Virtual power plant declaration adjustable capacity checking method and device

Abstract

The invention relates to a virtual power plant declaration adjustable capacity checking method and device, and belongs to the technical field of virtual power plant adjustable capacity checking, and the method comprises the following steps: determining the distributed resource type of a virtual power plant, and covering a virtual generator set, an adjustable load and virtual energy storage; relevant load data are collected, and the load adjusting capacity of the adjustable load, the virtual energy storage and the virtual generator set is output respectively. And based on the load regulation capabilities, formulating constraint conditions for constraining the distributed resource regulation capacity of the virtual power plant. And constructing a target function with the maximum adjustment capacity sum as a target, and solving in combination with constraint conditions to obtain the adjustable capacity of the virtual power plant. And obtaining the declaration adjustable capacity of the virtual power plant, checking the declaration adjustable capacity by using the obtained adjustable capacity, and outputting a result. According to the invention, the flexibility of distributed resources is fully mined, various resources are managed in a unified manner, and flexible deployment under different working conditions is realized.

Description

Technical Field

[0001] The present invention relates to a method and device for checking the adjustable capacity declared by a virtual power plant, and belongs to the technical field of checking the adjustable capacity of a virtual power plant. Background Art

[0002] With the acceleration of energy transformation and the large-scale access of distributed energy resources, the virtual power plant, as a virtual entity that uniformly coordinates and controls distributed generation, demand-side response, and energy storage resources, has become increasingly important in the power system. By integrating distributed resources, the virtual power plant can flexibly participate in power market transactions and grid operation dispatching, provide power support and auxiliary services for the grid, and improve energy utilization efficiency and the reliability and stability of grid operation. During the operation of the virtual power plant, accurately checking its adjustable capacity is crucial. The adjustable capacity is directly related to the ability of the virtual power plant to participate in grid dispatching and market transactions, and determines its value and role in the power system. However, the adjustable capacity of the virtual power plant is affected by various factors, including the type, characteristics, operating status of distributed resources, and the coordination and cooperation among them.

[0003] The prior art, such as the Chinese patent application with the publication number CN119093497A, discloses a method, system, and related device for optimizing the operation of the capacity regulation of a virtual power plant. The method includes: constructing a mathematical model with the installed capacity and operating efficiency of resources as target variables, and the mathematical model aims to minimize the annual economic cost; determining the constraint conditions of the mathematical model, and the constraint conditions include energy balance constraints, upper and lower limits of resource installed capacity constraints, and resource interaction constraints; introducing the capacity constraints of source-storage resources to ensure sufficient energy storage capacity to balance energy fluctuations; constructing an interactive operation optimization model of the virtual power plant under resource capacity constraints; determining source-load resource interaction constraints and incentive-based demand response constraints; determining the optimal solution of the interactive operation optimization model of the virtual power plant based on the source-load resource interaction constraints and incentive-based demand response constraints, and verifying and optimizing the results. However, the above patent only introduces simple source-storage resource capacity constraints, that is, the total capacity of the energy storage system needs to be greater than or equal to the minimum energy storage capacity, and fails to fully consider various technical constraints and dynamic characteristics of energy storage resources in actual operation. In addition, the above patent does not separately evaluate the regulation capabilities of different types of distributed resources, but generally constructs a mathematical model with the installed capacity and operating efficiency of resources as target variables, lacking refined consideration of the regulation capabilities of each resource. Summary of the Invention

[0004] In order to solve the problems existing in the above prior art, the present invention proposes a method and device for checking the adjustable capacity declared by a virtual power plant.

[0005] The technical solution of the present invention is as follows: On the one hand, the present invention provides a method for verifying the adjustable capacity declaration of a virtual power plant, including the following steps: Determine the types of distributed resources of the virtual power plant, including virtual power generation units, adjustable loads, and virtual energy storage; Collect load-related data of the adjustable load, virtual energy storage, and virtual power generation unit, and respectively output the load regulation capabilities of the adjustable load, virtual energy storage, and virtual power generation unit; Based on the load regulation capabilities of each distributed resource, formulate the constraint conditions for the regulation capacity of each distributed resource in the virtual power plant; Construct an objective function with the goal of maximizing the sum of regulation capacities, and solve the objective function based on the constraint conditions to obtain the adjustable capacity of the virtual power plant; Obtain the declared adjustable capacity of the virtual power plant, verify the declared adjustable capacity based on the adjustable capacity of the virtual power plant, and output the verification result. Preferably, collect the load-related data of the adjustable load, extract the load characteristics of the load-related data of the adjustable load, construct an adjustable load vector based on the load characteristics, and use the adjustable load vector and the load-related data of the adjustable load as the input of the support vector regression model to output the load regulation capacity of the adjustable load.

[0006] Preferably, collect the load-related data of the virtual energy storage, extract the energy storage characteristics of the load-related data of the virtual energy storage, and use the energy storage characteristics as the input of the decision tree model to output the load regulation capacity of the virtual energy storage.

[0007] Preferably, collect the load-related data of the virtual power generation unit, including historical load, and perform linearization processing on the historical load; Decompose the linearly processed historical load into the adjustable load and non-adjustable load of the virtual power generation unit; For the adjustable load of the virtual power generation unit, use the adjustable load of the virtual power generation unit as the input of the autoregressive integrated moving average model to output the load regulation capacity of the virtual power generation unit.

[0008] Preferably, based on the load regulation capabilities of each distributed resource, formulate the constraint conditions for the regulation capacity of each distributed resource in the virtual power plant, which are expressed by the formula: ; ; In the formula, represents the constraint condition, represents the th regulation capacity of the th distributed resource of the th virtual power plant at the th moment, The load regulation capacity of the th distributed resource of the th virtual power plant at the th virtual power plant at the proportion of virtual energy storage that can be down-regulated at the th virtual power plant's th distributed resource at the binary variable indicating whether to regulate at the th virtual power plant at the maximum regulation rate at the th virtual power plant's maximum regulation duration, the th virtual power plant's th distributed resource at the regulation capacity at represents the regulation period, represents the virtual power plant index, represents the time index, represents the quantity index of the distributed resources.

[0009] Preferably, a target function is constructed with the goal of maximizing the sum of the regulation capacities, which is expressed by the formula: ; ; In the formula, represents the regulation period, represents the virtual power plant index, represents the time index, represents the maximum value function, the th virtual power plant's th distributed resource at the regulation capacity at represents the quantity index of the distributed resources.

[0010] Preferably, the declared adjustable capacity of the virtual power plant is obtained, and the declared adjustable capacity is verified based on the adjustable capacity of the virtual power plant, which is expressed by the formula: ; ; In the formula, represents the judgment operator, the th virtual power plant at Declared adjustable capacity at a moment Indicates the th virtual power plant's adjustable capacity at moment, Indicates the th virtual power plant's resource combination factor, Indicates the th virtual power plant's conservatism factor, Indicates The default option when the operation is not valid, Indicates the adjustment period, Indicates the virtual power plant index, Indicates the time index.

[0011] Preferably, the resource combination factor is expressed by the formula: ; In the formula, Indicates the distributed resource type index, Indicates the number of distributed resource types, Indicates the th virtual power plant's th type of distributed resource's load regulation ability and its proportion in the total load regulation ability of the th virtual power plant, Indicates the th virtual power plant's th type of distributed resource's uncertainty coefficient.

[0012] Preferably, the conservatism factor is expressed by the formula: ; ; In the formula, Indicates the conservatism adjustment coefficient, Indicates the historical declared deviation of the th virtual power plant.

[0013] On the other hand, the present invention also provides an electronic device with a computer program stored thereon. When the computer program is executed by a processor, it implements the virtual power plant declared adjustable capacity verification method as described in any embodiment of the present invention.

[0014] The present invention has the following beneficial effects: 1. By identifying distributed resources in the virtual power plant, such as virtual generating units, adjustable loads, and virtual energy storage, the present invention can comprehensively understand the resource composition of the virtual power plant, thereby managing various resources in a targeted manner and improving resource utilization efficiency.

[0015] 2. The present invention fully exploits the flexibility of distributed resources, incorporates adjustable loads, virtual energy storage, and virtual power generation units into unified management, enables the virtual power plant to flexibly allocate various resources under different operating conditions, enhances the response ability of the virtual power plant to the power system demand, and better adapts to the dynamic changes in the power market.

[0016] 3. By collecting load-related data of various distributed resources and using methods such as support vector regression models, decision tree models, and autoregressive integrated moving average models, the present invention respectively outputs the load regulation capabilities of adjustable loads, virtual energy storage, and virtual power generation units, realizing the accurate quantitative assessment of the regulation capabilities of each distributed resource in the virtual power plant, and providing an accurate basis for formulating subsequent regulation capacity constraint conditions and constructing the objective function.

[0017] 4. Based on the load regulation capabilities of each distributed resource, the present invention formulates constraint conditions and constructs an objective function with the goal of maximizing the sum of regulation capacities. By solving the objective function, the adjustable capacity of the virtual power plant is obtained, and then the declared adjustable capacity is verified, which can ensure that the declared adjustable capacity of the virtual power plant matches the actual regulation ability, improve the accuracy of the adjustable capacity of the virtual power plant, and avoid problems such as power supply-demand imbalance and unfair market transactions caused by overestimated or underestimated declared capacity.

[0018] 5. Through reasonable verification of the regulation capacity, the present invention ensures that the virtual power plant can stably provide power regulation services within the declared adjustable capacity range, avoids problems such as grid frequency fluctuations and voltage instability caused by insufficient regulation ability or false reporting of the virtual power plant, improves the overall stability and reliability of the power system, and plays a positive supporting role in the safe and stable operation of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a flowchart of the method implementation of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0021] It should be understood that the step numbers used in the text are only for convenient description and do not limit the execution order of the steps.

[0022] It should be understood that the terms used in the specification of the present invention are merely for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0023] The terms "comprising" and "including" indicate the presence of the described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or their combinations.

[0024] The term "and / or" refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0025] Embodiment 1: See Figure 1 , the present invention provides a method for checking the adjustable capacity declaration of a virtual power plant, including the following steps: Determine the types of distributed resources of the virtual power plant, including virtual power generation units, adjustable loads, and virtual energy storage; Among them, the virtual power generation unit refers to a distributed energy resource that simulates the behavior of a traditional power generation unit, including renewable energy power generation facilities such as solar photovoltaic and wind energy.

[0026] The adjustable load includes price-based transferable load and incentive-based interruptible load. Reasonable scheduling of the adjustable load is conducive to maximizing resource utilization. For the price-based transferable load, adjust the operation period according to high or low electricity prices, specifically including: 1. Transfer the load from high electricity price periods (such as daytime) to low electricity price periods (such as late at night); 2. When the power grid issues a peak electricity price warning, completely turn off or significantly reduce the interruptible load.

[0027] For the incentive-based interruptible load, when the reliability of the power grid system is affected or the electricity consumption reaches the peak, by sending an interruption instruction to power users, the grid load can be effectively reduced, achieving the effect of peak shaving and valley filling.

[0028] The virtual energy storage is not a physical energy storage device in the traditional sense (such as a battery, pumped storage, etc.), but an energy balance mechanism realized through intelligent management and optimization technologies. Its core lies in using the flexibility of demand-side resources (such as adjustable loads, virtual power generation units) to simulate the charging and discharging behavior of physical energy storage, thereby optimizing the energy flow of the power system and achieving goals such as peak shaving and valley filling and improving the utilization rate of renewable energy.

[0029] Collect the load-related data of adjustable loads, virtual energy storage, and virtual power generation units, and respectively output the load regulation capabilities of adjustable loads, virtual energy storage, and virtual power generation units; Based on the load regulation capabilities of various distributed resources, formulate the constraint conditions for the regulation capacities of various distributed resources in the virtual power plant; Construct an objective function with the goal of maximizing the sum of regulation capacities, and solve the objective function based on the constraint conditions to obtain the adjustable capacity of the virtual power plant; Obtain the declared adjustable capacity of the virtual power plant, verify the declared adjustable capacity based on the adjustable capacity of the virtual power plant, and output the verification result. In at least one embodiment, the objective function can be solved through mathematical calculations and the optimization solver in the simulation software Matlab.

[0030] Preferably, collect the load-related data of the adjustable load at time, extract the load characteristics of the load-related data of the adjustable load, construct an adjustable load vector based on the load characteristics, use the adjustable load vector and the load-related data of the adjustable load as the input of the support vector regression model, and output the load regulation capacity of the adjustable load, which is expressed by the formula: ; In the formula, represents the load regulation capacity of the adjustable load of the th virtual power plant at time, represents the adjustable load vector, represents the data index, represents the number of the load-related data of the adjustable load, represents the Lagrange multiplier corresponding to the relevant data of the th adjustable load, represents the kernel function, represents the relevant data of the th adjustable load, represents the offset.

[0031] In at least one embodiment, the kernel function is a linear kernel function. The similarity is obtained by calculating the inner product of the adjustable load vector and the load-related data of the adjustable load. The adjustable load vector is a one-dimensional vector arranged in the order of load characteristics. The load-related data of the adjustable load includes historical power consumption data, ambient temperature data, and time information data. The load characteristics include daily average temperature, maximum temperature, minimum temperature, time period index, date type index, load value at the same time period of the previous day, and load value at the same time period of the previous week. The load characteristics are extracted through the intelligent electricity meter acquisition system.

[0032] Preferably, collect the load-related data of the virtual energy storage at moment, extract the energy storage characteristics of the load-related data of the virtual energy storage, use the energy storage characteristics as the input of the decision tree model, and output the load regulation ability of the virtual energy storage, which is expressed by the formula: ; In the formula, represents the load regulation ability of the virtual energy storage of the th virtual power plant at moment, represents the prediction function of the decision tree model, represents the energy storage characteristics, represents the decision tree.

[0033] In at least one embodiment, the load-related data of the virtual energy storage includes charging session data, operation data, and time information, and the energy storage characteristics include time period characteristics, date type, historical load characteristics, and charging behavior characteristics.

[0034] Preferably, collect the load-related data of the virtual generator set, including historical load, and perform linearization processing on the historical load, which is expressed by the formula: ; In the formula, represents the historical load of the virtual generator set after linearization processing, , represent the linear optimization parameters, represents the historical load of the virtual generator set; Decompose the historical load after linearization processing into the adjustable load and the non-adjustable load of the virtual generator set; For the adjustable load of the virtual generator set, use the adjustable load of the virtual generator set as the input of the autoregressive integrated moving average model, and output the th virtual power plant's virtual generator set at moment's load regulation ability.

[0035] The historical load of the virtual generator set exhibits non-linear and multi-time scale coupling characteristics. The linearization processing transforms the non-linear load model into a linear equation set through Taylor expansion or piecewise linear approximation, significantly reducing the computational complexity.

[0036] In at least one embodiment, the decomposition method includes: 1. Divide the load of basic equipment such as production lines, safety systems, and lighting systems that must operate continuously into the non-adjustable load of the virtual generator set; 2. Divide the air conditioning system, non-critical production equipment, energy storage system, etc. into the adjustable load of the virtual generator set.

[0037] The non-adjustable load of the virtual generator set is not processed in this embodiment due to its non-adjustable nature.

[0038] Preferably, based on the load regulation capabilities of various distributed resources, constraint conditions for the regulation capacities of various distributed resources in the virtual power plant are formulated, which are expressed by the formula: ; ; In the formula, represents the constraint condition, represents the th distributed resource of the th virtual power plant at the th time, represents the load regulation capacity of the th th virtual power plant at the th time; represents the proportion of the virtual energy storage that can be down-regulated in the th virtual power plant at the th time; is 1 when it is regulated, is 0 when it is not regulated; represents the th th virtual power plant at the th th maximum regulation rate at the th time; represents the th th distributed resource of the th virtual power plant at the represents the virtual power plant index, represents the time index, represents the quantity index of the distributed resources.

[0039] In at least one embodiment, the types of distributed resources in the virtual power plant include 3 types: virtual generator sets, adjustable loads, and virtual energy storage. However, the number of distributed resources can be multiple. For example, 1 virtual power plant has 5 virtual generator sets, 3 adjustable loads, and 6 virtual energy storages. It can be obtained that has a maximum value of 14, but the number of distributed resource types In this embodiment, the value is 3.

[0040] At this time, if the value is 1 - 5, then it represents the load regulation capacity of the virtual generating unit of the th virtual power plant at the moment. If the value is 6 - 8, then it represents the load regulation capacity of the adjustable load of the th virtual power plant at the moment. If the value is 9 - 14, then it represents the load regulation capacity of the virtual energy storage of the th virtual power plant at the moment.

[0041] If is 1, it represents the virtual generating unit. If is 2, it represents the adjustable load. If is 3, it represents the virtual energy storage.

[0042] Preferably, a target function aiming to maximize the sum of regulation capacities is constructed, which is expressed by the formula: ; ; In the formula, represents the regulation period, represents the virtual power plant index, represents the time index, represents the maximum value function, represents the th distributed resource of the th virtual power plant at the moment, and

[0043] represents the number index of the distributed resource. ; ; In the formula, represents the judgment operator for judging whether holds, represents the declared adjustable capacity of the th virtual power plant at the moment, and represents the th virtual power plant at the Adjustable capacity of the virtual power plant at a moment Indicates the resource combination factor of the th virtual power plant Conservatism factor of the Indicates default option when the operation is not valid Indicates the adjustment period Indicates the virtual power plant index Indicates the time index

[0044] Preferably, the resource combination factor is expressed by the formula: ; In the formula, Indicates the distributed resource type index Indicates the number of distributed resource types Indicates the th virtual power plant's th type of distributed resource's load regulation capacity and its proportion in the total load regulation capacity of the th virtual power plant Indicates the th virtual power plant's th type of distributed resource's uncertainty coefficient

[0045] The total load regulation capacity of the th virtual power plant is the sum of the load regulation capacities of all distributed resources of the th virtual power plant. In this embodiment, it is the sum of the load regulation capacities of 14 distributed resources; The th virtual power plant's th type of distributed resource's load regulation capacity sum is, if is 1, it indicates a virtual generating unit, that is, the sum of the load regulation capacities of 5 distributed resources with the distributed resource type of virtual generating unit

[0046] Preferably, the conservatism factor is expressed by the formula: ; ; In the formula, Indicates the conservatism adjustment coefficient Indicates the th virtual power plant's historical declared deviation

[0047] Implementation scenario: The load-related data of three types of distributed resources in the area are collected in real time through a Distributed Energy Resource Management System (DERMS). Based on the load-related data, predictions are made to obtain the adjustable capabilities of each distributed resource at each moment: Adjustable load adjustable capacity: 285 MW; Virtual energy storage adjustable capacity: 165 MW; Virtual generator set adjustable capacity: 320 MW; Considering multiple constraints such as the predicted power limit, participation in dispatching duration limit, and ramp rate limit of various distributed resources, the adjustable capabilities of distributed resources are aggregated and scheduled according to the objective function, and the adjustable capacity of the th virtual power plant at is obtained as 685 MW.

[0048] Before the virtual power plant participates in the electricity market or system dispatching, the th virtual power plant declares the declared adjustable capacity at as 580 MW. The declared adjustable capacity is checked for compliance according to the method described in the present invention to ensure that the declared value does not exceed the actually available regulation capacity. Expressed by the formula: ; ; Among them, for the resource combination factor, based on the resource composition of the virtual power plant, we set the following parameters: Table 1 Regulation capacity ratio table

[0049] Table 2 Uncertainty factor table

[0050] According to Table 1 and Table 2, the resource combination factor of the th virtual power plant is .

[0051] For the conservatism coefficient, based on the load-related data of the virtual power plant in the past 7 days, we statistically compared the declared capacity with the actual aggregated capacity, as shown in Table 3: Table 3 Relative deviation table

[0052] ; Considering the importance of the safe and stable operation of the power system, we set the conservatism adjustment coefficient as: ; Verification factor ; According to the obtained verification factor, its declared value of 580 MW < 685 * 0.97 * 0.94 = 624.583, and the verification result is normal.

[0053] Embodiment 2: This embodiment provides an electronic device on which a computer program is stored. When the computer program is executed by a processor, it implements the virtual power plant declared adjustable capacity verification method as described in any embodiment of the present invention.

[0054] In the embodiments of the present application, "at least one" means one or more, and "a plurality" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can represent the cases of A existing alone, A and B existing simultaneously, and B existing alone. Where A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects before and after. "At least one of the following" and its similar expressions refer to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, and c can represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c can be single or multiple.

[0055] Those of ordinary skill in the art can realize that the units and algorithm steps described in the embodiments disclosed herein can be implemented by a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0056] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0057] In several embodiments provided by the present application, if any function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present application. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs.

[0058] The above are only the embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be included in the patent protection scope of the present invention by the same token.

Claims

1. A method for verifying the adjustable capacity declaration of a virtual power plant, characterized in that, The steps include: Determine the types of distributed resources in the virtual power plant, including virtual generating units, adjustable loads, and virtual energy storage; collect the load-related data of each distributed resource, and for different types of distributed resources, use different single models to obtain the load regulation capabilities of the load-related data; based on the load regulation capabilities of each distributed resource, formulate the constraint conditions for the regulation capacities of each distributed resource in the virtual power plant; construct an objective function with the goal of maximizing the sum of regulation capacities, and solve the objective function based on the constraint conditions to obtain the adjustable capacity of the virtual power plant; obtain the declared adjustable capacity of the virtual power plant, check the declared adjustable capacity based on the adjustable capacity of the virtual power plant, and output the check result.

2. The virtual power plant declaration adjustable capacity verification method according to claim 1, wherein Collect the load-related data of the adjustable load, extract the load characteristics of the load-related data of the adjustable load, construct an adjustable load vector based on the load characteristics, and use the adjustable load vector and the load-related data of the adjustable load as the input of the support vector regression model to output the load regulation capacity of the adjustable load.

3. The virtual power plant declaration adjustable capacity verification method according to claim 1, wherein Collect the load-related data of the virtual energy storage, extract the energy storage characteristics of the load-related data of the virtual energy storage, and use the energy storage characteristics as the input of the decision tree model to output the load regulation capacity of the virtual energy storage.

4. The method for verifying the adjustable capacity declared by a virtual power plant according to claim 1, characterized in that, Collect the load-related data of the virtual generating unit, including historical load, and perform linearization processing on the historical load; Decompose the linearly processed historical load into the adjustable load and the non-adjustable load of the virtual generating unit; For the adjustable load of the virtual generating unit, use the adjustable load of the virtual generating unit as the input of the autoregressive integrated moving average model to output the load regulation capacity of the virtual generating unit.

5. The virtual power plant declaration adjustable capacity verification method according to claim 1, characterized in that Based on the load regulation capabilities of each distributed resource, formulate the constraint conditions for the regulation capacities of each distributed resource in the virtual power plant, which are expressed by the formula: ； ； In the formula, represents the constraints, Indicates Virtual power plant Distributed resources in The adjustment capacity at any time, Indicates Virtual power plant Distributed resources in Load regulation capability at all times, Indicates Virtual power plants in The proportion of virtual energy storage that can be reduced at the moment; Indicates Virtual power plant Distributed resources in A binary variable indicating whether the moment is adjusted. Indicates Virtual power plants in The maximum adjustment rate at the moment, Indicates The maximum adjustment time of a virtual power plant, Indicates Virtual power plant Distributed resources in The adjustment capacity at any time, Indicates the adjustment cycle, represents the virtual power plant index, Represents the time index, Indicates the quantity index of distributed resources.

6. The method for verifying the adjustable capacity declaration of a virtual power plant according to claim 1, wherein Construct an objective function with the goal of maximizing the sum of regulation capacities, which is expressed by the formula: ； ； In the formula, represents the regulation period, represents the virtual power plant index, represents the time index, represents the maximum value function, represents the th distributed resource of the th virtual power plant at the regulation capacity at the moment, and represents the quantity index of the distributed resources.

7. The virtual power plant declaration adjustable capacity verification method according to claim 1, characterized in that Obtain the declared adjustable capacity of the virtual power plant, check the declared adjustable capacity based on the adjustable capacity of the virtual power plant, which is expressed by the formula: ； ； In the formula, represents a judgment operator, represents the th declared adjustable capacity of the virtual power plant at time, represents the th adjustable capacity of the virtual power plant at time, represents the resource combination factor of the th virtual power plant, represents the conservatism factor of the th virtual power plant, represents the default option when the operation is not valid, represents the adjustment period, represents the virtual power plant index, represents the time index.

8. The virtual power plant declaration adjustable capacity verification method according to claim 7, wherein The resource combination factor is expressed by the formula: ； In the formula, represents the distributed resource type index, represents the quantity of distributed resource types, represents the th class of the load regulation capacity of distributed resources in the th virtual power plant and its proportion in the total load regulation capacity of the th virtual power plant, represents the th virtual power plant's uncertainty coefficient for the th class of distributed resources.

9. The virtual power plant declaration adjustable capacity verification method according to claim 7, characterized in that, The conservatism factor is expressed by the formula: ； ； In the formula, represents the conservatism adjustment coefficient, represents the historical declared deviation of the 10. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method for checking the declared adjustable capacity of the virtual power plant according to any one of claims 1 to 9.

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