Flexible resource scheduling method, device and equipment of virtual power plant and storage medium

Abstract

The invention provides a flexible resource scheduling method and device for a virtual power plant, equipment and a storage medium, and the method comprises the steps: receiving a scheduling task for flexible resources of the virtual power plant, and determining a load demand corresponding to the scheduling task, and based on the relationship between the real-time output data of the first-level flexibility resource and the second-level flexibility resource in the virtual power plant and the load demand, performing flexible resource scheduling by using the constructed target circle set, so that the real-time output data meets the load demand, the target circle set is obtained by dividing based on the weight of the flexible resources in the jurisdiction area of the virtual power plant. It can be seen that flexible resource scheduling is performed based on the target circle set obtained by dividing the weights of the flexible resources in the jurisdiction area of the virtual power plant, so that the real-time output data meets the load requirement, and the overall scheduling efficiency of the virtual power plant is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing, and in particular to a method, apparatus, device and storage medium for scheduling flexible resources of a virtual power plant. Background Art

[0002] Virtual power plants integrate various distributed energy resources, such as distributed energy resources, adjustable loads and energy storage systems, and use digital technology to grasp the power generation and power consumption of these distributed resources in real time. Based on the demand and price signals of the electricity spot market, they coordinate the output and power consumption of the above resources to provide the system with peak-shaving, frequency regulation, voltage regulation, standby, demand response and other services.

[0003] However, in related technologies, resource aggregation methods such as direct aggregation method, geometric calculation method, Monte Carlo simulation method and optimization solution method are usually used to schedule the flexibility resources of virtual power plants, resulting in low overall scheduling efficiency of virtual power plants. Summary of the Invention

[0004] In order to solve the above technical problems, the embodiments of the present disclosure provide a flexible resource scheduling method, device, equipment and storage medium for a virtual power plant.

[0005] In a first aspect, the present disclosure provides a method for scheduling flexibility resources of a virtual power plant, the method comprising:

[0006] Receiving a scheduling task for a flexibility resource of a virtual power plant and determining a load demand corresponding to the scheduling task;

[0007] Based on the relationship between the real-time output data of the first-level flexibility resources and the second-level flexibility resources in the virtual power plant and the load demand, the constructed target circle set is used to schedule flexibility resources so that the real-time output data meets the load demand; wherein, the target circle set is obtained by dividing the flexibility resources based on the weights of the flexibility resources in the area under the jurisdiction of the virtual power plant, the first-level flexibility resources include commercial energy storage, and the second-level flexibility resources include building temperature control and industrial production lines.

[0008] In a second aspect, the present disclosure provides a flexible resource scheduling device for a virtual power plant, the device comprising:

[0009] a determination module, configured to receive a scheduling task for flexibility resources of a virtual power plant and determine a load demand corresponding to the scheduling task;

[0010] A scheduling module is used to schedule flexibility resources based on the relationship between the real-time output data of the first-level flexibility resources and the second-level flexibility resources in the virtual power plant and the load demand, using the constructed target circle set to make the real-time output data meet the load demand; wherein, the target circle set is obtained by dividing the flexibility resources in the area under the jurisdiction of the virtual power plant based on the weights, the first-level flexibility resources include commercial energy storage, and the second-level flexibility resources include building temperature control and industrial production lines.

[0011] In a third aspect, the present disclosure provides a computer-readable storage medium, wherein instructions are stored in the computer-readable storage medium. When the instructions are executed on a terminal device, the terminal device implements the above method.

[0012] In a fourth aspect, the present disclosure provides a flexible resource scheduling device for a virtual power plant, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method when executing the computer program.

[0013] In a fifth aspect, the present disclosure provides a computer program product, which includes a computer program / instructions, and the computer program / instructions implement the above method when executed by a processor.

[0014] The technical solution provided by the embodiments of the present disclosure has at least the following advantages compared with the prior art:

[0015] An embodiment of the present disclosure provides a method for scheduling flexibility resources of a virtual power plant, which receives a scheduling task for flexibility resources of the virtual power plant, determines the load demand corresponding to the scheduling task, and performs flexibility resource scheduling based on the relationship between the real-time output data of the first-level flexibility resources and the second-level flexibility resources in the virtual power plant and the load demand using a constructed target circle set, so that the real-time output data meets the load demand, wherein the target circle set is obtained by dividing the flexibility resources in the area under the jurisdiction of the virtual power plant based on the weights, the first-level flexibility resources include commercial energy storage, and the second-level flexibility resources include building temperature control and industrial production lines. It can be seen that the present disclosure performs flexibility resource scheduling based on the target circle set obtained by dividing the flexibility resources in the area under the jurisdiction of the virtual power plant based on the weights, so that the real-time output data meets the load demand, thereby improving the overall scheduling efficiency of the virtual power plant. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0017] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0018] Figure 1 A flowchart of a flexibility resource scheduling method for a virtual power plant provided in an embodiment of the present disclosure;

[0019] Figure 2 A schematic structural diagram of a flexible resource scheduling device for a virtual power plant provided in an embodiment of the present disclosure;

[0020] Figure 3 A schematic structural diagram of a flexibility resource scheduling device for a virtual power plant provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0021] In order to more clearly understand the above-mentioned objectives, features and advantages of the present disclosure, the scheme of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features therein can be combined with each other in the absence of conflict.

[0022] In the following description, many specific details are set forth to facilitate a full understanding of the present disclosure, but the present disclosure may also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present disclosure, rather than all of the embodiments.

[0023] Virtual power plants provide peak-shaving capabilities for the system. Current research focuses on the feasible domain of aggregated and adjustable loads. Common resource aggregation methods include direct aggregation, geometric calculation, Monte Carlo simulation, and optimization solution. The direct aggregation method is only applicable to the aggregation of a single type of resource; both the Monte Carlo simulation method and the optimization solution method directly solve the aggregate flexibility region, but lack the characterization of the flexibility region of a single resource. Considering that the geometric method can more intuitively characterize the flexibility region of a single resource, it is convenient for aggregation and subsequent decomposition, and has the advantage of efficiently realizing the addition or deletion of a single resource. In further research on the aggregation of flexible resources using geometric methods, most of the methods used are inscribed hypercubes, hyperellipsoids, centrosymmetric Chino polyhedrons, and half-plane methods to approximate and obtain the feasible domain.

[0024] The various geometric methods studied above focus on solving the problem of different operating parameters and geographical locations of flexibility resources, without taking into account the peak-shaving capabilities and different economic benefits of several other types of flexibility resources in virtual power plants. The various geometric methods studied above have not yet achieved the goal of fully coordinated peak-shaving.

[0025] In addition, the current technologies used by virtual power plants for flexible resources to participate in system peak regulation are divided into two parts: the construction of a flexibility resource model and the construction of a feasible domain. The construction of the flexibility resource model does not introduce peak regulation capabilities and economic indicators, making it difficult to propose reasonable weights for the output of each flexibility resource when coordinating peak regulation. Similarly, the construction of the feasible domain relies solely on the location data of each flexibility resource, and uses geometric and other mathematical methods to aggregate it, without considering the weight of the output of each flexibility resource. As a result, although optimization technology is used internally, the peak regulation efficiency and economy of the aggregate after aggregation are difficult to optimize, resulting in low overall scheduling efficiency of the virtual power plant.

[0026] To this end, an embodiment of the present disclosure provides a method for scheduling flexibility resources of a virtual power plant, which receives a scheduling task for flexibility resources of the virtual power plant, determines the load demand corresponding to the scheduling task, and performs flexibility resource scheduling based on the relationship between the real-time output data of the first-level flexibility resources and the second-level flexibility resources in the virtual power plant and the load demand, using the constructed target circle set to make the real-time output data meet the load demand, wherein the target circle set is obtained by dividing the flexibility resources in the area under the jurisdiction of the virtual power plant based on the weights, the first-level flexibility resources include commercial energy storage, and the second-level flexibility resources include building temperature control and industrial production lines. It can be seen that the present disclosure performs flexibility resource scheduling based on the target circle set obtained by dividing the flexibility resources in the area under the jurisdiction of the virtual power plant based on the weights, so that the real-time output data meets the load demand, thereby improving the overall scheduling efficiency of the virtual power plant.

[0027] Based on this, the embodiment of the present disclosure provides a flexible resource scheduling method for a virtual power plant, referring to Figure 1 , is a flow chart of a flexibility resource scheduling method for a virtual power plant provided by an embodiment of the present disclosure, the method comprising:

[0028] S101. Receive a scheduling task for flexibility resources of a virtual power plant and determine a load demand corresponding to the scheduling task.

[0029] Among them, a virtual power plant is a power coordination and management system that uses advanced information and communication technologies and software systems to achieve the aggregation and coordinated optimization of distributed energy sources such as distributed power sources, energy storage systems, controllable loads, and electric vehicles, so as to participate in the power market and power grid operation as a special power plant. Flexibility resources refer to power resources with rapid adjustment capabilities, including the power generation side and the load side, which can respond to the grid dispatching needs. A dispatching task refers to a power adjustment instruction issued by the power grid or the upper system, requiring the virtual power plant to provide a specified amount of power supply or consumption during a specific period of time. Load demand refers to the amount of electrical energy required by the power system within a specific time period, usually expressed in power (such as kilowatts or megawatts).

[0030] In the embodiments of the present disclosure, virtual power plants can be summarized into four main types according to the characteristics of the resources they aggregate, namely load type, power type, energy storage type, and hybrid type. They can respectively aggregate adjustable loads (building temperature control, electric vehicles, industrial production lines), new energy power generation (distributed photovoltaic, wind power), regulating power generation (biomass power generation, coal power / gas power), energy storage resources (industrial and commercial energy storage, household energy storage), power load energy storage and various flexible resources.

[0031] In an embodiment of the present disclosure, after receiving a scheduling task for flexibility resources of a virtual power plant, the flexibility resource scheduling device parses the scheduling task to obtain a load demand corresponding to the scheduling task.

[0032] In this disclosed embodiment, the flexibility resources of a virtual power plant are leveraged to achieve system peak shaving within a region, with a focus on flexible resources such as building temperature control, electric vehicles, industrial production lines, and commercial energy storage. These resources are categorized into three tiers based on capacity: first-tier flexible resources are commercial energy storage, second-tier flexible resources are building temperature control and industrial production lines, and third-tier flexible resources are electric vehicles. Peak shaving activities using these resources include peak shaving, valley filling, and peak shifting and valley filling.

[0033] To facilitate understanding of the embodiments of the present disclosure, the process of determining the parameters of the flexibility resources is first described, and the peak-shaving capability of the flexibility resources is determined from aspects such as the capacity used for peak-shaving and the economic cost.

[0034] For first-level flexibility resources:

[0035] In the embodiments of the present disclosure, the commercial energy storage involved in the first-level flexibility resources is mainly electrochemical energy storage. The following characteristic quantities are collected and recorded for a single energy storage system:

[0036] Maximum charging power Maximum discharge power Charging efficiency η ch , discharge efficiency η dch , the upper limit of the state of charge allowed SOCes min, and the lower limit of the state of charge allowed for the energy storage system SOCes max.

[0037] Peak elimination capability of energy storage system in peak regulation capability T dch :

[0038]

[0039] The valley filling capability of the energy storage system in terms of peak load regulation capability ch :

[0040]

[0041] The operating life of lithium batteries in electrochemical energy storage is related to the depth of discharge, and the depreciation cost model of lithium batteries is:

[0042]

[0043] Among them, C D,t is the operating depreciation cost of the energy storage system, C0 is the initial investment cost of the energy storage system, N life is the average cycle life of the energy storage system, Q0 is the rated capacity of the energy storage system, is the charging power of the electrochemical energy storage system at time t, is the discharge power of the electrochemical energy storage system at time t, T refers to the peak elimination capability and valley filling capability mentioned above. If charging, T is the peak elimination capability T dch If it is discharging, then T is the valley filling capacity T ch .

[0044] During the charging and discharging process of the energy storage system, the operation and maintenance of the energy storage system equipment will incur costs. The operation and maintenance cost per unit time is related to the charging and discharging power:

[0045]

[0046] Among them, C M,t K is the operation and maintenance cost of the energy storage equipment during period t, M,t is the system operation and maintenance cost coefficient, is the charging power of the electrochemical energy storage system at time t, is the discharge power of the electrochemical energy storage system at time t, T refers to the peak elimination capability and valley filling capability mentioned above. If charging, T is the peak elimination capability T dch If it is discharging, then T is the valley filling capacity T ch .

[0047] The peak regulation cost of the energy storage system includes the cost of charging and discharging once, C s for:

[0048]

[0049] where N s is the maximum number of charging times designed for the energy storage system, C D,t is the operating depreciation cost of the energy storage system, C M,t is the operation and maintenance cost of the energy storage equipment during period t.

[0050] For the second level of flexibility resources:

[0051] Second-tier flexibility resources, such as building temperature control systems and industrial production lines, are defined as interruptible loads. This refers to loads that, according to pre-existing contracts between the supply and demand sides, are subject to partial power interruption during peak demand periods, when the power system dispatcher sends a request signal to the power user. These loads, while capable of peak load regulation, offer a rapid response, with the economic cost determined by the impact on the load-bearing party. Assume that N building temperature control systems and industrial production lines have signed contracts within the virtual power plant's jurisdiction, denoted by S.

[0052] For the third-level flexible resources, take the peak load scheduling task as an example:

[0053] Electric vehicles also utilize electrochemical charging and discharging, and their peak-load balancing and valley-loading capabilities are similar to those described above. However, the cost of peak-load shaving for electric vehicles involves the following: upon receiving a peak-load shaving instruction, the driver must visit a charging station for charging and discharging. This includes the cost of reaching the station and the time spent waiting for charging. This cost is also related to the vehicle's current location. For example, in a commercial area, where congestion may be high, the cost of reaching the charging station will be higher.

[0054] The peak load regulation cost of electric vehicles includes the cost of charging and discharging once. b for:

[0055]

[0056] Among them, N b is the maximum number of charging times designed for the electric vehicle battery, C D,t is the operating depreciation cost of electric vehicle batteries, C M,t is the operation and maintenance cost of the electric vehicle battery during period t, C tran is the cost of reaching the charging station, which is calculated by the following formula:

[0057] C tran =L b *o b *(1+w b ) (7)

[0058] Among them L b is the distance from the electric vehicle to the nearest charging station; b is the fuel price per kilometer of the electric car; w b It is the converted cost coefficient of the time spent on the congestion degree coefficient, and its value is between 0 and 1. If it is very congested, the value tends to 1, and if it is very unobstructed, the value tends to 0.

[0059] S102. Based on the relationship between the real-time output data of the first-level flexibility resources and the second-level flexibility resources in the virtual power plant and the load demand, the constructed target circle set is used to schedule the flexibility resources so that the real-time output data meets the load demand.

[0060] Among them, the target circle set is divided based on the weight of the flexibility resources within the area under the jurisdiction of the virtual power plant. The first-level flexibility resources include commercial energy storage, and the second-level flexibility resources include building temperature control and industrial production lines.

[0061] In the embodiments of the present disclosure, real-time output data refers to the record of the actual power values ​​generated or consumed by various types of flexible resources at a specific point in time. The target circle set refers to the set of circles obtained by dividing the flexible resources in the area under the jurisdiction of the virtual power plant according to their weights. Commercial energy storage refers to equipment and systems used for power storage, which can store electrical energy when power demand is low and release electrical energy when demand peaks. Building temperature control is a system for regulating the temperature and comfort inside a building. It can reduce power consumption by adjusting the temperature control system (such as lowering the air conditioning temperature setting) during peak power demand periods, thereby helping to balance the load on the power grid. Industrial production lines refer to equipment and machinery used in the manufacturing and production processes. The operation of these equipment in different time periods can be adjusted. For example, you can choose to increase production when electricity prices are low or power supply is sufficient, or reduce operation during peak demand.

[0062] In the embodiment of the present disclosure, after receiving the scheduling task for the flexibility resources of the virtual power plant, the flexibility resource scheduling device parses the scheduling task and obtains the load demand corresponding to the scheduling task. Then, based on the size relationship between the real-time output data of the first-level flexibility resources and the second-level flexibility resources in the virtual power plant and the load demand, the flexibility resources in the constructed target circle are used for scheduling so that the real-time output data meets the load demand.

[0063] To facilitate understanding of the target circle set, in an optional implementation, the target circle set construction process includes:

[0064] Step A: Based on capacity and economic cost, determine the weights corresponding to each first-level flexibility resource and each second-level flexibility resource.

[0065] Capacity refers to the maximum power output that a flexibility resource can provide, typically measured in kilowatts (kW) or megawatts (MW), reflecting its power generation or supply capabilities. Economic cost refers to the cost of using a flexibility resource.

[0066] In the embodiment of the present disclosure, the flexibility resource scheduling device determines the corresponding weights of each first-level flexibility resource and each second-level flexibility resource according to their corresponding capacities and economic costs respectively.

[0067] Taking a real-world scenario as an example, before starting flexible resource scheduling, it is necessary to calculate the weights of the energy storage power stations under the jurisdiction of the virtual power plant (i.e., the energy storage power stations corresponding to commercial energy storage), the declared and approved building temperature control, and the industrial production lines. The weights are calculated using two parameters: capacity (represented by e) and economic cost (represented by p). Assuming that there are n energy storage power stations in the virtual power plant, forming the energy storage power station set S = {S1, S2, ..., S n}; At the same time, there are m number of building temperature control and industrial production lines (assuming that the scheduling characteristics of the two are the same), forming the building temperature control and industrial production line set M = {M1, M2, ..., M m}, where each building temperature control and industrial production line M i The p-value can be initially set by the impact on the industry line or building.

[0068] The economic cost p needs to be normalized to a value between [0,1]. s :

[0069] p s =C s / C0 (8)

[0070] Among them, C s The peak-shaving cost of the energy storage system includes the cost of charging and discharging once, and C0 is the initial investment cost of the energy storage system.

[0071] For the economic cost of building temperature control or industrial production line m , filled in by the user when applying and approved, between [0.9,1].

[0072] The total capacity E of the first-level flexibility resources and the second-level flexibility resources in the virtual power plant is:

[0073]

[0074] The weight Q of each member of the energy storage power station set S i :

[0075] Q i =(e si * P si ) / E (10)

[0076] Among them, e si The capacity of each member of the energy storage power station set S, P si The economic cost of each member of the energy storage power station set S.

[0077] The weight Q of each member of the building temperature control and industrial production line set M j :

[0078] Q j =(e Mj * P Mj ) / E (11)

[0079] Among them, e Mi The capacity of each member of the building temperature control and industrial production line set M, P Mi The economic cost of each member of the building temperature control and industrial production line group M.

[0080] Step B: Merge the first-level flexibility resources and the second-level flexibility resources into a target point set in descending order of weight.

[0081] The target point set is a set of flexibility resources arranged in descending order according to the weights of the first-level flexibility resources and the second-level flexibility resources.

[0082] In the embodiment of the present disclosure, the first-level flexibility resources and the second-level flexibility resources are constructed into a sequence with weights from large to small in the order of their weights from large to small, and the sequence is the target point set.

[0083] For example, the energy storage power station set S, the building temperature control set, and the industrial production line set M are merged into a target point set L in descending order of weight, whose elements are elements of S or M, and the number of elements is the sum of the number of elements of S and M.

[0084] Step C: Divide the area governed by the virtual power plant based on the target point set to obtain a first circle set.

[0085] Among them, the first circle set is a set of spatial areas formed by dividing the virtual power plant jurisdiction area based on the target point set, which is used to centrally manage and dispatch various flexibility resources to optimize power supply and demand response.

[0086] In the embodiment of the present disclosure, the area governed by the virtual power plant is divided into circles with different radii based on the target point set, and the set consisting of circles with different radii is the first circle set.

[0087] To facilitate understanding of the first circle set, in an optional implementation, the process of constructing the first circle set includes steps C1 to C4.

[0088] Step C1: Select two points from the beginning of the target point set, use the two points as the center of the circle, and construct two tangent circles.

[0089] The radii of the two circles are determined based on the distance between the two points and the weights of the flexibility resources corresponding to the two points.

[0090] In the embodiment of the present disclosure, after the target point set is constructed, two flexibility resources with the largest weights are selected from the target point set, and the geographical locations of the two flexibility resources are used as the centers of the circles to construct two tangent circles.

[0091] For ease of understanding, let's continue to use the above target point set L as an example:

[0092] First, select two points L1 and L2 from the head of the target point set L, and draw two tangent circles with these two points as the center. To this end, calculate the distance between the two circle centers and distribute the radius of the two circles according to the weights of the two elements, that is:

[0093]

[0094] r1=D*Q1 / (Q1+Q2)

[0095] r2=D-r1 (12)

[0096] Among them, x1 and y1 are the geographical coordinates of L1, x2 and y2 are the geographical coordinates of L2, Q1 is the weight of the flexibility resource corresponding to L1, Q2 is the weight of the flexibility resource corresponding to L2, r1 is the radius of the circle corresponding to L1, and r2 is the radius of the circle corresponding to L2.

[0097] Step C2: Select the next point from the beginning to the end of the target point set in descending order of weight. If the point is within two circles, add the flexibility resource corresponding to the point to the corresponding circle.

[0098] In the embodiment of the present disclosure, the flexibility resource with the largest weight is selected from the remaining flexibility resources in the target point set, and the geographic coordinates of the flexibility resource are determined. If the geographic coordinates of the flexibility resource are within the above two circles, the flexibility resource is added to the corresponding circle.

[0099] For example, the next point, namely L3, is selected from the head to the tail of the target point set in descending order of weight. If point L3 is located within the above two circles, the flexibility resources corresponding to point L3 are merged into the corresponding circle.

[0100] Step C3: If the point is not within the two circles, determine the circle with the smallest distance from the point to the centers of the two circles, and construct a circumscribed circle of the circle with the smallest distance with the point as the center.

[0101] In the embodiment of the present disclosure, the flexibility resource with the largest weight is selected from the remaining flexibility resources in the target point set, and the geographic coordinates of the flexibility resource are determined. If the geographic coordinates of the flexibility resource are not within the above two circles, the circle with the smallest distance between the geographic coordinates of the flexibility resource and the centers of the above two circles is determined, and then the circumscribed circle with the circle with the smallest distance is constructed with the geographic coordinates of the flexibility resource as the center.

[0102] For example, if point L3 is not within the two circles, the distance from point L3 to the centers of the two circles is calculated to determine the minimum center distance L. min , and L min The corresponding circle radius R min , then take point L3 as the center and make a circle with a radius of (L min -R min ) of the circle R new .

[0103] Step C4: Repeat the step of selecting the next point from the head to the tail of the target point set until all elements in the target point set are processed.

[0104] In the embodiment of the present disclosure, the flexibility resource with the largest weight is continuously selected from the remaining flexibility resources in the target point set, and the above method is repeated until all elements in the target point set are processed.

[0105] In the embodiment of the present disclosure, the circles obtained above are constructed into a first circle set, wherein each circle in the circle set includes {center position, circle radius, flexibility resource 1, ..., flexibility resource n}.

[0106] Furthermore, the weight of each circle in the first circle set is calculated, that is, the weight of each flexibility resource contained therein is accumulated to obtain the new content of each circle as {center position, circle radius, weight, flexibility resource 1, ..., flexibility resource n}.

[0107] Step D: Add the third-level flexibility resources that meet the scheduling task to the first circle set to obtain the target circle set.

[0108] Among them, the third-level flexibility resources that meet the scheduling tasks are third-level flexibility resources whose time to start participating in the scheduling tasks is less than the time of the current scheduling tasks. The time to start participating in the scheduling tasks is determined based on the economic cost of the third-level flexibility resources. The third-level flexibility resources include electric vehicles.

[0109] In the embodiment of the present disclosure, the position of each flexibility resource is used as the center of the circle, and the radius is used to determine the area between the flexibility resources according to their weight ratio, thereby forming a first circle set within the area under the jurisdiction of the virtual power plant. Afterwards, the third-level flexibility resources that meet the scheduling task are added to the first circle set to obtain the target circle set, in which each circle contains aggregated multi-level flexibility resources.

[0110] The process of determining when the third-level flexibility resource begins to participate in the scheduling task is as follows:

[0111] Collect the third-level flexibility resources that respond to the scheduling task and form the third-level flexibility resource set T, whose elements are the attribute set A of a power station car. The elements of the attribute set A include {location, charging power, C tran , current remaining power SOC, maximum remaining power SOC max , and the minimum remaining charge SOC min For each electric car in T, calculate the distance L to the nearest charging station b , and calculate the cost C to the charging station tran .

[0112] The peak shaving time starts from the time when the peak shaving information is issued. At this time, the first-level flexibility resources and the second-level flexibility resources can participate in the scheduling task immediately, but the third-level flexibility resources need to reach the time to start participating in the scheduling task before they can participate in the scheduling task. Specifically, it is necessary to predict the starting charging time T of each element in the third-level flexibility resource set T. c (i.e. the time when it starts to participate in the scheduling task), so as to estimate the next real-time peak-shaving power.

[0113] The electric vehicle charging cost C calculated according to formula (7) tran The value contains distance and time information, statistics C tran The distribution of values, and the minimum C tran min The starting charging time T0 corresponding to the value is set to 10 sampling cycles (i.e. 10 sampling cycles T after the first-level flexibility resources and the second-level flexibility resources start peaking). s Initially, the sampling period of scheduling automation is generally 5 seconds), let C tran max Corresponding to (T0+T max ) sampling period (if the value is 300, it is about 30 minutes), then the time T when the elements of attribute set A start to participate in the scheduling task can be calculated c :

[0114] T c =T0+T max *(C tran -C tranmin ) / (C tran max -C tran min )

[0115] Among them, T c is the starting charging time of each element in the third-level flexible resource set T, T0 is the minimum C tran min The starting charging time corresponding to the value, C tran is the cost of reaching the charging station, C tran min The minimum cost to reach the charging station is C tran max The cost of reaching the charging station is the largest.

[0116] Therefore, the elements of the third-level flexibility resource set T include {location, charging power, starting charging time T c , C tran , current remaining power SOC, maximum remaining power SOC max , and the minimum remaining charge SOC min}.

[0117] It should be noted that in the process of constructing the target circle set, in order to avoid the problem of too many circles in the circle set, which will lead to increased system complexity, increased management difficulty, and reduced resource allocation efficiency, flexible resources with high load are given priority to construct the circle set.

[0118] The above step D includes: if the third-level flexibility resources that meet the scheduling task are located in the first circle set, then the third-level flexibility resources that meet the scheduling task are added to the corresponding circle.

[0119] In an embodiment of the present disclosure, if the geographical coordinates of the third-level flexibility resources that meet the scheduling task are located within the first circle set, the third-level flexibility resources that meet the scheduling task are added to the corresponding circle.

[0120] If the third-level flexibility resources that meet the scheduling task are not located in the first circle set, the third-level flexibility resources that meet the scheduling task will be added to the circle with the smallest distance based on the distance from their location to the centers of the circles in the first circle set.

[0121] In an embodiment of the present disclosure, if the geographical coordinates of the third-level flexibility resource that meets the scheduling task are not located within the first circle set, the circle with the shortest distance is determined based on the distance from its location to the centers of each circle in the first circle set, and the third-level flexibility resource that meets the scheduling task is added to the circle with the shortest distance.

[0122] Continuing with the third-level flexible resource set T as an example, based on the position information P(x, y) of the elements of the T set, if point P is not located in the first circle set, the distance L from point p to the center of each circle in the first circle set R is calculated. min , select the circle with the smallest distance as the host of this T-set element, add the T-set element to the circle, and obtain the target circle set. Each circle in the target circle set contains {circle center position, circle radius, weight, first-level flexibility resource 1, ..., first-level flexibility resource n, second-level flexibility resource 1, ..., second-level flexibility resource m, third-level flexibility resource 1, ..., third-level flexibility resource b}, which respectively represent n first-level flexibility resources, m second-level flexibility resources, and b third-level flexibility resources. It should be noted that the weight corresponding to each circle in the target circle set is the sum of the weights of the first flexibility resource and the second flexibility resource in each circle.

[0123] If the difference between the real-time output data of the first-level flexibility resources and the second-level flexibility resources in the virtual power plant and the load demand is greater than the preset threshold, the first-level flexibility resources and the second-level flexibility resources in the constructed target circle are used to schedule the flexibility resources so that the real-time output data meets the load demand.

[0124] The preset threshold can be set based on demand.

[0125] In an embodiment of the present disclosure, if the difference between the real-time output data of the first-level flexibility resources and the second-level flexibility resources in the virtual power plant and the load demand is greater than a preset threshold, it indicates that the real-time output data of the first-level flexibility resources and the second-level flexibility resources far meet the load demand. At this time, there is no need for the third-level flexibility resources to participate in the scheduling. The first-level flexibility resources and the second-level flexibility resources in the constructed target circle can be directly used to schedule the flexibility resources, so that the real-time output data can meet the load demand.

[0126] In the embodiment of the present disclosure, after calculating the weights of the energy storage power station set, the building temperature control set, and the industrial production line set, the peak load power is used to give the real-time peak load output according to the weights. E (i.e. load demand), if the real-time amount of the first-level and second-level flexible resources in the virtual power plant (i.e. real-time output data) E is much greater than G E (that is, the difference between the real-time output data and the load demand is greater than the preset threshold), the scheduling task can be completed without considering the third-level flexibility resources, that is, the first-level flexibility resources and the second-level flexibility resources in the constructed target circle are used to schedule flexibility resources so that the real-time output data meets the load demand.

[0127] In an optional implementation, based on the total weight of the flexibility resources in each circle in the target circle set, the first-level flexibility resources and second-level flexibility resources in the circle with a large total weight are preferentially selected to participate in the flexibility resource scheduling so that their real-time output data meets the load demand.

[0128] The total weight of the flexibility resources within the circle refers to the sum of the weights of the first-level flexibility resources and the second-level flexibility resources included in the circle.

[0129] In the embodiment of the present disclosure, by analyzing the total weight of the flexibility resources in each circle in the target circle set, the first-level flexibility resources and the second-level flexibility resources in the circle with the larger total weight are selected to participate in the flexibility resource scheduling, so as to maximize the resource utilization efficiency while meeting the load demand, effectively cope with fluctuations in power demand, and enhance the flexibility and stability of the power system.

[0130] If the difference between the real-time output data of the first-level flexibility resources and the second-level flexibility resources in the virtual power plant and the load demand is not greater than the preset threshold, the first-level flexibility resources, second-level flexibility resources and third-level flexibility resources in the constructed target circle are used to schedule flexibility resources so that the real-time output data meets the load demand.

[0131] If the difference between the real-time output data of the first-level flexibility resources and the second-level flexibility resources in the virtual power plant and the load demand is not greater than the preset threshold, that is, E is not much greater than G E In this case, the third level of flexibility resources is required to provide the scheduling real-time quantity ΔG E =G E -E. After issuing a scheduling task, allow third-level flexibility resources to participate in scheduling.

[0132] In an optional implementation, each circle in the target circle set is used as an intelligent entity, and the first-level flexibility resources and second-level flexibility resources in the target circle set are started to perform flexibility resource scheduling so that the real-time output data of the first-level flexibility resources and the second-level flexibility resources meet the load requirements.

[0133] In the embodiment of the present disclosure, each circle in the target circle set is taken as an intelligent body, and the circles in the target circle set are first sorted from large to small according to their weights, and then the first-level flexibility resource and the second-level flexibility resource with the earliest joining time are selected from each circle in turn until the real-time output data of the selected first-level flexibility resource and the second-level flexibility resource meet the load requirements.

[0134] In the embodiment of the present disclosure, an introduction is made by taking a target circle set including three circles R1, R2, and R3 as an example. First, the circles in each target circle set are sorted from large to small according to their weights. Assuming that the weight of R1 is greater than the weight of R2, which is greater than the weight of R3, then according to the order of the time of joining of the flexibility resources, a first-level flexibility resource and a second-level flexibility resource with the earliest joining time are selected from R1, and then a first-level flexibility resource and a second-level flexibility resource with the earliest joining time are selected from R2, and then a first-level flexibility resource and a second-level flexibility resource with the earliest joining time are selected from R3, and then the step of selecting a first-level flexibility resource and a second-level flexibility resource with the earliest joining time from R1 is continued until the real-time output data of the first-level flexibility resources and the second-level flexibility resources meet the load requirements.

[0135] Furthermore, the flexibility resource scheduling device can also monitor in real time whether there are third-level flexibility resources added to the target circle set, whether there are flexibility resources in the target circle set that have reached the minimum remaining power and need to exit the scheduling task, and whether there are flexibility resources in the target circle set that have reached the declared adjustable total power and thus exit the scheduling task, so that when the real-time output data of the first-level flexibility resources and the second-level flexibility resources do not meet the load demand, flexibility resource scheduling can be performed based on the third-level flexibility resources to meet the load demand.

[0136] Specifically, each circle in the target circle set is an intelligent agent. Through self-monitoring and information exchange, these agents coordinate scheduling. These agents first activate first- and second-level flexibility resources for flexible resource scheduling, and begin outputting energy in increments according to a sampling period Ts. Simultaneously, as the scheduling task progresses, the agent continuously monitors whether electric vehicles (i.e., third-level flexibility resources) within the circle have activated and participated in the scheduling task; whether any first-level flexibility resources within the circle have reached their minimum remaining charge and need to exit the scheduling task; and whether any second-level flexibility resources within the circle have reached their declared total adjustable charge and need to exit the scheduling task. The agent then calculates the energy output within this sampling period in real time.

[0137] Agents communicate with each other, publishing their real-time calculated output energy values ​​for the sampling period. Each agent subscribes to this information to understand the overall scheduling status of the virtual power plant during that sampling period. Obviously, as more and more electric vehicles are added to the dynamic scheduling, the energy output (i.e., real-time output data) will far exceed the actual energy required (i.e., load demand). Therefore, each agent needs to coordinate and control the electric vehicles within its scheduling to ensure that the energy output meets the actual energy demand.

[0138] It should be noted that if the flexibility resources within the area under the jurisdiction of the virtual power plant cannot be added to the circle set, this part of the flexibility resources can assume the role of the third-level flexibility resources and participate in scheduling.

[0139] In the disclosed embodiment, the parameters of the peak-shaving capacity of the flexibility resources are first determined, and then the feasible domain of aggregation is calculated, and finally the scheduling task within the jurisdiction of the virtual power plant is collaboratively completed.

[0140] For example, take the peak load scheduling task as an example:

[0141] At time t, the power P of the virtual power plant participating in the system peak regulation t :

[0142]

[0143] Among them, N r is the number of circles participating in peak regulation in the target circle concentration, n i is the number of first-level flexible resources participating in peak load regulation within the circle, m i is the number of second-level flexible resources participating in peak load regulation within the circle, b i is the number of electric vehicles participating in peak load regulation within the circle whose starting time (i.e., the time when they start participating in the scheduling task) is less than time t; is the maximum charging power of a first-level flexible resource participating in peak load regulation within the circle, P mj2 is the charging power of a second-level flexibility resource participating in peak load regulation within the circle; P bdchj3 It is the charging power of an electric vehicle participating in peak load regulation within the circle whose starting time is less than time t.

[0144] In the embodiment of the present disclosure, through the above-mentioned collaborative peak-shaving method, the power P of the virtual power plant participating in the system peak-shaving is calculated and adjusted at each specific moment. t , ensuring that it approaches the power curve specified by the peak-shaving task, can achieve accurate response to the peak-shaving demand of the power grid load, and ensure that the output power is basically consistent with the peak-shaving target curve, thereby improving the flexibility and stability of peak-shaving.

[0145] In practical applications, taking the dispatch task of peak regulation as an example, the energy storage and large load contained in the virtual power plant are used as the first-level flexible peak regulation resources, and the rated capacity, charging and discharging speed and power load change rate are used as parity indicators to give the weight of coordinated peak regulation; each time the system peak regulation is carried out, the energy storage power station is selected according to the current status parameters of each energy storage power station; the location of the energy storage power station where the energy storage power station is concentrated is used as the center of the circle, and the area is divided by the circumscribed circle, and the ratio of the weight is the ratio of the circumscribed circle radius; in the area outside the circumscribed circle, according to the amount of electricity required for peak regulation, the large load is selected according to the size of the peak regulation capacity, forming a set of energy storage power stations and large loads used for this peak regulation; The position of the large load where the large load is concentrated is the center of the circle, and the area is divided by the circumscribed circle, and the ratio of the weights is the ratio of the radii of the circumscribed circle; in this way, the area under the jurisdiction of the virtual power plant is divided into many circles of different radii and tangent to each other, and the capacity and economic cost of other small flexible resources in each circle are calculated, and added to the capacity and economic cost values ​​of the circle; the proportion of the peak-shaving output of each circle is calculated according to the capacity and economic cost values ​​of each circle, and the peak-shaving process of the load and equipment in each circle is started according to this result. It can be seen that the embodiment of the present disclosure provides an aggregated scheduling strategy for the participation of flexible resources of a virtual power plant in peak-shaving, which enables the virtual power plant to better perform system peak-shaving from the perspectives of multiple levels and different economic benefits and capabilities.

[0146] In the flexibility resource scheduling method for a virtual power plant provided by an embodiment of the present disclosure, a scheduling task for the flexibility resources of the virtual power plant is received, the load demand corresponding to the scheduling task is determined, and based on the relationship between the real-time output data and the load demand of the first-level flexibility resources and the second-level flexibility resources in the virtual power plant, the flexibility resource scheduling is performed using the constructed target circle set so that the real-time output data meets the load demand, wherein the target circle set is obtained by dividing the flexibility resources in the area under the jurisdiction of the virtual power plant based on the weights, the first-level flexibility resources include commercial energy storage, and the second-level flexibility resources include building temperature control and industrial production lines. It can be seen that the present disclosure performs flexibility resource scheduling based on the target circle set obtained by dividing the flexibility resources in the area under the jurisdiction of the virtual power plant based on the weights, so that the real-time output data meets the load demand, thereby improving the overall scheduling efficiency of the virtual power plant.

[0147] Based on the above method embodiment, the present disclosure also provides a flexibility resource scheduling device for a virtual power plant, referring to Figure 2 , is a structural diagram of a flexible resource scheduling device for a virtual power plant provided by an embodiment of the present disclosure, the device comprising:

[0148] A determination module 201 is configured to receive a scheduling task for flexibility resources of a virtual power plant and determine a load demand corresponding to the scheduling task;

[0149] The scheduling module 202 is used to schedule flexibility resources based on the relationship between the real-time output data of the first-level flexibility resources and the second-level flexibility resources in the virtual power plant and the load demand, using the constructed target circle set to make the real-time output data meet the load demand; wherein, the target circle set is obtained by dividing the flexibility resources in the area under the jurisdiction of the virtual power plant based on the weights, the first-level flexibility resources include commercial energy storage, and the second-level flexibility resources include building temperature control and industrial production lines.

[0150] In an optional implementation, a construction module is used in the process of constructing the target circle set, and the construction module includes:

[0151] A first determination submodule is configured to determine weights corresponding to each first-level flexibility resource and each second-level flexibility resource based on capacity and economic cost;

[0152] a merging submodule, configured to merge the first-level flexibility resources and the second-level flexibility resources into a target point set in descending order of the weights;

[0153] a partitioning submodule, configured to partition the area governed by the virtual power plant based on the target point set to obtain a first circle set;

[0154] The second determination submodule is used to add the third-level flexibility resources that meet the scheduling task to the first circle set to obtain the target circle set; wherein, the third-level flexibility resources that meet the scheduling task are third-level flexibility resources whose time to start participating in the scheduling task is less than the time of the current scheduling task, and the time to start participating in the scheduling task is determined based on the economic cost of the third-level flexibility resources, and the third-level flexibility resources include electric vehicles.

[0155] In an optional embodiment, the division submodule is used to

[0156] Selecting two points from the head of the target point set, and constructing two tangent circles with the two points as the centers; wherein the radii of the two circles are determined based on the distance between the two points and the weights of the flexibility resources corresponding to the two points;

[0157] Selecting the next point from the beginning to the end of the target point set in descending order of the weights, and if the point is within the two circles, adding the flexibility resource corresponding to the point to the corresponding circle;

[0158] If the point is not within the two circles, determine a circle with the smallest distance from the point to the centers of the two circles, and construct a circumscribed circle of the circle with the smallest distance, with the point as the center.

[0159] Repeat the step of continuously selecting the next point from the head to the tail of the target point set until all elements in the target point set are processed.

[0160] In an optional embodiment, the second determining submodule is used to

[0161] If the third-level flexibility resource that meets the scheduling task is within the first circle set, then adding the third-level flexibility resource that meets the scheduling task to the corresponding circle;

[0162] If the third-level flexibility resource that meets the scheduling task is not located in the first circle set, the third-level flexibility resource that meets the scheduling task will be added to the circle with the smallest distance based on the distance from its location to the center of each circle in the first circle set.

[0163] In an optional implementation, the scheduling module 202 is used to

[0164] a first scheduling submodule for scheduling flexibility resources using the first-level flexibility resources and the second-level flexibility resources in the constructed target circle set when the difference between the real-time output data of the first-level flexibility resources and the second-level flexibility resources in the virtual power plant and the load demand is greater than a preset threshold, so that the real-time output data meets the load demand;

[0165] The second scheduling submodule is used to schedule flexibility resources using the first-level flexibility resources, second-level flexibility resources and third-level flexibility resources in the constructed target circle when the difference between the real-time output data of the first-level flexibility resources and the second-level flexibility resources in the virtual power plant and the load demand is no more than a preset threshold, so that the real-time output data meets the load demand.

[0166] In an optional implementation manner, the first scheduling submodule is specifically configured to

[0167] Based on the total weight of the flexibility resources in each circle in the target circle set, the first-level flexibility resources and second-level flexibility resources in the circle with large total weight are preferentially selected to participate in the flexibility resource scheduling so that their real-time output data can meet the load demand.

[0168] In an optional embodiment, the second scheduling submodule is specifically configured to

[0169] Taking each circle in the target circle set as an intelligent agent, activating the first-level flexibility resources and the second-level flexibility resources in the target circle set to perform flexibility resource scheduling, so that the real-time output data of the first-level flexibility resources and the second-level flexibility resources meet the load demand;

[0170] Real-time monitoring is performed to determine whether third-level flexibility resources are added to the target circle set, whether flexibility resources in the target circle set have reached the minimum remaining power and need to exit the scheduling task, and whether flexibility resources in the target circle set have reached the declared total adjustable power and thus exit the scheduling task, so as to perform flexibility resource scheduling based on the third-level flexibility resources to meet the load demand when the real-time output data of the first-level flexibility resources and the second-level flexibility resources do not meet the load demand.

[0171] In the flexibility resource scheduling device of the virtual power plant provided by the embodiment of the present disclosure, a scheduling task for the flexibility resources of the virtual power plant is received, the load demand corresponding to the scheduling task is determined, and based on the relationship between the real-time output data and the load demand of the first-level flexibility resources and the second-level flexibility resources in the virtual power plant, the flexibility resource scheduling is performed using the constructed target circle set so that the real-time output data meets the load demand, wherein the target circle set is obtained by dividing the flexibility resources in the area under the jurisdiction of the virtual power plant based on the weights, the first-level flexibility resources include commercial energy storage, and the second-level flexibility resources include building temperature control and industrial production lines. It can be seen that the present disclosure performs flexibility resource scheduling based on the target circle set obtained by dividing the flexibility resources in the area under the jurisdiction of the virtual power plant based on the weights, so that the real-time output data meets the load demand, thereby improving the overall scheduling efficiency of the virtual power plant.

[0172] In addition to the above-mentioned methods and devices, the embodiments of the present disclosure also provide a computer-readable storage medium, which stores instructions. When the instructions are executed on a terminal device, the terminal device implements the flexibility resource scheduling method of the virtual power plant described in the embodiments of the present disclosure.

[0173] An embodiment of the present disclosure also provides a computer program product, which includes a computer program / instructions. When the computer program / instructions are executed by a processor, the flexibility resource scheduling method of the virtual power plant described in the embodiment of the present disclosure is implemented.

[0174] In addition, the present disclosure also provides a flexible resource scheduling device for a virtual power plant, see Figure 3 As shown, this may include:

[0175] Processor 301, memory 302, input device 303 and output device 304. The number of processors 301 in the flexibility resource scheduling device of the virtual power plant can be one or more. Figure 3 In some embodiments of the present disclosure, the processor 301, the memory 302, the input device 303 and the output device 304 may be connected via a bus or other means, wherein: Figure 3The bus connection is taken as an example.

[0176] The memory 302 can be used to store software programs and modules. The processor 301 executes various functional applications and data processing of the flexibility resource scheduling device of the virtual power plant by running the software programs and modules stored in the memory 302. The memory 302 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function, etc. In addition, the memory 302 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage device. The input device 303 can be used to receive input digital or character information, and to generate signal input related to user settings and function control of the flexibility resource scheduling device of the virtual power plant.

[0177] Specifically in this embodiment, the processor 301 will load the executable files corresponding to the processes of one or more applications into the memory 302 in accordance with the following instructions, and the processor 301 will run the applications stored in the memory 302, thereby realizing the various functions of the flexibility resource scheduling device of the above-mentioned virtual power plant.

[0178] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0179] The foregoing description is intended only to provide specific embodiments of the present disclosure, intended to enable those skilled in the art to understand and implement the present disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the embodiments described herein, but rather to be construed in the broadest manner consistent with the principles and novel features disclosed herein.

Claims

1. A flexibility resource scheduling method for a virtual power plant, characterized in that: The method comprises: Receiving a scheduling task for a flexibility resource of a virtual power plant and determining a load demand corresponding to the scheduling task; Based on the relationship between the real-time output data of the first-level flexibility resources and the second-level flexibility resources in the virtual power plant and the load demand, the constructed target circle set is used to schedule flexibility resources so that the real-time output data meets the load demand; wherein, the target circle set is obtained by dividing the flexibility resources based on the weights of the flexibility resources in the area under the jurisdiction of the virtual power plant, the first-level flexibility resources include commercial energy storage, and the second-level flexibility resources include building temperature control and industrial production lines.

2. The method according to claim 1, characterized in that The process of constructing the target circle set includes: Determine the weights of each first-tier flexibility resource and each second-tier flexibility resource based on capacity and economic cost; Merging the first-level flexibility resources and the second-level flexibility resources into a target point set in descending order of the weights; Dividing the area governed by the virtual power plant based on the target point set to obtain a first circle set; The third-level flexibility resources that meet the scheduling task are added to the first circle set to obtain the target circle set; wherein, the third-level flexibility resources that meet the scheduling task are third-level flexibility resources whose time of starting to participate in the scheduling task is less than the time of the current scheduling task, and the time of starting to participate in the scheduling task is determined based on the economic cost of the third-level flexibility resources, and the third-level flexibility resources include electric vehicles.

3. The method according to claim 2, characterized in that The area governed by the virtual power plant is divided based on the target point set to obtain a first circle set, including: Selecting two points from the head of the target point set, and constructing two tangent circles with the two points as the centers; wherein the radii of the two circles are determined based on the distance between the two points and the weights of the flexibility resources corresponding to the two points; Selecting the next point from the beginning to the end of the target point set in descending order of the weights, and if the point is within the two circles, adding the flexibility resource corresponding to the point to the corresponding circle; If the point is not within the two circles, determine a circle with the smallest distance from the point to the centers of the two circles, and construct a circumscribed circle of the circle with the smallest distance, with the point as the center. Repeat the step of continuously selecting the next point from the head to the tail of the target point set until all elements in the target point set are processed.

4. The method according to claim 2, characterized in that The step of adding the third-level flexibility resources that meet the scheduling task to the first circle set to obtain a target circle set includes: If the third-level flexibility resource that meets the scheduling task is within the first circle set, then adding the third-level flexibility resource that meets the scheduling task to the corresponding circle; If the third-level flexibility resource that meets the scheduling task is not located in the first circle set, the third-level flexibility resource that meets the scheduling task will be added to the circle with the smallest distance based on the distance from its location to the center of each circle in the first circle set.

5. The method according to claim 1, wherein The scheduling of the flexible resources using the constructed target circle set based on the relationship between the real-time output data of the first-level flexible resources and the second-level flexible resources in the virtual power plant and the load demand so that the real-time output data meets the load demand includes: If the difference between the real-time output data of the first-level flexibility resources and the second-level flexibility resources in the virtual power plant and the load demand is greater than a preset threshold, the first-level flexibility resources and the second-level flexibility resources in the constructed target circle are used to perform flexibility resource scheduling so that the real-time output data meets the load demand; If the difference between the real-time output data of the first-level flexibility resources and the second-level flexibility resources in the virtual power plant and the load demand is not greater than a preset threshold, the first-level flexibility resources, second-level flexibility resources and third-level flexibility resources in the constructed target circle are used to schedule flexibility resources so that the real-time output data meets the load demand.

6. The method according to claim 5, characterized in that The utilizing the first-level flexibility resources and the second-level flexibility resources in the constructed target circle set to perform flexibility resource scheduling so that the real-time output data meets the load demand includes: Based on the total weight of the flexibility resources in each circle in the target circle set, the first-level flexibility resources and second-level flexibility resources in the circle with large total weight are preferentially selected to participate in the flexibility resource scheduling so that their real-time output data can meet the load demand.

7. The method according to claim 5, characterized in that The utilizing the first-level flexibility resources, the second-level flexibility resources, and the third-level flexibility resources in the constructed target circle set to perform flexibility resource scheduling so that the real-time output data meets the load demand includes: Taking each circle in the target circle set as an intelligent agent, activating the first-level flexibility resources and the second-level flexibility resources in the target circle set to perform flexibility resource scheduling, so that the real-time output data of the first-level flexibility resources and the second-level flexibility resources meet the load demand; Real-time monitoring is performed to determine whether third-level flexibility resources are added to the target circle set, whether flexibility resources in the target circle set have reached the minimum remaining power and need to exit the scheduling task, and whether flexibility resources in the target circle set have reached the declared total adjustable power and thus exit the scheduling task, so as to perform flexibility resource scheduling based on the third-level flexibility resources to meet the load demand when the real-time output data of the first-level flexibility resources and the second-level flexibility resources do not meet the load demand.

8. A flexible resource scheduling device for a virtual power plant, characterized in that: The device comprises: a determination module, configured to receive a scheduling task for flexibility resources of a virtual power plant and determine a load demand corresponding to the scheduling task; A scheduling module is used to schedule flexibility resources based on the relationship between the real-time output data of the first-level flexibility resources and the second-level flexibility resources in the virtual power plant and the load demand, using the constructed target circle set to make the real-time output data meet the load demand; wherein, the target circle set is obtained by dividing the flexibility resources in the area under the jurisdiction of the virtual power plant based on the weights, the first-level flexibility resources include commercial energy storage, and the second-level flexibility resources include building temperature control and industrial production lines.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores instructions, and when the instructions are executed on a terminal device, the terminal device implements the method according to any one of claims 1 to 7.

10. A flexible resource scheduling device for a virtual power plant, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

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