A new energy power system frequency support capability quantitative evaluation method and system based on frequency band analysis

Abstract

The application discloses a new energy power system frequency support capacity quantitative evaluation method and system based on frequency band analysis. ∞ The application can accurately reveal the response difference and contribution of synchronous machines and wind-solar-storage power electronic interface power sources in each frequency band, and provides a unified and effective frequency domain analysis method for frequency modulation control design and frequency stability evaluation of the new energy power system.

Description

Technical Field

[0001] This invention belongs to the field of novel power system stability analysis, and in particular relates to a method and system for quantitatively evaluating the frequency support capability of new energy power systems based on frequency band analysis. It can be used for quantitative analysis of the frequency support capability of hybrid systems containing power electronic interface power sources such as wind power, photovoltaic, and energy storage. Background Technology

[0002] With the high proportion of renewable energy sources such as wind and solar power integrated into the power system, the overall inertia level of the power system has decreased significantly, and the frequency dynamic characteristics exhibit complex features with multiple time scales and multiple node distributions. Traditional time-domain analysis methods typically rely on simulating the frequency trajectory after disturbances, but they are difficult to comprehensively reflect the stability of the system at different time scales. In particular, the power system uses a large number of power electronic devices, whose frequency responses vary significantly, making it difficult for traditional methods to accurately describe the supporting role of these devices in frequency fluctuations.

[0003] Existing literature has established frequency response equations for multi-machine systems based on synchronous machine models to analyze initial power distribution and inertia response characteristics. While such methods can characterize the dynamic differences in the early stages of a fault, they only cover a short time window from the start of the disturbance to the lowest frequency point, failing to reflect the overall frequency stability characteristics during the primary frequency modulation phase.

[0004] Furthermore, existing studies often unify the frequency regulation dynamics of all power generation equipment into a damping-governer-inertia model, failing to adequately consider the differences between heterogeneous power generation equipment. Grid-type converters provide inertia and damping support through droop control or virtual synchronous machine control, while grid-connected converters rely on phase-locked loops for frequency detection, resulting in a significant lag in their frequency response during transient phases. While time-domain simulations can demonstrate this difference, it is difficult to quantitatively analyze its contribution to the system's frequency support capability.

[0005] In contrast, frequency-domain-based system norm analysis methods can characterize the system's disturbance rejection performance from the perspective of input-output response. This is achieved by calculating H² / H... ∞ The norm quantifies a system's ability to absorb or suppress disturbance energy. However, traditional full-band norms cannot distinguish between inertial response and frequency dynamic characteristics during primary frequency regulation, making it difficult to reflect the system's true performance at different time scales. Therefore, this invention proposes a frequency support capability quantitative assessment method for new energy power systems based on frequency band analysis, achieving dynamic frequency quantification at different time scales. Summary of the Invention

[0006] To overcome the above shortcomings, this invention proposes a quantitative evaluation method and system for the frequency support capability of new energy power systems based on frequency band analysis. This method calculates the frequency response energy index within the target frequency band by frequency domain decomposition of the system's transfer function matrix, quantitatively characterizing the frequency support capability of the system's power generation equipment for the global or nodal levels in different frequency bands, thereby achieving quantitative analysis of frequency stability.

[0007] The technical solution of the present invention adopts the following steps:

[0008] A quantitative assessment method for the frequency support capability of a new energy power system based on frequency band analysis includes the following steps:

[0009] 1) Based on the parameter information of the wind, solar and energy storage power electronic interface power supply containing synchronous machines, grid-connected converters and grid-connected converters in the new energy power system, establish a frequency dynamic model;

[0010] 2) Combining the power system network topology and the power relationship between nodes, based on the frequency dynamic model, construct a multi-machine system transfer function matrix that can characterize the mapping relationship between input power disturbance and node frequency response;

[0011] 3) Select the system global or target node as the analysis object according to the evaluation requirements, and determine the corresponding dynamic transmission relationship;

[0012] 4) Set the target frequency range, and calculate the frequency band H2 / H of the analyzed object within the frequency range based on the transfer function matrix of the multi-machine system. ∞ Norm indices are used to characterize the system's frequency support capability against power disturbances;

[0013] 5) Perform capacity normalization and frequency normalization on the norm index to achieve comparative evaluation of frequency support capabilities between different devices and systems.

[0014] In the above technical solution, step 1) specifically involves performing small disturbance linearization processing on the oscillation equation of the synchronous machine, the virtual synchronous control equation of the grid-type converter, and the phase-locked loop dynamic equation of the grid-type converter near the steady-state operating point.

[0015] Further, step 2) specifically involves: combining the power system network topology and the power relationships between nodes, establishing a multi-machine system transfer function matrix to represent the mapping relationship between input power disturbances and node frequency responses, expressed as:

[0016]

[0017] Where s is the Laplace operator, ω0 is the angular frequency reference value, satisfying ω0=2πf0, and f0 is the reference frequency; Δω represents the angular frequency change of each node in the system, including the phase angle change vector Δω of each internal node of the synchronous machine, the grid-type converter, and the follow-me-to-the-grid converter. SG , Δω GFM , Δω GFL and the vector of angular frequency change of each non-internal node Δω NI ;ΔP L For power disturbance, ΔP LSG ΔP LGFM ΔP LGFL and ΔP LNI These are the corresponding power disturbance vectors for each node; H(s) represents the sum of the system network matrix and the device matrix, where H(s) = L(s) + G(s), where L(s) is the system network matrix, G(s) is the device dynamic matrix for synchronous machines, network-type converters, and grid-connected converters, N represents the total number of nodes in the system, and the matrix elements H ij (s) represents the dynamic transmission relationship between the power disturbance of node j and the angular frequency change of node i.

[0018] The system network matrix L(s) is derived from the node admittance matrix and network topology and is used to describe the power coupling relationship between nodes. The equipment dynamic matrix G(s) includes synchronous machine inertia and damping terms, virtual inertia and damping control terms for grid-type converters, and frequency response control terms for grid-connected converters. The parameters are obtained through equipment parameters, operating data, or simulation models.

[0019] Furthermore, in step 3), the system global or target node is selected as the analysis object based on the evaluation requirements, and the corresponding dynamic transmission relationship is determined. Specifically:

[0020] Let the selected analysis object be T(s). When the analysis object is a global indicator, T(s) = H(s); when the analysis object is a node indicator, T(s) = H i eq (s), H i eq (s) represents the equivalent dynamic channel of the angular frequency response of the i-th node to the disturbance input.

[0021] Further, in step 4), a target frequency range is set, and the frequency band H2 / H of the analyzed object within the frequency range is calculated based on the multi-machine system transfer function matrix. ∞ The norm index, which characterizes the system's frequency support capability to power disturbances, is calculated as follows:

[0022]

[0023] Where tr(*) represents the trace of the matrix * corresponding to the analysis object, and the superscript "H" indicates the conjugate transpose; (*) represents the maximum singular value of the matrix * corresponding to the object being analyzed, ω up and ω low These represent the upper and lower angular frequency boundaries of the selected frequency band, respectively. sup represents the supremum, and T(jω) represents the frequency response of the analyzed object T(s) at s=jω.

[0024] Furthermore, in step 5), the obtained frequency band norm is normalized for both capacity and frequency to achieve a unified evaluation of frequency support capabilities under different system scales and equipment configurations. The capacity normalization is based on the system's rated capacity, and the frequency normalization is based on the reference frequency, in order to eliminate the influence of different system scales and operating conditions.

[0025] For the frequency band H2 / H obtained in step 4) ∞ The norm index is further adjusted, resulting in the frequency band H2 / H. ∞ The formula for calculating the norm is as follows:

[0026]

[0027] in, This is the sum of active power disturbances under the system's baseline capacity. This is the system reference frequency.

[0028] Furthermore, in step 4), the frequency range is divided into low-frequency, mid-frequency, and high-frequency bands based on the dynamic characteristics of the power system frequency, wherein:

[0029] 1) Less than 0.1Hz: This is classified as a low-frequency band to characterize inertial support capability;

[0030] 2) 0.1Hz-10Hz: This is divided into the mid-frequency band to characterize primary frequency modulation capability;

[0031] 3) Greater than 10Hz: This is classified as a high-frequency band to characterize control response capability;

[0032] Calculate H2 / H in each frequency range. ∞ Norm indicators are used to achieve segmented quantitative assessment of frequency support capabilities under different dynamic mechanisms.

[0033] This invention also provides a quantitative evaluation system for the frequency support capability of new energy power systems based on frequency band analysis, comprising:

[0034] The frequency dynamic model construction module is used to establish a system frequency dynamic model based on the parameter information of the wind, solar and energy storage power electronic interface power supply composed of synchronous machines, grid-connected converters and grid-connected converters in the new energy power system.

[0035] The transfer function matrix construction module is used to construct a multi-machine system transfer function matrix that can characterize the mapping relationship between input power disturbance and node frequency response, based on the frequency dynamic model, by combining the power system network topology and the power relationship between nodes.

[0036] The analysis object selection module is used to select the system global or target node as the analysis object according to the evaluation requirements, and to determine the dynamic transmission relationship corresponding to the analysis object;

[0037] Frequency band H2 / H ∞ The norm calculation module is used to set a target frequency range and, based on the transfer function matrix of the multi-machine system, calculate the frequency band H2 / H of the analyzed object within the specified frequency range. ∞ Norm indices are used to characterize the system's frequency support capability against power disturbances;

[0038] The normalization module is used to normalize the obtained indicators in terms of capacity and frequency, enabling a comparison of frequency support capabilities between different devices and systems.

[0039] The present invention also provides an electronic device, comprising:

[0040] One or more processors;

[0041] Memory, used to store one or more programs;

[0042] When the one or more programs are executed by the one or more processors, the one or more processors perform the method as described in any of the preceding methods.

[0043] The present invention also provides a computer-readable storage medium storing computer-executable instructions, which, when executed, are used to implement the method described in any of the preceding claims.

[0044] The beneficial effects of this invention are:

[0045] This invention introduces the frequency norm index to quantify the frequency support capabilities of synchronous machines and various types of power electronic interface power supplies in different frequency bands within a unified framework, enabling multi-timescale analysis from inertial response to the entire process of primary frequency regulation. Compared with traditional time-domain simulation or full-band norm methods, this invention can not only distinguish the dynamic characteristics of the system in different frequency ranges, but also intuitively reflect the response strength of each node to disturbances and the overall disturbance rejection capability of the system, providing an effective quantitative tool for frequency regulation control parameter design and system stability analysis. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the process of the present invention;

[0047] Figure 2This invention provides an improved 4-machine 2-area system topology in a specific embodiment. Detailed Implementation

[0048] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0049] This invention relates to a method for quantitatively evaluating the frequency support capability of new energy power systems based on frequency band analysis. This method addresses the frequency response differences among various types of power generation equipment in new energy power systems by establishing a unified system frequency response model in the frequency domain and employing frequency band analysis to quantify the frequency support capability of power generation equipment in different frequency bands. For example... Figure 1 As shown, it includes the following steps:

[0050] 1) Establish a frequency dynamic model based on the parameter information of the wind, solar and energy storage power electronic interface power supply composed of synchronous machines, grid-connected converters and grid-connected converters in the new energy power system;

[0051] 2) Combining the power system network topology and the power relationship between nodes, based on the frequency dynamic model, construct a multi-machine system transfer function matrix that can characterize the mapping relationship between input power disturbance and node frequency response;

[0052] 3) Select the system global or target node as the analysis object according to the evaluation requirements, and determine the corresponding dynamic transmission relationship;

[0053] 4) Set the target frequency range, and calculate the frequency band H2 / H of the analyzed object within the frequency range based on the transfer function matrix of the multi-machine system. ∞ Norm indices are used to characterize the system's frequency support capability against power disturbances;

[0054] 5) Perform capacity normalization and frequency normalization on the norm index to achieve comparative evaluation of frequency support capabilities between different devices and systems.

[0055] This invention can accurately reveal the response differences and contributions of synchronous machines and wind-solar-storage power electronic interface power supplies in various frequency bands, providing a unified and effective frequency domain analysis method for frequency regulation control design and frequency stability assessment of new energy power systems. Specifically:

[0056] Step 1) specifically involves linearizing the oscillation equation of the synchronous machine, the virtual synchronous control equation of the grid-type converter, and the dynamic equation of the phase-locked loop of the grid-type converter near the steady-state operating point using small disturbances.

[0057] Step 2) specifically involves: combining the power system network topology and the power relationships between nodes, establishing a multi-machine system transfer function matrix to represent the mapping relationship between input power disturbances and node frequency responses, expressed as:

[0058]

[0059] Where s is the Laplace operator, ω0 is the angular frequency reference value, satisfying ω0=2πf0, and f0 is the reference frequency (50Hz or 60Hz); Δω represents the angular frequency change of each node in the system, including the phase angle change vector Δω of each internal node of the synchronous machine, grid-type converter, and mesh-type converter. SG , Δω GFM , Δω GFL and the vector of angular frequency change of each non-internal node Δω NI ;ΔP L For power disturbance, ΔP LSG ΔP LGFM ΔP LGFL and ΔP LNI These are the corresponding power disturbance vectors for each node; H(s) represents the sum of the system network matrix and the device matrix, where H(s) = L(s) + G(s), where L(s) is the system network matrix, G(s) is the device dynamic matrix for synchronous machines, network-type converters, and grid-connected converters, N represents the total number of nodes in the system, and the matrix elements H ij (s) represents the dynamic transmission relationship between the power disturbance of node j and the angular frequency change of node i. The system network matrix L(s) is derived from the node admittance matrix and network topology and is used to describe the power coupling relationship between nodes; the equipment dynamic matrix G(s) includes synchronous machine inertia and damping terms, virtual inertia and damping control terms for grid-type converters, and frequency response control terms for grid-connected converters. The parameters are obtained through equipment parameters, operating data, or simulation models.

[0060] Step 3) Selects the system global or target node as the analysis object based on the evaluation requirements, and determines the corresponding dynamic transmission relationship. Specifically:

[0061] Let the selected analysis object be T(s). When the analysis object is a global indicator, T(s) = H(s); when the analysis object is a node indicator, T(s) = H i eq (s), H i eq (s) represents the equivalent dynamic channel of the angular frequency response of the i-th node to the disturbance input.

[0062] Step 4) sets the target frequency range and calculates the frequency band H2 / H of the analyzed object within the frequency range based on the multi-machine system transfer function matrix. ∞ The norm index, which characterizes the system's frequency support capability to power disturbances, is calculated as follows:

[0063]

[0064] Where tr(*) represents the trace of the matrix * corresponding to the analysis object, and the superscript "H" indicates the conjugate transpose; (*) represents the maximum singular value of the matrix * corresponding to the object being analyzed, ω up and ω low These represent the upper and lower angular frequency boundaries of the selected frequency band, respectively. sup represents the supremum, and T(jω) represents the frequency response of the analyzed object T(s) at s=jω.

[0065] The frequency range is divided into low-frequency, mid-frequency, and high-frequency bands based on the dynamic characteristics of the power system frequency.

[0066] 1) Less than 0.1Hz: This is classified as a low-frequency band to characterize inertial support capability;

[0067] 2) 0.1Hz-10Hz: This is divided into the mid-frequency band to characterize primary frequency modulation capability;

[0068] 3) Greater than 10Hz: This is classified as a high-frequency band to characterize control response capability;

[0069] Calculate H2 / H in each frequency range. ∞ Norm indicators are used to achieve segmented quantitative assessment of frequency support capabilities under different dynamic mechanisms.

[0070] Step 5) involves normalizing the obtained indicators for capacity and frequency, and normalizing the obtained frequency band norm for capacity and frequency. This achieves a unified evaluation of frequency support capabilities under different system scales and equipment configurations. The capacity normalization is based on the system's rated capacity, and the frequency normalization is based on the reference frequency. This is done to eliminate the impact of different system sizes and operating conditions, namely:

[0071] For the frequency band H2 / H obtained in step 4) ∞ The norm index is further adjusted, resulting in the frequency band H2 / H. ∞ The formula for calculating the norm is as follows:

[0072]

[0073] in, This is the sum of active power disturbances under the system's baseline capacity. This is the system reference frequency.

[0074] This invention introduces the frequency norm index, enabling the quantification of the frequency support capabilities of synchronous machines and various types of power electronic interface power supplies across different frequency bands within a unified framework. This allows for multi-timescale analysis from inertial response to the entire process of primary frequency regulation. Compared to traditional time-domain simulation or full-band norm methods, this invention not only distinguishes the dynamic characteristics of the system within different frequency ranges but also intuitively reflects the response strength of each node to disturbances and the overall system's anti-disturbance capability, providing an effective quantitative tool for frequency regulation control parameter design and system stability analysis.

[0075] Specific embodiments of the present invention are as follows:

[0076] We use the method proposed in this invention to... Figure 2 The system shown is used for calculation. Experimental conditions are set at t=5 s, with a load step applied at node 11 as a power disturbance, satisfying ΔP. 11 L =0.15 pu, and ΔP for all other nodes j L =0 (j≠11), calculate the norm of the node where each power generation device is located. By comparing the results with those of traditional norm calculations, the method proposed in this invention can be verified.

[0077] The simulation calculations of the embodiments were performed using the method of the present invention, and the results are shown in Table 1:

[0078] Table 1 Comparison of H-norm calculation results in the 0.1Hz-10Hz frequency band

[0079]

[0080] First, Table 1 shows the results of the H-norm under the original definition ( and Regarding the traditional norm description, in the low-frequency range, the amplitude of the nodal spatiotemporal damping under a unit step disturbance is not zero (i.e., there is a deviation between the quasi-steady-state frequency trajectory and the rated frequency in the time domain), causing the traditional H2 norm to be unable to effectively characterize the nodal frequency response characteristics; in the high-frequency range, due to the infinite gain of the grid-connected converter, the traditional H2 norm is also unable to effectively characterize the nodal frequency response characteristics. ∞ The norm loses its representative meaning. In contrast, using the frequency band H-norm proposed in this invention for frequency domain feature quantification analysis, the index remains effective. The 0.1Hz-10Hz frequency band was selected, and the results are shown in Table 1. The frequency domain indices of each node differ significantly. Among them, the grid-type converter has the highest frequency band H2 norm, indicating weak inertia support capability and the worst overall frequency response characteristics in this frequency band; the grid-type converter's frequency band H2 norm... ∞ It has the lowest norm, strong anti-interference capability for this frequency band, and can clearly identify the system dynamic characteristics of each node in a specific frequency band.

[0081] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention 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.

[0082] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. 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 illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0083] 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.

[0084] 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.

[0085] The above specific embodiments are used to explain and illustrate the present invention, but not to limit the present invention. Any modifications and changes made to the present invention within the spirit and scope of the claims shall fall within the protection scope of the present invention.

Claims

1. A quantitative evaluation method for the frequency support capability of a new energy power system based on frequency band analysis, characterized in that, Includes the following steps: 1) Based on the parameter information of the wind, solar and energy storage power electronic interface power supply containing synchronous machines, grid-connected converters and grid-connected converters in the new energy power system, establish a frequency dynamic model; 2) Combining the power system network topology and the power relationship between nodes, based on the frequency dynamic model, construct a multi-machine system transfer function matrix that can characterize the mapping relationship between input power disturbance and node frequency response; 3) Select the system global or target node as the analysis object according to the evaluation requirements, and determine the corresponding dynamic transmission relationship; 4) Set the target frequency range, and calculate the frequency band H2 / H of the analyzed object within the frequency range based on the transfer function matrix of the multi-machine system. ∞ Norm indices are used to characterize the system's frequency support capability against power disturbances; 5) Perform capacity and frequency normalization on the aforementioned norm indices to enable comparative evaluation of frequency support capabilities among different devices and systems. Specifically: The capacity normalization is based on the system's rated capacity, and the frequency normalization is based on the reference frequency to eliminate the influence of different system sizes and operating conditions, i.e., the frequency band H2 / H obtained in step 4). ∞ Norm index , Further corrections were made, resulting in the corrected frequency band H2 / H. ∞ norm , The calculation formula is as follows: ， in, This is the sum of active power disturbances under the system's baseline capacity. This is the system reference frequency.

2. The method for quantitatively evaluating the frequency support capability of a new energy power system based on frequency band analysis according to claim 1, characterized in that, Step 1) specifically involves linearizing the oscillation equation of the synchronous machine, the virtual synchronous control equation of the grid-type converter, and the dynamic equation of the phase-locked loop of the grid-type converter near the steady-state operating point using small disturbances.

3. The method for quantitatively evaluating the frequency support capability of a new energy power system based on frequency band analysis according to claim 1, characterized in that, Step 2) specifically involves: combining the power system network topology and the power relationships between nodes, establishing a multi-machine system transfer function matrix to represent the mapping relationship between input power disturbances and node frequency responses, expressed as: ， Where s is the Laplace operator, ω0 is the angular frequency reference value, satisfying ω0=2πf0, and f0 is the reference frequency; Δω represents the angular frequency change of each node in the system, including the phase angle change vector Δω of each internal node of the synchronous machine, the grid-type converter, and the follow-me-to-the-grid converter. SG , Δω GFM , Δω GFL and the vector of angular frequency change of each non-internal node Δω NI ;ΔP L For power disturbance, ΔP LSG ΔP LGFM ΔP LGFL and ΔP LNI These are the power disturbance vectors corresponding to each node; H(s) represents the sum of the system network matrix and the device matrix, where H(s) = L(s) + G(s), where L(s) is the system network matrix, derived from the node admittance matrix and network topology, used to describe the power coupling relationship between nodes; G(s) is the device dynamic matrix for synchronous machines, grid-type converters, and grid-connected converters, including synchronous machine inertia and damping terms, grid-type converter virtual inertia and damping control terms, and grid-connected converter frequency response control terms, with parameters obtained from device parameters, operating data, or simulation models; N represents the total number of nodes in the system, and matrix elements H... ij (s) represents the dynamic transmission relationship between the power disturbance of node j and the angular frequency change of node i.

4. The method for quantitatively evaluating the frequency support capability of a new energy power system based on frequency band analysis according to claim 3, characterized in that, Step 3) Selects the system global or target node as the analysis object based on the evaluation requirements, and determines the corresponding dynamic transmission relationship. Specifically: Let the selected analysis object be T(s). When the analysis object is a global indicator, T(s) = H(s); when the analysis object is a node indicator, T(s) = H i eq (s), H i eq (s) represents the equivalent dynamic channel of the angular frequency response of the i-th node to the disturbance input.

5. The method for quantitatively evaluating the frequency support capability of a new energy power system based on frequency band analysis according to claim 4, characterized in that, Step 4) sets the target frequency range and calculates the frequency band H2 / H of the analyzed object within the frequency range based on the multi-machine system transfer function matrix. ∞ The norm index, which characterizes the system's frequency support capability to power disturbances, is calculated as follows: ， Where tr(*) represents the trace of the matrix * corresponding to the analysis object, and the superscript "H" indicates the conjugate transpose; (*) represents the maximum singular value of the matrix * corresponding to the object being analyzed, ω up and ω low These represent the upper and lower angular frequency boundaries of the selected frequency band, respectively. sup represents the supremum, and T(jω) represents the frequency response of the analyzed object T(s) at s=jω.

6. The method for quantitatively evaluating the frequency support capability of a new energy power system based on frequency band analysis according to claim 1, characterized in that, In step 4), the frequency range is divided into low-frequency, mid-frequency, and high-frequency bands based on the dynamic characteristics of the power system frequency, where: 1) Less than 0.1Hz: This is classified as a low-frequency band to characterize inertial support capability; 2) 0.1Hz-10Hz: This is divided into the mid-frequency band to characterize primary frequency modulation capability; 3) Greater than 10Hz: This is classified as a high-frequency band to characterize control response capability; Calculate H2 / H in each frequency range. ∞ Norm indicators are used to achieve segmented quantitative assessment of frequency support capabilities under different dynamic mechanisms.

7. A quantitative evaluation system for the frequency support capability of a new energy power system based on frequency band analysis, characterized in that, The system for implementing the method as described in any one of claims 1-6 comprises: The frequency dynamic model construction module is used to establish a system frequency dynamic model based on the parameter information of the wind, solar and energy storage power electronic interface power supply containing synchronous machines, grid-connected converters and grid-connected converters in the new energy power system. The transfer function matrix construction module is used to construct a multi-machine system transfer function matrix that can characterize the mapping relationship between input power disturbance and node frequency response, based on the frequency dynamic model, by combining the power system network topology and the power relationship between nodes. The analysis object selection module is used to select the system global or target node as the analysis object according to the evaluation requirements, and to determine the dynamic transmission relationship corresponding to the analysis object; Frequency band H2 / H ∞ The norm calculation module is used to set a target frequency range and, based on the transfer function matrix of the multi-machine system, calculate the frequency band H2 / H of the analyzed object within the specified frequency range. ∞ Norm indices are used to characterize the system's frequency support capability against power disturbances; The normalization module is used to normalize the obtained indicators in terms of capacity and frequency, enabling a comparison of frequency support capabilities between different devices and systems.

8. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-6.

9. A computer-readable storage medium storing computer-executable instructions, which, when executed, are used to implement the method of any one of claims 1 to 6.

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