comprises: obtaining power grid regulation-related data, calling the experience parameters and operation rules of the virtual instructor in the simulation training process; obtaining the initial power flow section of power grid simulation according to the obtained power grid regulation-related data; generating the long-process operation section of the power grid and the initial expected fault set according to the initial power flow section of the power grid simulation and the experience parameters and operation rules of the virtual instructor in the simulation training process; and automatically generating a training lesson plan including the long-process operation mode of the power grid and the probability fault according to the long-process operation section of the power grid and the initial expected fault set, and based on the equipment operation power and abnormal operation time, performing probability fault calculation, question difficulty calculation, and student skill matching. The present invention can provide dispatching training simulation services, and improve the intelligence and practicality of dispatching training simulation.

Description

Technical Field

[0001] The invention provides a method and system for generating a teaching plan for training a virtual instructor for power grid dispatching, and belongs to the technical field of power grid simulation. Background Art

[0002] The uncertainty of the operation state of the new power system has increased, the number of vulnerable components has increased, the fault form, path, and characteristics are complex, the diversification of changes in the operation mode of the power grid and the diversification of the types of power grid faults have put forward higher requirements for the coordinated handling of multi-level power grid faults and the skill level of control and operation personnel. Conducting joint dispatching exercises is an effective means to improve the coordinated handling of faults by control and operation personnel. At present, the dispatching profession mainly relies on dispatcher training simulation to conduct joint anti-accident exercises and talent training, but there are still defects in scene simulation and interaction methods, resulting in low utilization rate and poor practicality of the exercise system.

[0003] First, current training simulations are based on a single fixed grid operation mode for fault simulation and calculation, which is out of touch with the actual grid operation status and cannot simulate the changes in grid operation status at multiple time scales;

[0004] Second, real instructors are required to prepare lesson plans before training, monitor and control the drill process during training, and conduct comprehensive evaluation after training. This requires high professional capabilities of instructors and makes it difficult to configure real instructors on time and as needed to support dispatcher training and drills.

[0005] Third, in terms of interaction and progress during the exercise, the exercise was carried out step by step according to the script prepared in advance, with the problem of focusing more on "exercise" and less on "practice", which failed to reflect the control personnel's ability to deal with sudden failures. Summary of the invention

[0006] The present invention proposes a method and system for generating a lesson plan for a virtual instructor training of a power grid dispatching. The present invention can provide dispatching training simulation services, thereby improving the intelligence and practicality of dispatching training simulation.

[0007] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0008] In a first aspect, the present invention provides a virtual instructor training system for power grid dispatching, comprising:

[0009] A virtual instructor designer is used to set the experience parameters and operation rules of the virtual instructor during the simulation training process; the operation rules include simulation operation rules, simulation fault triggering rules and simulation evaluation rules;

[0010] A virtual instructor controller, the virtual instructor controller comprising:

[0011] The module for generating lesson plans for initial training of virtual trainers is used to generate long-term operation sections of power grids and initial expected fault sets;

[0012] The virtual instructor probabilistic fault trigger module is used to calculate probabilistic faults, calculate the difficulty of questions, and match trainee skills based on the equipment operating power and abnormal operating time, and automatically generate training lesson plans that include the long-term operation mode of the power grid and probabilistic faults.

[0013] The virtual instructor training evaluation module is used for the virtual instructor to evaluate and score the trainees' performance during the entire training process after the simulation is completed;

[0014] The virtual instructor executor is used to control the entire training process according to the calculation logic of the virtual instructor controller;

[0015] And the virtual teacher management center is used to collect the control instructions of the virtual teacher controller and the operating status of the virtual teacher actuator in real time.

[0016] As a further improvement of the present invention, in the virtual instructor designer, the experience parameters and operating rules of the virtual instructor in the simulation training process are set by an experienced dispatcher based on historical training conditions, and control centers at all levels specify different rules based on their respective power grid characteristics and the overall skill level of their personnel.

[0017] As a further improvement of the present invention, the simulation operation rules include:

[0018] When the training time reaches the total simulation time, the virtual instructor automatically stops the training simulation; the total simulation time is the product of the maximum number of simulated faults and the upper limit of the single fault handling time;

[0019] The virtual instructor loads the long-process operation section of the power grid according to the simulation time interval of the long-process operation section of the power grid;

[0020] The virtual instructor needs to determine whether to continue the simulation training based on the simulation end conditions.

[0021] As a further improvement of the present invention, the simulation end condition includes:

[0022] a) The simulation duration is greater than the total simulation duration;

[0023] b) The current fault handling time is greater than the upper limit of single fault handling time;

[0024] c) The number of triggered grid probabilistic faults has reached the maximum number of simulated faults, and the trainee has handled the last grid fault;

[0025] d) The power flow calculation does not converge.

[0026] As a further improvement of the present invention, the simulation fault triggering rule includes:

[0027] Set the number of initial expected faults and the initial expected fault triggering time interval, and the virtual instructor automatically triggers the initial expected fault according to the initial expected fault triggering time interval;

[0028] The virtual instructor calls the probability fault calculation module once every minimum triggering time interval of multiple probability faults;

[0029] The virtual instructor evaluates the rapidity of fault handling based on the standard handling time for a single fault and the upper limit handling time for a single fault;

[0030] The total duration of this training simulation is limited by setting the maximum number of simulated faults. When the number of faults triggered during this training simulation has reached the maximum number of simulated faults, the probability fault calculation and triggering will no longer be performed.

[0031] According to the average score, the difficulty matching range of the questions is set to obtain the matching rules between the difficulty of the questions and the level of the students.

[0032] As a further improvement of the present invention, the simulation evaluation rule includes:

[0033] The maximum value of active power flow transfer entropy and voltage transfer entropy are set according to the operation characteristics of each power grid and historical operation experience;

[0034] The active over-limit coefficient and the voltage over-limit coefficient are obtained according to the influence of the active over-limit branch and the voltage over-limit node on the operation of the power grid;

[0035] The normalized weight coefficient of the difficulty of the question is calculated according to the weight ratio between the difficulty of active power flow adjustment, the difficulty of voltage regulation and the difficulty of multi-agency dispatching and coordination;

[0036] According to the weight ratio of the equipment over-limit handling score, the power supply restoration score of the power-off equipment and the fault point isolation score in the fault handling correctness score, the fault handling correctness score distribution ratio is obtained;

[0037] The single deduction value for the rationality of fault handling is obtained based on the deduction value of a single over-limit event, a single power-off device, and a single misoperation behavior;

[0038] The normalized weight coefficient of the comprehensive score is obtained according to the weight ratio among the correctness, rationality and speed of fault handling.

[0039] As a further improvement of the present invention, the virtual instructor initial training lesson plan generation module includes:

[0040] The long-term operation section generation unit of the power grid is used for:

[0041] Obtain the current state estimation section from the control cloud platform as the initial simulation section;

[0042] According to the total duration of this simulation , obtain the daily power generation plan, new energy forecast and load forecast data in the future simulation period, and form m future power grid operation sections, where , l is the time granularity of intraday real-time plan forecast;

[0043] According to the long process operation section simulation time interval of the power grid , perform linear interpolation on m future operation sections of the power grid to obtain k long-term operation sections of the power grid, where ; Verify the power flow convergence of k long-term operation sections of the power grid;

[0044] The initial expected fault set generation unit is used to:

[0045] According to the initial expected number of faults and initial expected fault triggering time interval To formulate an initial set of anticipated faults;

[0046] if , then conduct N-1 static safety analysis on the initial operation section and select the equipment failure with the greatest risk of power grid operation as the initial expected failure;

[0047] if , then N-1 static safety analysis is performed on the initial simulation section and the rth long-term operation section of the power grid, and the equipment failure with the greatest risk of power grid operation under each section is selected as the initial expected fault set; among them, .

[0048] As a further improvement of the present invention, in the virtual instructor probability fault trigger module,

[0049] Perform probabilistic failure calculations, the probability of equipment failure for

[0050]

[0051] in, is the failure probability of equipment i at time t without considering the historical operation conditions; is the influencing factor, which indicates the influence of equipment load rate and time on the growth of failure probability. The abnormal operation time of the equipment. The maximum allowed abnormal operation time of the equipment.

[0052] As a further improvement of the present invention, in the virtual instructor probability fault trigger module, the question difficulty calculation is performed, and the question difficulty D is:

[0053]

[0054] In the formula, For the difficulty of the question, is the normalized power grid active power flow transfer entropy weight coefficient, is the normalized grid voltage transfer entropy weight coefficient, is the fault handling management difficulty weight coefficient, ; is the normalized power grid active power flow transfer entropy, is the normalized grid voltage transfer entropy, S Increase the difficulty of troubleshooting management.

[0055] As a further improvement of the present invention, the virtual instructor training evaluation module comprises:

[0056] The treatment rationality scoring unit is used to calculate the treatment rationality score during the entire simulation process. The trainee's operation does not further cause new equipment to exceed the limit or power outage, and the operation complies with the five-defense operation regulations of the power grid. ;

[0057] The handling speed score unit is used to require that fault handling be completed within a specified time. The longer the completion time, the lower the handling speed score. If the maximum fault handling time is exceeded, the handling speed score will be is 0;

[0058] The comprehensive score unit is used to indicate that if the score of handling correctness or handling speed is 0, it indicates that the trainee does not have the ability to handle the fault and the comprehensive score is 0; in other cases, the comprehensive score is the normalized calculated value of the above three scores.

[0059] As a further improvement of the present invention, the virtual instructor executor is specifically used to feed back the grid operation status and trainee behavior to the virtual instructor controller in real time, call the corresponding modules in the virtual instructor controller for calculation according to the training process, and receive control instructions to guide the simulation process into different branches.

[0060] As a further improvement of the present invention, the virtual instructor management center comprises:

[0061] The training lesson plan management unit is used to store the long-process operation section of the power grid, expected faults and probabilistic faults of the training simulation into the lesson plan library, and use the difficulty of the question as the difficulty label of the lesson plan;

[0062] The trainee skill management unit is used to store the trainee operations in the training simulation into the trainee behavior library, and store the trainee scores in this training simulation into the trainee portrait library;

[0063] The operation rule optimization unit is used to adjust the relevant parameters and rules in the virtual instructor designer according to the difficulty distribution of the lesson plans in the lesson plan library and the skill level distribution of the students.

[0064] In a second aspect, the present invention provides a method for generating a teaching plan for a virtual instructor training of power grid dispatching, comprising:

[0065] Obtain relevant data on power grid regulation and control, and call upon the experience parameters and operating rules of the virtual instructor during simulation training;

[0066] The initial power flow section of the power grid simulation is obtained according to the obtained power grid control related data;

[0067] According to the initial power flow section of the power grid simulation and the experience parameters and operation rules of the virtual instructor in the simulation training process, the long-term operation section of the power grid and the initial expected fault set are generated;

[0068] According to the long-term operation section of the power grid and the initial expected fault set, and based on the equipment operating power and abnormal operation time, probabilistic fault calculations, question difficulty calculations, and trainee skill matching are performed to automatically generate training lesson plans that include the long-term operation mode of the power grid and probabilistic faults.

[0069] As a further improvement of the present invention, the generating of the long-term operation section of the power grid and the initial expected fault set includes:

[0070] Obtain the current state estimation section from the control cloud platform as the initial simulation section;

[0071] According to the total duration of this simulation , obtain the daily power generation plan, new energy forecast and load forecast data in the future simulation period, and form m future power grid operation sections, where , l is the time granularity of intraday real-time plan forecast;

[0072] According to the long process operation section simulation time interval of the power grid , perform linear interpolation on m future operation sections of the power grid to obtain k long-term operation sections of the power grid, where ; Verify the power flow convergence of k long-term operation sections of the power grid;

[0073] According to the initial expected number of faults and initial expected fault triggering time interval To formulate an initial set of anticipated faults;

[0074] if , then conduct N-1 static safety analysis on the initial operation section and select the equipment failure with the greatest risk of power grid operation as the initial expected failure;

[0075] if , then N-1 static safety analysis is performed on the initial simulation section and the rth long-term operation section of the power grid, and the equipment failure with the greatest risk of power grid operation under each section is selected as the initial expected fault set; among them, .

[0076] As a further improvement of the present invention, in the probability failure calculation, the failure probability of the equipment for:

[0077]

[0078] in, is the failure probability of equipment i at time t without considering the historical operation conditions; is the influencing factor, which indicates the influence of equipment load rate and time on the growth of failure probability. The abnormal operation time of the equipment. The maximum allowed abnormal operation time of the equipment.

[0079] As a further improvement of the present invention, in the problem difficulty calculation, the problem difficulty D is:

[0080]

[0081] In the formula, is the normalized power grid active power flow transfer entropy weight coefficient, is the normalized grid voltage transfer entropy weight coefficient, is the fault handling management difficulty weight coefficient, ; is the normalized power grid active power flow transfer entropy, is the normalized grid voltage transfer entropy, and S is the difficulty of fault handling management.

[0082] As a further improvement of the present invention, the method of automatically generating a training lesson plan including the long-term operation mode of the power grid and the probabilistic faults according to the long-term operation section of the power grid and the initial expected fault set, and based on the equipment operating power and abnormal operation time, performing probabilistic fault calculation, question difficulty calculation, and student skill matching, includes:

[0083] S401, loading the initial power grid operation section;

[0084] S402, constructing an initial fault set, and performing initial fault simulation based on an initial power grid operation section;

[0085] S403, performing power flow calculation based on the initial fault simulation to obtain an initial power flow section of the power grid simulation;

[0086] S404: During the simulation clock advancement period, determine whether the simulation exit condition is reached:

[0087] If yes, S405, evaluate the simulation results and end the simulation;

[0088] If not, S406, determine whether the power grid long process operation section simulation time interval has been reached: if so, S407, load the power grid long process simulation section, and then proceed to S408; if not, directly enter S408;

[0089] S408, determining whether the initial expected fault triggering time interval has been reached:

[0090] If yes, S409, perform initial expected fault simulation and proceed to S410; if no, directly proceed to S410;

[0091] S410, determining whether the minimum triggering time interval of multiple probability faults has been reached:

[0092] If not, return to S403;

[0093] If yes, S411, determine whether the maximum number of simulated faults has been reached: If yes, S412, return to S403;

[0094] If not, S413, sample the current probability fault set, calculate the difficulty of the question, and determine whether it matches the student's skills based on the difficulty of the question;

[0095] If yes, S414, simulate probabilistic fault; return to S403, perform power flow calculation;

[0096] If not, return to S404.

[0097] As a further improvement of the present invention, in S405, performing simulation result evaluation includes:

[0098] The correctness score of the treatment is evaluated by judging the final operating state of the power grid at the end of the simulation , including equipment out-of-limit handling points , Power supply restoration score for power outage equipment And the fault point isolation score ;

[0099] Calculate the rationality score of the operation during the entire simulation process, if the trainee's operation does not cause any further equipment over-limit or power outage, and the operation complies with the five-defense operation regulations of the power grid. ;

[0100] Calculating the speed score :

[0101]

[0102] in, The actual time taken by students to handle the faults. is the standard processing time for a single fault, is the upper limit of single fault handling time, and Set up in the Virtual Instructor Designer;

[0103] Get the comprehensive score. If the score of the correctness of handling or the speed of handling is 0, it means that the trainee does not have the ability to handle the fault, and the comprehensive score is 0. In other cases, the comprehensive score is the normalized calculated value of the above three scores.

[0104] The simulation results are evaluated based on the comprehensive score.

[0105] In a third aspect, the present invention provides a system for generating lesson plans for training virtual instructors for power grid dispatching, comprising:

[0106] The acquisition and calling module is used to obtain the relevant data of power grid regulation and call the experience parameters and operation rules of the virtual instructor in the simulation training process;

[0107] An initial power flow section calculation module is used to obtain the initial power flow section of the power grid simulation according to the acquired power grid control related data;

[0108] The operation section generation module is used to generate the long-term operation section of the power grid and the initial expected fault set according to the initial power flow section of the power grid simulation and the experience parameters and operation rules of the virtual instructor in the simulation training process;

[0109] The training lesson plan generation module is used to automatically generate training lesson plans that include the long-term operation mode of the power grid and probabilistic faults based on the long-term operation section of the power grid and the initial expected fault set, and based on the equipment operating power and abnormal operation time, perform probabilistic fault calculations, question difficulty calculations, and student skill matching.

[0110] In a fourth aspect, the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method for generating lesson plans for training virtual instructors for power grid dispatching when executing the computer program.

[0111] In a fifth aspect, the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for generating lesson plans for training virtual instructors for power grid dispatching is implemented.

[0112] In a sixth aspect, the present invention provides a computer program product, wherein the computer program product includes computer instructions, and the computer instructions instruct a computer to execute the method for generating lesson plans for training virtual instructors for power grid dispatching.

[0113] The beneficial effects of the present invention compared with the prior art are as follows:

[0114] The present invention proposes a method for constructing a virtual instructor for power grid dispatching. Through a virtual instructor designer, a virtual instructor controller, a virtual instructor executor and a virtual instructor management center, the power grid operation mode is transformed from a single-section operation mode to a time-sequential advancement of a long-process operation mode of the power grid; the fault simulation is transformed from a deterministic anticipated fault simulation to a probabilistic fault simulation related to a real-time operation mode; and the simulation interaction is transformed from a trainee manually inputting training scenarios and question difficulty to automatically matching questions according to the trainee's skill level, thereby realizing a comprehensive digital replacement of the role of a real instructor in dispatching skill training, realizing a one-to-many, 24-hour all-weather and personalized dispatching training simulation service, and improving the intelligence and practicality of the dispatching training simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0115] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the embodiments of the present invention or the drawings of related technical solutions in the prior art are introduced below. It should be understood that the drawings introduced below are only for the convenience of clearly describing some embodiments of the technical solutions of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0116] Figure 1 A schematic diagram of the overall architecture of a virtual instructor for power grid dispatching according to an embodiment of the present invention;

[0117] Figure 2 A schematic diagram of a virtual teacher rule design system according to an embodiment of the present invention;

[0118] Figure 3 A functional diagram of a virtual instructor controller for power grid dispatching according to an embodiment of the present invention;

[0119] Figure 4 A schematic diagram of the operation flow of a virtual instructor executor for power grid dispatching according to an embodiment of the present invention;

[0120] Figure 5 A schematic diagram of operation branches of a virtual instructor executor for power grid dispatching according to an embodiment of the present invention. DETAILED DESCRIPTION

[0121] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and are not to be construed as limitations of the present invention. For the step numbers in the following embodiments, they are only provided for the convenience of explanation, and the order between the steps is not limited in any way, and the execution order of each step in the embodiment can be adaptively adjusted according to the understanding of those skilled in the art.

[0122] In the description of the present invention, unless otherwise clearly defined, terms such as setting, installing, connecting, etc. should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meanings of the above terms in the present invention in combination with the specific content of the technical solution.

[0123] Knowledge and skills training of power system-related majors is an important part of enterprise talent development. Currently, a large number of simulation systems and training resources put into operation have certain problems such as difficulty in use, low resource utilization, and low training efficiency. The power grid dispatching virtual instructor construction method proposed in this invention can provide a technical foundation and R&D framework for the digital and intelligent development of other professional knowledge and skills training exercises.

[0124] The present invention proposes a method for generating training lesson plans based on a virtual instructor for power grid dispatching, aiming to completely replace the role of real instructors in dispatching skill training through digital means, and realize intelligent, personalized and all-weather dispatching training simulation services. It includes the following aspects:

[0125] Virtual Instructor Designer: Set the experience parameters and operation rules of the virtual instructor in simulation training. It can be manually set by experienced dispatchers based on historical training conditions. Control centers at all levels can specify different rules based on the characteristics of the power grid and the skill level of personnel. The rule design system includes simulation operation rules, simulation fault triggering rules, simulation evaluation rules, etc.

[0126] The first object of the present invention is to provide a virtual instructor training system for power grid dispatching, comprising:

[0127] A virtual instructor designer is used to set the experience parameters and operation rules of the virtual instructor during the simulation training process; the operation rules include simulation operation rules, simulation fault triggering rules and simulation evaluation rules;

[0128] A virtual instructor controller, the virtual instructor controller comprising:

[0129] The module for generating lesson plans for initial training of virtual trainers is used to generate long-term operation sections of power grids and initial expected fault sets;

[0130] The virtual instructor probabilistic fault trigger module is used to calculate probabilistic faults, calculate the difficulty of questions, and match trainee skills based on the equipment operating power and abnormal operating time, and automatically generate training lesson plans that include the long-term operation mode of the power grid and probabilistic faults.

[0131] The virtual instructor training evaluation module is used for the virtual instructor to evaluate and score the trainees' performance during the entire training process after the simulation is completed;

[0132] The virtual instructor executor is used to control the entire training process according to the calculation logic of the virtual instructor controller;

[0133] And the virtual teacher management center is used to collect the control instructions of the virtual teacher controller and the operating status of the virtual teacher actuator in real time.

[0134] The present invention first generates an initial training lesson plan and triggers a probabilistic fault. The initial training lesson plan includes a long-process operation section of the power grid and an initial expected fault set. The fault probability is calculated based on the equipment operating power and abnormal operation time, and the difficulty of the questions is matched with the skill level of the trainees. The virtual instructor actuator controls the training process according to the calculation logic of the virtual instructor controller. The power grid state and the trainee behavior are fed back to the controller in real time. The simulation process is guided into different branches according to the control instructions. The simulation execution of initial faults and probabilistic faults is supported. The control instructions and actuator states are collected in real time, and the training lesson plan management, trainee skills and operation rule optimization functions are provided. The centralized management of the training lesson plan is realized. The trainee skill evaluation and operation rules are continuously optimized. The single-section operation mode is changed to the long-process operation mode to improve the simulation authenticity. The probabilistic fault is simulated in combination with the real-time operation mode to enhance the diversity and randomness of the fault simulation. The difficulty of the questions is automatically matched according to the skill level of the trainees to realize personalized training. The trainees' fault handling ability is comprehensively evaluated through the simulation evaluation rules, and the training effect is fed back in real time.

[0135] Therefore, the present invention improves trainees' dispatching skills and ability to cope with complex power grid faults through personalized and intelligent training methods.

[0136] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0137] The present invention combines the concept of virtual digital human and robotic process automation technology, and proposes a method for constructing a virtual instructor for power grid dispatching. Through a virtual instructor designer, a virtual instructor controller, a virtual instructor executor and a virtual instructor management center, the power grid operation mode is transformed from a single-section operation mode to a time-sequential advancement of a long-process operation mode of the power grid; the fault simulation is transformed from a deterministic expected fault simulation to a probabilistic fault simulation related to a real-time operation mode; the simulation interaction is transformed from the trainees manually inputting training scenarios and question difficulty to automatically matching questions according to the trainees' skill levels, thereby realizing a comprehensive digital replacement of the role of real instructors in dispatching skill training, realizing a one-to-many, 24-hour all-weather and personalized dispatching training simulation service, and improving the intelligence and practicality of the dispatching training simulation.

[0138] The overall architecture of the power grid dispatching virtual instructor training system based on the power grid dispatching virtual instructor is as follows: Figure 1 As shown below. Figure 1 Provide detailed description of each part.

[0139] 1. Virtual Instructor Designer: The virtual instructor designer is used to set the experience parameters and operation rules of the virtual instructor during the simulation training process. It can be manually set by an experienced dispatcher based on historical training conditions. Control centers at all levels can specify different rules based on their own power grid characteristics and overall personnel skill levels. The rule design system for virtual instructors is as follows: Figure 2 shown.

[0140] (1) Simulation operation rules

[0141] 1) Total simulation time : It is the product of the maximum number of simulated faults and the upper limit of the handling time for a single fault. When the current training time reaches the total simulation time, the virtual instructor automatically stops the training simulation.

[0142] 2) Simulation time interval of long-term operation section of power grid ; Virtual instructors follow The time interval is used to load the long operation section of the power grid.

[0143] 3) Simulation end conditions: The virtual instructor needs to determine whether to continue the simulation training based on factors such as the trainee's skill level, fault handling time, and simulation process. When the following rules are met, it indicates that the trainee's skill level is insufficient or has reached the training goal, and the probabilistic fault will no longer be triggered, and the virtual instructor will automatically stop the training simulation:

[0144] a. The simulation duration is longer than the total simulation duration;

[0145] b. The current fault handling time is greater than the upper limit of single fault handling time;

[0146] c. The number of triggered grid probabilistic faults has reached the maximum number of simulated faults, and the trainee has handled the last grid fault;

[0147] d. The power flow calculation does not converge.

[0148] (2) Simulation fault triggering rules

[0149] 1) Initial expected number of faults : The triggering of probabilistic faults is random. In order to ensure that there will be expected faults triggered during this training, the initial number of expected faults needs to be set. The minimum value is 1, and the maximum value can be determined according to the student's skill level. The higher the student's skill level, The bigger.

[0150] 2) Initial expected fault triggering time interval :If the initial expected number of faults If it is greater than 1, it is necessary to set the triggering time interval between multiple initial expected faults. The virtual instructor is based on Automatically trigger the initial expected fault.

[0151] 3) Minimum triggering time interval for multiple probability faults : Probabilistic faults cannot be triggered frequently and irregularly. The virtual instructor time, calling the probability fault calculation module once.

[0152] 4) Standard handling time for single fault And the upper limit of single fault handling time : It is related to the difficulty of troubleshooting. The virtual instructor and Conduct rapid fault handling assessment.

[0153] 5) Maximum number of simulated faults :It is related to the skill level of the trainees. The total duration of the training simulation is limited by setting the maximum number of simulated faults. When the number of faults triggered during the training simulation reaches , the virtual instructor no longer performs probability fault calculation and triggering.

[0154] 6) Rules for matching question difficulty with student level: The rules for matching question difficulty with student level are shown in Table 1 below.

[0155] Table 1

[0156]

[0157] (3) Simulation evaluation rules

[0158] 1) Maximum value of active power flow transfer entropy and the maximum value of voltage transfer entropy : In order to normalize the active power flow transfer entropy and voltage transfer entropy, these two values ​​are set according to the operating characteristics of each provincial power grid and historical operating experience.

[0159] 2) Active power over-limit coefficient And voltage over-limit coefficient : and It is to highlight the impact of active power exceeding limit branches and voltage exceeding limit nodes on grid operation, both of which are greater than 1.

[0160] 3) Normalized weight coefficient of question difficulty: the weight ratio of the question between the difficulty of active power flow adjustment, voltage regulation difficulty and multi-agency dispatching and coordination difficulty.

[0161] 4) Fault handling correctness score distribution ratio: Equipment over-limit handling score , Power supply restoration score for power outage equipment And the fault point isolation score The weight ratio of the three aspects in the fault handling correctness score.

[0162] 5) Individual deduction points for rationality of fault handling: deduction points for a single out-of-limit event, a single power outage device, or a single incorrect operation behavior.

[0163] 6) Normalized weight coefficient of comprehensive score: the weight ratio between the correctness of fault handling, the rationality of fault handling, and the speed of fault handling.

[0164] 2. Virtual Instructor Controller

[0165] (1) Virtual instructor initial training lesson plan generation module: The initial training lesson plan includes two parts: the long-term operation section of the power grid and the initial expected fault set.

[0166] 1) Generation of long-term operation sections of power grid, including:

[0167] Obtain the current state estimation section from the control cloud platform as the initial simulation section;

[0168] According to the total duration of this simulation , obtain the daily power generation plan, new energy forecast and load forecast data in the future simulation period (the time granularity of the daily real-time plan forecast is l, for example, l is 15 minutes), and form m future power grid operation sections, where .

[0169] According to the long process operation section simulation time interval of the power grid , perform linear interpolation on m future operation sections of the power grid to obtain k long-term operation sections of the power grid, where The power flow convergence is verified for k long-term operation sections of the power grid. If the power flow does not converge, in order to ensure that the impact on the operation status of the power grid within the grid is small, the equivalent units or equivalent loads at the boundary of the tie line are used to distribute and adjust the power flow unbalance to ensure the convergence of the power flow of the entire power grid.

[0170] 2) Generate the initial expected fault set, including:

[0171] According to the initial expected number of faults and initial expected fault triggering time interval To formulate an initial set of anticipated faults.

[0172] if , then perform N-1 static safety analysis on the initial operation section and select the equipment failure with the greatest risk of power grid operation as the initial expected failure.

[0173] if , then N-1 static safety analysis is performed on the initial simulation section and the rth long-process operation section of the power grid, and the equipment failure with the greatest risk of power grid operation under each section is selected as the initial expected fault set.

[0174] in,

[0175] (2) Virtual instructor probabilistic fault trigger module, including:

[0176] The virtual instructor's probabilistic fault triggering module includes three parts: probabilistic fault calculation, question difficulty calculation, and student skill matching.

[0177] 1) Probabilistic failure calculation, including:

[0178] According to the operation reliability theory, the equipment outage probability p is closely related to the equipment operating power, and a straight line segment is often used to fit the equipment outage probability curve that changes with the power flow. The present invention does not consider the probability of hidden protection failure. The formula is simplified as follows.

[0179]

[0180] In the formula, is the failure probability of equipment i at time t without considering the historical operation status, is the rated power of device i, is the maximum operating power of device i.

[0181] The longer the equipment is overloaded or exceeds the limit, the greater the probability of equipment failure. If the trainees fail to deal with it in time, it will cause a wider range of failures. Therefore, the above failure probability function is superimposed with an exponentially growing time function.

[0182]

[0183]

[0184] In the formula, is the failure probability of equipment i at time t considering the historical operation conditions, is the influencing factor, which indicates the influence of equipment load rate and time on the growth of failure probability. The abnormal operation time of the equipment (i.e. the operation time when the power is between the rated power and the limit operation power). This is the moment when the device exceeds the rated power for the first time. The following constraints should be met

[0185]

[0186] In the formula, The maximum allowed abnormal operation time of the equipment. , then the probability of equipment failure is 1.

[0187] After normalization of the above formula, the final equipment failure probability is obtained: for

[0188]

[0189] In the formula, is the normalized failure probability of device i at time t.

[0190] The present invention mainly calculates the fault probability of four types of equipment, namely, AC lines, transformers, busbars and converters, and obtains a probabilistic fault set by sampling.

[0191] 2) Question difficulty calculation, including:

[0192] Each time a probabilistic fault is triggered, a new training question is triggered for the trainees, and the difficulty of the question, that is, the difficulty of handling the fault, needs to be calculated to provide a basis for the subsequent evaluation of the trainees' skill level. The difficulty of the question is judged from the perspective of power grid operation and fault handling.

[0193] In terms of power grid operation, the power flow transfer entropy is used to describe the impact of power flow transfer in a short period of time on the entire power grid after a certain device is disconnected.

[0194] In the traditional power flow transfer entropy calculation method, the active power flow change distribution coefficient It represents the proportion of active power flow change borne by branch a after branch b is disconnected. The calculation formula is as follows

[0195]

[0196] in, is the change in active power flow of branch a after branch b is disconnected, is the total number of power grid branches.

[0197] The traditional power flow transfer entropy calculation method does not consider the influence of branch limit transmission capacity on the rationality of power grid power flow distribution. The present invention adds active over-limit coefficient to the above calculation method. If the active power flow of branch a exceeds the limit after branch b is disconnected, the power flow change distribution coefficient of branch b should be appropriately expanded to indicate the irrationality of the current power flow distribution of the power grid.

[0198]

[0199] in, is the active power of branch a, is the upper limit of active power of branch a.

[0200] Power Grid Active Power Flow Transfer Entropy The calculation formula is as follows

[0201]

[0202] Active power flow transfer entropy Normalization is performed. If the breaking active power flow of branch b is borne by only one branch, then The minimum value is 0. The maximum value of Perform normalization processing and set the maximum value of active power flow transfer entropy according to the characteristics of each provincial power grid . Normalized power grid active power flow transfer entropy The calculation is as follows

[0203]

[0204] Similarly, the grid voltage transfer entropy can be calculated: and normalized grid voltage transfer entropy

[0205]

[0206]

[0207]

[0208] in, is the total number of power grid buses, represents the voltage change at node c after branch d is disconnected. It represents the voltage change ratio of node c after branch d is disconnected. is the voltage over-limit coefficient. If the voltage at node c exceeds the limit after branch d is disconnected, then It should be appropriately expanded to show the irrationality of the current grid voltage distribution, and the maximum value of voltage transfer entropy should be set according to the characteristics of each provincial grid. , is the voltage value of node c, is the lower limit of the voltage at node c, is the upper voltage limit of node c.

[0209] In terms of fault handling management, the number of control agencies and power stations involved in the fault handling is counted based on the power outage equipment, over-limit equipment, overloaded equipment and abnormal equipment affected by the fault. The larger the affected scope, the greater the dispatch difficulty and the longer the fault handling time, and thus the greater the difficulty of fault handling.

[0210]

[0211] Among them, S is the difficulty of fault handling management, D is the number of regulatory agencies involved in this fault, and S is the number of plants and stations involved in this fault. is the total number of regulatory agencies, The total number of plants and stations.

[0212] Total number of regulatory agencies Calculation method:

[0213] If the power grid at this level is controlled by the state, the total number of regulatory agencies is the sum of the national regulatory agencies, the network regulatory agencies and the provincial regulatory agencies, which is 34 in total.

[0214] If the power grid at this level is grid-regulated, the total number of regulating agencies shall be the sum of the national regulating agencies, the grid-regulated agencies and all provincial regulating agencies dispatched by the grid-regulated agencies.

[0215] If the power grid at this level is provincially controlled, the total number of control agencies is the sum of the number of network control agencies under the provincial control, the provincial control agencies, and all local control centers under the provincial control agencies.

[0216] If the power grid at this level is a local dispatching system, the total number of dispatching agencies is the sum of the number of provincial dispatching systems to which the local dispatching system belongs, local dispatching systems, and other local dispatching control centers that are topologically connected with the local dispatching systems.

[0217] In summary, the calculation formula for the difficulty D of the question is:

[0218]

[0219] In the formula, is the normalized power grid active power flow transfer entropy, is the normalized grid voltage transfer entropy, S is the difficulty of fault handling management, is the normalized power grid active power flow transfer entropy weight coefficient, is the normalized grid voltage transfer entropy weight coefficient, are the fault handling management difficulty weight coefficients. These three coefficients are set in the virtual instructor designer to meet the following constraints

[0220] .

[0221] 3) Student skills matching, including:

[0222] The difficulty of the question and the matching rules of the student's skills specified in the virtual instructor designer are used to determine whether the current question should be pushed to the student.

[0223] (3) Virtual Instructor Training Evaluation Module

[0224] After the simulation, the virtual instructor evaluates and scores the trainees' performance throughout the training process, evaluating them from three aspects: correctness of handling, rationality of handling, and speed of handling.

[0225] 1) Correctness score of treatment :

[0226] The correctness of fault handling is evaluated by judging the final operating state of the power grid at the end of the simulation. It mainly includes the equipment over-limit handling score , Power supply restoration score for power outage equipment And the fault point isolation score The total score of the correctness of the treatment is 100 points, and the distribution ratio of the three aspects is determined by the virtual instructor designer.

[0227] .

[0228] 2) Reasonableness score of disposal :

[0229] The rationality of the handling requires that during the entire simulation process, the trainees' operations do not cause new equipment to exceed the limit or equipment power outage, and the operations comply with the five-prevention operation regulations of the power grid.

[0230]

[0231] in, is the number of devices that exceed the limit. It is the deduction value for a single limit-crossing event; is the number of power outage devices, Point deduction value for individual power outage equipment; is the number of misoperated devices, Points are deducted for a single incorrect operation.

[0232] 3) Processing speed score :

[0233] Speed ​​of handling requires trainees to complete fault handling within the specified time. The longer the completion time, the lower the speed of handling score. If the maximum fault handling time is exceeded, the speed of handling score is 0.

[0234]

[0235] in, The actual time taken by students to handle the faults. is the standard processing time for a single fault, is the upper limit of single fault handling time, and Set up in the Virtual Trainer Designer.

[0236] 4) Comprehensive score:

[0237] If the score of the correctness of handling or the speed of handling is 0, it means that the trainee does not have the ability to handle the fault, and the comprehensive score is 0. In other cases, the comprehensive score is the normalized calculated value of the above three scores.

[0238]

[0239] in, is the treatment accuracy weight coefficient, Weight coefficient of rationality of disposal, To handle the speed weight coefficient, these three coefficients are set in the virtual trainer designer

[0240] 3. Virtual instructor actuator, including:

[0241] The virtual instructor actuator controls the entire training process according to the calculation logic of the virtual instructor controller. Figure 4 During the execution of the virtual instructor, the grid operation status and trainee behavior are fed back to the virtual instructor controller in real time. According to the training process, the corresponding modules in the virtual instructor controller are called to perform calculations and receive control instructions to guide the simulation process into different branches.

[0242] The specific process includes the following steps:

[0243] S401, loading the initial power grid operation section;

[0244] S402, constructing an initial fault set, and performing initial fault simulation based on an initial power grid operation section;

[0245] S403, performing power flow calculation based on the initial fault simulation to obtain an initial power flow section of the power grid simulation;

[0246] S404, during the simulation clock advancement period, determining whether a simulation exit condition is reached;

[0247] If yes, S405, evaluate the simulation results and end the simulation;

[0248] If not, S406, determining whether the simulation time interval of the long-process operation section of the power grid has been reached;

[0249] If yes, S407, load the long process simulation section of the power grid, and then proceed to S408; if no, directly enter S408;

[0250] S408, determining whether the initial expected fault triggering time interval has been reached;

[0251] If yes, S409, perform initial expected fault simulation and proceed to S410; if no, directly proceed to S410;

[0252] S410, determining whether the minimum triggering time interval of multiple probability faults has been reached;

[0253] If not, return to S403;

[0254] If yes, S411, determine whether the maximum number of simulated faults has been reached;

[0255] If yes, S412, return to S403;

[0256] If not, S413, sample the current probability fault set, calculate the difficulty of the question, and determine whether it matches the student's skills based on the difficulty of the question;

[0257] If yes, S414, simulate the probabilistic fault, return to S403, and perform power flow calculation;

[0258] If not, return to S404.

[0259] Figure 5 This is a schematic diagram of the operation branches of the virtual instructor actuator for power grid dispatching. The horizontal axis is the initial fault development process, and the vertical axis is the probabilistic fault development process during the simulation. The operations of different trainees will lead to different power grid operation states, triggering different probabilistic faults, and thus entering different simulation branches.

[0260] in, represents the initial fault development time, Indicates the probability of failure development time, t1, t2, t3 are three time points,

[0261] is the initial fault, n is a different time point, is a probabilistic failure, n is 1, 23, 4…

[0262] 4. Virtual Teacher Management Center, including:

[0263] The virtual instructor management center collects the control instructions of the virtual instructor controller and the operating status of the virtual instructor actuator in real time, and has three major functions: training lesson plan management, student skills and operating rules optimization.

[0264] 1) Training lesson plan management: The long-process operation section of the power grid, expected faults and probabilistic faults simulated in this training are stored in the lesson plan library, and the difficulty of the question is used as the difficulty label of this lesson plan to facilitate the subsequent analysis of the difficulty of the questions in the lesson plan library.

[0265] 2) Trainee skill management: Store the trainee operations in this training simulation into the trainee behavior library, and store the trainee scores in this training simulation into the trainee portrait library, to facilitate subsequent analysis of the trainee skill levels.

[0266] 3) Operation rule optimization: According to the distribution of lesson plan difficulty and the distribution of students’ skill levels in the lesson plan library, adjust the relevant parameters and rules in the virtual instructor designer to ensure that the distribution of lesson plan difficulty is reasonable and the student skill levels are reasonably matched in the entire system.

[0267] Through the construction of a virtual instructor for power grid dispatching, training lesson plans that include long-term power grid operation modes and probabilistic faults are automatically generated. The training process is automatically guided according to the trainees' skill level, realizing a comprehensive digital replacement of the role of real instructors in dispatching skills training, providing one-to-many, 24-hour, all-weather and personalized dispatching training simulation services, and improving the efficiency of dispatching professional talent training.

[0268] The probabilistic fault generation technology in the present invention takes into account the impact of equipment load rate and equipment fault abnormal time on fault probability, and proposes a probabilistic fault generation method in scheduling training simulation. It can adjust the training lesson plan in real time according to the performance of trainees and the operation status of the power grid during the training process, thereby realizing the transformation from "script-based" training to "script-free" training.

[0269] The method of calculating the difficulty of questions and the technology of matching students' skills are used to evaluate the difficulty of training questions from the perspectives of power grid operation and fault handling. The impact of branch limit transmission capacity on the rationality of power grid flow distribution is considered. Improved flow transfer entropy and voltage transfer entropy are used to evaluate the technical difficulty of fault handling. The fault impact range is used to evaluate the difficulty of fault handling management. A normalized matching method for question difficulty and student skills is proposed, thereby achieving "teaching students in accordance with their aptitude" in dispatcher training.

[0270] The virtual instructor online intelligent guidance technology forms an overall architecture of virtual instructor online intelligent guidance by designing four functional modules and interaction mechanisms: virtual instructor designer, controller, actuator, and management center, providing a complete solution for the integration and application of virtual instructors in scheduling training simulation systems.

[0271] The present invention is implemented by relying on the dispatching training simulation system of the control cloud platform. At present, pilot construction and application have been carried out to verify the effectiveness and practicality of the method. The control cloud platform has been used as one of the unified construction projects for the construction of the energy Internet and has broad application prospects. The present invention can effectively improve the accident handling efficiency of control personnel, reduce accident risks, and improve the safety and stability level of the power grid, with significant economic and social benefits.

[0272] The second object of the present invention is to provide a method for generating a teaching plan for training a virtual instructor for power grid dispatching, comprising:

[0273] Obtain relevant data on power grid regulation and control, and call upon the experience parameters and operating rules of the virtual instructor during simulation training;

[0274] The initial power flow section of the power grid simulation is obtained according to the obtained power grid control related data;

[0275] According to the initial power flow section of the power grid simulation and the experience parameters and operation rules of the virtual instructor in the simulation training process, the long-term operation section of the power grid and the initial expected fault set are generated;

[0276] According to the long-term operation section of the power grid and the initial expected fault set, and based on the equipment operating power and abnormal operation time, probabilistic fault calculations, question difficulty calculations, and trainee skill matching are performed to automatically generate training lesson plans that include the long-term operation mode of the power grid and probabilistic faults.

[0277] As an optional solution, the generation of a long-term operation section of the power grid and an initial expected fault set includes:

[0278] Obtain the current state estimation section from the control cloud platform as the initial simulation section;

[0279] According to the total duration of this simulation , obtain the daily power generation plan, new energy forecast and load forecast data in the future simulation period, and form m future power grid operation sections, where , l is the time granularity of intraday real-time plan forecast;

[0280] According to the long process of power grid operation section simulation time interval , perform linear interpolation on m future operation sections of the power grid to obtain k long-term operation sections of the power grid, where ; Verify the power flow convergence of k long-term operation sections of the power grid;

[0281] According to the initial expected number of faults and initial expected fault triggering time interval To formulate an initial set of anticipated faults;

[0282] if , then conduct N-1 static safety analysis on the initial operation section and select the equipment failure with the greatest risk of power grid operation as the initial expected failure;

[0283] if , then N-1 static safety analysis is performed on the initial simulation section and the rth long-term operation section of the power grid, and the equipment failure with the greatest risk of power grid operation under each section is selected as the initial expected fault set; among them, .

[0284] As an optional solution, in the above probability failure calculation, the failure probability of the equipment for:

[0285]

[0286] in, is the failure probability of equipment i at time t without considering the historical operation conditions; is the influencing factor, which indicates the influence of equipment load rate and time on the growth of failure probability. The abnormal operation time of the equipment. The maximum allowed abnormal operation time of the equipment.

[0287] As an optional solution, in the problem difficulty calculation, the problem difficulty D is:

[0288]

[0289] In the formula, is the normalized power grid active power flow transfer entropy weight coefficient, is the normalized grid voltage transfer entropy weight coefficient, is the fault handling management difficulty weight coefficient, ; is the normalized power grid active power flow transfer entropy, is the normalized grid voltage transfer entropy, and S is the difficulty of fault handling management.

[0290] As an optional solution, the method automatically generates a training lesson plan including the long-term operation mode of the power grid and the probabilistic faults according to the long-term operation section of the power grid and the initial expected fault set, and based on the equipment operating power and abnormal operation time, the probabilistic fault calculation, the question difficulty calculation, and the trainee skill matching, including:

[0291] S401, loading the initial power grid operation section;

[0292] S402, constructing an initial fault set, and performing initial fault simulation based on an initial power grid operation section;

[0293] S403, performing power flow calculation based on the initial fault simulation to obtain an initial power flow section of the power grid simulation;

[0294] S404: During the simulation clock advancement period, determine whether the simulation exit condition is reached:

[0295] If yes, S405, evaluate the simulation results and end the simulation;

[0296] If not, S406, determine whether the power grid long process operation section simulation time interval has been reached: if so, S407, load the power grid long process simulation section, and then proceed to S408; if not, directly enter S408;

[0297] S408, determining whether the initial expected fault triggering time interval has been reached:

[0298] If yes, S409, perform initial expected fault simulation and proceed to S410; if no, directly proceed to S410;

[0299] S410, determining whether the minimum triggering time interval of multiple probability faults has been reached:

[0300] If not, return to S403;

[0301] If yes, S411, determine whether the maximum number of simulated faults has been reached: If yes, S412, return to S403;

[0302] If not, S413, sample the current probability fault set, calculate the difficulty of the question, and determine whether it matches the student's skills based on the difficulty of the question;

[0303] If yes, S414, simulate probabilistic fault; return to S403, perform power flow calculation;

[0304] If not, return to S404.

[0305] As an optional solution, in S405, performing simulation result evaluation includes:

[0306] The correctness score of the treatment is evaluated by judging the final operating state of the power grid at the end of the simulation , including equipment out-of-limit handling points , Power supply restoration score for power outage equipment And the fault point isolation score ;

[0307] Calculate the rationality score of the operation during the entire simulation process, if the trainee's operation does not cause any further equipment over-limit or power outage, and the operation complies with the five-defense operation regulations of the power grid. ;

[0308] Calculating the speed score :

[0309]

[0310] in, The actual time taken by students to handle the faults. is the standard processing time for a single fault, is the upper limit of single fault handling time, and Set up in the Virtual Instructor Designer;

[0311] Get the comprehensive score. If the score of the correctness of handling or the speed of handling is 0, it means that the trainee does not have the ability to handle the fault, and the comprehensive score is 0. In other cases, the comprehensive score is the normalized calculated value of the above three scores.

[0312] The simulation results are evaluated based on the comprehensive score.

[0313] The third object of the present invention is to provide a system for generating teaching plans for training virtual instructors for power grid dispatching, comprising:

[0314] The acquisition and calling module is used to obtain the relevant data of power grid regulation and call the experience parameters and operation rules of the virtual instructor in the simulation training process;

[0315] An initial power flow section calculation module is used to obtain the initial power flow section of the power grid simulation according to the acquired power grid control related data;

[0316] The operation section generation module is used to generate the long-term operation section of the power grid and the initial expected fault set according to the initial power flow section of the power grid simulation and the experience parameters and operation rules of the virtual instructor in the simulation training process;

[0317] The training lesson plan generation module is used to automatically generate training lesson plans that include the long-term operation mode of the power grid and probabilistic faults based on the long-term operation section of the power grid and the initial expected fault set, and based on the equipment operating power and abnormal operation time, perform probabilistic fault calculations, question difficulty calculations, and student skill matching.

[0318] The system for generating lesson plans for training virtual instructors for power grid dispatching of the present invention is based on a method for generating lesson plans for training virtual instructors for power grid dispatching.

[0319] The fourth objective of an embodiment of the present invention is to provide an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for generating lesson plans for training virtual instructors for power grid dispatching when executing the computer program.

[0320] A fifth objective of an embodiment of the present invention is to provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-mentioned method for generating lesson plans for virtual instructor training for power grid dispatching.

[0321] A sixth objective of an embodiment of the present invention is to provide a computer program product, wherein the computer program product includes computer instructions, and the computer instructions instruct a computer to execute the above-mentioned method for generating lesson plans for virtual instructor training for power grid dispatching.

[0322] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0323] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0324] The present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0325] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0326] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0327] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A virtual instructor training system for power grid dispatching, characterized in that: include: A virtual instructor designer is used to set the experience parameters and operation rules of the virtual instructor during the simulation training process; the operation rules include simulation operation rules, simulation fault triggering rules and simulation evaluation rules; A virtual instructor controller, the virtual instructor controller comprising: The module for generating lesson plans for initial training of virtual trainers is used to generate long-term operation sections of power grids and initial expected fault sets; The virtual instructor probabilistic fault trigger module is used to calculate probabilistic faults, calculate the difficulty of questions, and match trainee skills based on the equipment operating power and abnormal operating time, and automatically generate training lesson plans that include the long-term operation mode of the power grid and probabilistic faults. The virtual instructor training evaluation module is used for the virtual instructor to evaluate and score the trainees' performance during the entire training process after the simulation is completed; The virtual instructor executor is used to control the entire training process according to the calculation logic of the virtual instructor controller; The virtual teacher management center is used to collect the control instructions of the virtual teacher controller and the operating status of the virtual teacher actuator in real time; The virtual instructor initial training lesson plan generation module includes: The long-term operation section generation unit of the power grid is used for: Obtain the current state estimation section from the control cloud platform as the initial simulation section; According to the total duration of this simulation , obtain the daily power generation plan, new energy forecast and load forecast data in the future simulation period, and form m future power grid operation sections, where , l is the time granularity of intraday real-time plan forecast; According to the long process operation section simulation time interval of the power grid , perform linear interpolation on m future operation sections of the power grid to obtain k long-term operation sections of the power grid, where ; Verify the power flow convergence of k long-term operation sections of the power grid; The initial expected fault set generation unit is used to: According to the initial expected number of faults and initial expected fault triggering time interval To formulate an initial set of anticipated faults; if , then conduct N-1 static safety analysis on the initial operation section and select the equipment failure with the greatest risk of power grid operation as the initial expected failure; if , then N-1 static safety analysis is performed on the initial simulation section and the rth long-term operation section of the power grid, and the equipment failure with the greatest risk of power grid operation under each section is selected as the initial expected fault set; among them, ; In the virtual instructor probability fault trigger module, Perform probabilistic failure calculations, the probability of equipment failure for in, is the failure probability of equipment i at time t without considering the historical operation conditions; is the influencing factor, which indicates the influence of equipment load rate and time on the growth of failure probability. The abnormal operation time of the equipment. The maximum permissible abnormal operation time of the equipment; The virtual trainer training assessment module includes: The handling correctness scoring unit is used to evaluate the correctness of fault handling by judging the final operating state of the power grid at the end of the simulation. Including equipment out-of-limit disposal score , Power supply restoration score for power outage equipment And the fault point isolation score ; The treatment rationality scoring unit is used to calculate the treatment rationality score during the entire simulation process. The trainee's operation does not further cause new equipment to exceed the limit or power outage, and the operation complies with the five-defense operation regulations of the power grid. ; The handling speed score unit is used to require that fault handling be completed within a specified time. The longer the completion time, the lower the handling speed score. If the maximum fault handling time is exceeded, the handling speed score will be is 0; The comprehensive score unit is used to indicate that if the score of handling correctness or handling speed is 0, it indicates that the trainee does not have the ability to handle the fault and the comprehensive score is 0; in other cases, the comprehensive score is the normalized calculated value of the above three scores.

2. A virtual instructor training system for power grid dispatching according to claim 1, characterized in that: In the virtual instructor designer, the experience parameters and operating rules of the virtual instructor in the simulation training process are set by an experienced dispatcher based on historical training situations, and different levels of control centers specify different rules based on their respective power grid characteristics and the overall skill level of their personnel.

3. A virtual instructor training system for power grid dispatching according to claim 1, characterized in that: The simulation operation rules include: When the training time reaches the total simulation time, the virtual instructor automatically stops the training simulation; the total simulation time is the product of the maximum number of simulated faults and the upper limit of the single fault handling time; The virtual instructor loads the long-process operation section of the power grid according to the simulation time interval of the long-process operation section of the power grid; The virtual instructor needs to determine whether to continue the simulation training based on the simulation end conditions.

4. A virtual instructor training system for power grid dispatching according to claim 3, characterized in that: The simulation end condition includes: a) The simulation duration is greater than the total simulation duration; b) The current fault handling time is greater than the upper limit of single fault handling time; c) The number of triggered grid probabilistic faults has reached the maximum number of simulated faults, and the trainee has handled the last grid fault; d) The power flow calculation does not converge.

5. A virtual instructor training system for power grid dispatching according to claim 1, characterized in that: The simulation fault triggering rule includes: Set the number of initial expected faults and the initial expected fault triggering time interval, and the virtual instructor automatically triggers the initial expected fault according to the initial expected fault triggering time interval; The virtual instructor calls the probability fault calculation module once every minimum triggering time interval of multiple probability faults; The virtual instructor evaluates the rapidity of fault handling based on the standard handling time for a single fault and the upper limit handling time for a single fault; The total duration of this training simulation is limited by setting the maximum number of simulated faults. When the number of faults triggered during this training simulation has reached the maximum number of simulated faults, the probability fault calculation and triggering will no longer be performed. According to the average score, the difficulty matching range of the questions is set to obtain the matching rules between the difficulty of the questions and the level of the students.

6. A virtual instructor training system for power grid dispatching according to claim 1, characterized in that: The simulation evaluation rules include: The maximum value of active power flow transfer entropy and voltage transfer entropy are set according to the operation characteristics of each power grid and historical operation experience; The active over-limit coefficient and the voltage over-limit coefficient are obtained according to the influence of the active over-limit branch and the voltage over-limit node on the operation of the power grid; The normalized weight coefficient of the difficulty of the question is calculated according to the weight ratio between the difficulty of active power flow adjustment, the difficulty of voltage regulation and the difficulty of multi-agency dispatching and coordination; According to the weight ratio of the equipment over-limit handling score, the power supply restoration score of the power-off equipment and the fault point isolation score in the fault handling correctness score, the fault handling correctness score distribution ratio is obtained; The single deduction value for the rationality of fault handling is obtained based on the deduction value of a single over-limit event, a single power-off device, and a single misoperation behavior; The normalized weight coefficient of the comprehensive score is obtained according to the weight ratio among the correctness, rationality and speed of fault handling.

7. A virtual trainer training system for power grid dispatching according to claim 1, characterized in that: In the virtual instructor probability fault trigger module, the question difficulty is calculated, and the question difficulty D is: In the formula, is the normalized power grid active power flow transfer entropy weight coefficient, is the normalized grid voltage transfer entropy weight coefficient, is the fault handling management difficulty weight coefficient, ; is the normalized power grid active power flow transfer entropy, is the normalized grid voltage transfer entropy, S Increase the difficulty of troubleshooting management.

8. A virtual trainer training system for power grid dispatching according to claim 1, characterized in that: The virtual instructor actuator is specifically used to feed back the grid operation status and trainee behavior to the virtual instructor controller in real time, call the corresponding modules in the virtual instructor controller for calculation according to the training process, and receive control instructions to guide the simulation process into different branches.

9. A virtual instructor training system for power grid dispatching according to claim 1, characterized in that: The virtual instructor management center includes: The training lesson plan management unit is used to store the long-process operation section of the power grid, expected faults and probabilistic faults of the training simulation into the lesson plan library, and use the difficulty of the question as the difficulty label of the lesson plan; The trainee skill management unit is used to store the trainee operations in the training simulation into the trainee behavior library, and store the trainee scores in this training simulation into the trainee portrait library; The operation rule optimization unit is used to adjust the relevant parameters and rules in the virtual instructor designer according to the difficulty distribution of the lesson plans in the lesson plan library and the skill level distribution of the students.

10. A method for generating lesson plans for virtual instructor training of power grid dispatching, characterized in that: include: Obtain relevant data on power grid regulation and control, and call upon the experience parameters and operating rules of the virtual instructor during simulation training; The initial power flow section of the power grid simulation is obtained according to the obtained power grid control related data; According to the initial power flow section of the power grid simulation and the experience parameters and operation rules of the virtual instructor in the simulation training process, the long-term operation section of the power grid and the initial expected fault set are generated; According to the long-term operation section of the power grid and the initial expected fault set, the probability fault calculation, question difficulty calculation, and trainee skill matching are performed based on the equipment operating power and abnormal operation time, and a training lesson plan including the long-term operation mode of the power grid and the probability fault is generated; The generating of the long-term operation section of the power grid and the initial expected fault set includes: Obtain the current state estimation section from the control cloud platform as the initial simulation section; According to the total duration of this simulation , obtain the daily power generation plan, new energy forecast and load forecast data in the future simulation period, and form m future power grid operation sections, where , l is the time granularity of intraday real-time plan forecast; According to the long process operation section simulation time interval of the power grid , perform linear interpolation on m future operation sections of the power grid to obtain k long-term operation sections of the power grid, where ; Verify the power flow convergence of k long-term operation sections of the power grid; According to the initial expected number of faults and initial expected fault triggering time interval To formulate an initial set of anticipated faults; if , then conduct N-1 static safety analysis on the initial operation section and select the equipment failure with the greatest risk of power grid operation as the initial expected failure; if , then N-1 static safety analysis is performed on the initial simulation section and the rth long-term operation section of the power grid, and the equipment failure with the greatest risk of power grid operation under each section is selected as the initial expected fault set; among them, ; In the above probability failure calculation, the failure probability of the equipment for in, is the failure probability of equipment i at time t without considering the historical operation conditions; is the influencing factor, which indicates the influence of equipment load rate and time on the growth of failure probability. The abnormal operation time of the equipment. The maximum allowed abnormal operation time of the equipment.

11. A method for generating teaching plans for virtual instructor training for power grid dispatching according to claim 10, characterized in that: In the above-mentioned problem difficulty calculation, the problem difficulty D is: In the formula, is the normalized power grid active power flow transfer entropy weight coefficient, is the normalized grid voltage transfer entropy weight coefficient, is the fault handling management difficulty weight coefficient, ; is the normalized power grid active power flow transfer entropy, is the normalized grid voltage transfer entropy, and S is the difficulty of fault handling management.

12. A method for generating teaching plans for virtual instructor training for power grid dispatching according to claim 10, characterized in that: According to the long-term operation section of the power grid and the initial expected fault set, the probability fault calculation, the question difficulty calculation, and the trainee skill matching are performed based on the equipment operating power and abnormal operation time, and a training lesson plan including the long-term operation mode of the power grid and the probability fault is automatically generated, including: S401, loading the initial power grid operation section; S402, constructing an initial fault set, and performing initial fault simulation based on an initial power grid operation section; S403, performing power flow calculation based on the initial fault simulation to obtain an initial power flow section of the power grid simulation; S404: During the simulation clock advancement period, determine whether the simulation exit condition is reached: If yes, S405, evaluate the simulation results and end the simulation; If not, S406, determine whether the power grid long process operation section simulation time interval has been reached: if so, S407, load the power grid long process simulation section, and then proceed to S408; if not, directly enter S408; S408, determining whether the initial expected fault triggering time interval has been reached: If yes, S409, perform initial expected fault simulation and proceed to S410; if no, directly proceed to S410; S410, determining whether the minimum triggering time interval of multiple probability faults has been reached: If not, return to S403; If yes, S411, determine whether the maximum number of simulated faults has been reached: If yes, S412, return to S403; If not, S413, sample the current probability fault set, calculate the difficulty of the question, and determine whether it matches the student's skills based on the difficulty of the question; If yes, S414, simulate probabilistic fault; return to S403, perform power flow calculation; If not, return to S404.

13. A method for generating teaching plans for virtual instructor training for power grid dispatching according to claim 12, characterized in that: In S405, performing simulation result evaluation includes: The correctness score of the treatment is evaluated by judging the final operating state of the power grid at the end of the simulation , including equipment out-of-limit handling points , Power supply restoration score for power outage equipment And the fault point isolation score ; Calculate the rationality score of the operation during the entire simulation process, if the trainee's operation does not cause any further equipment over-limit or power outage, and the operation complies with the five-defense operation regulations of the power grid. ; Calculating the speed score : in, The actual time taken by students to handle the faults. is the standard processing time for a single fault, is the upper limit of single fault handling time, and Set up in the Virtual Instructor Designer; Get the comprehensive score. If the score of the correctness of handling or the speed of handling is 0, it means that the trainee does not have the ability to handle the fault, and the comprehensive score is 0. In other cases, the comprehensive score is the normalized calculated value of the above three scores. The simulation results are evaluated based on the comprehensive score.

14. A system for generating lesson plans for training virtual instructors for power grid dispatching, based on the method for generating lesson plans for training virtual instructors for power grid dispatching as claimed in any one of claims 10 to 13; characterized in that: include: The acquisition and calling module is used to obtain the relevant data of power grid regulation and call the experience parameters and operation rules of the virtual instructor in the simulation training process; An initial power flow section calculation module is used to obtain the initial power flow section of the power grid simulation according to the acquired power grid control related data; The operation section generation module is used to generate the long-term operation section of the power grid and the initial expected fault set according to the initial power flow section of the power grid simulation and the experience parameters and operation rules of the virtual instructor in the simulation training process; The training lesson plan generation module is used to automatically generate training lesson plans that include the long-term operation mode of the power grid and probabilistic faults based on the long-term operation section of the power grid and the initial expected fault set, and based on the equipment operating power and abnormal operation time, perform probabilistic fault calculations, question difficulty calculations, and student skill matching.

15. An electronic device, characterized in that: It includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for generating lesson plans for training virtual instructors for power grid dispatching as described in any one of claims 10 to 13 is implemented.

16. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for generating lesson plans for training virtual instructors for power grid dispatching as described in any one of claims 10-13 is implemented.

17. A computer program product, comprising computer instructions, characterized in that: The computer instructions instruct the computer to execute the method for generating teaching plans for training virtual instructors for power grid dispatching as described in any one of claims 10-13.

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