A virtual power plant load regulation method, device and medium

Abstract

The present invention relates to a virtual power plant load regulation method, device and medium, belonging to the field of virtual power plant load regulation technology, comprising the following steps: obtaining load instruction data of the virtual power plant; determining the load resource scheduling cost, demand response capacity deviation penalty, and load response willingness and reliability equivalent cost of the virtual power plant based on the load instruction data; constructing a load instruction decomposition objective function of the virtual power plant with the goal of minimizing the load resource scheduling cost, demand response capacity deviation penalty, and load response willingness and reliability equivalent cost of the virtual power plant; formulating constraints corresponding to the load instruction decomposition, solving the load instruction decomposition objective function based on the constraints to obtain the load regulation instruction of the virtual power plant; and regulating the load of the virtual power plant according to the load regulation instruction. The present invention can achieve the goal of reducing the operating expenses of the virtual power plant while meeting the load demand.

Description

Technical Field

[0001] The present invention relates to a virtual power plant load regulation method, equipment and medium, and belongs to the technical field of virtual power plant load regulation. Background Art

[0002] With the energy transition and the development of smart grids, virtual power plants (VPPs), specialized power plants that integrate distributed energy resources and adjustable loads, are gaining increasing attention. Leveraging advanced communications, control, and information technologies, VPPs aggregate numerous dispersed energy resources, enabling them to participate in the operation and dispatch of power systems. They play a key role in ensuring the stable and reliable operation of the power grid and promoting the integration of renewable energy. Load regulation is a core task in VPP operations. A sound load regulation strategy ensures that VPPs meet grid load demands while optimizing resource utilization, reducing operating costs, and improving economic efficiency.

[0003] Prior art, such as the Chinese invention patent application with publication number CN119093497A, discloses a virtual power plant capacity control and operation optimization method, system, and related equipment. The system includes: constructing a mathematical model with the installed capacity and operating efficiency of resources as target variables, with the mathematical model targeting the lowest annual economic cost; determining the constraints of the mathematical model, including energy balance constraints, upper and lower limits on resource installed capacity, and resource interaction constraints; introducing capacity constraints on source-storage resources to ensure sufficient storage capacity to balance energy fluctuations; constructing a virtual power plant interactive operation optimization model under resource capacity constraints; determining source-load resource interaction constraints and incentive-based demand response constraints; determining the optimal solution of the virtual power plant interactive operation optimization model based on the source-load resource interaction constraints and incentive-based demand response constraints, and verifying and optimizing the results. However, the above patent focuses on optimization from the perspective of installed capacity and operating efficiency of energy resources, and does not deeply evaluate the reliability of each load during the regulation process. Some loads may fail during regulation or fail to achieve the expected regulation capacity due to equipment aging, improper maintenance, and other reasons. In addition, the above-mentioned patent does not fully consider the reliability of each load, and may over-rely on unreliable load resources, resulting in problems such as insufficient regulation capacity or regulation interruption in actual operation, reducing the overall reliability of the virtual power plant operation, and is not conducive to the safe and stable operation of the power grid. Summary of the Invention

[0004] In order to solve the above problems existing in the prior art, the present invention proposes a virtual power plant load regulation method, equipment and medium.

[0005] The technical solutions of the present invention are as follows:

[0006] In one aspect, the present invention provides a virtual power plant load adjustment method, comprising the following steps:

[0007] Obtain load instruction data of virtual power plants;

[0008] Determining the load resource dispatching cost, demand response capacity deviation penalty, and load response willingness and reliability equivalent cost of the virtual power plant based on the load instruction data;

[0009] With the goal of minimizing the load resource scheduling cost of the virtual power plant, the penalty for demand response capacity deviation, and the equivalent cost of load response willingness and reliability, the load command decomposition objective function of the virtual power plant is constructed.

[0010] Formulate constraints corresponding to load instruction decomposition, and solve the load instruction decomposition objective function based on the constraints to obtain the load regulation instruction of the virtual power plant;

[0011] The load of the virtual power plant is adjusted according to the load adjustment instruction.

[0012] Preferably, the load resource scheduling cost of the virtual power plant is expressed as:

[0013] ;

[0014] ;

[0015] ;

[0016] Where, represents the load resource scheduling cost of the virtual power plant, Represents the time index, represents the load index, Indicates the The load in The virtual cost of dispatching to respond to demand at all times, Indicates the The load in The response capacity at the moment, Indicates the adjustment cycle, Indicates the The load in The interruption state at the moment, Indicates the The load in The interruptible capacity at the moment.

[0017] Preferably, the demand response capacity deviation penalty of the virtual power plant is expressed as:

[0018] ;

[0019] ;

[0020] Where, represents the demand response capacity deviation penalty of the virtual power plant, Indicates The time penalty coefficient of the moment, Indicates The actual response capacity at any moment exceeds the penalty threshold of the demand capacity. Indicates The actual response adjustment capacity at any moment is lower than the demand capacity penalty threshold. Represents the time index, Indicates the adjustment period.

[0021] Preferably, the load response willingness and reliability equivalent cost of the virtual power plant are expressed as follows:

[0022] ;

[0023] ;

[0024] ;

[0025] Where, represents the load response willingness and reliability equivalent cost of the virtual power plant, Represents the time index, represents the load index, Indicates the preset confidence level part, express Moment The load is in the first The response reliability coefficient of the segment, Indicates the The load in The response willingness rating coefficient at the moment, express Moment The load is in the first The response capacity of the segment, Indicates the adjustment cycle, Indicates the The load in The response capacity at the time, Indicates the The load in The interruption state at the moment, Indicates the The load in Interruptible capacity at the time;

[0026] in, and There is the following relationship, which can be expressed as a formula:

[0027] .

[0028] Preferably, the response reliability coefficient is expressed as follows:

[0029] ;

[0030] Where, Indicates the The lower limit of load regulation, express Moment The load forecast value of each load, Indicates the preset confidence level The load adjustment of the segment, Indicates the power adjustment. represents the probability density function;

[0031] The lower limit of adjustment is expressed as follows:

[0032] ;

[0033] Where, Indicates the The historical minimum load value of a load, express Moment The upper limit of the adjustable capacity of each load, represents the minimum function.

[0034] Preferably, the response willingness score coefficient is expressed as follows:

[0035] ;

[0036] Where, Indicates the The load in The actual response rate at the moment, represents the price impact coefficient, Indicates the The load in Price sensitivity at the moment;

[0037] The actual response rate is expressed as:

[0038] ;

[0039] Where, Indicates the The load in The number of times the user accepts and executes the demand response instruction at time t, Indicates the The load in The total number of invitation signals sent by the power grid system at time t;

[0040] Price sensitivity is expressed as:

[0041] ;

[0042] Where, Indicates the The load in The change in the reporting ratio at each moment, Indicates the The load in The change in the market clearing price at time , Indicates the The load in The market clearing price at time , Indicates the The load in The reporting ratio at the time.

[0043] Preferably, the load instruction decomposition objective function of the virtual power plant is constructed with the goal of minimizing the load resource scheduling cost of the virtual power plant, the demand response capacity deviation penalty, and the load response willingness and reliability equivalent cost, which can be expressed as follows:

[0044] ;

[0045] Where, represents the load resource scheduling cost of the virtual power plant, represents the demand response capacity deviation penalty of the virtual power plant, represents the load response willingness and reliability equivalent cost of the virtual power plant, represents the minimum function.

[0046] Preferably, the constraints corresponding to the load instruction decomposition are formulated and expressed as follows:

[0047] ;

[0048] ;

[0049] Where, represents the constraints, Indicates the preset confidence level part, Represents the time index, represents the load index, Indicates the adjustment cycle, Indicates The actual response capacity at any moment exceeds the penalty threshold of the demand capacity. Indicates The actual response capacity at any moment is lower than the penalty threshold of the demand capacity express Moment The load is in the first The response capacity of the segment, Indicates the The load in The response capacity at the moment, express Moment The load response capacity of the power grid system allocated to each load, express Moment The load is in the first The upper limit of the segment's response capacity, express Moment A binary variable indicating whether the load is adjusted. Indicates the The load in The lower limit of the response capacity at time Indicates the The load in The upper limit of the response capacity at the moment, Indicates the upper limit of continuous adjustment time. Indicates the The load in A binary variable indicating whether the moment is shifted downward, Indicates the The load in A binary variable indicating whether the moment is shifted upwards, Indicates the The load in The interruption state at the moment, express Time has come The length of the time interval between moments, Indicates the maximum interruption duration. Indicates the load upward climbing rate, Indicates the load downward climbing rate, Indicates the The load in The response capacity at the moment, Indicates the The load in Response capacity at the moment;

[0050] in, Moment The load is in the first Upper limit of the segment's response capacity It can be expressed as:

[0051] ;

[0052] Where, Indicates the preset confidence level The load adjustment of the segment, Indicates the preset confidence level The load adjustment amount of the segment.

[0053] On the other hand, the present invention further provides an electronic device having a computer program stored thereon, wherein when the computer program is executed by a processor, the virtual power plant load regulation method as described in any embodiment of the present invention is implemented.

[0054] On the other hand, the present invention also provides a computer-readable storage medium for storing one or more programs, which, when executed by the one or more processors, enables the one or more processors to implement the virtual power plant load regulation method as described in any embodiment of the present invention.

[0055] The present invention has the following beneficial effects:

[0056] 1. This invention constructs an objective function by comprehensively considering indicators such as load resource scheduling costs, demand response capacity deviation penalties, load response willingness, and reliability equivalent costs. Load instructions are decomposed and adjusted with the goal of minimizing these costs. This allows the virtual power plant to meet load demand while minimizing overall load resource scheduling costs, reducing operating expenses and improving economic benefits.

[0057] 2. This invention takes into account demand response capacity deviation penalties, ensuring that the actual response capacity is as close to the demand capacity as possible, minimizing the amount that exceeds or falls below the demand capacity penalty threshold. This reduces penalty fees incurred due to deviations and further improves the economic efficiency of the virtual power plant.

[0058] 3. The present invention takes into account the load response willingness and reliability equivalent cost, wherein the calculation of the response reliability coefficient involves the load regulation lower limit, load forecast value, load regulation amount of preset reliability, etc. In this way, the reliable response capability of each load under different preset reliability is fully evaluated, ensuring that during the load regulation process, the load resources relied on can stably and reliably provide the corresponding response capacity, thereby enhancing the reliability of the entire virtual power plant dispatch. The present invention introduces the load response willingness factor and determines the response willingness scoring coefficient based on the user's actual response rate, price sensitivity, etc. This enables the virtual power plant to fully respect the user's wishes and needs when formulating load regulation instructions, and to make personalized adjustments based on the characteristics of different users. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 The present invention is a flowchart for implementing the method. DETAILED DESCRIPTION

[0060] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0061] It should be understood that the step numbers used herein are only for convenience of description and are not intended to limit the order in which the steps are to be executed.

[0062] It should be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, the singular forms "a", "an" and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0063] The terms “include” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0064] The term "and / or" refers to and includes any and all possible combinations of one or more of the associated listed items.

[0065] Example 1:

[0066] See also Figure 1 This embodiment provides a virtual power plant load adjustment method, comprising the following steps:

[0067] Obtain load instruction data of virtual power plants;

[0068] Determining the load resource dispatching cost, demand response capacity deviation penalty, and load response willingness and reliability equivalent cost of the virtual power plant based on the load instruction data;

[0069] With the goal of minimizing the load resource scheduling cost of the virtual power plant, the penalty for demand response capacity deviation, and the equivalent cost of load response willingness and reliability, the load command decomposition objective function of the virtual power plant is constructed.

[0070] Formulate constraints corresponding to load instruction decomposition, and solve the load instruction decomposition objective function based on the constraints to obtain the load regulation instruction of the virtual power plant;

[0071] The load of the virtual power plant is adjusted according to the load adjustment instruction.

[0072] In at least one embodiment, the load command decomposition objective function of the virtual power plant can be solved by an optimization solver in the mathematical calculation and simulation software MATLAB.

[0073] Preferably, the load resource scheduling cost of the virtual power plant is expressed as:

[0074] ;

[0075] ;

[0076] ;

[0077] Where, represents the load resource scheduling cost of the virtual power plant, Represents the time index, represents the load index, Indicates the The load in The virtual cost of dispatching to respond to demand at all times, Indicates the The load in The response capacity at the time, Indicates the adjustment cycle, Indicates the The load in The interruption state at the moment, Indicates the The load in The interruptible capacity at the moment.

[0078] The load includes the load of the virtual generator set, the load of the adjustable load and the load of the virtual energy storage.

[0079] Preferably, the demand response capacity deviation penalty of the virtual power plant is expressed as:

[0080] ;

[0081] ;

[0082] Where, represents the demand response capacity deviation penalty of the virtual power plant, Indicates The time penalty coefficient of the moment, Indicates The actual response capacity at any moment exceeds the penalty threshold of the demand capacity. Indicates The actual response adjustment capacity at any moment is lower than the demand capacity penalty threshold. Represents the time index, Indicates the adjustment period.

[0083] Preferably, the load response willingness and reliability equivalent cost of the virtual power plant are expressed as follows:

[0084] ;

[0085] ;

[0086] ;

[0087] Where, represents the load response willingness and reliability equivalent cost of the virtual power plant, Represents the time index, represents the load index, Indicates the preset confidence level part, express Moment The load is in the first The response reliability coefficient of the segment, Indicates the The load in The response willingness rating coefficient at the moment, express Moment The load is in the first The response capacity of the segment, Indicates the adjustment cycle, Indicates the The load in The response capacity at the time, Indicates the The load in The interruption state at the moment, Indicates the The load in Interruptible capacity at the time;

[0088] in, and There is the following relationship, which can be expressed as a formula:

[0089] .

[0090] In at least one embodiment, the first The segment can be set to any of 0%, 10%, 20%, ..., 90%, 100%.

[0091] Preferably, the response reliability coefficient is expressed as follows:

[0092] ;

[0093] Where, Indicates the The lower limit of load regulation, express Moment The load forecast value of each load, Indicates the preset confidence level The load adjustment of the segment, Indicates the power adjustment. represents the probability density function;

[0094] The lower limit of adjustment is expressed as follows:

[0095] ;

[0096] Where, Indicates the The historical minimum load value of a load, express Moment The upper limit of the adjustable capacity of each load, represents the minimum function.

[0097] The probability density function acquisition steps are:

[0098] Get the The historical load data of each load is used to construct a two-dimensional load distribution diagram;

[0099] Among them, the x-axis is time and the y-axis is load data;

[0100] Take the y-axis distribution curve as the probability density function.

[0101] In at least one embodiment, the load forecast value Forecasting is performed based on the long short-term memory network (LSTM) and historical load data.

[0102] Preferably, the response willingness score coefficient is expressed as follows:

[0103] ;

[0104] Where, Indicates the The load in The actual response rate at the moment, represents the price impact coefficient, Indicates the The load in Price sensitivity at the moment;

[0105] The actual response rate is expressed as:

[0106] ;

[0107] Where, Indicates the The load in The number of times the user accepts and executes the demand response instruction at time t, Indicates the The load in The total number of invitation signals sent by the power grid system at time t;

[0108] Price sensitivity is expressed as:

[0109] ;

[0110] Where, Indicates the The load in The change in the reporting ratio at each moment, Indicates the The load in The change in the market clearing price at time , Indicates the The load in The market clearing price at time , Indicates the The load in The reporting ratio of the time;

[0111] The change in the market clearing price is expressed as:

[0112] ;

[0113] Where, Indicates the The load in The market clearing price at time ;

[0114] The change in the declared ratio is expressed as follows:

[0115] ;

[0116] Where, Indicates the The load in The reporting ratio of the time;

[0117] The declaration ratio is expressed as follows:

[0118] ;

[0119] Where, Indicates the The load in The response capacity reported by the user at that moment.

[0120] Preferably, the load instruction decomposition objective function of the virtual power plant is constructed with the goal of minimizing the load resource scheduling cost of the virtual power plant, the demand response capacity deviation penalty, and the load response willingness and reliability equivalent cost, which can be expressed as follows:

[0121] ;

[0122] Where, represents the load resource scheduling cost of the virtual power plant, represents the demand response capacity deviation penalty of the virtual power plant, represents the load response willingness and reliability equivalent cost of the virtual power plant, represents the minimum function.

[0123] Preferably, the constraints corresponding to the load instruction decomposition are formulated and expressed as follows:

[0124] ;

[0125] ;

[0126] Where, represents the constraints, Indicates the preset confidence level part, Represents the time index, represents the load index, Indicates the adjustment cycle, Indicates The actual response capacity at any moment exceeds the penalty threshold of the demand capacity. Indicates The actual response capacity at any moment is lower than the penalty threshold of the demand capacity express Moment The load is in the first The response capacity of the segment, Indicates the The load in The response capacity at the moment, express Moment The load response capacity of the power grid system allocated to each load, express Moment The load is in the first The upper limit of the segment's response capacity, express Moment A binary variable indicating whether the load is adjusted. If it is 1, it is regulated. If it is 0, it means it is not adjusted. Indicates the The load in The lower limit of the response capacity at time Indicates the The load in The upper limit of the response capacity at the moment, Indicates the upper limit of continuous adjustment time. Indicates the The load in A binary variable indicating whether the moment is shifted downward, Indicates the The load in A binary variable indicating whether the moment is shifted upwards, If it is 0, it means it has not been transferred. If it is 1, it means it is transferred. Indicates the The load in The interruption state at the moment, express Time has come The length of the time interval between moments, Indicates the maximum interruption duration. Indicates the load upward climbing rate, Indicates the load downward climbing rate, Indicates the The load in The response capacity at the moment, Indicates the The load in Response capacity at the moment;

[0127] in, Moment The load is in the first Upper limit of the segment's response capacity It can be expressed as:

[0128] ;

[0129] Where, Indicates the preset confidence level The load adjustment of the segment, Indicates the preset confidence level The load adjustment amount of the segment.

[0130] Example 2:

[0131] This embodiment provides an electronic device having a computer program stored thereon, and when the computer program is executed by a processor, the virtual power plant load regulation method as described in any embodiment of the present invention is implemented.

[0132] Example 3:

[0133] This embodiment provides a computer-readable storage medium for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the virtual power plant load regulation method as described in any embodiment of the present invention.

[0134] In the embodiments of the present application, "at least one" refers to one or more, and "more" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone. Among them, A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single 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, c can be single or multiple.

[0135] Those skilled in the art will appreciate that the various units and algorithm steps described in the embodiments disclosed herein can be implemented using a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0136] Those skilled in the art will 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 aforementioned method embodiments and will not be repeated here.

[0137] In the several embodiments provided in this 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 this application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of this application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory; hereinafter referred to as: ROM), random access memory (Random Access Memory; hereinafter referred to as: RAM), magnetic disk or optical disk, and other media that can store program code.

[0138] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention's description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A virtual power plant load adjustment method, characterized in that: The following steps are involved: Obtain load instruction data of virtual power plants; Determining the load resource dispatching cost, demand response capacity deviation penalty, and load response willingness and reliability equivalent cost of the virtual power plant based on the load instruction data; The demand response capacity deviation penalty is expressed as: ； ； Where, represents the demand response capacity deviation penalty of the virtual power plant, Indicates The time penalty coefficient of the moment, Indicates The actual response capacity at any moment exceeds the penalty threshold of the demand capacity. Indicates The actual response adjustment capacity at any moment is lower than the demand capacity penalty threshold. Represents the time index, Indicates the adjustment cycle; The load response willingness and reliability equivalent cost are expressed as follows: ； ； Where, represents the load response willingness and reliability equivalent cost of the virtual power plant, represents the load index, Indicates the preset confidence level part, express Moment The load is in the first The response reliability coefficient of the segment, Indicates the The load in The response willingness rating coefficient at the moment, express Moment The load is in the first The response capacity of the segment, Indicates the The load in The response capacity at the moment, Indicates the The load in The interruption state at the moment, Indicates the The load in Interruptible capacity at the time; in, and There is the following relationship, which can be expressed as a formula: ； The response reliability coefficient is expressed as follows: ； Where, Indicates the The lower limit of load regulation, express Moment The load forecast value of each load, Indicates the preset confidence level The load adjustment of the segment, Indicates the power adjustment. represents the probability density function; The lower limit of adjustment is expressed as follows: ； Where, Indicates the The historical minimum load value of a load, express Moment The upper limit of the adjustable capacity of each load, represents the minimum function; With the goal of minimizing the load resource scheduling cost of the virtual power plant, the penalty for demand response capacity deviation, and the equivalent cost of load response willingness and reliability, the load command decomposition objective function of the virtual power plant is constructed. Formulate constraints corresponding to load instruction decomposition, and solve the load instruction decomposition objective function based on the constraints to obtain the load regulation instruction of the virtual power plant; The load of the virtual power plant is adjusted according to the load adjustment instruction.

2. The virtual power plant load adjustment method according to claim 1, characterized in that: The load resource scheduling cost of the virtual power plant is expressed as follows: ； ； ； Where, represents the load resource scheduling cost of the virtual power plant, Indicates the The load in The virtual cost of dispatching to respond to demand at all times, Indicates the The load in The interrupt status at the moment.

3. The virtual power plant load adjustment method according to claim 1, characterized in that: The response willingness score coefficient is expressed as follows: ； Where, Indicates the The load in The actual response rate at the moment, represents the price impact coefficient, Indicates the The load in Price sensitivity at the moment; The actual response rate is expressed as: ； Where, Indicates the The load in The number of times the user accepts and executes the demand response instruction at time t, Indicates the The load in The total number of invitation signals sent by the power grid system at time t; Price sensitivity is expressed as: ； Where, Indicates the The load in The change in the reporting ratio at each moment, Indicates the The load in The change in the market clearing price at time , Indicates the The load in The market clearing price at time , Indicates the The load in The reporting ratio at the time.

4. The virtual power plant load adjustment method according to claim 1, characterized in that: With the goal of minimizing the load resource scheduling cost of the virtual power plant, the penalty for demand response capacity deviation, and the equivalent cost of load response willingness and reliability, the load instruction decomposition objective function of the virtual power plant is constructed and expressed as follows: ； Where, represents the load resource scheduling cost of the virtual power plant, represents the minimum function.

5. The virtual power plant load adjustment method according to claim 1, characterized in that: Formulate the constraints corresponding to the load instruction decomposition, which can be expressed as follows: ； ； Where, represents the constraints, express Moment The load response capacity of the power grid system allocated to each load, express Moment The load is in the first The upper limit of the segment's response capacity, To express Moment A binary variable indicating whether the load is adjusted. Indicates the The load in The lower limit of the response capacity at time Indicates the The load in The upper limit of the response capacity at the moment, Indicates the upper limit of continuous adjustment time. To indicate the The load in A binary variable indicating whether the moment is shifted downward, Indicates the The load in A binary variable indicating whether the moment is shifted upwards, Indicates the The load in The interruption state at the moment, express Time has come The length of the time interval between moments, Indicates the maximum interruption duration. Indicates the load upward climbing rate, Indicates the load downward climbing rate, Indicates the The load in The response capacity at the moment, Indicates the The load in Response capacity at the moment; in, Moment The load is in the first Upper limit of the segment's response capacity It can be expressed as: ； Where, Indicates the preset confidence level The load adjustment of the segment, Indicates the preset confidence level The load adjustment amount of the segment.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the virtual power plant load regulation method according to any one of claims 1 to 5 is implemented.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the virtual power plant load regulation method as described in any one of claims 1 to 5 is implemented.

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