Dynamic layered and partitioned frequency modulation control method

Abstract

According to the dynamic layered and partitioned frequency modulation control method, system inertia is evaluated by using real-time operation data of a power grid, N-1 fault analysis of the power grid is synchronously carried out, and the initial frequency change rate and the maximum frequency deviation value of 500kV and above nodes of the power grid under the N-1 fault are calculated; dynamic partitioning is performed according to the initial frequency change rate and the maximum frequency deviation value in combination with a power grid topological structure, a low-inertia weak frequency modulation region, a low-inertia strong frequency modulation region, a high-inertia weak frequency modulation region and a high-inertia strong frequency modulation region are divided, and the frequency adaptability, the transmission section transmission limit and the voltage level in the region are combined according to the partitioning result; a frequency modulation control structure of each area is divided into an upper global optimization layer and a lower local execution layer, differentiated frequency modulation parameters, optimization targets and execution objects are configured for different areas, the upper layer adopts MPC to optimize a secondary frequency modulation instruction, and the lower layer adopts a DMPC or PID controller to execute local unit power adjustment. The frequency stability and the large disturbance resistance of the whole system are improved, and the frequency collapse risk is suppressed.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid control, and in particular to a dynamic hierarchical and partitioned frequency modulation control method. Background Art

[0002] With the large-scale access of new energy to the power grid, the power system presents the characteristics of "low inertia and high fluctuation". The traditional power system frequency regulation control method faces severe challenges. The existing technology mainly has the following problems: the current power system does not carry out effective zoning frequency regulation, and cannot reflect the difference in inertia spatial distribution in real time. When a large disturbance occurs in the low inertia area, due to the setting of homogenized frequency regulation control parameters, the low inertia area cannot maximize the use of its own frequency regulation potential and cannot suppress its own frequency fluctuation, which in turn causes power oscillation to spread to the high inertia area, and eventually leads to system collapse; at the same time, the current secondary frequency regulation control level coordination efficiency is low, and the provincial power grid secondary frequency regulation system is First, the use of interconnection line power frequency deviation control cannot effectively suppress the system power oscillation caused by the current imbalance in source and load time and space distribution and the system power electronics; the parameter configuration and regional characteristics are mismatched, which aggravates the frequency oscillation risk; the frequency regulation functions at different time scales (inertia response, primary frequency regulation, secondary frequency regulation) cannot effectively coordinate with each other, and there is a reverse regulation situation; new frequency regulation resources (grid-type new energy, flexible direct current, energy storage / hybrid energy storage) cannot coordinate frequency regulation, which aggravates the system risk. In summary, the power system based on fixed topology partitioning and homogenized control parameters aggravates the frequency instability risk of the new power system. Summary of the Invention

[0003] In view of this, the present invention proposes a dynamic hierarchical and partitioned frequency regulation control method, which dynamically divides differentiated frequency regulation areas and constructs a hierarchical control architecture with an upper global optimization layer and a lower local execution layer to reduce the risk of frequency instability in the power system.

[0004] The technical solution of the present invention is achieved as follows: A dynamic hierarchical partition frequency modulation control method includes the following steps: Step S1: Collect real-time grid operation data to evaluate inertia and obtain equivalent inertia; Step S2: Conduct grid N-1 fault analysis and calculate the initial frequency change rate and maximum frequency deviation value of the grid 500 kV and above nodes under N-1 fault; Step S3: Dynamically partition the grid based on the equivalent inertia, the initial frequency change rate, and the maximum frequency deviation value in combination with the grid topology to obtain a plurality of regions; Step S4: combining frequency adaptability, transmission section transmission limit, and voltage level to divide the regional frequency modulation control structure into an upper global optimization layer and a lower local execution layer; Step S5: configuring differentiated parameters, optimization goals, and execution objects for different regions; Step S6: The upper global optimization layer uses centralized model predictive control to generate the regional total frequency modulation power demand instruction and the safety constraint set of key sections / nodes in the region to the lower local execution layer. The lower local execution layer uses distributed model predictive control or a coordinated controller with constrained optimization to coordinate the local execution units.

[0005] Preferably, the specific steps of step S1 include: Step S11: collecting real-time power grid operation data provided by a wide-area measurement system or an advanced measurement system; Step S12: Taking 500 kV and above nodes or stations as basic units, the equivalent inertia is calculated based on the generator rotor motion equation or system frequency response model using real-time grid operation data; Step S13: using a state estimation or data-driven method to improve the calculation accuracy of the equivalent inertia.

[0006] Preferably, the specific steps of step S2 include: using real-time topology and operating status, based on power system simulation software or online fast simulation module, simulating and calculating the dynamic response of all 500kV and above nodes in the power grid after N-1 breaking faults occur, and calculating the initial frequency change rate and maximum frequency deviation of the entire network under each fault scenario.

[0007] Preferably, the specific steps of step S3 include: Step S31: setting an inertia threshold and a frequency vulnerability threshold; Step S32: When the equivalent inertia is less than the inertia threshold, and the initial frequency change rate or the maximum frequency deviation value is greater than the frequency vulnerability threshold, the area is divided into a low inertia weak frequency modulation area; Step S33: when the equivalent inertia is less than the inertia threshold, and the initial frequency change rate and the maximum frequency deviation value are less than or equal to the frequency vulnerability threshold, the system is divided into a low-inertia and high-frequency region; Step S34: When the equivalent inertia is greater than or equal to the inertia threshold, and the initial frequency change rate or the maximum frequency deviation value is greater than the frequency vulnerability threshold, the area is divided into a high inertia weak frequency modulation area; Step S35: When the equivalent inertia is greater than or equal to the inertia threshold, and the initial frequency change rate and the maximum frequency deviation value are less than or equal to the frequency vulnerability threshold, the process is divided into a high-inertia and high-frequency region.

[0008] Preferably, the specific steps of step S4 include: utilizing the frequency adaptability of each region, complying with the transmission limit constraints of the transmission section, and achieving efficient decoupling based on the voltage level, and then dividing the regional frequency modulation control structure into an upper global optimization layer and a lower local execution layer.

[0009] Preferably, the specific steps of configuring differentiated parameters for different regions in step S5 include: Step S51: configuring a virtual inertia constant and damping coefficient in the low-inertia weak frequency modulation area that are higher than those in other areas; Step S52: reducing the dead zone and increasing the slope of the modulation coefficient in the low-inertia weak frequency modulation area and the low-inertia strong frequency modulation area, and using relatively conservative parameters in the high-inertia weak frequency modulation area and the high-inertia strong frequency modulation area; Step S53: In the upper global optimization layer, different objective function weights and constraint tightness are set.

[0010] Preferably, the specific steps of configuring differentiated optimization targets for different regions in step S5 include: Step S54: In the low-inertia weak frequency modulation area and the low-inertia strong frequency modulation area, the primary goal is to quickly suppress the frequency deviation of the regional center / key nodes and maximize the use of local fast frequency modulation resources to prevent the spread of frequency collapse. The secondary goal is to meet the regional power balance and tie line plan. Step S55: In the high-inertia weak frequency modulation area and the high-inertia strong frequency modulation area, under the premise of meeting the power balance and safety of the area, optimize the power instructions supporting the low-inertia area, with the goals of minimizing the frequency deviation of the entire system, controlling the power deviation of the tie line, and achieving economy.

[0011] Preferably, the specific steps of configuring differentiated execution objects for different regions in step S5 include: Step S56: In the low-inertia frequency modulation area, priority is given to calling grid-forming new energy and energy storage to provide inertia response and rapid support at the primary frequency modulation level; Step S57: In the low-inertia frequency-stressing area and the high-inertia frequency-modulation area, coordinate the deployment of energy storage, grid-forming new energy, and traditional units, focusing on the connection between primary frequency modulation and secondary frequency modulation; Step S58: In the high-inertia frequency-stressed area, the traditional units are responsible for secondary frequency regulation, and the new resources serve as supplement or backup.

[0012] Preferably, the upper global optimization layer establishes a prediction model including a regional frequency dynamic model, a unit / resource regulation characteristic model, and a power grid security constraint model. The input of the prediction model is the regional real-time frequency deviation, the interconnection line power deviation, the regional available frequency regulation capacity, the key section transmission margin, the voltage over-limit information, and the status feedback from the lower local execution layer. The output is the optimized regional total frequency regulation power demand instruction and the safety constraint set of the key sections / nodes in the region.

[0013] Preferably, the local execution units include traditional thermal / hydro power generating units, grid-connected new energy power stations, energy storage power stations, and flexible DC converter stations.

[0014] Compared with the prior art, the present invention has the following beneficial effects: ① By real-time sensing of grid inertia distribution and fault frequency vulnerability, precise dynamic zoning is performed, and frequency regulation parameters are configured differently in different areas, enabling low-inertia areas to maximize and release their frequency regulation potential; ② Build a layered architecture consisting of an upper global optimization layer and a lower local execution layer. The upper and lower layers form a closed loop through information exchange. The upper layer can set differentiated optimization goals based on the dynamic characteristics and security requirements of different regions, and optimize secondary frequency modulation instructions under multiple constraints. The lower layer realizes the rapid and accurate allocation and execution of instructions among heterogeneous resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only preferred embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0016] Figure 1 This is a flow chart of a dynamic hierarchical partition frequency modulation control method of the present invention; Figure 2 This is a flow chart of step S1 of a dynamic hierarchical partition frequency modulation control method of the present invention; Figure 3 This is a flow chart of step S3 of a dynamic hierarchical partitioned frequency modulation control method of the present invention; Figure 4 This is a flow chart of step S5 of a dynamic hierarchical partitioned frequency modulation control method of the present invention. DETAILED DESCRIPTION

[0017] In order to better understand the technical content of the present invention, a specific embodiment is provided below, and the present invention is further described in conjunction with the accompanying drawings.

[0018] See also Figures 1 to 4 The present invention provides a dynamic hierarchical partition frequency modulation control method, comprising the following steps: Step S1: Collect real-time grid operation data to evaluate inertia and obtain equivalent inertia. The specific steps include: Step S11: collecting real-time grid operation data provided by a wide-area measurement system or an advanced measurement system. The real-time grid operation data includes the speed / power of generators across the entire network, output of new energy sources, load, voltage / frequency at key nodes, network topology, and other data. Step S12: Taking 500 kV and above nodes or stations as basic units, the equivalent inertia is calculated based on the generator rotor motion equation or system frequency response model and using real-time grid operation data (such as generator output change rate and system frequency change rate); Step S13: Using state estimation or data-driven methods (Kalman filtering, machine learning) to improve the calculation accuracy of equivalent inertia.

[0019] Step S2: Conduct N-1 fault analysis of the power grid and calculate the initial frequency change rate and maximum frequency deviation value of the 500kV and above nodes of the power grid under N-1 fault. The specific steps include: using real-time topology and operating status, based on power system simulation software (BPA, PSASP, PSS / E) or online fast simulation module, simulate and calculate the dynamic response of all 500kV and above nodes of the power grid after N-1 breaking fault occurs, and calculate the initial frequency change rate and maximum frequency deviation of the entire network under each fault scenario, focusing on the first swing dynamics after the fault occurs. After calculating the equivalent inertia, the initial frequency change rate and maximum frequency deviation of the entire network, they can be used for dynamic partitioning.

[0020] Step S3: Dynamically partition the grid based on the equivalent inertia, the initial frequency change rate, and the maximum frequency deviation value in combination with the grid topology to obtain several regions. The specific steps include: Step S31: setting an inertia threshold and a frequency vulnerability threshold; Step S32: When the equivalent inertia is less than the inertia threshold, and the initial frequency change rate or the maximum frequency deviation value is greater than the frequency vulnerability threshold, the region is divided into a low inertia weak frequency modulation region (LLR). The low inertia weak frequency modulation region has low inertia and severe frequency deterioration after disturbance. Step S33: When the equivalent inertia is less than the inertia threshold, and the initial frequency change rate and the maximum frequency deviation are less than or equal to the frequency vulnerability threshold, the region is divided into a low inertia emphasis frequency region (LHR). The low inertia emphasis frequency region has low inertia but strong local frequency modulation capability or favorable topology. Step S34: When the equivalent inertia is greater than or equal to the inertia threshold, and the initial frequency change rate or the maximum frequency deviation value is greater than the frequency vulnerability threshold, the area is divided into a high-inertia weak FM area (HLR) and a low-inertia strong FM area with high inertia but local vulnerability due to topology or FM resource distribution; Step S35: When the equivalent inertia is greater than or equal to the inertia threshold, and the initial frequency change rate and the maximum frequency deviation value are less than or equal to the frequency vulnerability threshold, the region is divided into a high inertia emphasis frequency region (HHR). The high inertia emphasis frequency region has high inertia and strong anti-interference capability.

[0021] The partitioning logic is to compare the equivalent inertia, initial frequency change rate and maximum frequency deviation with the preset inertia threshold and frequency vulnerability threshold. The frequency vulnerability threshold includes the thresholds corresponding to the initial frequency change rate and maximum frequency deviation respectively. It can be divided into four areas according to the comparison results. The partitioning results are not fixed and will be updated periodically (such as several minutes) or event-triggered (such as after a large disturbance) with the grid operation mode, renewable energy output, load changes, network topology changes (planned maintenance or after a fault), spot trading cycle and the real-time evaluation results of steps S1 and S2.

[0022] Step S4: Combine the frequency adaptability, transmission section transmission limit and voltage level to divide the regional frequency modulation control structure into an upper global optimization layer and a lower local execution layer; the specific steps are: utilize the frequency adaptability of each region, comply with the transmission section transmission limit constraint, and achieve efficient decoupling based on the voltage level, and then divide the regional frequency modulation control structure into an upper global optimization layer and a lower local execution layer, wherein the frequency adaptability drives the differentiated parameter configuration of the control layer in different regions, the transmission section transmission limit constrains the action range of the local execution layer, and the voltage level difference determines the decoupling method of the upper and lower layers.

[0023] The upper global optimization layer is responsible for the centralized optimization calculation of regional secondary frequency modulation instructions, with a control cycle of seconds or minutes. The core technology is the use of centralized model predictive control (MPC). The lower local execution layer is responsible for receiving upper-layer instructions, quickly and accurately distributing them to various frequency modulation execution units (conventional power sources, new energy sources, energy storage, flexible direct current) in the region, and performing local closed-loop control. The control cycle is from milliseconds to seconds. Step S5: configuring differentiated parameters, optimization goals, and execution objects for different regions; The specific steps for configuring differentiated parameters for different regions include: Step S51: Setting virtual inertia constants and virtual coefficients that match the dynamic characteristics of the region in which they are located for the grid-forming new energy and virtual synchronous machines. For example, setting a higher virtual inertia constant and damping coefficient in the low-inertia and weak-frequency modulation region than in other regions can simulate a stronger "inertia wall" effect and suppress the initial frequency change rate. Step S52: Differentiate the primary frequency regulation deadband, differential regulation coefficient (R), and power limit for each type of unit / resource. For example, in low-inertia weak frequency regulation areas and low-inertia strong frequency regulation areas, the deadband is reduced and the differential regulation coefficient slope is increased. This makes local resources more sensitive to small frequency changes and has a larger action amplitude, fully unleashing the frequency regulation potential. In high-inertia weak frequency regulation areas and high-inertia strong frequency regulation areas, relatively conservative parameters are used, or flexible adjustments are made based on inter-regional support needs. Step S53: In the upper global optimization layer, different objective function weights and constraint tightness are set to achieve parameter differentiation.

[0024] The specific steps to configure differentiated optimization goals for different regions include: Step S54: In the low-inertia weak frequency modulation area and the low-inertia strong frequency modulation area, the primary goal is to quickly suppress frequency deviations at regional centers / key nodes, maximize the use of local fast frequency modulation resources (such as energy storage and grid-forming new energy) to prevent the spread of frequency collapse, and the secondary goal is to meet regional power balance and tie line planning. Step S55: In the high-inertia weak frequency modulation area and the high-inertia strong frequency modulation area, more emphasis is placed on inter-area power support coordination. While ensuring power balance and safety in the area, the power instructions supporting the low-inertia area are optimized. The goals include minimizing the frequency deviation of the entire system, controlling the power deviation of the tie line (TBC or AGC standard mode), and economic efficiency (taking into account the regulation cost).

[0025] The specific steps to configure differentiated execution objects for different regions include: Step S56: In low-inertia frequency modulation areas, prioritize and quickly call upon network-building new energy and energy storage (especially power-type) to provide inertia response and rapid support at the primary frequency modulation level. The local execution layer must have ultra-fast response capabilities. Step S57: In the low-inertia frequency-stressing area and the high-inertia frequency-stressing area, coordinate the deployment of energy storage (energy-type / hybrid), grid-forming new energy, and traditional units, focusing on the connection between primary frequency regulation and secondary frequency regulation; Step S58: In the high-inertia frequency-stressed area, the traditional units are responsible for secondary frequency regulation, and the new resources serve as supplement or backup.

[0026] By real-time sensing of the grid inertia distribution and fault frequency vulnerability, precise dynamic zoning is performed, and frequency regulation parameters (such as reducing dead zones, increasing the slope of the regulation coefficient, and enhancing virtual inertia) are differentially configured in different areas (especially low-inertia weak frequency regulation areas (LLRs)). This allows low-inertia areas to maximize and release their own frequency regulation potential (especially local fast-moving resources such as energy storage and grid-connected new energy).

[0027] A hierarchical architecture consisting of an upper global optimization layer and a lower local execution layer is constructed. The upper centralized MPC sets differentiated optimization goals based on the dynamic characteristics and safety requirements of different regions (e.g., prioritizing frequency maintenance in LLR areas and focusing on economic support in HHR areas), and optimizes secondary frequency regulation instructions under multiple constraints (sections, voltages, etc.); the lower distributed MPC / PID realizes the rapid and accurate allocation and execution of instructions among heterogeneous resources.

[0028] The layered architecture of an upper global optimization layer and a lower local execution layer naturally decouples control tasks at different timescales. The lower local execution layer focuses on the extremely fast response of local fast resources (such as energy storage and grid-connected converters) at extremely fast timescales (inertia response and primary frequency modulation), while the upper global optimization layer is responsible for centralized optimization and coordination at the second-to-minute scale (secondary frequency modulation). Through differentiated parameter configuration (such as prioritizing fast response for local resources in the LLR zone) and setting optimization targets, the inertia response, primary frequency modulation, and secondary frequency modulation are ensured to have consistent action directions, complementary forces, and coherent timing.

[0029] Step S6: The upper global optimization layer uses centralized model predictive control to generate the regional total frequency regulation power demand instruction and the safety constraint set of key sections / nodes in the region to the lower local execution layer. The lower local execution layer uses distributed model predictive control or a coordinated controller with constraint optimization to coordinate local execution units. The local execution units include traditional thermal / hydropower units, grid-type new energy power stations, energy storage power stations, and flexible DC converter stations.

[0030] Preferably, the upper global optimization layer establishes a prediction model including a regional frequency dynamic model, a unit / resource regulation characteristic model, and a power grid security constraint model (section power flow inequality constraints, voltage upper and lower limit constraints). The input of the prediction model is the regional real-time frequency deviation, the tie line power deviation, the regional available frequency regulation capacity (including traditional units, new energy, and energy storage status), the key section transmission margin, voltage limit information, and status feedback from the lower local execution layer. The output is the optimized regional total frequency regulation power demand instruction and the safety constraint set of the key sections / nodes in the region for reference by the lower layer. The coordination mechanism between the upper and lower layers is as follows: Upper global optimization layer: Directly consider the dynamic characteristics and costs of various types of resources in the optimization model to achieve economic-safety coordinated optimization across resource types.

[0031] Lower local execution layer: Optimal combination and allocation based on resource characteristics (e.g. energy storage takes the lead with the fastest response, while thermal power provides continuous support).

[0032] For scenarios that require coordination of multiple local execution units (such as multiple units / hybrid energy storage in a station), the lower-level local execution layer adopts distributed model predictive control (DMPC) or a coordinated controller with constraint optimization. On the premise of meeting the total frequency regulation power demand instructions of the upper-level domain and the safety constraint set of key sections / nodes in the region, it optimizes the allocation based on the dynamic characteristics of each unit (response speed, regulation cost, SOC status). For scenarios with a single local execution unit or requiring extremely fast response (such as a single energy storage or a grid-type converter), a high-performance PID controller or direct power control is used to achieve millisecond-level precise tracking.

[0033] Heterogeneous resources, including traditional turbines, grid-connected renewable energy, energy storage (hybrid storage), and flexible direct current (HVDC), are seamlessly integrated into a unified control framework. The upper-level global optimization layer comprehensively considers the dynamic characteristics and costs of each resource during optimization. The lower-level local execution layer optimizes resource allocation based on their characteristics (speed, cost, and status), such as rapid response from energy storage and continuous support from traditional turbines.

[0034] A dynamic hierarchical and partitioned frequency regulation control method of the present invention dynamically divides differentiated frequency regulation areas by real-time evaluation of the grid inertia distribution and fault frequency characteristics, and constructs a hierarchical control architecture of "upper global optimization layer + lower local execution layer". It can accurately match regional dynamic characteristics, differentially configure frequency regulation parameters, fully release the frequency regulation potential of low-inertia areas, and effectively suppress the spread of frequency fluctuations; eliminate multi-time scale frequency regulation conflicts through a hierarchical coordination mechanism, and significantly improve the coordination efficiency of secondary frequency regulation; seamlessly integrate heterogeneous resources such as grid-forming new energy and energy storage to participate in collaboration, synchronously embed grid safety constraints, and systematically enhance the frequency stability and anti-disturbance capability of high-proportion new energy power grids, thereby achieving rapid frequency recovery and safe and stable operation.

[0035] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A dynamic hierarchical partition frequency modulation control method, characterized in that: The following steps are involved: Step S1: Collect real-time grid operation data to perform inertia evaluation and obtain equivalent inertia; Step S2: Conduct grid N-1 fault analysis and calculate the initial frequency change rate and maximum frequency deviation value of the grid 500 kV and above nodes under N-1 fault; Step S3: Dynamically partition the grid based on the equivalent inertia, the initial frequency change rate, and the maximum frequency deviation value in combination with the grid topology to obtain a plurality of regions; Step S4: combining frequency adaptability, transmission section transmission limit, and voltage level to divide the regional frequency modulation control structure into an upper global optimization layer and a lower local execution layer; Step S5: configuring differentiated parameters, optimization goals, and execution objects for different regions; Step S6: The upper global optimization layer uses centralized model predictive control to generate the regional total frequency modulation power demand instruction and the safety constraint set of key sections / nodes in the region to the lower local execution layer. The lower local execution layer uses distributed model predictive control or a coordinated controller with constrained optimization to coordinate the local execution units.

2. A dynamic hierarchical partition frequency modulation control method according to claim 1, characterized in that: The specific steps of step S1 include: Step S11: collecting real-time power grid operation data provided by a wide-area measurement system or an advanced measurement system; Step S12: Taking 500 kV and above nodes or stations as basic units, the equivalent inertia is calculated based on the generator rotor motion equation or system frequency response model using real-time grid operation data; Step S13: using a state estimation or data-driven method to improve the calculation accuracy of the equivalent inertia.

3. The dynamic hierarchical partition frequency modulation control method according to claim 1, characterized in that: The specific steps of step S2 include: using real-time topology and operating status, based on power system simulation software or online fast simulation module, simulating and calculating the dynamic response of all 500kV and above nodes in the power grid after N-1 disconnection faults occur, and calculating the initial frequency change rate and maximum frequency deviation of the entire network under each fault scenario.

4. The dynamic hierarchical partition frequency modulation control method according to claim 1, characterized in that: The specific steps of step S3 include: Step S31: setting an inertia threshold and a frequency vulnerability threshold; Step S32: When the equivalent inertia is less than the inertia threshold, and the initial frequency change rate or the maximum frequency deviation value is greater than the frequency vulnerability threshold, the area is divided into a low inertia weak frequency modulation area; Step S33: when the equivalent inertia is less than the inertia threshold, and the initial frequency change rate and the maximum frequency deviation value are less than or equal to the frequency vulnerability threshold, the system is divided into a low-inertia and high-frequency region; Step S34: When the equivalent inertia is greater than or equal to the inertia threshold, and the initial frequency change rate or the maximum frequency deviation value is greater than the frequency vulnerability threshold, the area is divided into a high inertia weak frequency modulation area; Step S35: When the equivalent inertia is greater than or equal to the inertia threshold, and the initial frequency change rate and the maximum frequency deviation value are less than or equal to the frequency vulnerability threshold, the process is divided into a high-inertia and high-frequency region.

5. The dynamic hierarchical partition frequency modulation control method according to claim 1, characterized in that: The specific steps of step S4 are: utilizing the frequency adaptability of each region, complying with the transmission limit constraints of the transmission section, and achieving efficient decoupling based on the voltage level, and then dividing the regional frequency modulation control structure into an upper global optimization layer and a lower local execution layer.

6. The dynamic hierarchical and partitioned frequency modulation control method according to claim 4, characterized in that: The specific steps of configuring differentiated parameters for different regions in step S5 include: Step S51: configuring a virtual inertia constant and damping coefficient in the low-inertia weak frequency modulation area that are higher than those in other areas; Step S52: reducing the dead zone and increasing the slope of the modulation coefficient in the low-inertia weak frequency modulation area and the low-inertia strong frequency modulation area, and using relatively conservative parameters in the high-inertia weak frequency modulation area and the high-inertia strong frequency modulation area; Step S53: In the upper global optimization layer, different objective function weights and constraint tightness are set.

7. The dynamic hierarchical partition frequency modulation control method according to claim 4, characterized in that: The specific steps of configuring differentiated optimization targets for different regions in step S5 include: Step S54: In the low-inertia weak frequency modulation area and the low-inertia strong frequency modulation area, the primary goal is to quickly suppress the frequency deviation of the regional center / key nodes and maximize the use of local fast frequency modulation resources to prevent the spread of frequency collapse. The secondary goal is to meet the regional power balance and tie line plan. Step S55: In the high-inertia weak frequency modulation area and the high-inertia strong frequency modulation area, under the premise of meeting the power balance and safety of the area, optimize the power instructions supporting the low-inertia area, with the goals of minimizing the frequency deviation of the entire system, controlling the power deviation of the tie line, and achieving economy.

8. The dynamic hierarchical and partitioned frequency modulation control method according to claim 4, characterized in that: The specific steps of configuring differentiated execution objects for different regions in step S5 include: Step S56: In the low-inertia frequency modulation area, priority is given to calling grid-forming new energy and energy storage to provide inertia response and rapid support at the primary frequency modulation level; Step S57: In the low-inertia frequency-stressing area and the high-inertia frequency-modulation area, coordinate the deployment of energy storage, grid-forming new energy, and traditional units, focusing on the connection between primary frequency modulation and secondary frequency modulation; Step S58: In the high-inertia frequency-stressed area, the traditional units are responsible for secondary frequency regulation, and the new resources serve as supplement or backup.

9. The dynamic hierarchical partition frequency modulation control method according to claim 1, characterized in that: The upper global optimization layer establishes a prediction model that includes a regional frequency dynamic model, a unit / resource regulation characteristic model, and a power grid security constraint model. The input of the prediction model is the regional real-time frequency deviation, the tie line power deviation, the regional available frequency regulation capacity, the key section transmission margin, the voltage over-limit information, and the status feedback from the lower local execution layer. The output is the optimized regional total frequency regulation power demand instruction and the safety constraint set of the key sections / nodes in the region.

10. The dynamic hierarchical and partitioned frequency modulation control method according to claim 1, characterized in that: The local execution units include traditional thermal / hydro power generation units, grid-connected new energy power stations, energy storage power stations, and flexible DC converter stations.

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