Virtual power plant internal resource calling method and device based on frequency modulation potential evaluation, medium and product

Abstract

The invention discloses a virtual power plant internal resource calling method and device based on frequency modulation potential evaluation, a medium and a product, and relates to the field of virtual power plant resource calling, and the method comprises the steps: determining a resource object which can be called and participates in frequency modulation in a virtual power plant at the current moment; calculating a frequency modulation evaluation index of each resource object; the frequency modulation evaluation indexes comprise rated power, response time, response speed, response precision, capacity capable of being adjusted up and capacity capable of being adjusted down; determining a comprehensive evaluation index of each resource object by adopting an analytic hierarchy process according to the frequency modulation evaluation index of each resource object; sequentially calling the resource objects to participate in frequency modulation according to a descending order of the comprehensive evaluation indexes of the resource objects until a set condition is met, and calling the resource objects at the next moment; the set condition is that the set frequency modulation requirement is met or all the resource objects at the current moment are called. The method and the device can quickly and accurately realize the calling of the internal resources of the virtual power plant.

Description

Technical Field

[0001] The present application relates to the field of virtual power plant resource calling, and in particular to a method, device, medium and product for calling internal resources of a virtual power plant based on frequency regulation potential assessment. Background Art

[0002] As the proportion of renewable energy such as wind power and solar energy in the energy structure gradually increases, the power system faces a series of new challenges. The uncontrollable and intermittent characteristics of new energy increase the volatility of the power system frequency, and the frequency regulation capability faces a greater test. The power system needs more flexible frequency regulation means to cope with the increasingly complex frequency fluctuations. Virtual power plants are a power coordination management system that uses advanced information and communication technologies and software systems to achieve the aggregation and coordinated optimization of distributed energy resources 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. Virtual power plants can mobilize and integrate various internal resources to provide faster and more accurate frequency regulation services to meet the system's demand for increasing frequency regulation capabilities. Using virtual power plants to participate in frequency regulation scenarios can achieve large-scale consumption of renewable energy and smooth access to the power grid. By flexibly dispatching the internal resources of virtual power plants, the frequency fluctuation problem caused by the volatility of new energy can be effectively solved, helping to achieve the stable operation of the power system and promoting the construction and development of a new power system with new energy as the main body.

[0003] When virtual power plants currently participate in frequency regulation scenarios, the strategies and algorithms for internal resource calls include the following: (1) prediction and response algorithms; (2) control algorithms based on model prediction; (3) energy storage and release strategies; (4) frequency response market participation strategies. The above strategies and algorithms for internal resource calls are relatively complex and the evaluation indicators considered are relatively simple. Therefore, how to quickly and accurately call the internal resources of virtual power plants has become a problem that needs to be solved urgently. Summary of the invention

[0004] The purpose of this application is to provide a method, device, medium and product for calling internal resources of a virtual power plant based on frequency regulation potential assessment, which can quickly and accurately realize the calling of internal resources of a virtual power plant.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In a first aspect, the present application provides a method for calling internal resources of a virtual power plant based on frequency regulation potential assessment, including:

[0007] Determine the resource objects that can be called to participate in frequency regulation within the virtual power plant at the current moment;

[0008] Calculate frequency modulation evaluation indicators for each resource object; the frequency modulation evaluation indicators include: rated power, response time, response speed, response accuracy, adjustable capacity, and adjustable capacity;

[0009] According to the frequency modulation evaluation index of each resource object, the hierarchical analysis method is used to determine the comprehensive evaluation index of each resource object;

[0010] According to the order of comprehensive evaluation indicators of each resource object from large to small, the resource objects are called in turn to participate in frequency modulation until the set conditions are met, and then the resource objects at the next moment are called; the set conditions are that the set frequency modulation requirements are met or all resource objects at the current moment are called.

[0011] Optionally, the rated power is equal to the power capacity configured by the resource object when participating in frequency modulation;

[0012] The calculation formula of the response time is:

[0013] T pre_n =T p2_n -T p1_n ;

[0014] Among them, T pre_n Indicates the response time of the nth resource object; T p1_n Indicates that the nth resource object has stepped out of P 0_n The adjustment dead zone time; T p2_n Indicates that the nth resource object enters P AGC_n The adjustment dead zone time; P 0_n Indicates the current output of the nth resource object; P AGC_n Indicates the frequency modulation instruction target value of the nth resource object;

[0015] The calculation formula of the response speed is:

[0016]

[0017] Among them, V AGC_n Indicates the response speed of the nth resource object;

[0018] The calculation formula of the response accuracy is:

[0019]

[0020] Among them, δ p_n Indicates the response accuracy of the nth resource object; P 1_n Indicates the output of the nth resource object after completing the frequency modulation command response; ΔP n Indicates the adjustment error allowed for the nth resource object;

[0021] The calculation formula for the adjustable capacity is:

[0022] Cap up_n =P upmax_n -P 0_n ;

[0023] Among them, Cap up_n Indicates the adjustable capacity of the nth resource object; P upmax_n Indicates the maximum output of the nth resource object considering the maximum upward climbing rate;

[0024] The calculation formula for the adjustable capacity is:

[0025] Cap dn_n =P 0_n -P dnmax_n ;

[0026] Among them, Cap dn_n Indicates the capacity that can be reduced for the nth resource object; P dnmax_n Indicates the minimum output of the nth resource object considering the maximum downward climbing rate.

[0027] Optionally, according to the frequency modulation evaluation index of each resource object, a hierarchical analysis method is used to determine the comprehensive evaluation index of each resource object, specifically including:

[0028] For any resource object, the frequency modulation evaluation index is normalized to obtain a normalized frequency modulation evaluation index;

[0029] For any resource object, the analytic hierarchy process is used to determine the weight of the frequency modulation evaluation index, and based on the normalized frequency modulation evaluation index and the weight, the weighted summation method is used to determine the comprehensive evaluation index of the resource object.

[0030] Optionally, the calculation formula of the comprehensive evaluation index is:

[0031]

[0032] Among them, Y n Represents the comprehensive evaluation index of the nth resource object; Indicates the normalized rated power of the nth resource object; Indicates the normalized response time of the nth resource object; Indicates the normalized response speed of the nth resource object; Indicates the normalized response accuracy of the nth resource object; Indicates the normalized increase capacity of the nth resource object; It represents the normalized capacity that can be adjusted down for the nth resource object; k1 represents the weight of the rated power; k2 represents the weight of the response time; k3 represents the weight of the response speed; k4 represents the weight of the response accuracy; k5 represents the weight of the capacity that can be adjusted up; and k6 represents the weight of the capacity that can be adjusted down.

[0033] Optionally, the weights of the frequency modulation evaluation indicators satisfy 0≤k1,k2,k3,k4,k5,k6≤1 and k1+k2+k3+k4+k5+k6=1.

[0034] Optionally, before determining the resource objects that can be called to participate in frequency regulation in the virtual power plant at the current moment, the method further includes:

[0035] Determine whether the virtual power plant is participating in frequency regulation scenarios at the current moment;

[0036] If so, determine that the resource objects that can be called to participate in frequency regulation in the virtual power plant at the current moment; otherwise, update the current moment and return to the step of determining whether the virtual power plant at the current moment participates in frequency regulation scenarios.

[0037] Optionally, for any resource object, the frequency modulation evaluation index is normalized to obtain a normalized frequency modulation evaluation index, which specifically includes:

[0038] For any resource object, the maximum-minimum normalization method is used to normalize the frequency modulation evaluation index to obtain a normalized frequency modulation evaluation index.

[0039] In a second aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any of the above-mentioned methods for calling internal resources of a virtual power plant based on frequency regulation potential assessment.

[0040] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-mentioned methods for calling internal resources of a virtual power plant based on frequency regulation potential assessment.

[0041] In a fourth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements any of the above-mentioned methods for calling internal resources of a virtual power plant based on frequency regulation potential assessment.

[0042] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0043] The present application provides a method, device, medium and product for calling the internal resources of a virtual power plant based on frequency regulation potential assessment. The method determines the resource objects that can be called to participate in frequency regulation, calculates the frequency regulation evaluation index of each resource object, and determines the comprehensive evaluation index of each resource object by adopting the hierarchical analysis method. The potential for participating in frequency regulation scenarios is evaluated, and the internal resources of the virtual power plant are called according to the ranking of the comprehensive evaluation index. The frequency regulation scenarios and their comprehensive potential assessment capabilities are taken into consideration, and the calling of the internal resources of the virtual power plant is realized quickly and accurately. The problem of how to call internal resource objects when the virtual power plant participates in frequency regulation scenarios is solved in a scientific and efficient manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0045] Figure 1 This is an application environment diagram of a virtual power plant internal resource calling method based on frequency regulation potential assessment in an embodiment of the present application;

[0046] Figure 2 A flow chart of a method for calling internal resources of a virtual power plant based on frequency regulation potential assessment provided in one embodiment of the present application;

[0047] Figure 3 A configuration flow chart of a method for calling internal resources of a virtual power plant based on frequency regulation potential assessment provided in an embodiment of the present application;

[0048] Figure 4 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0050] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0051] First, several relevant internal resource calling strategy algorithms are introduced.

[0052] (1) Prediction and response algorithm: using data analysis and prediction technology to monitor and predict power demand and energy resources in real time, and calling internal resources through intelligent scheduling algorithms to achieve rapid adjustment of system frequency. However, this method has high requirements on data prediction accuracy and large data requirements, and is relatively complex.

[0053] (2) Based on the model prediction control algorithm, the system dynamics model and control theory are combined to design advanced control algorithms such as model predictive control to achieve precise regulation of the internal resources of the virtual power plant. However, this method is relatively complex to establish the model of the internal resource objects.

[0054] (3) Energy storage and release strategy: Utilize various energy storage devices to implement energy storage and release strategies according to system frequency requirements to quickly adjust system frequency. However, this method mainly considers energy storage devices and lacks consideration of other available resources.

[0055] (4) Frequency response market participation strategy: Based on real-time market signals and demand response requirements, a dynamic resource call strategy is formulated to effectively improve frequency regulation services and maximize benefits. However, this method is greatly affected by market environment conditions and lacks consideration of technical performance.

[0056] Therefore, this application aims to solve the problem of how to call internal resource objects when a virtual power plant participates in frequency regulation scenarios. By sorting out the number of callable resource objects, frequency regulation indicators and conducting a comprehensive assessment of the potential of frequency regulation scenarios, the call is made according to the ranking of the comprehensive evaluation indicators. A method, equipment, medium and product for calling internal resources of a virtual power plant based on frequency regulation potential assessment are proposed.

[0057] The method for calling internal resources of a virtual power plant based on frequency regulation potential assessment provided in the embodiment of the present application can be applied to Figure 1In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be set up separately, integrated on the server 104, or placed on the cloud or other servers. The terminal 102 can send the resource objects that can be called to participate in frequency modulation within the virtual power plant at the current moment to the server 104. After the server 104 receives the resource objects that can be called to participate in frequency modulation within the virtual power plant at the current moment, for each resource object, the server 104 calculates the frequency modulation evaluation index of each resource object; according to the frequency modulation evaluation index of each resource object, the hierarchical analysis method is used to determine the comprehensive evaluation index of each resource object; according to the order of the comprehensive evaluation index of each resource object from large to small, the resource objects are called in turn to participate in frequency modulation until the set conditions are met, and the resource object at the next moment is called. The server 104 can feedback the call result of the obtained resource object to the terminal 102.

[0058] In addition, in some embodiments, the method for calling internal resources of a virtual power plant based on frequency regulation potential assessment can also be implemented independently by the server 104 or the terminal 102. For example, the terminal 102 can directly perform calculations on the resource objects that can be called to participate in frequency regulation within the virtual power plant, or the server 104 can obtain the resource objects that can be called to participate in frequency regulation within the virtual power plant from the data storage system and perform calculations on the resource objects that can be called to participate in frequency regulation within the virtual power plant.

[0059] The terminal 102 may be, but is not limited to, various desktop computers, laptop computers, smart phones, tablet computers, IoT devices, and portable wearable devices. The IoT devices may be smart speakers, smart TVs, smart air conditioners, smart vehicle-mounted devices, etc. The portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers, or may be a cloud server.

[0060] In an exemplary embodiment, Figure 2 As shown, a method for calling internal resources of a virtual power plant based on frequency regulation potential assessment is provided. The method is executed by a computer device, and can be executed by a computer device such as a terminal or a server alone, or by a terminal and a server together. In the embodiment of the present application, the method is applied to Figure 1 The server 104 in the example is used as an example to illustrate the method, which includes the following steps 201 to 204. Among them:

[0061] Step 201, determine the resource objects that can be called to participate in frequency regulation within the virtual power plant at the current moment.

[0062] Step 202, calculate the frequency regulation evaluation index of each resource object; the frequency regulation evaluation index includes: rated power, response time, response speed, response accuracy, adjustable capacity and adjustable capacity.

[0063] Step 203, according to the frequency modulation evaluation index of each resource object, the comprehensive evaluation index of each resource object is determined by using the hierarchical analysis method.

[0064] Step 204, in descending order of the comprehensive evaluation index of each resource object, call the resource objects in sequence to participate in frequency modulation until the set conditions are met, and then call the resource objects at the next moment; the set conditions are that the set frequency modulation requirements are met or all resource objects at the current moment are called.

[0065] Among them, the frequency regulation demand can be set according to the operation status of the power grid area, and can be obtained according to the frequency and the exchange power of the interconnection line. The frequency regulation demand is set including the regional control deviation ACE.

[0066] The embodiment of the present application sorts out the number of callable resource objects, sets frequency regulation indicators for each internal resource, calculates the performance of relevant technical indicators, implements an evaluation of the potential for participation in frequency regulation scenarios, and calls the internal resources of the virtual power plant according to the ranking of comprehensive evaluation indicators. It takes into account frequency regulation scenarios and their comprehensive potential evaluation capabilities, and achieves a scientific and efficient solution to the problem of how to call internal resource objects when the virtual power plant participates in frequency regulation scenarios.

[0067] In another exemplary embodiment of the present application, in step 202, the rated power is equal to the power capacity configured by the resource object when participating in frequency modulation.

[0068] The calculation formula of the response time is:

[0069] T pre_n =T p2_n -T p1_n ;

[0070] Among them, T pre_n Indicates the response time of the nth resource object; T p1_n Indicates that the nth resource object has stepped out of P 0_n The adjustment dead zone time; T p2_n Indicates that the nth resource object enters P AGC_n The adjustment dead zone time; P 0_n Indicates the current output of the nth resource object; P AGC_n Indicates the frequency modulation instruction target value of the nth resource object.

[0071] The calculation formula of the response speed is:

[0072]

[0073] Among them, V AGC_n Indicates the response speed of the nth resource object.

[0074] The calculation formula of the response accuracy is:

[0075]

[0076] Among them, δ p_n Indicates the response accuracy of the nth resource object; P 1_n Indicates the output of the nth resource object after completing the frequency modulation command response; ΔP n It represents the allowable regulation error of the nth resource object, which is usually 1.5% of the rated output.

[0077] The calculation formula for the adjustable capacity is:

[0078] Cap up_n =P upmax_n -P 0_n ;

[0079] Among them, Cap up_n Indicates the adjustable capacity of the nth resource object; P upmax_n Indicates the maximum output of the nth resource object considering the maximum upward climbing rate.

[0080] The calculation formula for the adjustable capacity is:

[0081] Cap dn_n =P 0_n -P dnmax_n ;

[0082] Among them, Cap dn_n Indicates the capacity that can be reduced for the nth resource object; P dnmax_n Indicates the minimum output of the nth resource object considering the maximum downward climbing rate.

[0083] In another exemplary embodiment of the present application, step 203 specifically includes:

[0084] (1) For any resource object, the frequency modulation evaluation index is normalized to obtain a normalized frequency modulation evaluation index. Specifically, for any resource object, the frequency modulation evaluation index is normalized using a maximum-minimum normalization method to obtain a normalized frequency modulation evaluation index.

[0085] Among them, the calculation formula of the maximum-minimum normalization method is:

[0086]

[0087] In the formula, y1 * is the normalized value of the frequency regulation evaluation index with the larger value being preferred. The rated power, response speed, response accuracy, adjustable capacity and adjustable capacity are calculated according to this method; 2 * is the normalized value of the frequency modulation evaluation index with smaller value being preferred, and the response time is calculated according to this method; y min ,y max are the minimum and maximum values ​​of the sample data of the frequency modulation evaluation index respectively, and y is the value of the frequency modulation evaluation index to be calculated at this time.

[0088] (2) For any resource object, the weight of the frequency modulation evaluation index is determined by using the hierarchical analysis method, and the comprehensive evaluation index of the resource object is determined by using the weighted summation method based on the normalized frequency modulation evaluation index and the weight.

[0089] The calculation formula of the comprehensive evaluation index is:

[0090]

[0091] Among them, Y n Represents the comprehensive evaluation index of the nth resource object; Indicates the normalized rated power of the nth resource object; Indicates the normalized response time of the nth resource object; Indicates the normalized response speed of the nth resource object; Indicates the normalized response accuracy of the nth resource object; Indicates the normalized increase capacity of the nth resource object; represents the normalized down-adjustable capacity of the nth resource object; k1 represents the weight of the rated power; k2 represents the weight of the response time; k3 represents the weight of the response speed; k4 represents the weight of the response accuracy; k5 represents the weight of the up-adjustable capacity; k6 represents the weight of the down-adjustable capacity. Further, k1, k2, k3, k4, k5 and k6 can be obtained based on the principal hierarchy analysis method and with the opinions of experts in related fields. The weights of the frequency regulation evaluation indicators satisfy 0≤k1,k2,k3,k4,k5,k6≤1 and k1+k2+k3+k4+k5+k6=1.

[0092] In another exemplary embodiment of the present application, before step 201, it also includes: determining whether the virtual power plant at the current moment participates in a frequency regulation scenario; if so, determining the resource objects that can be called to participate in frequency regulation within the virtual power plant at the current moment, that is, executing step 201, otherwise updating the current moment, and returning to the step of determining whether the virtual power plant at the current moment participates in a frequency regulation scenario.

[0093] Combine the following Figure 3, an implementation process of the above-mentioned virtual power plant internal resource calling method based on frequency regulation potential assessment in practical application is introduced.

[0094] See also Figure 3 , the configuration process of this method is as follows:

[0095] (1) Determine the resource objects that can be called to participate in frequency regulation within the virtual power plant at time t (the initial value of t is 0). Assuming that there are N resource objects that can be called to participate in frequency regulation scenarios, the nth resource object is S n (n=1,2,3...,N).

[0096] (2) Calculate the nth resource object S n Frequency modulation evaluation indicators, including rated power P p_n , response time T pre_n , Response speed V AGC_n , Response accuracy δ p_n , adjustable capacity Cap up_n And adjustable capacity Cap dn_n The calculation formulas of each indicator will not be repeated here.

[0097] (3) Evaluate the potential of each internal resource to participate in frequency modulation scenarios.

[0098] The above frequency modulation evaluation indexes are normalized according to the maximum-minimum normalization method, and the specific process will not be repeated here.

[0099] The comprehensive evaluation index Y of each internal resource participating in frequency modulation is obtained by using the hierarchical analysis method. n The specific calculation formula will not be repeated here.

[0100] (4) Comprehensive evaluation index Y of each internal resource object involved in frequency modulation n Sort from large to small, and prioritize resource objects with large comprehensive evaluation indicators to participate in frequency modulation until the set conditions are met, and proceed to step (6).

[0101] (5) If the virtual power plant does not participate in the frequency regulation scenario at this moment, proceed to step (6).

[0102] (6) t = t + Δt. If t is greater than the required call time T, the process ends; otherwise, the process continues with step (1).

[0103] The method for calling internal resources of a virtual power plant based on frequency regulation potential assessment provided in the embodiment of the present application has the following advantages:

[0104] (1) Frequency regulation indicators are set for frequency regulation scenarios. The technical performance considered is comprehensive. The potential of the resource objects that can be called upon to participate in frequency regulation scenarios in the virtual power plant is evaluated based on the principal hierarchy analysis method based on expert experience. This method is simple to calculate and easy to operate.

[0105] (2) According to the comprehensive evaluation index of each internal callable resource object participating in frequency modulation, the objects are sorted from large to small according to the comprehensive performance, and the internal resource objects are called in sequence according to the ranking to meet the needs of frequency modulation scenarios. The better resources can be called first to meet the frequency modulation needs, which is easy to operate and can better meet the frequency modulation performance.

[0106] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store resource objects that can be called to participate in frequency modulation within the virtual power plant. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for calling internal resources of a virtual power plant based on frequency modulation potential assessment is implemented.

[0107] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0108] In an exemplary embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0109] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0110] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0111] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0112] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, etc., but is not limited thereto.

[0113] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0114] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for calling internal resources of a virtual power plant based on frequency regulation potential assessment, characterized in that: The method for calling internal resources of a virtual power plant based on frequency regulation potential assessment includes: Determine the resource objects that can be called to participate in frequency regulation within the virtual power plant at the current moment; Calculate frequency modulation evaluation indicators for each resource object; the frequency modulation evaluation indicators include: rated power, response time, response speed, response accuracy, adjustable capacity, and adjustable capacity; According to the frequency modulation evaluation index of each resource object, the hierarchical analysis method is used to determine the comprehensive evaluation index of each resource object; According to the order of comprehensive evaluation indicators of each resource object from large to small, the resource objects are called in turn to participate in frequency modulation until the set conditions are met, and then the resource objects at the next moment are called; the set conditions are that the set frequency modulation requirements are met or all resource objects at the current moment are called.

2. The method for calling internal resources of a virtual power plant based on frequency regulation potential assessment according to claim 1 is characterized in that: The rated power is equal to the power capacity configured by the resource object when participating in frequency modulation; The calculation formula of the response time is: T pre_n =T p2_n -T p1_n ; Among them, T pre_n Indicates the response time of the nth resource object; T p1_n Indicates that the nth resource object has stepped out of P 0_n The adjustment dead zone time; T p2_n Indicates that the nth resource object enters P AGC_n The adjustment dead zone time; P 0_n Indicates the current output of the nth resource object; P AGC_n Indicates the frequency modulation instruction target value of the nth resource object; The calculation formula of the response speed is: Among them, V AGC_n Indicates the response speed of the nth resource object; The calculation formula of the response accuracy is: Among them, δ p_n Indicates the response accuracy of the nth resource object; P 1_n Indicates the output of the nth resource object after completing the frequency modulation command response; ΔP n Indicates the adjustment error allowed for the nth resource object; The calculation formula for the adjustable capacity is: Cap up_n =P upmax_n -P 0_n ; Among them, Cap up_n Indicates the adjustable capacity of the nth resource object; P upmax_n Indicates the maximum output of the nth resource object considering the maximum upward climbing rate; The calculation formula for the adjustable capacity is: Cap dn_n =P 0_n -P dnmax_n ; Among them, Cap dn_n Indicates the capacity that can be reduced for the nth resource object; P dnmax_n Indicates the minimum output of the nth resource object considering the maximum downward climbing rate.

3. The method for calling internal resources of a virtual power plant based on frequency regulation potential assessment according to claim 1 is characterized in that: According to the frequency modulation evaluation index of each resource object, the hierarchical analysis method is used to determine the comprehensive evaluation index of each resource object, including: For any resource object, the frequency modulation evaluation index is normalized to obtain a normalized frequency modulation evaluation index; For any resource object, the analytic hierarchy process is used to determine the weight of the frequency modulation evaluation index, and based on the normalized frequency modulation evaluation index and the weight, the weighted summation method is used to determine the comprehensive evaluation index of the resource object.

4. The method for calling internal resources of a virtual power plant based on frequency regulation potential assessment according to claim 3 is characterized in that: The calculation formula of the comprehensive evaluation index is: Among them, Y n Represents the comprehensive evaluation index of the nth resource object; Indicates the normalized rated power of the nth resource object; Indicates the normalized response time of the nth resource object; Indicates the normalized response speed of the nth resource object; Indicates the normalized response accuracy of the nth resource object; Indicates the normalized increase capacity of the nth resource object; It represents the normalized capacity that can be adjusted down for the nth resource object; k1 represents the weight of the rated power; k2 represents the weight of the response time; k3 represents the weight of the response speed; k4 represents the weight of the response accuracy; k5 represents the weight of the capacity that can be adjusted up; and k6 represents the weight of the capacity that can be adjusted down.

5. The method for calling internal resources of a virtual power plant based on frequency regulation potential assessment according to claim 4 is characterized in that: The weights of frequency modulation evaluation indicators satisfy 0≤k1,k2,k3,k4,k5,k6≤1 and k1+k2+k3+k4+k5+k6=1.

6. The method for calling internal resources of a virtual power plant based on frequency regulation potential assessment according to claim 1 is characterized in that: Before determining the resource objects that can be called to participate in frequency regulation within the virtual power plant at the current moment, it also includes: Determine whether the virtual power plant is participating in frequency regulation scenarios at the current moment; If so, determine that the resource objects that can be called to participate in frequency regulation in the virtual power plant at the current moment; otherwise, update the current moment and return to the step of determining whether the virtual power plant at the current moment participates in frequency regulation scenarios.

7. The method for calling internal resources of a virtual power plant based on frequency regulation potential assessment according to claim 3 is characterized in that: For any resource object, the frequency modulation evaluation index is normalized to obtain a normalized frequency modulation evaluation index, which specifically includes: For any resource object, the maximum-minimum normalization method is used to normalize the frequency modulation evaluation index to obtain a normalized frequency modulation evaluation index.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for calling internal resources of a virtual power plant based on frequency regulation potential assessment as described in any one of claims 1-7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the method for calling internal resources of a virtual power plant based on frequency regulation potential assessment as described in any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, it implements the method for calling internal resources of a virtual power plant based on frequency regulation potential assessment as described in any one of claims 1 to 7.

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