A method and apparatus for identifying new energy power plants that affect grid impedance stability

Abstract

This invention relates to a method and apparatus for identifying renewable energy power plants that affect grid impedance stability. The method includes: acquiring sample datasets of system stability margins corresponding to each output level of the renewable energy power generation system and the output of each renewable energy power plant; determining the weight of each renewable energy power plant in the renewable energy power generation system based on the sample datasets of system stability margins corresponding to each output level and the output of each renewable energy power plant; and identifying renewable energy power plants that affect grid impedance stability based on the weights of each renewable energy power plant in the renewable energy power generation system. The technical solution provided by this invention identifies key renewable energy power plants affecting grid impedance stability based on the weight of the renewable energy power plants, which allows for more precise adjustment of the output levels and control characteristics of relevant renewable energy power plants, thereby reshaping their impedance characteristics, improving system stability, and reducing oscillation risks.

Description

Technical Field

[0001] This invention relates to the field of new energy grid connection, and specifically to a method and device for identifying new energy power plants that affect the stability of grid impedance. Background Technology In areas where new energy power generation is concentrated, the load is low or virtually nonexistent. Therefore, a radial power grid structure is mostly adopted. New energy power plants are connected to the end of the grid, and the voltage is gradually amplified through radial lines before being connected to the main grid. Under this connection method, the distance between the wind farms connected at the end and the main grid substation can be up to hundreds of kilometers, resulting in very low grid strength at the end. Therefore, under the current development model of new energy power generation, weak power grids have become a common problem. The complex control functions of numerous devices are intertwined with the characteristics of weak power grids, making the dynamic characteristics of the new energy base power grid extremely complex, with prominent oscillation and stability issues.

[0002] Currently, numerous factors influence system impedance stability and cause oscillations in areas with large-scale renewable energy aggregation. However, the primary factor is the coupling between the impedance of renewable energy power plants with different geographical locations and unit models and the grid impedance, which affects system impedance stability. With the network topology remaining constant in the aggregation area, different renewable energy power plants, due to their varying impedance characteristics, have different degrees of impact on system impedance stability. At the operational level, differences in their output levels also affect the system power flow distribution and alter their own impedance characteristics. In areas with insufficient impedance stability, changing the output level and control characteristics of renewable energy power plants can reduce the risk of oscillations. However, due to the large number of renewable energy power plants in aggregation areas, how to adjust the output of relevant renewable energy power plants to change the system impedance characteristics is unclear. Therefore, it is urgent to identify the renewable energy power plants that affect system stability. Summary of the Invention

[0003] To address the shortcomings of existing technologies, the present invention aims to provide a method and apparatus for identifying new energy power plants that affect grid impedance stability. By identifying key new energy power plants that affect grid impedance stability, the output level and control characteristics of relevant new energy power plants can be adjusted more accurately, thereby reshaping their impedance characteristics, improving system stability, and reducing oscillation risks.

[0004] The objective of this invention is achieved through the following technical solution: This invention provides a method for identifying new energy power plants that affect grid impedance stability, the improvement of which is that the method includes: Obtain sample datasets of system stability margins and power output of each new energy power generation station corresponding to each output level of the new energy power generation system. The weights of each new energy power station in the new energy power generation system are determined based on the system stability margin corresponding to each output level of the new energy power generation system and the sample dataset of the output of each new energy power station. Identify new energy power plants that affect grid impedance stability based on the weights of each new energy power plant in the new energy power generation system.

[0005] Preferably, the new energy power station consists of new energy generating units of the same model that are connected to the same 35kV feeder.

[0006] Preferably, the sample dataset includes the system stability margin corresponding to each output level of the new energy power generation system and the output of each new energy power station. The formula for calculation is:

[0007] In the above formula, , For new energy power generation systems in the first Sample data corresponding to each output level For new energy power generation systems in the first The output of the j-th renewable energy power station at each output level. For new energy power generation systems in the first The system stability margin corresponding to each output level This represents the total number of new energy power plants in the new energy power generation system. The total output level of new energy power generation systems.

[0008] Furthermore, the new energy power generation system in the first... The process of obtaining the system stability margin corresponding to each output level includes: Obtaining new energy power generation systems in the first Impedance values ​​of new energy power plants and grid impedance at each output level; Using the impedance numerical sequence of the new energy power station and the ratio of the grid impedance, a new energy power generation system is constructed in the first... Nyquist curves of the open-loop transfer function corresponding to each output level; According to the new energy power generation system in the The Nyquist curve of the open-loop transfer function corresponding to the output level determines the new energy power generation system at the . The system stability margin corresponding to each output level.

[0009] Furthermore, the new energy power generation system in the first... System stability margin at each output level The formula for calculation is:

[0010] In the above formula, For new energy power generation systems in the first The distance vector between a point on the Nyquist curve of the open-loop transfer function corresponding to a given output level and the point on the real axis (-1, 0).

[0011] Preferably, determining the weight of each new energy power station in the new energy power generation system based on the system stability margin corresponding to each output level of the new energy power generation system and the sample dataset of the output of each new energy power station includes: M random samplings with replacement are performed in the sample dataset to obtain each sample. At each sampling, the top Y samples are selected from the sequence of Euclidean distances between the remaining samples in the sample dataset and the sampled samples in ascending order as the nearest neighbors of the corresponding sampled samples. The intermediate weights of each new energy power station, the intermediate weights of the system stability margin, and the intermediate coupling weights between each new energy power station and the system stability margin are calculated based on each extracted sample and its corresponding nearest neighbor sample. The weights of each new energy power station in the new energy power generation system are calculated based on the intermediate weights of each new energy power station, the intermediate weights of the system stability margin, and the intermediate coupling weights between each new energy power station and the system stability margin.

[0012] Furthermore, the calculation of the intermediate weights of each new energy power station in the new energy power generation system, the intermediate weights of the system stability margin, and the intermediate coupling weights between each new energy power station and the system stability margin based on each extracted sample and its corresponding nearest neighbor sample includes: Calculate the initial weights of each new energy power station, the initial weights of the system stability margin, and the initial coupling weights between each new energy power station and the system stability margin based on each extracted sample and its corresponding nearest neighbor sample. The initial weights of each new energy power station, the initial weights of the system stability margin, and the initial coupling weights between each new energy power station and the system stability margin are respectively used as the intermediate weights of each new energy power station, the intermediate weights of the system stability margin, and the intermediate coupling weights between each new energy power station and the system stability margin in the new energy power generation system.

[0013] Furthermore, the calculation of the initial weights of each extracted sample, the initial weights of the system stability margin, and the initial coupling weights between each new energy power station and the system stability margin based on each extracted sample and its corresponding nearest neighbor sample includes: With the first The initial weights of each new energy power station corresponding to the sample obtained from the second sampling are used as the weights of the third sampling. The initial values ​​of each new energy power station corresponding to the sample obtained from the second sampling are calculated according to the iterative calculation formula for the initial values ​​of new energy power stations. The initial values ​​of each new energy power station in the sample obtained from the first sampling are iterated Y times to obtain the first... The initial weights of each new energy power station corresponding to the sample obtained from the second sampling; With the first The initial weights of the system stability margin corresponding to the samples obtained from the second sampling are used as the weights of the third sampling. The initial system stability margin corresponding to the sample obtained from the second sampling is used to calculate the system stability margin according to the iterative formula for the initial system stability margin. The initial value of the system stability margin obtained from the sample obtained in the first sampling is used to obtain the Yth iteration. The initial weights of the system stability margin corresponding to the sampled samples obtained from the second sampling; With the first The initial coupling weights of each new energy power station and the system stability margin corresponding to the sample obtained from the second sampling are used as the first... The initial values ​​of the coupling between each renewable energy power station and the system stability margin corresponding to the sampled samples obtained in the second sampling are used to calculate the initial values ​​of the renewable energy power station and the system stability margin according to the iterative calculation formula. The initial value of the system stability margin of the new energy power station obtained from the sampling in the first sampling is used to obtain the Y-th iteration to obtain the first... The initial coupling weights of each new energy power station and the system stability margin corresponding to the sample obtained by the second sampling; in, ,when At that time, the initial values ​​of the new energy power station, the initial value of the system stability margin, and the initial value of the coupling between the new energy power station and the system stability margin are all preset values.

[0014] Furthermore, the first The sample obtained from the second sampling is the first The initial values ​​of the first new energy power station were analyzed. The value at the next iteration The iterative calculation formula is shown below:

[0015] The first The initial value of the system stability margin obtained from the second sampling is used for the third sampling. The value at the next iteration The iterative calculation formula is shown below:

[0016] The first The j-th renewable energy power station in the sample obtained from the second sampling is compared with the initial value of the system stability margin. The value at the next iteration The iterative calculation formula is shown below:

[0017] In the above formula, For the first The sample obtained from the second sampling is the first The initial values ​​of the first new energy power station were analyzed. The result of the iteration , For the first The second sampling yielded the first sample. The first new energy power station and the first In the nearest neighbor sample, the first The difference in output between the two new energy power stations For the first The second sampling obtained the sample and the first Euclidean distance between nearest neighbor samples For the first The initial value of the system stability margin obtained from the second sampling is used for the third sampling. The result of the iteration For the first The system stability margin obtained from the second sampling is related to the first sampling. The difference in system stability margin among the nearest neighbor samples. For the first The initial values ​​of the stability margin of the new energy power stations and the system obtained from the second sampling are then used for the third sampling. The result of the next iteration.

[0018] Furthermore, in the aforementioned new energy power generation system, the first The weight of each new energy power station The calculation formula is as follows:

[0019] In the above formula, The first in the new energy power generation system The intermediate coupling weight between the new energy power station and the system stability margin As the intermediate weight for the system stability margin in new energy power generation systems, The first in the new energy power generation system The intermediate weight of each new energy power station.

[0020] Preferably, the step of identifying new energy power plants affecting grid impedance stability based on the weights of each new energy power plant in the new energy power generation system includes: If the weight of the new energy power station is less than the preset weight threshold, then the new energy power station has no impact on the stability of the power grid impedance. If the weight of a new energy power station is greater than or equal to a pre-set weight threshold, then the new energy power station with a weight greater than or equal to the pre-set weight threshold will be identified as a new energy power station that affects the stability of the power grid impedance.

[0021] Based on the same inventive concept, this invention provides a new energy power station identification device that affects the stability of power grid impedance. The improvement lies in that the device includes: The acquisition module is used to acquire the system stability margin corresponding to each output level of the new energy power generation system and the sample dataset of the output of each new energy power station; The determination module is used to determine the weight of each new energy power station in the new energy power generation system based on the system stability margin corresponding to each output level of the new energy power generation system and the sample dataset of the output of each new energy power station. The identification module is used to identify new energy power plants that affect the stability of the power grid impedance based on the weight of each new energy power plant in the new energy power generation system.

[0022] Compared with the closest existing technology, the present invention has the following advantages: This invention provides a method and apparatus for identifying renewable energy power plants that affect grid impedance stability. It acquires sample datasets of system stability margins corresponding to various output levels of the renewable energy power generation system and the output of each renewable energy power plant. Based on these sample datasets, it determines the weight of each renewable energy power plant in the system and identifies those plants that affect grid impedance stability. This invention's solution identifies key renewable energy power plants affecting grid impedance stability based on their weights, allowing for more precise adjustments to the output levels and control characteristics of relevant renewable energy power plants, thereby reshaping their impedance characteristics, improving system stability, and reducing oscillation risks. Attached Figure Description

[0023] Figure 1 This is a flowchart of a method for identifying new energy power plants that affect the stability of power grid impedance, provided by the present invention. Figure 2 This invention provides a method for identifying new energy power stations that affect grid impedance stability, which includes the Nyquist curve. Figure 3 This is a structural diagram of a new energy power station identification device that affects the stability of power grid impedance, provided by the present invention. Figure 4(a) is a diagram of the inverter grid-connected system in the equivalent circuit model composed of the impedance of the new energy device and the grid impedance in the embodiment provided by the present invention; Figure 4(b) is an equivalent small-signal circuit model diagram in the equivalent circuit model composed of the impedance of the new energy device and the grid impedance in the embodiment provided by the present invention; Figure 5 This is the small-signal transfer function model of the inverter grid-connected system in the embodiments provided by the present invention. Detailed Implementation

[0024] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] Example 1 This invention provides a method for identifying new energy power plants that affect grid impedance stability, such as... Figure 1 As shown, the method includes: Obtain sample datasets of system stability margins and power output of each new energy power generation station corresponding to each output level of the new energy power generation system. The weights of each new energy power station in the new energy power generation system are determined based on the system stability margin corresponding to each output level of the new energy power generation system and the sample dataset of the output of each new energy power station. Identify new energy power plants that affect grid impedance stability based on the weights of each new energy power plant in the new energy power generation system.

[0027] Specifically, the new energy power station consists of new energy generating units of the same model connected to the same 35kV feeder.

[0028] Specifically, the system stability margin corresponding to each output level of the new energy power generation system and the sample dataset of the output of each new energy power station. The formula for calculation is:

[0029] In the above formula, , For new energy power generation systems in the first Sample data corresponding to each output level For new energy power generation systems in the first The output of the j-th renewable energy power station at each output level. For new energy power generation systems in the first The system stability margin corresponding to each output level This represents the total number of new energy power plants in the new energy power generation system. The total output level of new energy power generation systems.

[0030] Furthermore, the new energy power generation system in the first... The process of obtaining the system stability margin corresponding to each output level includes: Obtaining new energy power generation systems in the first Impedance values ​​of new energy power plants and grid impedance at each output level; Using the impedance numerical sequence of the new energy power station and the ratio of the grid impedance, a new energy power generation system is constructed in the first... The Nyquist curves of the open-loop transfer function corresponding to each output level are shown below. Figure 2 As shown; According to the new energy power generation system in the The Nyquist curve of the open-loop transfer function corresponding to the output level determines the new energy power generation system at the . The system stability margin corresponding to each output level.

[0031] Furthermore, the new energy power generation system in the first... System stability margin at each output level The formula for calculation is:

[0032] In the above formula, For new energy power generation systems in the first The distance vector between a point on the Nyquist curve of the open-loop transfer function corresponding to a given output level and the point on the real axis (-1, 0).

[0033] Specifically, determining the weight of each new energy power station in the new energy power generation system based on the system stability margin corresponding to each output level of the new energy power generation system and the sample dataset of the output of each new energy power station includes: M random samplings with replacement are performed in the sample dataset to obtain each sample. At each sampling, the top Y samples are selected from the sequence of Euclidean distances between the remaining samples in the sample dataset and the sampled samples in ascending order as the nearest neighbors of the corresponding sampled samples. The intermediate weights of each new energy power station, the intermediate weights of the system stability margin, and the intermediate coupling weights between each new energy power station and the system stability margin are calculated based on each extracted sample and its corresponding nearest neighbor sample. The weights of each new energy power station in the new energy power generation system are calculated based on the intermediate weights of each new energy power station, the intermediate weights of the system stability margin, and the intermediate coupling weights between each new energy power station and the system stability margin.

[0034] Furthermore, the calculation of the intermediate weights of each new energy power station in the new energy power generation system, the intermediate weights of the system stability margin, and the intermediate coupling weights between each new energy power station and the system stability margin based on each extracted sample and its corresponding nearest neighbor sample includes: Calculate the initial weights of each new energy power station, the initial weights of the system stability margin, and the initial coupling weights between each new energy power station and the system stability margin based on each extracted sample and its corresponding nearest neighbor sample. The initial weights of each new energy power station, the initial weights of the system stability margin, and the initial coupling weights between each new energy power station and the system stability margin are respectively used as the intermediate weights of each new energy power station, the intermediate weights of the system stability margin, and the intermediate coupling weights between each new energy power station and the system stability margin in the new energy power generation system.

[0035] Furthermore, the calculation of the initial weights of each extracted sample, the initial weights of the system stability margin, and the initial coupling weights between each new energy power station and the system stability margin based on each extracted sample and its corresponding nearest neighbor sample includes: With the first The initial weights of each new energy power station corresponding to the sample obtained from the second sampling are used as the weights of the third sampling. The initial values ​​of each new energy power station corresponding to the sample obtained from the second sampling are calculated according to the iterative calculation formula for the initial values ​​of new energy power stations. The initial values ​​of each new energy power station in the sample obtained from the first sampling are iterated Y times to obtain the first... The initial weights of each new energy power station corresponding to the sample obtained from the second sampling; With the first The initial weights of the system stability margin corresponding to the samples obtained from the second sampling are used as the weights of the third sampling. The initial system stability margin corresponding to the sample obtained from the second sampling is used to calculate the system stability margin according to the iterative formula for the initial system stability margin. The initial value of the system stability margin obtained from the sample obtained in the first sampling is used to obtain the Yth iteration. The initial weights of the system stability margin corresponding to the sampled samples obtained from the second sampling; With the first The initial coupling weights of each new energy power station and the system stability margin corresponding to the sample obtained from the second sampling are used as the first... The initial values ​​of the coupling between each renewable energy power station and the system stability margin corresponding to the sampled samples obtained in the second sampling are used to calculate the initial values ​​of the renewable energy power station and the system stability margin according to the iterative calculation formula. The initial value of the system stability margin of the new energy power station obtained from the sampling in the first sampling is used to obtain the Y-th iteration to obtain the first... The initial coupling weights of each new energy power station and the system stability margin corresponding to the sample obtained by the second sampling; in, ,when At that time, the initial values ​​of the new energy power station, the initial value of the system stability margin, and the initial value of the coupling between the new energy power station and the system stability margin are all preset values.

[0036] Furthermore, the first The sample obtained from the second sampling is the first The initial values ​​of the first new energy power station were analyzed. The value at the next iteration The iterative calculation formula is shown below:

[0037] The first The initial value of the system stability margin obtained from the second sampling is used for the third sampling. The value at the next iteration The iterative calculation formula is shown below:

[0038] The first The j-th renewable energy power station in the sample obtained from the second sampling is compared with the initial value of the system stability margin. The value at the next iteration The iterative calculation formula is shown below:

[0039] In the above formula, For the first The sample obtained from the second sampling is the first The initial values ​​of the first new energy power station were analyzed. The result of the iteration , For the first The second sampling yielded the first sample. The first new energy power station and the first In the nearest neighbor sample, the first The difference in output between the two new energy power stations For the first The second sampling obtained the sample and the first Euclidean distance between nearest neighbor samples For the first The initial value of the system stability margin obtained from the second sampling is used for the third sampling. The result of the iteration For the first The system stability margin obtained from the second sampling is related to the first sampling. The difference in system stability margin among the nearest neighbor samples. For the first The initial values ​​of the stability margin of the new energy power stations and the system obtained from the second sampling are then used for the third sampling. The result of the next iteration.

[0040] Among them, the first in the new energy power generation system The weight of each new energy power station The calculation formula is as follows:

[0041] In the above formula, The first in the new energy power generation system The intermediate coupling weight between the new energy power station and the system stability margin As the intermediate weight for the system stability margin in new energy power generation systems, The first in the new energy power generation system The intermediate weight of each new energy power station.

[0042] Specifically, the step of identifying new energy power plants affecting grid impedance stability based on the weights of each new energy power plant in the new energy power generation system includes: If the weight of the new energy power station is less than the preset weight threshold, then the new energy power station has no impact on the stability of the power grid impedance. If the weight of a new energy power station is greater than or equal to a pre-set weight threshold, then the new energy power station with a weight greater than or equal to the pre-set weight threshold will be identified as a new energy power station that affects the stability of the power grid impedance.

[0043] Example 2 This invention provides a new energy power station identification device that affects the stability of power grid impedance, such as... Figure 3 As shown, the device includes: The acquisition module is used to acquire the system stability margin corresponding to each output level of the new energy power generation system and the sample dataset of the output of each new energy power station; The determination module is used to determine the weight of each new energy power station in the new energy power generation system based on the system stability margin corresponding to each output level of the new energy power generation system and the sample dataset of the output of each new energy power station. The identification module is used to identify new energy power plants that affect the stability of the power grid impedance based on the weight of each new energy power plant in the new energy power generation system.

[0044] Specifically, the new energy power station consists of new energy generating units of the same model connected to the same 35kV feeder.

[0045] Specifically, the system stability margin corresponding to each output level of the new energy power generation system and the sample dataset of the output of each new energy power station. The formula for calculation is:

[0046] In the above formula, , For new energy power generation systems in the first Sample data corresponding to each output level For new energy power generation systems in the first The output of the j-th renewable energy power station at each output level. For new energy power generation systems in the first The system stability margin corresponding to each output level This represents the total number of new energy power plants in the new energy power generation system. The total output level of new energy power generation systems.

[0047] Furthermore, the new energy power generation system in the first... The process of obtaining the system stability margin corresponding to each output level includes: Obtaining new energy power generation systems in the first Impedance values ​​of new energy power plants and grid impedance at each output level; Using the impedance numerical sequence of the new energy power station and the ratio of the grid impedance, a new energy power generation system is constructed in the first... Nyquist curves of the open-loop transfer function corresponding to each output level; According to the new energy power generation system in the The Nyquist curve of the open-loop transfer function corresponding to the output level determines the new energy power generation system at the . The system stability margin corresponding to each output level.

[0048] Furthermore, the new energy power generation system in the first... System stability margin at each output level The formula for calculation is:

[0049] In the above formula, For new energy power generation systems in the first The distance vector between a point on the Nyquist curve of the open-loop transfer function corresponding to a given output level and the point on the real axis (-1, 0).

[0050] Specifically, the determining module includes: The extraction unit is used to randomly draw M samples with replacement from the sample dataset to obtain each sample. At each extraction, the top Y samples are selected as the nearest neighbors of the corresponding sample from the sequence of Euclidean distances between the remaining samples in the sample dataset and the extracted samples in ascending order. The first calculation unit is used to calculate the intermediate weight of each new energy power station in the new energy power generation system, the intermediate weight of the system stability margin, and the intermediate coupling weight between each new energy power station and the system stability margin based on each extracted sample and its corresponding nearest neighbor sample. The second calculation unit is used to calculate the weight of each new energy power station in the new energy power generation system based on the intermediate weight of each new energy power station in the new energy power generation system, the intermediate weight of the system stability margin, and the intermediate coupling weight between each new energy power station and the system stability margin.

[0051] Furthermore, the first computing unit includes: The calculation submodule is used to calculate the initial weight of each new energy power station corresponding to each sample, the initial weight of the system stability margin, and the initial coupling weight between each new energy power station and the system stability margin based on each sample and its corresponding nearest neighbor sample. As a submodule, it is used to take the initial weights of each new energy power station, the initial weights of the system stability margin, and the initial coupling weights between each new energy power station and the system stability margin corresponding to the sample obtained from the Mth sampling as the intermediate weights of each new energy power station, the intermediate weights of the system stability margin, and the intermediate coupling weights between each new energy power station and the system stability margin in the new energy power generation system, respectively.

[0052] Furthermore, the computing submodule is specifically used for: With the first The initial weights of each new energy power station corresponding to the sample obtained from the second sampling are used as the weights of the third sampling. The initial values ​​of each new energy power station corresponding to the sample obtained from the second sampling are calculated according to the iterative calculation formula for the initial values ​​of new energy power stations. The initial values ​​of each new energy power station in the sample obtained from the first sampling are iterated Y times to obtain the first... The initial weights of each new energy power station corresponding to the sample obtained from the second sampling; With the first The initial weights of the system stability margin corresponding to the samples obtained from the second sampling are used as the weights of the third sampling. The initial system stability margin corresponding to the sample obtained from the second sampling is used to calculate the system stability margin according to the iterative formula for the initial system stability margin. The initial value of the system stability margin obtained from the sample obtained in the first sampling is used to obtain the Yth iteration. The initial weights of the system stability margin corresponding to the sampled samples obtained from the second sampling; With the first The initial coupling weights of each new energy power station and the system stability margin corresponding to the sample obtained from the second sampling are used as the first... The initial values ​​of the coupling between each renewable energy power station and the system stability margin corresponding to the sampled samples obtained in the second sampling are used to calculate the initial values ​​of the renewable energy power station and the system stability margin according to the iterative calculation formula. The initial value of the system stability margin of the new energy power station obtained from the sampling in the first sampling is used to obtain the Y-th iteration to obtain the first... The initial coupling weights of each new energy power station and the system stability margin corresponding to the sample obtained by the second sampling; in, ,when At that time, the initial values ​​of the new energy power station, the initial value of the system stability margin, and the initial value of the coupling between the new energy power station and the system stability margin are all preset values.

[0053] Furthermore, the first The sample obtained from the second sampling is the first The initial values ​​of the first new energy power station were analyzed. The value at the next iteration The iterative calculation formula is shown below:

[0054] The first The initial value of the system stability margin obtained from the second sampling is used for the third sampling. The value at the next iteration The iterative calculation formula is shown below:

[0055] The first The j-th renewable energy power station in the sample obtained from the second sampling is compared with the initial value of the system stability margin. The value at the next iteration The iterative calculation formula is shown below:

[0056] In the above formula, For the first The sample obtained from the second sampling is the first The initial values ​​of the first new energy power station were analyzed. The result of the iteration , For the first The second sampling yielded the first sample. The first new energy power station and the first In the nearest neighbor sample, the first The difference in output between the two new energy power stations For the first The second sampling obtained the sample and the first Euclidean distance between nearest neighbor samples For the first The initial value of the system stability margin obtained from the second sampling is used for the third sampling. The result of the iteration For the first The system stability margin obtained from the second sampling is related to the first sampling. The difference in system stability margin among the nearest neighbor samples. For the first The initial values ​​of the stability margin of the new energy power stations and the system obtained from the second sampling are then used for the third sampling. The result of the next iteration.

[0057] Furthermore, in the aforementioned new energy power generation system, the first The weight of each new energy power station The calculation formula is as follows:

[0058] In the above formula, The first in the new energy power generation system The intermediate coupling weight between the new energy power station and the system stability margin As the intermediate weight for the system stability margin in new energy power generation systems, The first in the new energy power generation system The intermediate weight of each new energy power station.

[0059] Specifically, the identification module is used for: If the weight of the new energy power station is less than the preset weight threshold, then the new energy power station has no impact on the stability of the power grid impedance. If the weight of a new energy power station is greater than or equal to a pre-set weight threshold, then the new energy power station with a weight greater than or equal to the pre-set weight threshold will be identified as a new energy power station that affects the stability of the power grid impedance.

[0060] Example 3 In areas where new energy power generation is concentrated, some places have low or almost no load. Therefore, a radial power grid structure is mostly adopted. New energy power plants are connected to the end of the grid, and the voltage is gradually increased through radial lines before being connected to the main grid. Under this connection method, the distance between the wind farms connected at the end and the main grid substation can be up to hundreds of kilometers, and the grid strength at the end is very low. Therefore, under the current development model of new energy power generation, weak power grids have become a common problem. The complex control functions of a large number of devices are intertwined with the characteristics of weak power grids, making the dynamic characteristics of the power grid in new energy bases extremely complex, and the problem of oscillation and stability is prominent.

[0061] Impedance analysis is an important method for analyzing and solving system oscillation stability problems. In recent years, impedance-based modeling and stability analysis of renewable energy grid-connected systems has become a hot topic in academia and industry. The basic idea is to describe the dynamic characteristics of a renewable energy power generation system as a frequency domain transfer function model with small-signal voltage disturbances and small-signal current responses as inputs and outputs, defined as the small-signal frequency domain impedance (or admittance) of the renewable energy power generation system. ,in For small-signal voltage disturbances in new energy grid-connected systems, To account for the small-signal current disturbance in the renewable energy grid-connected system, the renewable energy grid-connected system can be modeled as an equivalent circuit model composed of the impedance of the renewable energy device and the grid impedance. This equivalent model consists of the inverter grid-connected system shown in Figure 4(a) and the equivalent small-signal circuit model shown in Figure 4(b). Based on the equivalent circuit model, the small-signal model of the system can be described as the ratio of the grid impedance to the renewable energy impedance. For a single-input single-output closed-loop system with open-loop gain, such as Figure 5 As shown, where For grid impedance, For new energy impedance, This is a small-signal voltage disturbance in the power grid. Therefore, the stability of the system can be determined by the Nyquist criterion in classical control theory.

[0062] In areas with large-scale renewable energy aggregation, numerous factors influence system impedance stability. However, the primary factor is the coupling between the impedance of renewable energy power plants (based on different geographical locations and unit models) and the grid impedance, which affects system impedance stability. With the network topology remaining constant in the aggregation area, different renewable energy power plants, due to their varying impedance characteristics, have different degrees of impact on system impedance stability. At the operational level, differences in their output levels also affect the system power flow distribution and alter their own impedance characteristics. In areas with insufficient impedance stability, changing the output levels and control characteristics of renewable energy power plants can reduce oscillation risks. However, due to the large number of renewable energy power plants in aggregation areas, how to adjust the output of relevant power plants to change system impedance characteristics is unclear. It is necessary to prioritize the impact of renewable energy power plants on system stability, quantitatively identify the most influential power plants, and make precise adjustments to improve the control efficiency of renewable energy power plants.

[0063] Many scholars have studied impedance stability analysis methods for three-phase grid-connected inverters, but little work has been done on identifying key renewable energy power plants. Different renewable energy power plants contribute differently to system stability. By identifying renewable energy power plants whose output has a significant impact on impedance stability, more precise and effective control of these power plants can be implemented, output levels can be adjusted, oscillation risks reduced, and system stability improved. Therefore, this invention, based on the sensitivity analysis of the impact of different renewable energy power plant outputs on system impedance stability under the same renewable energy base network topology, uses the identification method provided by this invention to identify renewable energy power plants in a renewable energy power generation system, including the following steps: Step 1: Construct a variable set for new energy power plants in new energy power generation agglomeration areas, and determine the impedance sequence of different new energy power plants under different output levels; Step 2: Select the evaluation index for the stability margin of power grid impedance analysis; Step 3: Construct a sample set of variable data and corresponding impedance stability margins for energy power plants; Step 4: Train the sample set based on the sample training method, obtain the index weights of each new energy power station, and identify important new energy power stations.

[0064] Step 1 involves constructing a cluster of new energy power stations within the power grid of a new energy power generation base. These new energy power stations include wind farms and photovoltaic power stations. For new energy power stations with the same type of generating unit on the same 35kV feeder, they are merged to ultimately form a cluster with… N The set of variables for the Weixin Energy Power Station.

[0065] For each new energy power station with the same type of generator unit, obtain the impedance characteristic curve data of the station at different output levels. , This is a set of selected new energy power plant output levels, and its selection requirements cover the normal operating conditions of the new energy power plants. There are a total of [number missing]. Group output level.

[0066] At a certain output level Below, the impedance sequence curve is a sequence that varies with frequency. The impedance sequence of a new energy power station can be obtained by deriving an analytical expression or by measuring it through hardware-in-the-loop simulation. Analytical expression modeling requires knowledge of the detailed structure and parameters of the device control. Impedance scanning based on controller-in-the-loop simulation avoids the need for detailed control structure and parameters. The impedance sequence obtained by the scan is a characteristic curve composed of discrete frequency values, represented as follows: , This is a collection of impedance characteristic curves for new energy power stations that do not require power output. The frequency range for simulation scanning or actual measurement can be set as needed. f min , f max For inverters commonly used in new energy power generation, they can generally be set to [1Hz, 1000Hz]. That is, the power output level of the new energy power station is The impedance numerical sequence at that time, , i = 1,2,…, N O , That is, the power output level of the new energy power station is Below, the disturbance frequency is f i The impedance value at that time.

[0067] For different power output levels of new energy power plants, the power plant impedance will also be different, and the corresponding grid impedance will also change.

[0068] Step 2 involves selecting impedance stability margin evaluation indicators. Power grid impedance stability margin indicators are generally Bode plots or Nyquist gain margin and phase margin, both of which serve the same purpose in representing stability margin. To more accurately and comprehensively reflect the system stability margin, and to facilitate comparison of stability margins under different steady-state conditions, the following impedance stability margin evaluation indicators are selected.

[0069] Taking the outlet side of the new energy power station as the node to be analyzed, the grid impedance is... The impedance of the new energy power station is expressed as The stability of the interactive system depends on the ratio of the grid impedance to the impedance of the new energy power station. The Nyquist criterion is applied to analyze the stability of grid-connected systems, and an open-loop transfer function is constructed. G The Nyquist curve. The distance vector between a point on the Nyquist curve representing the ratio of the power output level of a new energy power generation system to its corresponding grid impedance and the point on the real axis (-1, j0) is: The minimum distance is used as the system stability margin index. That is: The stability margin evaluation index can quantitatively evaluate the impedance stability characteristics and stability margin of the system.

[0070] Step 3 involves constructing variable output data for energy stations and corresponding impedance stability margin sample sets.

[0071] The variable output data of the new energy power station can be randomly obtained based on the historical output of the new energy power station, or it can be sampled from the time-series output sequence of the new energy power station considering the time-series correlation through Monte Carlo sampling.

[0072] The corresponding impedance stability margin refers to the system stability margin index obtained by performing system impedance matching analysis based on the grid network topology of the new energy base, HVDC transmission lines, the status of thermal power units, and the output level of new energy power plants. .

[0073] The impedance matching analysis includes setting impedance analysis nodes, with a new energy power station on one side and an equivalent power grid on the other side. The broadband impedance of the power grid is calculated using the node impedance matrix. At the same time, the impedance sequence of the new energy power station is determined according to its output level. The Nyquist curve is obtained based on the ratio of the power grid impedance to the new energy power station impedance, and the stability margin is calculated.

[0074] Let the number of samples be The sample set refers to the set of data that represents the data. Group New Energy Power Station Output Level M Group impedance analysis yielded A stable margin, forming a stable margin A sample set of dimensions is represented as follows:

[0075] In the above formula, , For the first Sample data corresponding to each output level For the first The output of the j-th renewable energy power station in the output level, For the first The system stability margin corresponding to the output level of the new energy power generation system at each output level. This represents the total number of new energy power plants in the new energy power generation system. This represents the total number of samples in the sample dataset.

[0076] Step 4, which trains the sample set based on the sample training method to obtain the index weights of each new energy power station, refers to using a machine learning algorithm to train the sample set and obtain the weights of the variables of each new energy power station.

[0077] The machine algorithm sample training refers to processing and calculating the sample set using the RRelielF algorithm. Its input is the sample set. S The output is the weight of each new energy power station. The new energy power stations with different impacts on system stability are identified by sorting them according to their weights.

[0078] M random samplings with replacement are performed in the sample dataset to obtain each sample. At each sampling, the top Y samples are selected from the sequence of Euclidean distances between the remaining samples in the sample dataset and the sampled samples in ascending order as the nearest neighbors of the corresponding sampled samples. The intermediate weights of each new energy power station, the intermediate weights of the system stability margin, and the intermediate coupling weights between each new energy power station and the system stability margin are calculated based on each extracted sample and its corresponding nearest neighbor sample. The weights of each new energy power station in the new energy power generation system are calculated based on the intermediate weights of each new energy power station, the intermediate weights of the system stability margin, and the intermediate coupling weights between each new energy power station and the system stability margin.

[0079] Furthermore, the calculation of the intermediate weights of each new energy power station in the new energy power generation system, the intermediate weights of the system stability margin, and the intermediate coupling weights between each new energy power station and the system stability margin based on each extracted sample and its corresponding nearest neighbor sample includes: Calculate the initial weights of each new energy power station, the initial weights of the system stability margin, and the initial coupling weights between each new energy power station and the system stability margin based on each extracted sample and its corresponding nearest neighbor sample. The initial weights of each new energy power station, the initial weights of the system stability margin, and the initial coupling weights between each new energy power station and the system stability margin are respectively used as the intermediate weights of each new energy power station, the intermediate weights of the system stability margin, and the intermediate coupling weights between each new energy power station and the system stability margin in the new energy power generation system.

[0080] Furthermore, the calculation of the initial weights of each extracted sample, the initial weights of the system stability margin, and the initial coupling weights between each new energy power station and the system stability margin based on each extracted sample and its corresponding nearest neighbor sample includes: With the first The initial weights of each new energy power station corresponding to the sample obtained from the second sampling are used as the weights of the third sampling. The initial values ​​of each new energy power station corresponding to the sample obtained from the second sampling are calculated according to the iterative calculation formula for the initial values ​​of new energy power stations. The initial values ​​of each new energy power station in the sample obtained from the first sampling are iterated Y times to obtain the first... The initial weights of each new energy power station corresponding to the sample obtained from the second sampling; With the first The initial weights of the system stability margin corresponding to the samples obtained from the second sampling are used as the weights of the third sampling. The initial system stability margin corresponding to the sample obtained from the second sampling is used to calculate the system stability margin according to the iterative formula for the initial system stability margin. The initial value of the system stability margin obtained from the sample obtained in the first sampling is used to obtain the Yth iteration. The initial weights of the system stability margin corresponding to the sampled samples obtained from the second sampling; With the first The initial coupling weights of each new energy power station and the system stability margin corresponding to the sample obtained from the second sampling are used as the first... The initial values ​​of the coupling between each renewable energy power station and the system stability margin corresponding to the sampled samples obtained in the second sampling are used to calculate the initial values ​​of the renewable energy power station and the system stability margin according to the iterative calculation formula. The initial value of the system stability margin of the new energy power station obtained from the sampling in the first sampling is used to obtain the Y-th iteration to obtain the first... The initial coupling weights of each new energy power station and the system stability margin corresponding to the sample obtained by the second sampling; in, ,when At that time, the initial values ​​of the new energy power station, the initial value of the system stability margin, and the initial value of the coupling between the new energy power station and the system stability margin are all preset values.

[0081] Furthermore, the first The sample obtained from the second sampling is the first The initial values ​​of the first new energy power station were analyzed. The value at the next iteration The iterative calculation formula is shown below:

[0082] The first The initial value of the system stability margin obtained from the second sampling is used for the third sampling. The value at the next iteration The iterative calculation formula is shown below:

[0083] The first The j-th renewable energy power station in the sample obtained from the second sampling is compared with the initial value of the system stability margin. The value at the next iteration The iterative calculation formula is shown below:

[0084] In the above formula, For the first The sample obtained from the second sampling is the first The initial values ​​of the first new energy power station were analyzed. The result of the iteration , For the first The second sampling yielded the first sample. The first new energy power station and the first In the nearest neighbor sample, the first The difference in output between the two new energy power stations For the first The second sampling obtained the sample and the first Euclidean distance between nearest neighbor samples For the first The initial value of the system stability margin obtained from the second sampling is used for the third sampling. The result of the iteration For the first The system stability margin obtained from the second sampling is related to the first sampling. The difference in system stability margin among the nearest neighbor samples. For the first The initial values ​​of the stability margin of the new energy power stations and the system obtained from the second sampling are then used for the third sampling. The result of the next iteration; The above is the first The second sampling yielded the first sample. The first new energy power station and the first In the nearest neighbor sample, the first The difference in output of each new energy power station The calculation formula is as follows:

[0085] The first The system stability margin obtained from the second sampling is related to the first sampling. The difference in system stability margin among the nearest neighbor samples The calculation formula is as follows:

[0086] For the first The second sampling yielded the first sample. The output of each new energy power station No. The k-th nearest neighbor sample obtained from the second sampling is the k-th sample. The output of each new energy power station For the sample set The maximum output of each new energy power station For the sample set The minimum output of a new energy power station For the first The system stability margin corresponding to the sampled sample is obtained by the second sampling. For the first The system stability margin corresponding to the k-th nearest neighbor sample of the sampled sample is obtained by the second sampling. The maximum value of the system stability margin in the sample set. This represents the minimum stability margin of the system in the sample set.

[0087] Among them, the first in the new energy power generation system The weight of each new energy power station The calculation formula is as follows:

[0088] In the above formula, The first in the new energy power generation system The intermediate coupling weight between the new energy power station and the system stability margin As the intermediate weight for the system stability margin in new energy power generation systems, The first in the new energy power generation system The intermediate weight of each new energy power station.

[0089] Set variable weight thresholds For weights Variables below the threshold are removed, and new energy power stations with different impacts on system stability are identified by sorting them according to their weights.

[0090] By identifying the variables of new energy power plants that have a significant impact on system stability, the control of new energy power plants can be improved, thereby enhancing the impedance stability of new energy base grid connection.

[0091] This embodiment analyzes the new energy power stations in the Yandun area of ​​Hami, Xinjiang. This area is primarily characterized by wind power aggregation. Based on wind turbine models and geographical location, the wind farms are clustered into 19 new energy power stations. From 8760 sets of historical output data from these 19 power stations, 200 sets of output data are selected as the output sample for the new energy power stations. The weights of the new energy power stations are then determined, as shown in Table 1. Table 1 Sample Set

[0092] Based on the weights of each new energy power station obtained in Table 1, new energy power stations that have a significant impact on system stability are identified.

[0093] In summary, the identification method proposed in this invention analyzes the system impedance stability under different output levels of new energy power generation systems, obtains different impedance stability margins, calculates and ranks the weights of new energy power stations by analyzing sample data, and thus identifies key new energy power stations that have a significant impact on grid impedance stability. This method improves the scientific rigor and purposefulness of new energy power station control in terms of grid impedance stability, and helps grid operators more accurately identify weak links in system stability and carry out dispatch control.

[0094] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0095] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0096] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0097] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0098] Finally, 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 the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for identifying new energy power plants that affect grid impedance stability, characterized in that, The method includes: Obtain sample datasets of system stability margins and power output of each new energy power generation station corresponding to each output level of the new energy power generation system. The weights of each new energy power station in the new energy power generation system are determined based on the system stability margin corresponding to each output level of the new energy power generation system and the sample dataset of the output of each new energy power station. Identify new energy power plants that affect grid impedance stability based on the weight of each new energy power plant in the new energy power generation system; The system stability margin corresponding to each output level of the new energy power generation system and the sample dataset of the output of each new energy power station. The formula for calculation is: In the above formula, , For new energy power generation systems in the first Sample data corresponding to each output level For new energy power generation systems in the first The output of the j-th renewable energy power station at each output level. For new energy power generation systems in the first The system stability margin corresponding to each output level This represents the total number of new energy power plants in the new energy power generation system. The total output level of new energy power generation systems; The determination of the weights of each new energy power station in the new energy power generation system based on the system stability margin corresponding to each output level of the new energy power generation system and the sample dataset of the output of each new energy power station includes: M random samplings with replacement are performed in the sample dataset to obtain each sample. At each sampling, the top Y samples are selected from the sequence of Euclidean distances between the remaining samples in the sample dataset and the sampled samples in ascending order as the nearest neighbors of the corresponding sampled samples. The intermediate weights of each new energy power station, the intermediate weights of the system stability margin, and the intermediate coupling weights between each new energy power station and the system stability margin are calculated based on each extracted sample and its corresponding nearest neighbor sample. The weights of each new energy power station in the new energy power generation system are calculated based on the intermediate weights of each new energy power station, the intermediate weights of the system stability margin, and the intermediate coupling weights between each new energy power station and the system stability margin. The calculation of the intermediate weights of each new energy power station, the intermediate weights of the system stability margin, and the intermediate coupling weights between each new energy power station and the system stability margin based on each extracted sample and its corresponding nearest neighbor sample includes: Calculate the initial weights of each new energy power station, the initial weights of the system stability margin, and the initial coupling weights between each new energy power station and the system stability margin based on each extracted sample and its corresponding nearest neighbor sample. The initial weights of each new energy power station, the initial weights of the system stability margin, and the initial coupling weights between each new energy power station and the system stability margin are respectively used as the intermediate weights of each new energy power station, the intermediate weights of the system stability margin, and the intermediate coupling weights between each new energy power station and the system stability margin in the new energy power generation system.

2. The method as described in claim 1, characterized in that, The new energy power station consists of new energy generating units of the same model that are connected to the same 35kV feeder.

3. The method as described in claim 1, characterized in that, The new energy power generation system in the first The process of obtaining the system stability margin corresponding to each output level includes: Obtaining new energy power generation systems in the first Impedance values ​​of new energy power plants and grid impedance at each output level; Using the impedance numerical sequence of the new energy power station and the ratio of the grid impedance, a new energy power generation system is constructed in the first... Nyquist curves of the open-loop transfer function corresponding to each output level; According to the new energy power generation system in the The Nyquist curve of the open-loop transfer function corresponding to the output level determines the new energy power generation system at the . The system stability margin corresponding to each output level.

4. The method as described in claim 3, characterized in that, The new energy power generation system in the first System stability margin at each output level The formula for calculation is: In the above formula, For new energy power generation systems in the first The distance vector between a point on the Nyquist curve of the open-loop transfer function corresponding to a given output level and the point on the real axis (-1, 0).

5. The method as described in claim 1, characterized in that, The calculation of the initial weights of each extracted sample, the initial weights of the system stability margin, and the initial coupling weights between each extracted sample and its corresponding nearest neighbor sample for each new energy power station includes: With the first The initial weights of each new energy power station corresponding to the sample obtained from the second sampling are used as the weights of the third sampling. The initial values ​​of each new energy power station corresponding to the sample obtained from the second sampling are calculated according to the iterative calculation formula for the initial values ​​of new energy power stations. The initial values ​​of each new energy power station in the sample obtained from the first sampling are iterated Y times to obtain the first... The initial weights of each new energy power station corresponding to the sample obtained from the second sampling; With the first The initial weights of the system stability margin corresponding to the samples obtained from the second sampling are used as the weights of the third sampling. The initial system stability margin corresponding to the sample obtained from the second sampling is used to calculate the system stability margin according to the iterative formula for the initial system stability margin. The initial value of the system stability margin obtained from the sample obtained in the first sampling is used to obtain the Yth iteration. The initial weights of the system stability margin corresponding to the sampled samples obtained from the second sampling; With the first The initial coupling weights of each new energy power station and the system stability margin corresponding to the sample obtained from the second sampling are used as the first... The initial values ​​of the coupling between each renewable energy power station and the system stability margin corresponding to the sampled samples obtained in the second sampling are used to calculate the initial values ​​of the renewable energy power station and the system stability margin according to the iterative calculation formula. The initial value of the system stability margin of the new energy power station obtained from the sampling in the first sampling is used to obtain the Y-th iteration to obtain the first... The initial coupling weights of each new energy power station and the system stability margin corresponding to the sample obtained by the second sampling; in, ,when At that time, the initial values ​​of the new energy power station, the initial value of the system stability margin, and the initial value of the coupling between the new energy power station and the system stability margin are all preset values.

6. The method as described in claim 5, characterized in that, The first The sample obtained from the second sampling is the first The initial values ​​of the first new energy power station were analyzed. The value at the next iteration The iterative calculation formula is shown below: The first The initial value of the system stability margin obtained from the second sampling is used for the third sampling. The value at the next iteration The iterative calculation formula is shown below: The first The j-th renewable energy power station in the sample obtained from the second sampling is compared with the initial value of the system stability margin. The value at the next iteration The iterative calculation formula is shown below: In the above formula, For the first The sample obtained from the second sampling is the first The initial values ​​of the first new energy power station were analyzed. The result of the iteration , For the first The second sampling yielded the first sample. The first new energy power station and the first In the nearest neighbor sample, the first The difference in output between the two new energy power stations For the first The second sampling obtained the sample and the first Euclidean distance between nearest neighbor samples For the first The initial value of the system stability margin obtained from the second sampling is used for the third sampling. The result of the iteration For the first The system stability margin obtained from the second sampling is related to the first sampling. The difference in system stability margin among the nearest neighbor samples. For the first The initial values ​​of the stability margin of the new energy power stations and the system obtained from the second sampling are then used for the third sampling. The result of the next iteration.

7. The method as described in claim 1, characterized in that, The first in the new energy power generation system The weight of each new energy power station The calculation formula is as follows: In the above formula, The first in the new energy power generation system The intermediate coupling weight between the new energy power station and the system stability margin As the intermediate weight for the system stability margin in new energy power generation systems, The first in the new energy power generation system The intermediate weight of each new energy power station.

8. The method as described in claim 1, characterized in that, The method of identifying new energy power plants that affect grid impedance stability based on the weights of each new energy power plant in the new energy power generation system includes: If the weight of the new energy power station is less than the preset weight threshold, then the new energy power station has no impact on the stability of the power grid impedance. If the weight of a new energy power station is greater than or equal to a pre-set weight threshold, then the new energy power station with a weight greater than or equal to the pre-set weight threshold will be identified as a new energy power station that affects the stability of the power grid impedance.

9. A new energy power station identification device affecting grid impedance stability, used in the method described in claim 1, characterized in that, The device includes: The acquisition module is used to acquire the system stability margin corresponding to each output level of the new energy power generation system and the sample dataset of the output of each new energy power station; The determination module is used to determine the weight of each new energy power station in the new energy power generation system based on the system stability margin corresponding to each output level of the new energy power generation system and the sample dataset of the output of each new energy power station. The identification module is used to identify new energy power plants that affect the stability of the power grid impedance based on the weight of each new energy power plant in the new energy power generation system.

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