Frequency modulation strategy optimization method, system and device and storage medium

Abstract

The invention discloses a frequency modulation strategy optimization method, system and device and a storage medium, and relates to the technical field of computer platform load balancing, and the method comprises the steps: collecting power grid dispatching data, and carrying out the preprocessing to obtain a frequency distribution standard deviation; summarizing unit data, and calculating a damping average value by taking the summarized unit data as input; acquiring a load frequency factor, a frequency modulation dead zone and a frequency modulation control coefficient; the frequency distribution standard deviation, the damping average value, the load frequency factor, the frequency modulation dead zone and the frequency modulation control coefficient serve as input, the disturbance scene probability is calculated, and the random disturbance average amplitude is estimated according to the disturbance scene probability; the frequency distribution standard deviation is changed into a target frequency standard deviation, the frequency distribution standard deviation, the damping average value, the load frequency factor, the frequency modulation dead zone and the frequency modulation control coefficient are input again, and the disturbance scene probability after the frequency quality is improved is calculated; and outputting a frequency modulation control strategy according to the random disturbance average amplitude. The method provided by the invention realizes probabilistic description and computable quantization.

Description

Technical Field

[0001] This invention relates to the field of power system automation control technology, specifically to a frequency regulation strategy optimization method, system, device, and storage medium. Background Technology

[0002] Synchronous generators are being largely replaced by power electronic converters, and the random disturbances from intermittent power sources such as wind and solar power, as well as new loads such as electric vehicles, are intensifying. This dual impact is rapidly reducing the rotational inertia of the power system, gradually undermining the foundation for resisting power imbalances. The direct consequence is that grid frequency fluctuations are becoming increasingly frequent and their amplitudes are significantly increasing, posing an unprecedented challenge to the safety margin for stable system operation.

[0003] Grid frequency is a core indicator of system dynamic balance, and its probability distribution is key data for assessing system operating status and safety risks. Increased frequency distribution broadening not only signifies a decrease in frequency compliance but also frequently triggers and consumes valuable primary frequency regulation reserve resources, driving up operating costs. In extreme cases, it can even threaten the sufficiency of regulation resources and system reliability. Therefore, analyzing the evolution and underlying physical mechanisms of frequency distribution under high-proportion renewable energy sources has become a crucial issue for optimizing frequency defense systems and ensuring the safe operation of new power systems.

[0004] In summary, existing models still have shortcomings, severely restricting the assessment of frequency risk and the optimization of control strategies. Therefore, based on the research on the mechanism of operating frequency distribution characteristics, a frequency regulation strategy optimization method and system should be proposed to improve the operating frequency distribution characteristics of the power grid. Summary of the Invention

[0005] In view of the above-mentioned problems, the present invention is proposed.

[0006] Therefore, the technical problem solved by this invention is that existing power grid frequency regulation control methods have strong dependence on historical statistical parameters, inaccurate evaluation of disturbance scenarios, and low adaptability of frequency control strategies. The problem is how to construct a disturbance probability quantification and closed-loop iterative update mechanism under the conditions of combining frequency distribution standard deviation, damping average value, frequency regulation dead zone and control coefficient, so as to form a computable frequency regulation optimization strategy.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a frequency regulation strategy optimization method, which includes collecting power grid dispatch data and performing preprocessing to obtain the standard deviation of frequency distribution.

[0008] The unit data is aggregated and used as input to calculate the average damping value.

[0009] Obtain the load frequency factor, frequency modulation dead zone, and frequency modulation control coefficient.

[0010] Using the standard deviation of frequency distribution, average damping value, load frequency factor, frequency modulation dead zone, and frequency modulation control coefficient as inputs, the probability of disturbance scenarios is calculated, and the average amplitude of random disturbances is estimated based on the probability of disturbance scenarios.

[0011] Transform the frequency distribution standard deviation to the target frequency standard deviation, re-input the frequency distribution standard deviation, damping average value, load frequency factor, frequency modulation dead zone and frequency modulation control coefficient, and calculate the probability of disturbance scenarios after improving frequency quality.

[0012] The frequency modulation control strategy is based on the average amplitude of random disturbances.

[0013] As a preferred embodiment of the frequency regulation strategy optimization method described in this invention, the collected data includes extracting data from the power grid dispatch database with a continuous time length of... Historical frequency sampling sequence.

[0014] Preprocessing includes threshold removal and standard deviation calculation of the collected historical frequency sampling sequences.

[0015] Threshold rejection includes removing samples exceeding the length of the sliding window from consecutive sampling points. The frequency threshold is obtained by multiplying the standard deviation of the window, and frequencies exceeding the frequency threshold are discarded.

[0016] Standard deviation calculation includes calculating the standard deviation of the frequency distribution.

[0017] As a preferred embodiment of the frequency regulation strategy optimization method described in this invention, the calculation of the average damping value includes summarizing unit data.

[0018] The generator set data includes the number of generator sets, the inertia of each generator set, and the damping of each generator set.

[0019] The average damping value is calculated by taking the summarized unit data as input.

[0020] The formula for calculating the average value of damping is expressed as: , in, This represents the average value of the damping. Indicates the first The inertia of the generator set Indicates the first Damping of the generator set, This indicates the number of generator sets.

[0021] As a preferred embodiment of the frequency regulation strategy optimization method described in this invention, the step of obtaining the load frequency factor includes directly obtaining the frequency factor of the power grid load through offline simulation of real data.

[0022] Calculating the frequency regulation dead zone includes determining the primary frequency regulation dead zone of the power grid using offline data from power grid dispatching.

[0023] The calculation of frequency regulation control coefficients includes weighting the frequency regulation control coefficients according to the unit's inertia.

[0024] The formula for calculating the frequency modulation control coefficient is expressed as follows: , in, Indicates the first Frequency regulation control coefficient of the generator set This represents the frequency modulation control coefficient.

[0025] As a preferred embodiment of the frequency modulation strategy optimization method described in this invention, the calculation of the disturbance scenario probability includes using the frequency distribution standard deviation, damping average value, load frequency factor, frequency modulation dead zone, and frequency modulation control coefficient as inputs to calculate the disturbance scenario probability.

[0026] Frequency distribution standard deviation, damping average value, load frequency factor, frequency modulation dead zone and frequency modulation control coefficient include load frequency factor, damping average value, frequency modulation control coefficient, frequency modulation dead zone and frequency distribution standard deviation.

[0027] The formula for calculating the probability of a disturbance scenario is expressed as: , in, Indicates the FM dead zone. This represents the probability of a perturbation scenario. The cumulative distribution function represents the standard normal distribution.

[0028] Estimating the average amplitude of random disturbances involves taking the probability of the disturbance scenario as input and estimating the average amplitude of the random disturbance using the formula for estimating the average amplitude of random disturbances. The formula for estimating the average amplitude of random disturbances is expressed as follows: , in, This represents the average amplitude of the random disturbance.

[0029] As a preferred embodiment of the frequency modulation strategy optimization method described in this invention, the change to the target frequency standard deviation includes changing the frequency distribution standard deviation to the target standard deviation, and ensuring that the frequency distribution standard deviation is greater than the target standard deviation.

[0030] Calculating the probability of disturbance scenarios after improving frequency quality involves taking the standard deviation of frequency distribution, average damping value, load frequency factor, frequency modulation dead zone, and frequency modulation control coefficient as inputs, and then recalculating the probability of disturbance scenarios after improving frequency quality.

[0031] The formula for calculating the probability of a disturbance scenario after improving frequency quality is expressed as: , in, Indicates the target standard deviation. This represents the probability of a disturbance scenario after improving frequency quality.

[0032] As a preferred embodiment of the frequency modulation strategy optimization method described in this invention, the output frequency modulation control strategy includes: setting the initial frequency modulation control quantity to 0.0010 of the total load; and using the initial frequency modulation control quantity, the average amplitude of random disturbances, and the probability of disturbance scenarios after improving frequency quality as inputs to calculate the first... The standard deviation of the frequency at the next iteration.

[0033] Calculate the first The formula for the standard deviation of the frequency at the next iteration is expressed as: , , in, Indicates the first The standard deviation of the frequency at the next iteration.

[0034] Determine whether the frequency modulation control quantity requirement is met. If the frequency modulation control quantity requirement is met, output the current frequency modulation control quantity as the frequency modulation control strategy; otherwise, update the frequency modulation control quantity and continue iterating.

[0035] The formula for determining whether the frequency modulation control quantity requirement is met is expressed as: , in, This represents the relative error threshold, which is set according to specific accuracy requirements.

[0036] The formula for updating the frequency modulation control quantity is expressed as follows: , in, This indicates an update to the frequency modulation control value. This represents the boundary reference standard deviation, ensuring that the boundary reference standard deviation value is greater than the first... The frequency standard deviation and the target standard deviation at the next iteration.

[0037] Another objective of this invention is to provide a frequency regulation strategy optimization system that can solve the problems of current power grid frequency regulation control technology, such as over-reliance on empirical tuning, inaccurate description of disturbance scenarios, and lack of calculable closed-loop mechanisms in the control strategy, by acquiring the load frequency factor and frequency regulation control coefficient.

[0038] As a preferred embodiment of the frequency modulation strategy optimization system described in this invention, it includes a frequency preprocessing module, a damping calculation module, a parameter acquisition module, a disturbance probability estimation module, a target probability calculation module, and a strategy generation module.

[0039] The frequency preprocessing module is used to collect power grid dispatch data and perform preprocessing to obtain the standard deviation of frequency distribution.

[0040] The damping calculation module is used to summarize unit data and use the summarized unit data as input to calculate the average damping value.

[0041] The parameter acquisition module is used to acquire the load frequency factor, frequency modulation dead zone, and frequency modulation control coefficient.

[0042] The disturbance probability estimation module is used to take the frequency distribution standard deviation, damping average value, load frequency factor, frequency modulation dead zone and frequency modulation control coefficient as inputs, calculate the disturbance scenario probability, and estimate the average amplitude of random disturbance based on the disturbance scenario probability.

[0043] The target probability calculation module is used to change the standard deviation of the frequency distribution to the standard deviation of the target frequency, re-input the standard deviation of the frequency distribution, the average damping value, the load frequency factor, the frequency modulation dead zone and the frequency modulation control coefficient, and calculate the probability of the disturbance scenario after improving the frequency quality.

[0044] The strategy generation module is used to output a frequency modulation control strategy based on the average amplitude of random disturbances.

[0045] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement a frequency modulation strategy optimization method.

[0046] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of a frequency modulation strategy optimization method.

[0047] The beneficial effects of this invention are as follows: The frequency regulation strategy optimization method provided by this invention achieves accurate quantification of frequency fluctuation characteristics by collecting scheduling data and calculating the standard deviation of frequency distribution; it achieves a unified characterization of the overall system damping level by summarizing unit inertia and damping and calculating the average damping value; it achieves standardized and engineering acquisition of key frequency regulation parameters by obtaining load frequency factors, frequency regulation dead zones, and control coefficients; it achieves probabilistic description and computable quantification of random disturbances by calculating the probability of disturbance scenarios and estimating the average amplitude of random disturbances; and it achieves computable convergence and fine adjustment of the frequency regulation control strategy through probability recalculation and closed-loop iteration driven by the target frequency standard deviation. This invention achieves better results in frequency characteristic statistical analysis, unified modeling of system parameters, and iterative optimization of control strategies. Attached Figure Description

[0048] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is an overall flowchart of a frequency modulation strategy optimization method provided in Embodiment 1 of the present invention. Detailed Implementation

[0050] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0051] Example 1, referring to Figure 1 As an embodiment of the present invention, a frequency modulation strategy optimization method is provided, comprising: S1: Collect power grid dispatch data and preprocess it to obtain the standard deviation of frequency distribution.

[0052] Extract the continuous time length from the power grid dispatch database. Historical frequency sampling sequence.

[0053] The historical frequency sampling sequence is represented as: , in, Indicates the total number of sampling points. Represents historical frequency sampling sequences. This indicates historical frequency sampling.

[0054] Preprocessing includes threshold removal and standard deviation calculation of the collected historical frequency sampling sequences.

[0055] Threshold rejection includes removing samples exceeding the length of the sliding window from consecutive sampling points. The frequency threshold is obtained by multiplying the standard deviation of the window, and frequencies exceeding the frequency threshold are discarded.

[0056] The formula for obtaining the frequency threshold is expressed as: , in, Indicates the first in the window Each frequency sample value, Indicates the length of the sliding window. This indicates the threshold for identifying outliers. Indicates the number of sampling points. Set a fixed value of 300, and the length of the sliding window is a positive integer.

[0057] Standard deviation calculation includes calculating the standard deviation of the frequency distribution.

[0058] The formula for calculating the standard deviation of the frequency distribution is expressed as: , in, This represents the global frequency mean. It represents the standard deviation of the frequency distribution.

[0059] S2: Summarize the unit data and use the summarized unit data as input to calculate the average damping value.

[0060] Summarize the unit data.

[0061] The generator set data includes the number of generator sets, the inertia of each generator set, and the damping of each generator set.

[0062] The average damping value is calculated by taking the summarized unit data as input.

[0063] The formula for calculating the average value of damping is expressed as: , in, This represents the average value of the damping. Indicates the first The inertia of the generator set Indicates the first Damping of the generator set, This indicates the number of generator sets.

[0064] S3: Obtain the load frequency factor, frequency modulation dead zone, and frequency modulation control coefficient.

[0065] The frequency factor of the power grid load is obtained directly by simulating real data offline.

[0066] Calculating the frequency regulation dead zone includes determining the primary frequency regulation dead zone of the power grid using offline data from power grid dispatching.

[0067] The calculation of frequency regulation control coefficients includes weighting the frequency regulation control coefficients according to the unit's inertia.

[0068] The formula for calculating the frequency modulation control coefficient is expressed as follows: , in, Indicates the first Frequency regulation control coefficient of the generator set This represents the frequency modulation control coefficient.

[0069] S4: Using the standard deviation of frequency distribution, average damping value, load frequency factor, frequency modulation dead zone and frequency modulation control coefficient as inputs, calculate the probability of disturbance scenarios, and estimate the average amplitude of random disturbances based on the probability of disturbance scenarios.

[0070] The frequency distribution standard deviation, damping average value, load frequency factor, frequency modulation dead zone, and frequency modulation control coefficient are used as inputs to calculate the probability of the disturbance scenario.

[0071] Frequency distribution standard deviation, damping average value, load frequency factor, frequency modulation dead zone and frequency modulation control coefficient include load frequency factor, damping average value, frequency modulation control coefficient, frequency modulation dead zone and frequency distribution standard deviation.

[0072] The formula for calculating the probability of a disturbance scenario is expressed as: , in, Indicates the FM dead zone. This represents the probability of a perturbation scenario. The cumulative distribution function represents the standard normal distribution.

[0073] Estimating the average amplitude of random disturbances involves taking the probability of the disturbance scenario as input and estimating the average amplitude of the random disturbance using the formula for estimating the average amplitude of random disturbances. The formula for estimating the average amplitude of random disturbances is expressed as follows: , in, This represents the average amplitude of the random disturbance.

[0074] S5: Change the standard deviation of the frequency distribution to the standard deviation of the target frequency, re-enter the standard deviation of the frequency distribution, the average damping value, the load frequency factor, the frequency modulation dead zone and the frequency modulation control coefficient, and calculate the probability of the disturbance scenario after improving the frequency quality.

[0075] Change the standard deviation of the frequency distribution to the target standard deviation, and ensure that the standard deviation of the frequency distribution is greater than the target standard deviation.

[0076] Calculating the probability of disturbance scenarios after improving frequency quality involves taking the standard deviation of frequency distribution, average damping value, load frequency factor, frequency modulation dead zone, and frequency modulation control coefficient as inputs, and then recalculating the probability of disturbance scenarios after improving frequency quality.

[0077] The formula for calculating the probability of a disturbance scenario after improving frequency quality is expressed as: , in, Indicates the target standard deviation. This represents the probability of a disturbance scenario after improving frequency quality.

[0078] S5: Output frequency modulation control strategy based on the average amplitude of random disturbance.

[0079] The initial frequency modulation control value is set to 0.0010 of the total load. The initial frequency modulation control value, the average amplitude of random disturbances, and the probability of disturbance scenarios after improving frequency quality are used as inputs to calculate the first... The standard deviation of the frequency at the next iteration.

[0080] Calculate the first The formula for the standard deviation of the frequency at the next iteration is expressed as: , , in, Indicates the first The standard deviation of the frequency at the next iteration.

[0081] Determine whether the frequency modulation control quantity requirement is met. If the frequency modulation control quantity requirement is met, output the current frequency modulation control quantity as the frequency modulation control strategy; otherwise, update the frequency modulation control quantity and continue iterating.

[0082] The formula for determining whether the frequency modulation control quantity requirement is met is expressed as: , in, This represents the relative error threshold, which is set according to specific accuracy requirements.

[0083] The formula for updating the frequency modulation control quantity is expressed as follows: , in, This indicates an update to the frequency modulation control value. This represents the boundary reference standard deviation, ensuring that the boundary reference standard deviation value is greater than the first... The frequency standard deviation and the target standard deviation at the next iteration.

[0084] Example 2, an embodiment of the present invention, provides a frequency modulation strategy optimization system, including a frequency preprocessing module, a damping calculation module, a parameter acquisition module, a disturbance probability estimation module, a target probability calculation module, and a strategy generation module.

[0085] The frequency preprocessing module is used to collect power grid dispatch data and perform preprocessing to obtain the standard deviation of frequency distribution.

[0086] The damping calculation module is used to summarize unit data and use the summarized unit data as input to calculate the average damping value.

[0087] The parameter acquisition module is used to obtain the load frequency factor, frequency modulation dead zone, and frequency modulation control coefficient.

[0088] The disturbance probability estimation module takes the frequency distribution standard deviation, damping average value, load frequency factor, frequency modulation dead zone and frequency modulation control coefficient as inputs, calculates the disturbance scenario probability, and estimates the average amplitude of random disturbances based on the disturbance scenario probability.

[0089] The target probability calculation module is used to transform the standard deviation of the frequency distribution into the standard deviation of the target frequency, re-input the standard deviation of the frequency distribution, the average damping value, the load frequency factor, the frequency modulation dead zone and the frequency modulation control coefficient, and calculate the probability of the disturbance scenario after improving the frequency quality.

[0090] The strategy generation module is used to output frequency modulation control strategies based on the average amplitude of random disturbances.

[0091] This embodiment also provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the doubly fed converter commissioning method proposed in the above embodiment.

[0092] This embodiment also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the doubly-fed converter commissioning method proposed in the above embodiment.

[0093] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0094] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0095] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0096] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0097] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A frequency modulation strategy optimization method, characterized in that, include: The standard deviation of the frequency distribution is obtained by collecting and preprocessing power grid dispatch data. Summarize the unit data and use the summarized unit data as input to calculate the average damping value; Obtain the load frequency factor, frequency modulation dead zone, and frequency modulation control coefficient; The frequency distribution standard deviation, damping average value, load frequency factor, frequency modulation dead zone and frequency modulation control coefficient are used as inputs to calculate the probability of disturbance scenarios, and the average amplitude of random disturbances is estimated based on the probability of disturbance scenarios. Transform the standard deviation of the frequency distribution to the standard deviation of the target frequency, re-input the standard deviation of the frequency distribution, the average damping value, the load frequency factor, the frequency modulation dead zone and the frequency modulation control coefficient, and calculate the probability of the disturbance scenario after improving the frequency quality. The frequency modulation control strategy is based on the average amplitude of random disturbances.

2. The frequency modulation strategy optimization method as described in claim 1, characterized in that: The collected data includes, Extract the continuous time length from the power grid dispatch database. Historical frequency sampling sequence; Preprocessing includes threshold removal and standard deviation calculation of the collected historical frequency sampling sequences; Threshold rejection includes removing samples exceeding the length of the sliding window from consecutive sampling points. The frequency threshold is obtained by taking points that are multiples of the standard deviation of the window, and frequencies exceeding the frequency threshold are discarded. Standard deviation calculation includes calculating the standard deviation of the frequency distribution.

3. The frequency modulation strategy optimization method as described in claim 2, characterized in that: The calculated average damping value includes, Summarize unit data; The generator set data includes the number of generator sets, the inertia of each generator set, and the damping of each generator set; The average damping value is calculated by taking the summarized unit data as input. The formula for calculating the average value of damping is expressed as: ， in, This represents the average value of the damping. Indicates the first The inertia of the generator set Indicates the first Damping of the generator set, This indicates the number of generator sets.

4. The frequency modulation strategy optimization method as described in claim 3, characterized in that: The acquisition of the load frequency factor includes, The frequency factor of the power grid load is obtained directly by simulating real data offline. Calculating the frequency regulation dead zone includes determining the primary frequency regulation dead zone of the power grid using offline power grid dispatch data; The calculation of frequency regulation control coefficients includes weighting the frequency regulation control coefficients according to the unit's inertia; The formula for calculating the frequency modulation control coefficient is expressed as follows: ， in, Indicates the first Frequency regulation control coefficient of the generator set This represents the frequency modulation control coefficient.

5. The frequency modulation strategy optimization method as described in claim 4, characterized in that: The calculated probability of the disturbance scenario includes The frequency distribution standard deviation, damping average value, load frequency factor, frequency modulation dead zone and frequency modulation control coefficient are used as inputs to calculate the probability of the disturbance scenario. Frequency distribution standard deviation, damping average value, load frequency factor, frequency modulation dead zone and frequency modulation control coefficient include load frequency factor, damping average value, frequency modulation control coefficient, frequency modulation dead zone and frequency distribution standard deviation; The formula for calculating the probability of a disturbance scenario is expressed as: ， in, Indicates the FM dead zone. This represents the probability of the perturbation scenario. The cumulative distribution function represents the standard normal distribution; Estimating the average amplitude of random disturbances involves taking the probability of the disturbance scenario as input and estimating the average amplitude of the random disturbance using the formula for estimating the average amplitude of random disturbances. The formula for estimating the average amplitude of random disturbances is expressed as follows: ， in, This represents the average amplitude of the random disturbance.

6. The frequency modulation strategy optimization method as described in claim 5, characterized in that: The change, which is the standard deviation of the target frequency, includes: Change the standard deviation of the frequency distribution to the target standard deviation, and ensure that the standard deviation of the frequency distribution is greater than the target standard deviation; Calculating the probability of disturbance scenarios after improving frequency quality involves taking the standard deviation of frequency distribution, average damping value, load frequency factor, frequency modulation dead zone, and frequency modulation control coefficient as inputs, and recalculating the probability of disturbance scenarios after improving frequency quality. The formula for calculating the probability of a disturbance scenario after improving frequency quality is expressed as: ， in, Indicates the target standard deviation. This represents the probability of a disturbance scenario after improving frequency quality.

7. The frequency modulation strategy optimization method as described in claim 6, characterized in that: The output frequency modulation control strategy includes: The initial frequency modulation control value is set to 0.0010 of the total load. The initial frequency modulation control value, the average amplitude of random disturbances, and the probability of disturbance scenarios after improving frequency quality are used as inputs to calculate the first... The standard deviation of the frequency at the next iteration; Calculate the first The formula for the standard deviation of the frequency at the next iteration is expressed as: ， ， in, Indicates the first The standard deviation of the frequency at the next iteration; Determine whether the frequency modulation control quantity requirement is met. If the frequency modulation control quantity requirement is met, output the current frequency modulation control quantity as the frequency modulation control strategy; otherwise, update the frequency modulation control quantity and continue iterating. The formula for determining whether the frequency modulation control quantity requirement is met is expressed as: ， in, This indicates the relative error threshold, which can be set according to specific accuracy requirements. The formula for updating the frequency modulation control quantity is expressed as follows: ， in, This indicates an update to the frequency modulation control value. This represents the boundary reference standard deviation, ensuring that the boundary reference standard deviation value is greater than the first... The frequency standard deviation and the target standard deviation at the next iteration.

8. A frequency modulation strategy optimization system, employing the frequency modulation strategy optimization method as described in any one of claims 1 to 7, characterized in that: It includes a frequency preprocessing module, a damping calculation module, a parameter acquisition module, a disturbance probability estimation module, a target probability calculation module, and a strategy generation module; The frequency preprocessing module is used to collect power grid dispatch data and perform preprocessing to obtain the standard deviation of frequency distribution. The damping calculation module is used to summarize unit data and use the summarized unit data as input to calculate the average damping value. The parameter acquisition module is used to acquire the load frequency factor, frequency modulation dead zone, and frequency modulation control coefficient. The disturbance probability estimation module is used to take the frequency distribution standard deviation, damping average value, load frequency factor, frequency modulation dead zone and frequency modulation control coefficient as inputs, calculate the disturbance scenario probability, and estimate the average amplitude of random disturbance based on the disturbance scenario probability. The target probability calculation module is used to change the standard deviation of frequency distribution to the standard deviation of target frequency, re-input the standard deviation of frequency distribution, damping average value, load frequency factor, frequency modulation dead zone and frequency modulation control coefficient, and calculate the probability of disturbance scenario after improving frequency quality. The strategy generation module is used to output a frequency modulation control strategy based on the average amplitude of random disturbances.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the frequency modulation strategy optimization method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the frequency modulation strategy optimization method according to any one of claims 1 to 7.

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