Equipment protection setting value optimization method and device, terminal equipment and storage medium

Abstract

The invention discloses an equipment protection setting value optimization method and device, terminal equipment and a storage medium, and relates to the technical field of power systems, and the method comprises the steps: constructing a simulation model of target equipment; generating a plurality of operation scenes, and performing simulation analysis on the protection constant value of the target equipment according to the simulation model in each operation scene to obtain a protection constant value simulation value of the target equipment; a genetic algorithm is adopted to optimize reference parameters of the protection setting value of the target equipment, and optimized reference parameters are obtained; and based on the optimized reference parameter, carrying out optimization processing on the protection constant value simulation value to obtain a final protection constant value. Through multi-operation scene simulation and heritage algorithm optimization, a complex and changeable operation environment of the power grid is considered, and the optimized protection setting value can cover different working conditions of the power grid, so that the method can adapt to dynamic changes of the power grid, and the accuracy and reliability of equipment protection setting value optimization are effectively improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of power systems, and particularly relates to a device protection setting value optimization method and device, a terminal device and a storage medium. BACKGROUND

[0002] In a power system, the protection setting value of a grid-connected device (such as a generator, a transformer, and a transmission line) is a key link for ensuring safe operation of the device and stability of the power grid.

[0003] The existing device protection setting value optimization method is usually to set the device protection setting value according to past experience and industry standards, for example, the overcurrent protection setting value is set to a certain fixed multiple of the rated current, and the differential protection setting value is estimated according to the electrical parameters of the device. However, the operation mode of the power grid is complex and variable, and it is difficult to adapt to the dynamic changes of the power grid by setting the device protection setting value according to past experience and industry standards, resulting in low accuracy of the device protection setting value. SUMMARY

[0004] The present application provides a device protection setting value optimization method and device, a terminal device and a storage medium, which can solve the technical problem that the device protection setting value is set according to past experience and industry standards in the prior art, which is difficult to adapt to the dynamic changes of the power grid, resulting in low accuracy of the device protection setting value.

[0005] The present application provides a device protection setting value optimization method, comprising: constructing a simulation model of a target device; generating a plurality of operation scenarios, and performing simulation analysis on the protection setting value of the target device according to the simulation model under each operation scenario to obtain a protection setting value simulation value of the target device; optimizing reference parameters of the protection setting value of the target device using a genetic algorithm to obtain optimized reference parameters; optimizing the protection setting value simulation value based on the optimized reference parameters to obtain a final protection setting value.

[0006] Further, the simulation model of the target device is constructed, comprising: constructing a simulation model of the target device according to the physical characteristics, electrical parameters and operation characteristics of the target device.

[0007] Further, the simulation analysis on the protection setting value of the target device according to the simulation model under each operation scenario to obtain the protection setting value simulation value of the target device, comprising: configuring a plurality of operation scenarios in the simulation model, starting the simulation, and recording the electrical parameters of the target device under the plurality of operation scenarios; determining the protection setting value simulation value of the target device according to the electrical parameters.

[0008] Further, the genetic algorithm is used to optimize the reference parameter of the protection setting value of the target device, and an optimized reference parameter is obtained. Initialize a population, and generate several groups of random reference parameters; Take the reciprocal of the deviation of the reference parameter from the rated parameter of the device as a fitness function; Select the reference parameter with a fitness value higher than a preset value as a parent individual according to the fitness function by using a roulette wheel selection method; Generate a next generation population based on the parent individual through crossing, mutation and screening operations; After iterating a preset number of times, a final population is obtained, and the individuals in the final population are taken as the optimized reference parameter.

[0009] Further, the optimized reference parameter includes an optimized speed deviation amplification multiple of a governor and an optimized gain of an excitation system, and the protection setting value simulation value includes an overcurrent protection setting value simulation value and a differential protection setting value simulation value. The protection setting value simulation value is optimized based on the optimized reference parameter to obtain a final protection setting value, including: The final overcurrent protection setting value is determined according to the original setting value of the overcurrent protection and the optimized speed deviation amplification multiple of the governor; The final differential protection setting value is determined according to the original setting value of the differential protection, the optimized speed deviation amplification multiple of the governor and the optimized gain of the excitation system.

[0010] Further, after the protection setting value simulation value is optimized based on the optimized reference parameter to obtain a final protection setting value, including: The final protection setting value is written into a protection device, and the electrical parameters of the target device are continuously monitored by the protection device; when the electrical parameters are higher than the corresponding final protection setting value, a corresponding protection action is started.

[0011] The application provides a device protection setting value optimization device, including: A simulation model construction module is configured to construct a simulation model of a target device; A simulation analysis module is configured to generate multiple operation scenarios, and perform simulation analysis on the protection setting value of the target device according to the simulation model under each operation scenario to obtain a protection setting value simulation value of the target device; A parameter optimization module is configured to use a genetic algorithm to optimize a reference parameter of the protection setting value of the target device to obtain an optimized reference parameter; A protection setting value determination module is configured to optimize the protection setting value simulation value based on the optimized reference parameter to obtain a final protection setting value.

[0012] Further, the simulation analysis of the protection setting value of the target device according to the simulation model under each operation scenario to obtain the protection setting value simulation value of the target device comprises: A plurality of operation scenarios are configured in the simulation model, and the simulation is started to record the electrical parameters of the target device under the plurality of operation scenarios. The protection setting value simulation value of the target device is determined according to the electrical parameters.

[0013] The application provides a terminal device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the device protection setting value optimization method as described above when executing the computer program.

[0014] The application provides a computer readable storage medium, comprising a stored computer program, wherein the device where the computer readable storage medium is located executes the device protection setting value optimization method as described above when the computer program runs.

[0015] The application has the following beneficial effects: The application considers the complex and changeable operation environment of the power grid through the multi-operation scenario simulation and the optimization of the genetic algorithm, can make the optimized protection setting value cover different working conditions of the power grid, and thus can adapt to the dynamic changes of the power grid and effectively improve the accuracy and reliability of the device protection setting value optimization.

[0016] Further, the application can comprehensively evaluate the electrical parameter changes of the target device under different working conditions by configuring a plurality of operation scenarios in the simulation model, can ensure that the protection setting value is not only applicable to the normal operation state, but also can provide reliable protection under various abnormal conditions, and thus improves the reliability of the device operation. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the present application, the following will briefly introduce the drawings needed in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0018] Figure 1 is a flowchart of a device protection setting value optimization method provided by an embodiment of the application; Figure 2 is a structural schematic diagram of a device protection setting value optimization device provided by an embodiment of the application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0021] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0022] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0023] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0024] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0025] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0026] See Figure 1 To address the technical problem in existing technologies where setting equipment protection settings based on past experience and industry standards is difficult to adapt to dynamic changes in the power grid, resulting in low accuracy of equipment protection settings, an embodiment of the present invention provides a method for optimizing equipment protection settings, comprising: S1. Construct a simulation model of the target device; In this embodiment of the invention, the target device is a device that needs to be optimized for protection settings, such as a generator, transformer, or transmission line in a power system.

[0027] In this embodiment of the invention, a simulation model can be constructed based on the physical characteristics, electrical parameters, and operating characteristics of the target device.

[0028] S2. Generate multiple operating scenarios, and in each operating scenario, perform simulation analysis on the protection settings of the target device based on the simulation model to obtain the simulated protection settings of the target device; In this embodiment of the invention, multiple operating scenarios include normal operating scenarios, fault operating scenarios, and special operating scenarios.

[0029] Among them, normal operation scenarios can be generated based on the actual operation data of the power grid, including generator output, transformer load rate, and line transmission power; fault operation scenarios can be generated based on the historical fault records and fault types of the power grid, including single-phase ground fault, two-phase short-circuit fault, and three-phase short-circuit fault. In the process of generating fault operation scenarios, factors such as the location and duration of the fault can be considered; special operation scenarios are the operation scenarios of the power grid under special operating modes, such as line maintenance, generator shutdown, and load surges.

[0030] In this embodiment of the invention, the protection settings can be simulated and analyzed using numerical analysis methods through the simulation model in each operating scenario. The built-in algorithm of the power system simulation software is used to calculate the response of the target equipment under different operating conditions through time-domain simulation and eigenvalue analysis, and the simulated value of the protection settings is determined based on the response under different operating conditions.

[0031] S3. Use a genetic algorithm to optimize the reference parameters of the protection settings of the target equipment to obtain the optimized reference parameters; S4. Based on the optimized reference parameters, the simulated protection settings are optimized to obtain the final protection settings.

[0032] The embodiments of the present invention, through multi-operation scenario simulation and legacy algorithm optimization, take into account the complex and ever-changing operating environment of the power grid, enabling the optimized protection settings to cover different operating conditions of the power grid, thereby adapting to dynamic changes in the power grid and effectively improving the accuracy and reliability of equipment protection setting optimization.

[0033] In one embodiment, step S1, constructing a simulation model of the target device, includes: Based on the physical characteristics, electrical parameters, and operating characteristics of the target equipment, a simulation model of the target equipment is constructed.

[0034] In this embodiment of the invention, the simulation model of the target device includes a generator simulation model, a transformer simulation model, and a transmission line simulation model. The parameters of the generator simulation model are as follows: Physical characteristics: rated power (e.g., 500MW), rated voltage (e.g., 22kV), rated speed (e.g., 3000rpm).

[0035] Electrical parameters: stator resistance (e.g., 0.005Ω), stator reactance (e.g., 0.2Ω), rotor resistance (e.g., 0.002Ω), rotor reactance (e.g., 0.1Ω).

[0036] Operating characteristics: frequency regulation capability (e.g., ±0.5Hz), voltage regulation capability (e.g., ±5%), overload capability (e.g., 1.2 times the rated current for 10 seconds).

[0037] In this embodiment of the invention, a generator simulation model can be constructed using power system simulation software (such as PSASP, PSS / E). By inputting the above parameters, the model can accurately reflect the dynamic and static characteristics of the generator under different operating conditions.

[0038] The parameters of the transformer simulation model are as follows: Physical characteristics: rated capacity (e.g., 500MVA), rated voltage (e.g., 220kV / 110kV), rated current (e.g., 1300A / 2600A).

[0039] Electrical parameters: impedance (e.g., 10%), turns ratio (e.g., 220 / 110), short-circuit voltage percentage (e.g., 10%).

[0040] Operating characteristics: cooling method (e.g., oil-immersed air cooling), overload capacity (e.g., 1.3 times the rated current for 30 minutes), insulation level (e.g., 220kV).

[0041] In this embodiment of the invention, a transformer simulation model can be constructed using power system simulation software. By inputting the above parameters, the model can accurately reflect the dynamic and static characteristics of the transformer under different operating conditions.

[0042] The parameters of the transmission line simulation model are as follows: Physical characteristics: line length (e.g., 100km), conductor type (e.g., LGJ-400 / 50), conductor cross-sectional area (e.g., 400mm²).

[0043] Electrical parameters: resistance (e.g., 0.1Ω / km), reactance (e.g., 0.4Ω / km), capacitance (e.g., 10nF / km).

[0044] Operating characteristics: power transmission range (e.g., 300MW~500MW), thermal stability limit (e.g., 3000A).

[0045] In this embodiment of the invention, power system simulation software can be used to construct a transmission line simulation model. By inputting the above parameters, the model can be ensured to accurately reflect the dynamic and static characteristics of the line under different operating conditions.

[0046] The embodiments of the present invention comprehensively consider the physical characteristics (such as rated power and rated voltage), electrical parameters (such as resistance and reactance) and operating characteristics (such as frequency regulation capability and voltage regulation capability) of the target equipment, so that the simulation model can fully and accurately reflect the actual operating state and behavior of the equipment, thereby effectively improving the accuracy of simulation analysis and thus effectively improving the accuracy of protection setting optimization.

[0047] In one embodiment, step S2 involves performing simulation analysis on the protection settings of the target device based on the simulation model under each operating scenario to obtain the simulated protection settings of the target device, including: S21. Configure multiple operating scenarios in the simulation model, start the simulation, and record the electrical parameters of the target device under multiple operating scenarios; In this embodiment of the invention, by configuring multiple operating scenarios in the simulation model, the electrical parameters of the device under different operating scenarios and different responses are simulated.

[0048] S22. Determine the simulated protection settings of the target equipment based on the electrical parameters.

[0049] In this embodiment of the invention, it is assumed that the target device is a generator with a rated power of 500MW and a rated voltage of 22kV.

[0050] Protection settings include overcurrent protection settings and overvoltage protection settings. Overcurrent protection settings are used to detect overcurrent in generator windings or lines; overvoltage protection settings are used to protect generators from damage caused by excessively high voltage.

[0051] Operational scenario settings: Configure the following three operational scenarios in the simulation model: Normal operation scenario: The generator output is 450MW and the power grid is operating normally; Single-phase ground fault scenario: The fault location is 50km away from the starting point of the line and the duration is 0.1 seconds; Line maintenance scenario: A section of the line is shut down for maintenance and the generator output is adjusted to 300MW.

[0052] Under normal operating conditions, record the generator's electrical parameters, such as stator current and terminal voltage. Assume the recorded stator current is 90% of the rated current (i.e., 0.9 times the rated current), and the terminal voltage is 22kV.

[0053] In a single-phase ground fault scenario, record the stator current and terminal voltage after the fault occurs. Assume that after the fault occurs, the stator current instantly rises to 1.5 times the rated current, and the terminal voltage drops to 20kV.

[0054] In the line maintenance scenario, a section of the line is set up for power outage maintenance in the simulation model, and the stator current and terminal voltage of the generator are recorded. It is assumed that when the generator output is adjusted to 300MW, the stator current is 60% of the rated current (i.e., 0.6 times the rated current), and the terminal voltage is 22kV.

[0055] Under normal operating conditions, the stator current is 0.9 times the rated current.

[0056] In a single-phase ground fault scenario, the stator current rises to 1.5 times the rated current.

[0057] In a line maintenance scenario, the stator current is 0.6 times the rated current.

[0058] In a single-phase ground fault scenario, the stator current reaches 1.5 times the rated current. To ensure that the protection device can operate promptly under fault conditions, the overcurrent protection setting should be set slightly higher than the maximum current during normal operation and lower than the fault current. According to simulation results, the overcurrent protection setting can be set to 1.2 times the rated current (i.e., 1.2 times the rated current).

[0059] Overvoltage protection setting calculation: In normal operation, the terminal voltage is 22kV; in single-phase ground fault scenario, the terminal voltage drops to 20kV; in line maintenance scenario, the terminal voltage remains at 22kV.

[0060] Under normal operation and line maintenance scenarios, the terminal voltage remains near the rated voltage. In a single-phase ground fault scenario, the terminal voltage drops, but no overvoltage occurs. To ensure the protection device can operate promptly when the voltage is too high, the overvoltage protection setting should be set slightly higher than the maximum voltage during normal operation.

[0061] Based on the simulation results, the overvoltage protection setting can be set to 1.1 times the rated voltage (i.e., 24.2kV).

[0062] By configuring multiple operating scenarios in the simulation model, this invention can comprehensively evaluate the changes in electrical parameters of the target equipment under different operating conditions, ensuring that the protection settings are not only applicable to normal operating conditions, but also provide reliable protection under various abnormal conditions, thereby improving the reliability of equipment operation.

[0063] In one embodiment, step S3, optimizing the reference parameters of the protection settings of the target device using a genetic algorithm to obtain optimized reference parameters, includes: S31. Initialize the population and generate several sets of random reference parameters; In this embodiment of the invention, the target device can be two generators, with overcurrent protection settings and differential protection settings respectively. Based on the correlation between the protection settings and electrical parameters, the reference parameters are determined to be the excitation system adjustment gain and the speed governor speed deviation amplification factor.

[0064] In this embodiment of the invention, the population is initialized, and several sets of random excitation system adjustment gain and governor speed deviation amplification factor are generated. For example, the range of excitation system adjustment gain can be 0.1-0.5, and the range of governor speed deviation amplification factor can be 0.01-0.1.

[0065] S32. Use the reciprocal of the deviation between the reference parameter and the equipment's rated parameter as the fitness function; In this embodiment of the invention, the expression for the fitness function is as follows: ; The rated parameters of the equipment are the rated values ​​corresponding to the reference parameters.

[0066] S33. Using the roulette wheel selection method, reference parameters with fitness values ​​higher than the preset values ​​are selected as parent individuals based on the fitness function. S34. Based on the parent individuals, perform crossover, mutation, and selection operations to generate the next generation population; In this embodiment of the invention, a single-point crossover method can be used, randomly selecting two parent individuals for crossover to generate new offspring individuals. A random mutation method can be employed, mutating the newly generated offspring individuals to randomly change a reference parameter with a certain probability. This increases the mutation rate when the population fitness distribution is relatively concentrated, preventing local optima; and decreases the mutation rate when the population fitness distribution is relatively dispersed, preserving superior genes. A certain proportion of optimal individuals can be retained in each generation and passed on to the next generation to ensure the inheritance of superior genes and accelerate the convergence speed of the algorithm.

[0067] In this embodiment of the invention, in each generation of the population, a local search can be performed on individuals with high fitness to further optimize the excitation system adjustment gain and the speed governor speed deviation amplification factor, thereby improving the accuracy of the algorithm.

[0068] S35. After a preset number of iterations, the final population is obtained, and the individuals in the final population are used as the optimized reference parameters.

[0069] In this embodiment of the invention, the individual with the highest fitness in the final population can be used as the optimized reference parameter.

[0070] The embodiments of the present invention optimize reference parameters based on genetic algorithms, which can dynamically adapt to changes in the power grid, thereby improving the accuracy of equipment protection settings.

[0071] In one embodiment, the optimized reference parameters include the speed deviation amplification factor of the optimized speed governor and the gain of the optimized excitation system. Step S4, the protection setting simulation values ​​include the overcurrent protection setting simulation values ​​and the differential protection setting simulation values. Based on the optimized reference parameters, the simulated protection settings are further optimized to obtain the final protection settings, including: S41. Determine the final overcurrent protection setting based on the original setting of the overcurrent protection and the speed deviation amplification factor of the optimized speed governor; In this embodiment of the invention, if the initial setting of the overcurrent protection is the maximum current, the expression for the final overcurrent protection setting can be: ; in, This is the final overcurrent protection setting. For the maximum current, This is the amplification factor for the speed deviation of the optimized speed governor.

[0072] In this embodiment of the invention, if the original overcurrent protection setting is I 额定 The optimized speed governor's speed deviation amplification factor =0.05, then the final overcurrent protection setting is: .

[0073] S42. Determine the final differential protection setting based on the original setting of the differential protection, the speed deviation amplification factor of the optimized speed governor, and the gain of the optimized excitation system.

[0074] In this embodiment of the invention, the expression for the final differential protection setting is as follows: in, This is the final differential protection setting. This is the original setting for differential protection. To optimize the speed deviation amplification factor of the speed governor, To optimize the gain of the excitation system.

[0075] If the speed deviation amplification factor of the optimized speed governor and the gain of the optimized excitation system are 0.05 and 0.3 respectively, the original setting of the differential protection... It is 0.1 The final differential protection setting is: .

[0076] The embodiments of the present invention optimize the protection settings by optimizing the reference parameters. The optimized reference parameters can more accurately reflect the actual operating status of the equipment, thereby effectively improving the accuracy of the protection settings.

[0077] In one embodiment, after optimizing the protection setting simulation value based on the optimized reference parameters in step S4 to obtain the final protection setting value, the following steps are included: S5. Write the final protection setting into the protection device. The protection device continuously monitors the electrical parameters of the target equipment. When the electrical parameters are higher than the corresponding final protection setting, the corresponding protection action is activated.

[0078] In this embodiment of the invention, the electrical parameters may include stator current and differential current. If the stator current is higher than the corresponding overcurrent protection setting, a control command is generated to disconnect the circuit breaker to prevent damage to the generator windings or lines due to overcurrent. If the differential current is higher than the differential protection setting, a control command is generated to disconnect the circuit breaker to prevent the fault from escalating.

[0079] Implementing the embodiments of the present invention has the following beneficial effects: The embodiments of the present invention, through multi-operation scenario simulation and legacy algorithm optimization, take into account the complex and ever-changing operating environment of the power grid, enabling the optimized protection settings to cover different operating conditions of the power grid, thereby adapting to dynamic changes in the power grid and effectively improving the accuracy and reliability of equipment protection setting optimization.

[0080] Furthermore, by configuring multiple operating scenarios in the simulation model, this embodiment of the invention can comprehensively evaluate the changes in electrical parameters of the target equipment under different operating conditions, ensuring that the protection settings are not only applicable to normal operating conditions, but also provide reliable protection under various abnormal conditions, thereby improving the reliability of equipment operation.

[0081] like Figure 2 As shown, based on the above method embodiments, corresponding apparatus embodiments are provided; An embodiment of the present invention provides a device for optimizing equipment protection settings, comprising: Simulation model building module 10 is used to build a simulation model of the target device; The simulation analysis module 20 is used to generate multiple operating scenarios, and in each operating scenario, it performs simulation analysis on the protection settings of the target device based on the simulation model to obtain the simulation values ​​of the protection settings of the target device. The parameter optimization module 30 is used to optimize the reference parameters of the protection settings of the target device using a genetic algorithm to obtain the optimized reference parameters. The protection setting determination module 40 is used to optimize the protection setting simulation value based on the optimized reference parameters to obtain the final protection setting value.

[0082] In one embodiment, constructing a simulation model of the target device includes: Based on the physical characteristics, electrical parameters, and operating characteristics of the target equipment, a simulation model of the target equipment is constructed.

[0083] In one embodiment, under each operating scenario, the protection settings of the target device are simulated and analyzed based on the simulation model to obtain the simulated protection settings of the target device, including: Configure multiple operating scenarios in the simulation model, start the simulation, and record the electrical parameters of the target device under the multiple operating scenarios; The simulated protection settings of the target equipment are determined based on the electrical parameters.

[0084] In one embodiment, a genetic algorithm is used to optimize the reference parameters of the protection settings of the target device to obtain optimized reference parameters, including: Initialize the population and generate several sets of random reference parameters; The reciprocal of the deviation between the reference parameter and the equipment's rated parameter is used as the fitness function; The roulette wheel selection method is used to select reference individuals with fitness values ​​higher than the preset value as parent individuals based on the fitness function. The next generation population is generated by performing crossover, mutation, and selection operations on the parent individuals. After a preset number of iterations, the final population is obtained, and the individuals in the final population are used as the optimized reference parameters.

[0085] In one embodiment, the optimized reference parameters include the speed deviation amplification factor of the optimized speed governor and the gain of the optimized excitation system, and the protection setting simulation values ​​include the overcurrent protection setting simulation values ​​and the differential protection setting simulation values. Based on the optimized reference parameters, the simulated protection settings are further optimized to obtain the final protection settings, including: The final overcurrent protection setting is determined based on the original setting of the overcurrent protection and the speed deviation amplification factor of the optimized speed governor. The final differential protection setting is determined based on the original setting of the differential protection, the speed deviation amplification factor of the optimized speed governor, and the gain of the optimized excitation system.

[0086] In one embodiment, after optimizing the simulated protection settings based on the optimized reference parameters to obtain the final protection settings, the process includes: The final protection setting is written into the protection device, which continuously monitors the electrical parameters of the target equipment. When the electrical parameters exceed the corresponding final protection setting, the corresponding protection action is activated.

[0087] It is understood that the above-described device embodiments correspond to the method embodiments of the present invention, and can implement the device protection setting optimization method provided by any of the above-described method embodiments of the present invention.

[0088] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can specifically be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0089] Based on the above embodiments of the device protection setting optimization method, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the device protection setting optimization method of any embodiment of the present invention.

[0090] For example, in this embodiment, the computer program can be divided into one or more modules, one or more modules are stored in memory and executed by a processor to complete the present invention. One or more module elements can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in a terminal device.

[0091] Terminal devices can be computing devices such as desktop computers, laptops, handheld computers, and cloud servers. Terminal devices may include, but are not limited to, processors and memory.

[0092] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device through various interfaces and lines.

[0093] Based on the above-described method embodiments, another embodiment of the present invention provides a computer-readable storage medium including a stored computer program, wherein, when the computer program is running, it controls the device where the computer-readable storage medium is located to execute the device protection setting optimization method of any of the above-described method embodiments of the present invention.

[0094] The modules / units integrated into the device / terminal equipment, if implemented as software functional units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0095] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for optimizing equipment protection settings, characterized in that, include: Construct a simulation model of the target device; Multiple operating scenarios are generated, and under each operating scenario, the protection settings of the target device are simulated and analyzed according to the simulation model to obtain the simulated protection settings of the target device. A genetic algorithm is used to optimize the reference parameters of the protection settings of the target device to obtain the optimized reference parameters. Based on the optimized reference parameters, the simulated protection settings are optimized to obtain the final protection settings.

2. The equipment protection setting optimization method as described in claim 1, characterized in that, The simulation model of the target device includes: Based on the physical characteristics, electrical parameters, and operating characteristics of the target equipment, a simulation model of the target equipment is constructed.

3. The equipment protection setting optimization method as described in claim 1, characterized in that, In each of the aforementioned operating scenarios, the protection settings of the target device are simulated and analyzed based on the simulation model to obtain the simulated protection settings of the target device, including: Configure multiple operating scenarios in the simulation model, start the simulation, and record the electrical parameters of the target device under the multiple operating scenarios; The simulated protection settings of the target equipment are determined based on the electrical parameters.

4. The equipment protection setting optimization method as described in claim 1, characterized in that, The reference parameters for optimizing the protection settings of the target device using a genetic algorithm are obtained, including: Initialize the population and generate several sets of random reference parameters; The reciprocal of the deviation between the reference parameter and the equipment's rated parameter is used as the fitness function; The roulette wheel selection method is used to select reference parameters with fitness values ​​higher than preset values ​​as parent individuals based on the fitness function. Based on the parent individuals, crossover, mutation, and selection operations are performed to generate the next generation population; After a preset number of iterations, the final population is obtained, and the individuals in the final population are used as optimized reference parameters.

5. The equipment protection setting optimization method as described in claim 1, characterized in that, The optimized reference parameters include the speed deviation amplification factor of the optimized speed governor and the gain of the optimized excitation system; the protection setting simulation values ​​include the overcurrent protection setting simulation values ​​and the differential protection setting simulation values. The step of optimizing the simulated protection settings based on the optimized reference parameters to obtain the final protection settings includes: The final overcurrent protection setting is determined based on the original setting of the overcurrent protection and the speed deviation amplification factor of the optimized speed governor. The final differential protection setting is determined based on the original setting of the differential protection, the speed deviation amplification factor of the optimized speed governor, and the gain of the optimized excitation system.

6. The equipment protection setting optimization method as described in claim 1, characterized in that, After optimizing the simulated protection settings based on the optimized reference parameters to obtain the final protection settings, the process includes: The final protection setting is written into the protection device, which continuously monitors the electrical parameters of the target device. When the electrical parameters are higher than the corresponding final protection setting, the corresponding protection action is activated.

7. A device for optimizing equipment protection settings, characterized in that, include: The simulation model building module is used to build a simulation model of the target device; The simulation analysis module is used to generate multiple operating scenarios, and under each operating scenario, to perform simulation analysis on the protection settings of the target device based on the simulation model, so as to obtain the simulation values ​​of the protection settings of the target device. The parameter optimization module is used to optimize the reference parameters of the protection settings of the target device using a genetic algorithm to obtain the optimized reference parameters. The protection setting determination module is used to optimize the simulation value of the protection setting based on the optimized reference parameters to obtain the final protection setting.

8. The equipment protection setpoint optimization device as described in claim 7, characterized in that, In each of the aforementioned operating scenarios, the protection settings of the target device are simulated and analyzed based on the simulation model to obtain the simulated protection settings of the target device, including: Configure multiple operating scenarios in the simulation model, start the simulation, and record the electrical parameters of the target device under the multiple operating scenarios; The simulated protection settings of the target equipment are determined based on the electrical parameters.

9. A terminal device, characterized in that, The device includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements the device protection setting optimization method as described in any one of claims 1-6.

10. A computer-readable storage medium, characterized in that, include: A stored computer program, wherein, when the computer program is executed, it controls the device on which the computer-readable storage medium is located to perform the device protection setting optimization method as described in any one of claims 1-6.

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