A low-frequency defense strategy for power grids that considers wind power participation in frequency regulation

Abstract

This invention relates to a low-frequency defense strategy for power grids considering wind power participation in frequency regulation, and more particularly to a low-frequency defense strategy for power grids based on the Cuckoo Search algorithm. It can effectively construct a defense system for current low-frequency events in the power grid, creating a reliable defense line for power grid frequency stability. The steps include: Step 1, building a wind turbine participation model in power grid frequency regulation in power grid simulation software and inputting relevant parameters to simulate low-frequency events in the power grid; Step 2, constructing an objective function to evaluate the degree of frequency recovery before and after load shedding; Step 3, performing load shedding calculations to minimize the objective function; Step 4, outputting the results to obtain the optimized load reduction amount for the low-frequency defense strategy under this wind-to-thermal power ratio; Step 5, changing the wind-to-thermal power ratio in the power grid model and performing the above calculations again to obtain low-frequency defense strategies for different wind-to-thermal power ratios.

Description

Technical Field

[0001] This invention relates to a low-frequency defense strategy for power grids that takes into account wind power participation in frequency regulation, and more particularly to a low-frequency defense strategy for power grids that takes into account wind power participation in frequency regulation based on the Cuckoo Search algorithm. Background Technology

[0002] Frequency stability is a crucial safeguard for the safe and stable operation of the power system, and frequency is also a key indicator of power quality. The large-scale grid connection of new energy units has significantly reduced the power system's inertia, negatively impacting grid security and stability. How to coordinate the increasing proportion of new energy sources with the continuously decreasing system inertia is a key issue we need to address. When considering frequency response and virtual inertia control, wind turbines can release their hidden inertia, enabling them to assist thermal power units in participating in grid frequency regulation.

[0003] To ensure the safety and stability of the last line of defense for the power grid frequency, a low-frequency defense strategy needs to be formulated. The participation of large-scale wind turbine units in the primary frequency regulation of the system will have a significant impact on the formulation and implementation of the low-frequency load shedding strategy. The formulation of the low-frequency defense strategy can be based on theoretical derivation of formulas to determine the load shedding amount, or it can be optimized through numerical simulation analysis. That is, a model of wind turbine units participating in power grid frequency regulation is built in power system simulation software, electrical component parameters are edited, faults are set, and then the low-frequency defense calculation is completed.

[0004] Current research on low-frequency defense strategies mainly focuses on thermal power units or wind turbine units that consider frequency response. However, low-frequency defense strategies for wind turbine units that consider virtual inertia control and participate in grid frequency regulation are issues that need to be studied. Summary of the Invention

[0005] This invention addresses the shortcomings of existing technologies by providing a low-frequency defense strategy for wind power participation in frequency regulation based on the Cuckoo Search algorithm. Under accurate grid model and operating conditions, it considers the primary adjustment capability of wind turbines in grid regulation. A wind turbine participation frequency regulation model is built in grid simulation software, and relevant parameters are input to simulate low-frequency events. An objective function is constructed to evaluate the degree of frequency recovery before and after load shedding. The load shedding amount under wind power participation in grid frequency regulation is optimized using the Cuckoo Search algorithm, and the load shedding calculation is performed based on the proportion of wind turbines participating in grid frequency regulation under the current grid operating state in the simulation model, minimizing the objective function value. By changing the wind-thermal ratio in the grid model and recalculating, low-frequency defense strategies under different wind-thermal ratios are obtained. This provides a defense strategy for low-frequency events under wind power participation in frequency regulation, enabling the rest of the system to quickly recover to near-rated frequency and continue operating, thus creating a reliable defense for grid frequency stability.

[0006] To achieve the above objectives, the present invention adopts the following technical solution, comprising the following steps:

[0007] Step 1: Build a wind turbine generator participating in the power grid frequency regulation model in the power grid simulation software and input relevant parameters to simulate low-frequency events in the power grid;

[0008] Step 2: Based on Step 1, construct an objective function to evaluate the degree of frequency recovery before and after load removal;

[0009] Step 3: Optimize the load shedding amount under the grid frequency regulation of wind power based on the cuckoo search algorithm, and calculate the load shedding based on the proportion of wind turbines participating in grid frequency regulation under the current grid operation state in the simulation model, so that the objective function reaches a smaller value.

[0010] Step 4: Output the results to obtain the optimized load reduction for the power grid's low-frequency defense strategy under this wind-fire ratio.

[0011] Step 5: Change the wind-fire ratio in the power grid model and repeat the above steps to obtain the low-frequency defense strategy of the power grid under different wind-fire ratios.

[0012] Further, step 1 includes:

[0013] Step 1.1: Determine the types of wind turbines that can participate in grid frequency regulation;

[0014] Step 1.2: Retrieve the wind turbine model from the database and add it to the regional power grid model;

[0015] Step 1.3: Set the parameters for the wind turbine frequency response module and the virtual inertia control module to enable the wind turbine to respond to frequencies.

[0016] Step 1.4: Optimize and identify the parameters of the wind turbine frequency response module and the virtual inertia control module to make the simulation results more consistent with reality;

[0017] Step 1.5: Set the output status of each unit.

[0018] Further, in step 2, the objective function for evaluating the degree of frequency recovery before and after load removal includes the following:

[0019] Step 2.1: Define evaluation indicators to evaluate the difference between the grid frequency before the accident and the grid frequency after the load is disconnected. The evaluation indicators include the difference in the initial frequency reduction, the difference in the frequency recovery, and the frequency peak-to-valley difference.

[0020] Step 2.2: Establish the objective evaluation function;

[0021] Step 2.3: Conduct a low-frequency event test considering wind power participation in frequency regulation. Based on the load shedding scheme under the condition that wind power does not participate in frequency regulation, perform low-frequency load reduction calculations, obtain the above-mentioned evaluation index values, substitute them into the objective function for calculation, and obtain the objective function value under the load reduction amount.

[0022] Furthermore, step 3 includes:

[0023] Step 3.1: Given algorithm parameters based on the load reduction amount to be optimized;

[0024] Step 3.2: Randomly initialize the population of bird eggs to generate an initial solution and calculate the corresponding initial fitness value;

[0025] Step 3.3: Use Levy flight to update the solution, generate new eggs, and calculate fitness values;

[0026] Step 3.4: Compare the fitness values ​​to obtain candidate solutions;

[0027] Step 3.5: Substitute the candidate solutions obtained in Step 3.4 into the simulation calculation of wind power participation in frequency regulation to obtain the values ​​of each evaluation index;

[0028] Step 3.6: Substitute the solutions into the objective function for calculation, discard the candidate solutions with larger objective function calculation results, and retain the candidate solutions with the smallest objective function value;

[0029] Step 3.7: Update the location of the bird's nest;

[0030] Step 3.8: Update the initial solution;

[0031] Step 3.9 Termination Criteria: If the maximum allowed number of iterations is reached or the objective function value does not improve after multiple consecutive iterations, stop the calculation, output the result, and obtain the optimal load reduction.

[0032] Step 3.10: If the termination criterion is not met, repeat step 3 (step 3.3) to continue the calculation.

[0033] Furthermore, in step 1, the process of building a wind turbine participating in the power grid frequency regulation model in the power grid simulation software and inputting relevant parameters to simulate low-frequency events in the power grid is as follows:

[0034] a. Build a regional power grid model in power system simulation software, which is suitable for wind turbine units to participate in power grid frequency regulation;

[0035] b. In the simulation software, build electrical component models based on the actual situation of the regional power grid and set the parameters;

[0036] c. Set the power system operation mode;

[0037] d. Configure low-frequency event faults;

[0038] e. Conduct low-frequency event tests considering wind power participation in frequency regulation, and use the load shedding scheme under the condition that wind power does not participate in frequency regulation as the basis for low-frequency load reduction calculations to obtain the grid frequency change trajectory.

[0039] Furthermore, the process of constructing the objective function for evaluating the degree of frequency recovery before and after load removal in step 2 is as follows:

[0040] a. The indicator system is as follows:

[0041] Initial frequency reduction difference of the power grid: This is the absolute value of the numerical difference in the trajectory of the power grid frequency change from the initial frequency reduction to the lowest point after a low-frequency event occurs.

[0042] Frequency recovery difference: This is the absolute value of the difference in the frequency change trajectory of the power grid after the power grid frequency curve reaches a trough and then recovers to a stable state.

[0043] Frequency peak-valley difference: The absolute value of the maximum difference between the power grid frequency trajectory values ​​on the frequency axis when performing low-frequency defense calculations for the power grid;

[0044] b. The objective function is defined as follows:

[0045] F=λ1x1+λ2x2+λ3x3 (1)

[0046] In equation (1): F represents the objective function; x i Represents each evaluation indicator; λ i The three terms in the polynomial represent the weight coefficients corresponding to each evaluation indicator; the total of three terms in the polynomial represents the number of evaluation indicators included in the definition of the objective function.

[0047] Furthermore, in step 3, the load shedding amount under grid frequency regulation is optimized based on the cuckoo search algorithm, and the load shedding calculation is performed based on the proportion of wind turbines participating in grid frequency regulation under the current grid operating state in the simulation model, so that the objective function reaches a smaller value:

[0048] a. Randomly initialize the population of bird eggs to obtain an initial solution and calculate the fitness value;

[0049] b. Use Levy flight to update the solution, generate new eggs, and calculate fitness values;

[0050] c. Compare the fitness values ​​to obtain candidate solutions;

[0051] d. Modify the load reduction amount under low-frequency events in the simulation software;

[0052] e. Set the operating mode and faults, perform low-frequency defense calculations for wind turbines participating in grid frequency regulation, and obtain the frequency change trajectory;

[0053] f. Obtain the evaluation index of the frequency change trajectory and substitute it into the objective function for calculation;

[0054] g. Obtain the objective function value and compare it with the objective function value in the previous iteration. The one with the smaller objective function value will proceed to the next iteration, while the one with the larger objective function value will be discarded.

[0055] h. Repeat the above steps. If the maximum allowed number of iterations is reached or the objective function value does not improve after multiple consecutive iterations, stop the calculation, output the result, and obtain the optimal load reduction.

[0056] Furthermore, in step 5, the wind-thermal ratio in the power grid model is changed, and the above calculation steps are performed again to obtain the low-frequency defense strategy of the power grid under different wind-thermal ratios:

[0057] a. Locate the unit output summary table in the power system simulation model;

[0058] b. Calculate the ratio of wind turbine units to thermal power units currently in operation under the current wind power participation in grid frequency regulation;

[0059] c. With the total power output of the power grid in the region remaining unchanged, enter the parameter database, adjust the number of wind turbines and thermal power units that are turned on and off, and complete the modification of the wind-thermal ratio;

[0060] d. Perform simulation calculations under the new wind-fire ratio according to the algorithm optimization and low-frequency defense calculation steps;

[0061] e. Record the load reduction under different wind-fire ratios after optimization, in order to consider the low-frequency defense strategy for wind turbines participating in grid frequency regulation.

[0062] Compared with the prior art, the present invention has the following advantages.

[0063] This invention takes the participation of wind turbine units in power grid frequency regulation as its background. It can effectively build a defense system against low-frequency events in the current power grid, enabling the rest of the system to quickly recover to near the rated frequency and continue operating. This conforms to the actual operating conditions of the power system and creates a reliable defense for power grid frequency stability.

[0064] This invention considers a low-frequency defense strategy for wind turbines participating in grid frequency regulation. It extends the previous low-frequency load reduction scheme for thermal power units participating in frequency regulation by taking into account the frequency response and virtual inertia control of wind turbines in the modeling process, and proposes a more reliable low-frequency event defense scheme for large power grids.

[0065] This invention utilizes the Cuckoo Search algorithm to accurately optimize the load reduction in low-frequency defense strategies, and is applicable to regional power grids where wind turbines participate in grid frequency regulation, which is beneficial to the safe and stable operation of the power grid. Attached Figure Description

[0066] The present invention will be further described below with reference to the accompanying drawings and specific embodiments. The scope of protection of the present invention is not limited to the following description.

[0067] Figure 1 This is the overall flowchart of a low-frequency defense strategy for the power grid that takes into account wind power participation in frequency regulation.

[0068] Figure 2 This is a comparison chart of the load shedding amount for low-frequency defense strategies under different fire prevention ratios.

[0069] Figure 3-1 It is one of the power grid frequency trajectory diagrams based on the optimization of load reduction.

[0070] Figure 3-2 This is the second power grid frequency trajectory diagram based on the optimization of load reduction.

[0071] Figure 3-3 This is the third power grid frequency trajectory diagram based on the optimization of load reduction. Detailed Implementation

[0072] like Figures 1 to 3-3 As shown, the present invention provides a low-frequency defense strategy for power grids that considers wind power participation in frequency regulation, comprising the following steps:

[0073] Step 1) Build a wind turbine generator participating in the power grid frequency regulation model in the power grid simulation software and input relevant parameters to simulate low-frequency events in the power grid.

[0074] ① Determine the types of wind turbines that can participate in grid frequency regulation.

[0075] ② Call the wind turbine model from the database and add it to the regional power grid model.

[0076] ③ Set the parameters for the wind turbine frequency response module and the virtual inertia control module to enable the wind turbine to respond to frequencies.

[0077] ④ The parameters of the wind turbine frequency response module and the virtual inertia control module are optimized and identified to make the simulation results more consistent with reality.

[0078] ⑤ Set the output status of each unit.

[0079] Step 2) Based on Step 1), construct an objective function to evaluate the degree of frequency recovery before and after load removal; the objective function model can be summarized as follows:

[0080] ① Define evaluation indicators to evaluate the difference between the grid frequency before the accident and the grid frequency after the load is cut off. The evaluation indicators include the difference in the initial frequency reduction, the difference in the frequency recovery, and the frequency peak-valley difference.

[0081] ②Establish the objective evaluation function.

[0082] ③ Conduct low-frequency event tests considering wind power participation in frequency regulation. Based on the load shedding scheme under the condition that wind power does not participate in frequency regulation, perform low-frequency load reduction calculations, obtain the above-mentioned evaluation index values, substitute them into the objective function for calculation, and obtain the objective function value under the load reduction amount.

[0083] Step 3) Optimize the load shedding amount under the grid frequency regulation of wind power based on the cuckoo search algorithm, and calculate the load shedding based on the proportion of wind turbines participating in grid frequency regulation under the current grid operation state in the simulation model, so that the objective function reaches a smaller value.

[0084] The first step is to provide algorithm parameters based on the load reduction amount to be optimized.

[0085] The second step is to randomly initialize the population of bird eggs, generate an initial solution, and calculate the corresponding initial fitness value.

[0086] The third step is to use Levy flight to update the solution, generate new eggs, and calculate the fitness value.

[0087] Step 4: Compare the fitness values ​​to obtain candidate solutions.

[0088] Fifth, substitute the candidate solutions obtained in the fourth step into the simulation calculation of wind power participating in frequency regulation to obtain the values ​​of each evaluation index.

[0089] Step 6: Substitute the solutions into the objective function for calculation, discard the candidate solutions with larger objective function calculation results, and retain the candidate solutions with the smallest objective function value.

[0090] Step 7: Update the location of the bird's nest.

[0091] Step 8: Update the initial solution.

[0092] Step 9, Termination Criteria: If the maximum allowed number of iterations is reached or the objective function value does not improve after multiple consecutive iterations, stop the calculation, output the result, and obtain the optimal load reduction.

[0093] Step 10: If the termination criterion is not met, repeat step 3 to continue the calculation.

[0094] Step 4) Output the results to obtain the optimized load reduction amount for the low-frequency defense strategy of the power grid under this wind-fire ratio.

[0095] Step 5) Change the wind-fire ratio in the power grid model and perform the above steps again to obtain the low-frequency defense strategy of the power grid under different wind-fire ratios.

[0096] The process of building a wind turbine generator model in power grid simulation software to participate in power grid frequency regulation and inputting relevant parameters to simulate low-frequency events in the power grid is as follows:

[0097] a. Build a regional power grid model in power system simulation software, which is suitable for wind turbine units to participate in power grid frequency regulation.

[0098] b. In the simulation software, build electrical component models based on the actual situation of the regional power grid and set the parameters.

[0099] c. Set the power system operation mode.

[0100] d. Configure low-frequency event faults.

[0101] e. Conduct low-frequency event tests considering wind power participation in frequency regulation, and use the load shedding scheme under the condition that wind power does not participate in frequency regulation as the basis for low-frequency load reduction calculations to obtain the grid frequency change trajectory.

[0102] The process of constructing the objective function to evaluate the degree of frequency recovery before and after load removal is as follows:

[0103] a. The indicator system is as follows:

[0104] Initial frequency reduction difference of the power grid: This is the absolute value of the difference in the frequency change trajectory of the power grid from its initial drop to its lowest point after a low-frequency event.

[0105] Frequency recovery difference: This is the absolute value of the difference in the frequency change trajectory of the power grid after the power grid frequency curve reaches a trough and then recovers to a stable state.

[0106] Frequency peak-valley difference: The absolute value of the maximum difference between the power grid frequency trajectory values ​​on the frequency axis when performing low-frequency defense calculations for the power grid.

[0107] b. The objective function is defined as follows:

[0108] F=λ1x1+λ2x2+λ3x3 (1)

[0109] In equation (1): F represents the objective function; x i Represents each evaluation indicator; λ i The three terms in the polynomial represent the weight coefficients corresponding to each evaluation indicator; the total of three terms in the polynomial represents the number of evaluation indicators included in the definition of the objective function.

[0110] The load shedding amount under grid frequency regulation is optimized based on the cuckoo search algorithm, and the load shedding calculation is performed based on the proportion of wind turbines participating in grid frequency regulation under the current grid operating state in the simulation model. Achieving a smaller objective function means:

[0111] a. Randomly initialize the population of bird eggs to obtain an initial solution and calculate the fitness value.

[0112] b. Use Levy flight to update the solution, generate new eggs, and calculate fitness values.

[0113] c. Compare the fitness values ​​to obtain candidate solutions.

[0114] d. Modify the load reduction amount under low-frequency events in the simulation software.

[0115] e. Set the operating mode and faults, perform low-frequency defense calculations for wind turbines participating in grid frequency regulation, and obtain the frequency change trajectory.

[0116] f. Obtain the evaluation index of the frequency change trajectory and substitute it into the objective function for calculation.

[0117] g. Obtain the objective function value and compare it with the objective function value in the previous iteration. The objective function value with the smaller value will proceed to the next iteration, while the objective function value with the larger value will be discarded.

[0118] h. Repeat the above steps. If the maximum allowed number of iterations is reached or the objective function value does not improve after multiple consecutive iterations, stop the calculation, output the result, and obtain the optimal load reduction.

[0119] By changing the wind-thermal ratio in the power grid model and recalculating, the low-frequency defense strategies for the power grid under different wind-thermal ratios are as follows:

[0120] a. Locate the unit output summary table in the power system simulation model.

[0121] b. Calculate the ratio of wind turbine units to thermal power units currently in operation under the current wind power participation in grid frequency regulation.

[0122] c. With the total power output of the power grid in the region remaining unchanged, enter the parameter database, adjust the number of wind turbines and thermal power units that are turned on and off, and complete the modification of the wind-thermal power ratio.

[0123] d. Perform simulation calculations under the new wind-fire ratio according to the algorithm optimization and low-frequency defense calculation steps.

[0124] e. Record the load reduction under different wind-fire ratios after optimization, in order to consider the low-frequency defense strategy for wind turbines participating in grid frequency regulation.

[0125] like Figure 2 As shown, the load reduction amount of wind turbines participating in grid frequency regulation is optimized under different wind-to-thermal ratios. It can also be found that the load reduction amount required during low-frequency load reduction is less after wind power participates in frequency regulation, and the effect of less load reduction is more obvious as the proportion of wind power participating in frequency regulation increases.

[0126] like Figure 3-1 , Figure 3-2 , Figure 3-3 The figure shows the power grid frequency trajectory based on the optimized load reduction under different wind-to-fire ratios.

[0127] A fault was simulated with a grid loss of 6500MW of generating capacity. Comparative simulations were conducted under three scenarios with wind-to-thermal power ratios of 1:22, 1:15, and 1:8. In the stable state, the grid frequency recovered to approximately 49.8Hz. According to power industry standards, after the automatic low-frequency load shedding device is activated, the system steady-state frequency should recover to no less than 49.5Hz, and the frequency difference should ideally be no less than 0.2Hz, which meets the requirements. Furthermore, when the load shedding amount with wind power participating in frequency regulation is significantly less than when wind power does not participate in frequency regulation, the frequency curves after the load shedding are almost identical, which also demonstrates the importance of wind power participation in frequency regulation for the safe and stable operation of the power grid.

[0128] It is understood that the above specific description of the present invention is only for illustrating the present invention and is not limited to the technical solutions described in the embodiments of the present invention. Those skilled in the art should understand that modifications or equivalent substitutions can still be made to the present invention to achieve the same technical effect; as long as the use needs are met, they are all within the protection scope of the present invention.

Claims

1. A low-frequency defense strategy for power grids that considers wind power participation in frequency regulation, characterized in that: Includes the following steps: Step 1: Build a wind turbine generator participating in the power grid frequency regulation model in the power grid simulation software and input relevant parameters to simulate low-frequency events in the power grid; Step 2: Based on Step 1, construct an objective function to evaluate the degree of frequency recovery before and after load removal; Step 3: Optimize the load shedding amount under the grid frequency regulation of wind power based on the cuckoo search algorithm, and calculate the load shedding based on the proportion of wind turbines participating in grid frequency regulation under the current grid operation state in the simulation model, so that the objective function reaches a smaller value. Step 4: Output the results to obtain the optimized load reduction for the power grid's low-frequency defense strategy under this wind-fire ratio. Step 5: Change the wind-fire ratio in the power grid model, and repeat the above steps to obtain the low-frequency defense strategy of the power grid under different wind-fire ratios. The process of constructing the objective function for evaluating the degree of frequency recovery before and after load removal in step 2 is as follows: a. The indicator system is as follows: Initial frequency reduction difference of the power grid: This is the absolute value of the numerical difference in the trajectory of the power grid frequency change from the initial frequency reduction to the lowest point after a low-frequency event occurs. Frequency rise difference: This is the absolute value of the numerical difference in the power grid frequency change trajectory after the power grid frequency curve reaches a trough and then rises back to a stable state. Frequency peak-valley difference: The absolute value of the maximum difference between the power grid frequency trajectory values ​​on the frequency axis when performing low-frequency defense calculations for the power grid; b. The objective function is defined as follows: F=λ1x1+λ2x2+λ3x3 (1) In equation (1): F represents the objective function; x i Represents each evaluation indicator; λ i The three terms in the polynomial represent the weight coefficients corresponding to each evaluation indicator; the total of three terms in the polynomial represents the number of evaluation indicators included in the definition of the objective function.

2. A low-frequency defense strategy for power grids considering wind power participation in frequency regulation according to claim 1, characterized in that: Step 1 includes: Step 1.1: Determine the types of wind turbines that can participate in grid frequency regulation; Step 1.2: Retrieve the wind turbine model from the database and add it to the regional power grid model; Step 1.3: Set the parameters for the wind turbine frequency response module and the virtual inertia control module to enable the wind turbine to respond to frequencies. Step 1.4: Optimize and identify the parameters of the wind turbine frequency response module and the virtual inertia control module to make the simulation results more consistent with reality; Step 1.5: Set the output status of each unit.

3. A low-frequency defense strategy for power grids considering wind power participation in frequency regulation according to claim 1, characterized in that: In step 2, the objective function for evaluating the degree of frequency recovery before and after load removal includes the following: The objective function model comprises: Step 2.1: Define evaluation indicators to evaluate the difference between the grid frequency before the accident and the grid frequency after the load is disconnected. The evaluation indicators include the difference in the initial frequency reduction, the difference in the frequency recovery, and the frequency peak-to-valley difference. Step 2.2: Establish the objective evaluation function; Step 2.3: Conduct a low-frequency event test considering wind power participation in frequency regulation. Based on the load shedding scheme under the condition that wind power does not participate in frequency regulation, perform low-frequency load reduction calculations, obtain the above-mentioned evaluation index values, substitute them into the objective function for calculation, and obtain the objective function value under the load reduction amount.

4. A low-frequency defense strategy for power grids considering wind power participation in frequency regulation according to claim 1, characterized in that: Step 3 includes: Step 3.1: Given algorithm parameters based on the load reduction amount to be optimized; Step 3.2: Randomly initialize the population of bird eggs to generate an initial solution and calculate the corresponding initial fitness value; Step 3.3: Use Levy flight to update the solution, generate new eggs, and calculate fitness values; Step 3.4: Compare the fitness values ​​to obtain candidate solutions; Step 3.5: Substitute the candidate solutions obtained in Step 3.4 into the simulation calculation of wind power participation in frequency regulation to obtain the values ​​of each evaluation index; Step 3.6: Substitute the solutions into the objective function for calculation, discard the candidate solutions with larger objective function calculation results, and retain the candidate solutions with the smallest objective function value; Step 3.7: Update the location of the bird's nest; Step 3.8: Update the initial solution; Step 3.9 Termination Criteria: If the maximum allowed number of iterations is reached or the objective function value does not improve after multiple consecutive iterations, stop the calculation, output the result, and obtain the optimal load reduction. Step 3.10: If the termination criterion is not met, repeat step 3 to continue the calculation.

5. A low-frequency defense strategy for power grids considering wind power participation in frequency regulation according to claim 1, characterized in that: In step 1, the process of building a wind turbine model in the power grid simulation software to participate in power grid frequency regulation and inputting relevant parameters to simulate low-frequency events in the power grid is as follows: a. Build a regional power grid model in power system simulation software, which is suitable for wind turbine units to participate in power grid frequency regulation; b. In the simulation software, build electrical component models based on the actual situation of the regional power grid and set the parameters; c. Set the power system operation mode; d. Configure low-frequency event faults; e. Conduct low-frequency event tests considering wind power participation in frequency regulation, and use the load shedding scheme under the condition that wind power does not participate in frequency regulation as the basis for low-frequency load reduction calculations to obtain the grid frequency change trajectory.

6. A low-frequency defense strategy for power grids considering wind power participation in frequency regulation according to claim 1, characterized in that: In step 3, the load shedding amount under grid frequency regulation is optimized based on the cuckoo search algorithm, and the load shedding calculation is performed based on the proportion of wind turbines participating in grid frequency regulation under the current grid operating state in the simulation model, so that the objective function reaches a smaller value: a. Randomly initialize the population of bird eggs to obtain an initial solution and calculate the fitness value; b. Use Levy flight to update the solution, generate new eggs, and calculate fitness values; c. Compare the fitness values ​​to obtain candidate solutions; d. Modify the load reduction amount under low-frequency events in the simulation software; e. Set the operating mode and faults, perform low-frequency defense calculations for wind turbines participating in grid frequency regulation, and obtain the frequency change trajectory; f. Obtain the evaluation index of the frequency change trajectory and substitute it into the objective function for calculation; g. Obtain the objective function value and compare it with the objective function value in the previous iteration. The one with the smaller objective function value will proceed to the next iteration, while the one with the larger objective function value will be discarded. h. Repeat the above steps. If the maximum allowed number of iterations is reached or the objective function value does not improve after multiple consecutive iterations, stop the calculation, output the result, and obtain the optimal load reduction.

7. A low-frequency defense strategy for power grids considering wind power participation in frequency regulation according to claim 1, characterized in that: In step 5, the wind-thermal ratio in the power grid model is changed, and the above calculation steps are performed again to obtain the low-frequency defense strategy of the power grid under different wind-thermal ratios: a. Locate the unit output summary table in the power system simulation model; b. Calculate the ratio of wind turbine units to thermal power units currently in operation under the current wind power participation in grid frequency regulation; c. With the total power output of the power grid in the region remaining unchanged, enter the parameter database, adjust the number of wind turbines and thermal power units that are turned on and off, and complete the modification of the wind-thermal ratio; d. Perform simulation calculations under the new wind-fire ratio according to the algorithm optimization and low-frequency defense calculation steps; e. Record the load reduction under different wind-fire ratios after optimization, in order to consider the low-frequency defense strategy for wind turbines participating in grid frequency regulation.

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