Hierarchical aggregation method and system for active regulation resources of power distribution network under time delay difference

Abstract

The application belongs to the technical field of power system operation and control, and provides a hierarchical aggregation method and system under the time delay difference of active regulation resources of a distribution network, acquires the topology and resource parameters of the distribution network, divides the resources into multiple response levels according to the physical response speed and time delay difference of various distributed resources; introduces a delay activation flag bit, constructs a resource dynamic active output model considering the total time delay and physical ramp rate of the resources, and determines the boundary of the dynamic active output; constructs an extreme value evaluation model of a specified level under a single time section, solves the active power extreme value at the point of common coupling under the satisfaction of set constraints; based on the double-layer nested optimization cycle of level-time, the discrete extreme value points are smoothly spliced in the time domain, and the hierarchical dynamic active power envelope line cluster of the distribution network is generated. The application realizes the mathematical decoupling of the resources under multiple time scales, and enhances the engineering practicability of the active power capacity evaluation of the distribution network in the real main-distribution coordination scene.

Description

Technical Field

[0001] This invention belongs to the field of power system operation and control technology, specifically relating to a hierarchical aggregation method and system for active power regulation resources under time delay differences in distribution networks. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] With the integration of massive amounts of distributed energy resources (DERs) such as photovoltaics, energy storage, electric vehicles, and flexible loads into the distribution network, the traditional passive distribution network with unidirectional power reception is gradually evolving into an active distribution network with bidirectional power flow interaction capabilities. Aggregating the dispersed and heterogeneous resources in the distribution network into an equivalent model with overall response capabilities and accurately assessing its dynamic active power support capacity at the point of common coupling (PCC) is of great significance for improving the frequency stability and operational security of high-proportion renewable energy power grids.

[0004] Currently, the power capacity aggregation assessment of distribution networks mainly relies on static polyhedral projection or steady-state optimal power flow methods. However, existing technologies have the following shortcomings in practical engineering applications: Traditional methods ignore the dynamic response delay differences of heterogeneous resources, assuming that all resources can respond synchronously and instantly upon receiving scheduling commands, without considering inverter control delay, communication delay, and the physical ramp-up rate of equipment. This leads to an overestimation of the actual frequency regulation or downregulation support capacity of the distribution network in a short timescale after the system frequency drops (such as within a few seconds after the main grid issues a command), thereby causing the main grid frequency regulation control to fail.

[0005] Without establishing a multi-timescale hierarchical evaluation mechanism based on physical response speed, traditional optimization models uniformly aggregate all fast and slow resources at the same time point without differentiation, which cannot truly reflect the tiered support capability of the distribution network for multi-timescale control needs. Summary of the Invention

[0006] To address the aforementioned issues, this invention proposes a hierarchical aggregation method and system for active power control resources in distribution networks under varying time delays. This invention can take into account both the dynamic time delay characteristics of resources and the hierarchical classification of physical response speeds, effectively overcoming the overestimation of capabilities caused by neglecting time delays in traditional static assessments. It accurately characterizes the dynamic physical processes of heterogeneous resources at different time scales, providing a decision-making benchmark for emergency dispatching of the main distribution system.

[0007] According to some embodiments, the present invention adopts the following technical solution: A hierarchical aggregation method for active power control resources in a distribution network under time delay differences includes the following steps: Obtain the distribution network topology and resource parameters, and divide the resources into multiple response levels based on the differences in physical response speed and latency of various distributed resources; By introducing a delayed activation flag, a dynamic active power output model for resources is constructed, taking into account the total delay of resource response and the physical ramp rate, and the boundary of dynamic active power output is determined. Construct an extreme value evaluation model for a specified level under a single time section, and solve for the active power extreme value at the common connection point under the given constraints. Based on a hierarchical-time double-nested optimization loop, discrete extreme points are smoothly spliced ​​in the time domain to generate a hierarchical dynamic functional capacity envelope cluster of the distribution network, which is then applied to the coordinated scheduling of main and distribution networks.

[0008] As an alternative implementation method, the process of obtaining the distribution network topology and resource parameters and dividing the resources into multiple response levels based on the differences in physical response speed and latency of various distributed resources includes: obtaining the network topology parameters of the distribution network, including the set of nodes, the set of branches, and the line impedance parameters of the distribution network; Based on the differences in control delay and communication delay between various distributed resource devices, and following the principle of response speed from fast to slow, all distributed resources with active power regulation capabilities in the distribution network are divided into multiple response time levels.

[0009] As an alternative implementation method, the process of dividing all distributed resources with active power regulation capabilities within the distribution network into multiple response time levels includes: The first-level resource set includes energy storage systems and direct-controlled photovoltaics; The second-level resource set includes flexible loads and electric vehicle clusters; The third-level resource set includes industrial interruptible loads and temperature-controlled load clusters.

[0010] As an alternative implementation, the process of introducing a delayed activation flag and constructing a dynamic active power output model for resources that takes into account the total resource response delay and physical ramp rate includes: The dynamic active power output model for resources is as follows: ; ; ; In the formula, , Representing nodes respectively i The upper limit and lower limit of the active power capacity of the resource; Represents a node i The initial state of the resources is active power output; , Represents a node i The active power of the resource's uphill and downhill ramp rates; Represents a node i Total communication and control latency of the above resources.

[0011] As an alternative implementation method, the process of constructing an extreme value evaluation model at a specified level under a single time section includes: For any given single response level At a given time cross-section t s Under this condition, define the continuous decision variable vector x( t s ), construct the objective function To determine the active power supplied by the distribution network to the main grid at the PCC point. To find the minimum or maximum value, a standard mathematical optimization model is established as follows: Regarding the goal of minimizing active power: ; ; In the formula, express t s Time Node i The active contribution of distributed resources express t s Time Node i Active load; For the goal of maximizing active power: .

[0012] As an alternative implementation, the constraints include: resource cascading unlocking based on a given level; for unlocked resources, their output satisfies the generated dynamic active power upper and lower limit constraints and their own apparent power constraints; for slow-response resources that are forcibly locked, their output is strictly constrained by an equation to the initial state; as well as power balance constraints and voltage safety constraints based on linearized power flow.

[0013] As an alternative implementation, the process of a hierarchical-time-based double-nested optimization loop includes: outer loop: starting the response level from a set value and gradually increasing it with a set step size, establishing a dedicated extreme point cache sequence for each determined response level, and then entering the inner loop; Inner loop: Under the current determined response level, extract the time series set, let the discrete time section start from the set value, and increase to the predetermined value with the set step size. Under the given time section, call the optimization solution model to calculate and record the minimum active power point and the maximum active power point at the current time and the current level.

[0014] As an alternative implementation method, before smoothly stitching discrete extreme points in the time domain to generate a hierarchical dynamic functional capacity envelope cluster of the distribution network, the method further includes: setting the total observation time window and discrete time step size for the distribution network to participate in the dynamic regulation of the main grid, discretizing the continuous observation time window, and constructing a set of discrete time series.

[0015] As an alternative implementation method, the process of smoothly splicing discrete extreme points in the time domain to generate a distribution network hierarchical dynamic functional capacity envelope cluster includes: after the inner loop has traversed the total observation time window, the inner loop of the current level ends, all discrete extreme points in the cache sequence are extracted, and they are smoothly spliced ​​along the time dimension to directly generate the down-adjustment envelope set and the up-adjustment envelope set under the response level.

[0016] A hierarchical aggregation system for active power control resources in a distribution network under time delay differences includes: The resource partitioning module is configured to acquire the distribution network topology and resource parameters, and divide the resources into multiple response levels based on the differences in physical response speed and latency of various distributed resources. The dynamic active power output construction module is configured to introduce a delay activation flag, construct a dynamic active power output model that takes into account the total resource response delay and physical ramp rate, and determine the boundary of dynamic active power output. The optimization model module is configured to construct an extreme value evaluation model at a specified level under a single time section, and solve for the active power extreme value at the common connection point under the given constraints. The double-layer nested optimization module is configured as a hierarchical-time-based double-layer nested optimization loop, which smoothly splices discrete extreme points in the time domain to generate a hierarchical dynamic functional capacity envelope cluster of the distribution network, and applies it to the main and distribution coordinated scheduling.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention innovatively proposes a distribution network functional capacity aggregation method based on a distributed resource delay response model and a hierarchical response speed classification. This transforms the traditional idealized static capacity assessment into a dynamic envelope calculation that takes into account the response delay of heterogeneous resources. Furthermore, the proposed cascade unlocking mechanism based on "response speed" achieves mathematical decoupling of resources across multiple time scales, objectively presenting the hierarchical dynamic adjustment limits of the distribution network at different time sections. This provides a capacity benchmark for multi-time-scale system control and enhances the engineering practicality of distribution network functional capacity assessment in real-world main-distribution coordination scenarios.

[0018] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0019] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0020] Figure 1 A general method block diagram of one embodiment Figure 2 This is a diagram of a power distribution network topology according to one embodiment; Figure 3 A schematic diagram illustrating the second-level dead zone and dynamic ramping characteristics of a power distribution network according to one embodiment; Figure 4 This is a schematic diagram of a hierarchical functional capacity envelope cluster of a distribution network across all time scales, as one embodiment. Detailed Implementation

[0021] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0022] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0023] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0024] Where there is no conflict, the embodiments and features described in this application may be combined with each other.

[0025] Example 1 A hierarchical aggregation method for active power control resources in a distribution network under time delay differences includes the following steps: Step 1: Obtain distribution network topology data and resource parameters, and classify resources according to resource response speed.

[0026] Network topology parameters of the distribution network, including the set of nodes in the distribution network, are obtained through the distribution network management system and wide-area measurement system. Branch road set and line impedance parameters.

[0027] Of course, in other embodiments, other topology or resource-related parameters can also be obtained.

[0028] Based on the differences in control and communication delays among various distributed resource devices, and following the principle of decreasing response speed, all distributed resources with active power regulation capabilities within the distribution network are divided into... L The response time level, denoted as the first l Level regulation resource set is .

[0029] For example, in this embodiment, it is divided into three levels ( L =3): Level 1 resource collection Energy storage systems, direct-control photovoltaic systems, etc. (response time is in the millisecond range, relying on power electronic inverters, without mechanical inertia, used for ultra-fast power support); Second-level resource collection Flexible loads and electric vehicle clusters, etc. (response time is around tens of seconds, with significant communication delay); Third-level resource collection Industrial interruptible loads, temperature-controlled load clusters, etc. (response time is in the minute range, involving long production buffers or uncertainties in user behavior, and is only used as a slow backup method in extreme emergency situations).

[0030] Step 2: Construct a distribution network resource active power output model that considers time delay. In this embodiment, a delayed activation flag is introduced to construct the aforementioned distributed resources at any time. t Dynamic active power output limit and the lower limit of dynamic active power output The parsing expression: (1) (2) (3) In the formula, , Representing nodes respectively i The upper limit and lower limit of the active power capacity of the resource; Represents a node i The initial state of the resources is active power output; , Represents a node i The active power of the resource's uphill and downhill ramp rates; Represents a node i Total communication and control latency of the above resources.

[0031] The physical meaning of this model is: when the time it takes for a distributed resource to receive a command from the main network is less than the total latency of the device, the resource cannot function. hour, Its actual output Still in the initial state After the latency period, the distributed resources gradually expand their dynamic adjustment range based on their ramp-up rate. hour, And ultimately, it is determined by the extreme value of its physical installed capacity ( , (This is subject to) restrictions.

[0032] Step 3: Functional capacity assessment model at a specified level under a single time section For any given single response level At a given time cross-section t s Under this condition, define the continuous decision variable vector x( t s ), construct the objective function To determine the active power supplied by the distribution network to the main grid at the PCC point. The minimum (to assess maximum down-adjustment capability) or maximum (to assess maximum up-adjustment capability) value is determined. A standard mathematical optimization model is established as follows: To minimize active power (reduce capacity): (4) (5) In the formula, express t s Time Node i The active contribution of distributed resources express t s Time Node i Active load.

[0033] For the goal of maximizing active power (increasing capacity): (6) To ensure the feasibility of the above optimization objectives in a real physical power distribution network, the optimization model must comply with the following constraints: 1) Based on a given level l s Resource cascading unlocking and dynamic boundary constraints At a given response level l s Next, unlock The fast-response resources within the set are used as decision variables, and the set is forcibly locked. Slow-response resources within the system are being depleted.

[0034] For unlocked resources, their output must satisfy the dynamic active power upper and lower limit constraints generated in step 2 and their own apparent power constraints: (7) (8) In the formula, , Representing nodes respectively i Resources in time cross-section t s The contributions made and the contributions made without merit, Represents a node i The upper limit of the apparent power capacity of the resource.

[0035] For slow-response resources that are forcibly locked, their output is strictly constrained by an equation to the initial state: (9) 2) Power balance constraints According to Kirchhoff's current law, for any node in a distribution network... i The sum of power flowing into a node and local generation power must equal the sum of power flowing out of the node and local load. Therefore, every node in the distribution network must satisfy the power balance constraint: (10) (11) In the formula, Indicates power flowing into the node i The set of all adjacent nodes, Indicates power from node i The set of all adjacent nodes that flow out. , They represent t s From the node i Flow to Node j Active power and reactive power, , They represent t s Time Node i The active and reactive loads.

[0036] 3) Voltage safety constraints based on linearized power flow Any connected branch in the distribution network ij The voltage drop equation must satisfy the linear power flow physical relationship: (12) In the formula, Represents a node i exist t s The square of the voltage amplitude at time . Represents a node j exist t s The square of the voltage amplitude at time . , branch road ij Resistance and reactance.

[0037] To ensure the physical safety of the distribution network operation, strict upper and lower limits are imposed on the voltage amplitude at each node: (13) In the formula, , Representing nodes respectively i The minimum and maximum permissible voltage amplitudes.

[0038] By solving the above model, which includes the objective function and various constraints, using a solver, we can obtain the... l s In high-level scenarios, t s Minimum active power at PCC point that strictly meets the safety operation constraints of the distribution network at all times and active power .

[0039] Step 4: Full-time window scanning and generation of functional envelope Using the evaluation model in step 3 as the core, the discrete static extreme points are extended into a continuous dynamic capability envelope in the time domain through a double-layer nested loop of "time section driving" and "response speed level driving".

[0040] 1) Parameter initialization and time-domain discretization Set the total observation time window for the distribution network to participate in the dynamic regulation of the main grid. and discrete time step Discretize the continuous observation time window to construct a discrete time series set. Its mathematical expression is: (14) In the formula, Represents all discrete-time cross-sections The resulting time series set, where n is the index of the time step at the current cross-section. N The total number of scan steps within the time window, and satisfying the following conditions: .

[0041] 2) "Hierarchical-Time" Double-Nest Optimization Loop and Curve Generation Outer loop (response speed level scan): Set the response level l s Starting from 1, gradually increase in step size of 1 until... l s =L. At each defined response level l s Next, establish a dedicated extreme point cache sequence for this level and enter the inner loop.

[0042] Inner loop (time-section scan): at the currently determined response level l s Next, extract the time series set. Let discrete time section Starting from 0 Incrementing step size to At a given time cross-section Next, call the optimization solution model from step 3 to calculate and record the minimum active power point at the current time and level. With maximum active power point ; Single-level active power envelope generation: When the inner loop has completed traversing the total observation time window Then, the current level l s The inner loop ends. Extract all discrete extreme points from the cache sequence, smoothly concatenate them along the time dimension, and directly generate the first... l s Set of downregulation envelopes under the first-level response level With the up-adjusted envelope set : (15) (16) Then, return to the outer loop to proceed to the next response level. l s +1, until all levels have been traversed, generating...L The distribution network hierarchical dynamic functional capacity envelope is composed of a set of curves.

[0043] Finally, the aforementioned hierarchical dynamic active power capacity envelope of the distribution network is output to the main grid coordinated dispatch system. The dynamic envelope at the lower response level represents the "rapid dynamic support limit" of the distribution network within an extremely short timescale; the dynamic envelope at the highest response level represents the "full steady-state regulation limit" after all heterogeneous resources have completely overcome physical dead zones and been activated over time. This provides main grid dispatchers with a high-fidelity, refined, and tiered calculation basis for the dynamic active power reserve capacity of the distribution network to cope with grid fault conditions across multiple timescales.

[0044] Specific implementation examples The method of this invention is verified using an IEEE 33-node distribution network as an example. The distributed resource parameters of the distribution network are shown in Table 1. Table 1 Distributed Resource Parameters

[0045] Figure 3 and Figure 4 This embodiment demonstrates the method's ability to accurately assess the "hierarchical" and "dynamic" capabilities of the distribution network. Regarding dynamic evolution, the envelope expands outward in a stepped manner over time, precisely characterizing the tiered response dead zones and physical ramp-up trajectories of energy storage, photovoltaics, electric vehicles, and flexible loads, avoiding the overestimation error of short-term support capabilities in traditional static assessments. In terms of hierarchy, three sets of envelopes with different response levels are nested from the inside out, clearly defining the capability evolution boundary from "rapid response" to "extreme fallback." This active support capability characterization based on the physical response speed of equipment achieves mathematical decoupling of adjustment resources across multiple time scales. This ensures that when the main grid faces emergency conditions, the dispatching end can accurately grasp the actual available backup resource potential at each time segment, providing a reliable, purely physical decision-making benchmark for main-distribution coordinated control, unaffected by external market rules.

[0046] Example 2 A hierarchical aggregation system for active power control resources in a distribution network under time delay differences includes: The resource partitioning module is configured to acquire the distribution network topology and resource parameters, and divide the resources into multiple response levels based on the differences in physical response speed and latency of various distributed resources. The dynamic active power output construction module is configured to introduce a delay activation flag, construct a dynamic active power output model that takes into account the total resource response delay and physical ramp rate, and determine the boundary of dynamic active power output. The optimization model module is configured to construct an extreme value evaluation model at a specified level under a single time section, and solve for the active power extreme value at the common connection point under the given constraints. The double-layer nested optimization module is configured as a hierarchical-time-based double-layer nested optimization loop, which smoothly splices discrete extreme points in the time domain to generate a hierarchical dynamic functional capacity envelope cluster of the distribution network, and applies it to the main and distribution coordinated scheduling.

[0047] 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 one or more computer-usable storage media (including, but not limited to, disk storage, etc.) containing computer-usable program code. CD - ROM It takes the form of a computer program product implemented on (such as optical memory, etc.).

[0048] 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.

[0049] 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.

[0050] 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.

[0051] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made by those skilled in the art without creative effort within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A hierarchical aggregation method for power distribution network active regulation resources under time delay difference, characterized in that, Includes the following steps: Obtain the distribution network topology and resource parameters, and divide the resources into multiple response levels based on the differences in physical response speed and latency of various distributed resources; By introducing a delayed activation flag, a dynamic active power output model for resources is constructed, taking into account the total delay of resource response and the physical ramp rate, and the boundary of dynamic active power output is determined. Construct an extreme value evaluation model for a specified level under a single time section, and solve for the active power extreme value at the common connection point under the given constraints. Based on a hierarchical-time double-nested optimization loop, discrete extreme points are smoothly spliced ​​in the time domain to generate a hierarchical dynamic functional capacity envelope cluster of the distribution network, which is then applied to the coordinated scheduling of main and distribution networks.

2. The hierarchical aggregation method for active power control resources in a distribution network under time delay differences as described in claim 1, characterized in that, The process of obtaining the distribution network topology and resource parameters, and dividing the resources into multiple response levels based on the differences in physical response speed and latency of various distributed resources, includes: obtaining the network topology parameters of the distribution network, including the set of nodes, the set of branches, and the line impedance parameters of the distribution network; Based on the differences in control delay and communication delay between various distributed resource devices, and following the principle of response speed from fast to slow, all distributed resources with active power regulation capabilities in the distribution network are divided into multiple response time levels.

3. The hierarchical aggregation method for active power control resources in a distribution network under time delay differences as described in claim 2, characterized in that, The process of dividing all distributed resources with active power regulation capabilities within a distribution network into multiple response time levels includes: The first-level resource set includes energy storage systems and direct-controlled photovoltaics; The second-level resource set includes flexible loads and electric vehicle clusters; The third-level resource set includes industrial interruptible loads and temperature-controlled load clusters.

4. The hierarchical aggregation method for active power control resources in a distribution network under time delay differences as described in claim 1, characterized in that it introduces... The process of delaying the activation flag and constructing a dynamic active power output model for resources that takes into account the total resource response delay and physical ramp rate includes: The dynamic active power output model for resources is as follows: ； ； ； In the formula, , Representing nodes respectively i The upper limit and lower limit of the active power capacity of the resource; Represents a node i The initial state of the resources is active power output; , Represents a node i The active power of the resource's uphill and downhill ramp rates; Represents a node i Total communication and control latency of the above resources.

5. The hierarchical aggregation method for active power control resources in a distribution network under time delay differences as described in claim 1, characterized in that, The process of constructing an extreme value evaluation model for a specified level at a single time section includes: for any given single response level At a given time cross-section t s Under this condition, define the continuous decision variable vector x( t s ), construct the objective function To determine the active power supplied by the distribution network to the main grid at the PCC point. To find the minimum or maximum value, a standard mathematical optimization model is established as follows: Regarding the goal of minimizing active power: ； ； In the formula, express t s Time Node i The active contribution of distributed resources express t s Time Node i Active load; For the goal of maximizing active power: 。 6. The hierarchical aggregation method for active power control resources in a distribution network under time delay differences as described in claim 1, characterized in that, The constraints include: resource cascading unlocking based on a given level; for unlocked resources, their output satisfies the generated dynamic active power upper and lower limit constraints and their own apparent power constraints; for slow-response resources that are forcibly locked, their output is strictly constrained by an equation to the initial state; as well as power balance constraints and voltage safety constraints based on linearized power flow.

7. The hierarchical aggregation method for active power control resources in a distribution network under time delay differences as described in claim 1, characterized in that, The process of the hierarchical-time nested optimization loop includes: outer loop: starting from the set value, the response level is gradually increased with a set step size. Under each determined response level, a unique extreme point cache sequence is established for that level, and then the inner loop is entered. Inner loop: Under the current determined response level, extract the time series set, let the discrete time section start from the set value, and increase to the predetermined value with the set step size. Under the given time section, call the optimization solution model to calculate and record the minimum active power point and the maximum active power point at the current time and the current level.

8. The hierarchical aggregation method for active power control resources in a distribution network under time delay differences as described in claim 1, characterized in that, Before smoothly stitching together discrete extreme points in the time domain to generate a hierarchical dynamic functional capacity envelope cluster for the distribution network, the process also includes: setting the total observation time window and discrete time step size for the distribution network to participate in the dynamic regulation of the main grid, discretizing the continuous observation time window, and constructing a set of discrete time series.

9. The hierarchical aggregation method for active power control resources in a distribution network under time delay differences as described in claim 1, characterized in that, The process of smoothly stitching discrete extreme points in the time domain to generate a hierarchical dynamic functional envelope cluster of the distribution network includes: after the inner loop has traversed the total observation time window, the inner loop of the current level ends, all discrete extreme points in the cache sequence are extracted, and they are smoothly stitched along the time dimension to directly generate the set of downward and upward envelopes under the response level.

10. A hierarchical aggregation system for active power control resources in a distribution network under time delay differences, characterized in that, include: The resource partitioning module is configured to acquire the distribution network topology and resource parameters, and divide the resources into multiple response levels based on the differences in physical response speed and latency of various distributed resources. The dynamic active power output construction module is configured to introduce a delay activation flag, construct a dynamic active power output model that takes into account the total resource response delay and physical ramp rate, and determine the boundary of dynamic active power output. The optimization model module is configured to construct an extreme value evaluation model at a specified level under a single time section, and solve for the active power extreme value at the common connection point under the given constraints. The double-layer nested optimization module is configured as a hierarchical-time-based double-layer nested optimization loop, which smoothly splices discrete extreme points in the time domain to generate a hierarchical dynamic functional capacity envelope cluster of the distribution network, and applies it to the main and distribution coordinated scheduling.

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