Resource scheduling method and device based on virtual power plant, storage medium and computer device

Abstract

The application discloses a resource scheduling method and device based on a virtual power plant, a storage medium and computer equipment, and relates to the field of power resource scheduling. The method comprises the following steps: receiving a transaction demand from a dispatcher; determining a target resource pool in a plurality of preset resource pools according to a transaction type, wherein the target resource pool comprises a plurality of resources; monitoring the performance of each resource according to a transaction index requirement to obtain a performance parameter; comprehensively evaluating each resource according to the performance parameter to obtain an evaluation value, with the maximum overall benefit as a constraint condition; arranging each resource in the target resource pool in ascending order according to the evaluation value, and searching from the first resource until the transaction index requirement is met; generating a resource set based on the searched resource, and sending a control instruction to the resource set. The application can reduce the comprehensive transaction adjustment cost of the virtual power plant as much as possible while meeting the transaction index requirement of the virtual power plant, thereby optimizing the operation benefit of the virtual power plant.

Description

Technical Field

[0001] This application relates to the field of power resource dispatching, and in particular to a resource dispatching method, apparatus, storage medium and computer equipment based on a virtual power plant. Background Technology

[0002] A virtual power plant aggregates different types of distributed energy sources, such as distributed power sources, energy storage, and controllable loads, through advanced metering, communication, and control technologies without changing the grid connection mode of each distributed power source. It achieves coordinated and optimized operation of multiple DERs (Distributed Energy Resources) through a higher-level software architecture, providing ancillary services such as peak shaving, frequency regulation, and backup for the power grid, and providing users with an effective path to participate in the electricity market, thereby facilitating the rational and optimized allocation and utilization of resources.

[0003] The goal of virtual power plant operation and management is to rationally allocate resources to achieve maximum market benefits while comprehensively considering various market participation conditions and benefits. In addition to demand response and ancillary service market transactions, users can fully explore market potential by leveraging the flexibility of demand-side resources and the flexibility of supply and demand interaction. As operators of power aggregation services, virtual power plants should rationally allocate demand-side resources while comprehensively considering various market participation conditions and benefits. Achieving maximum market benefits through the optimized management of multiple resources is a pressing issue that needs to be addressed. Summary of the Invention

[0004] This application provides a resource scheduling method, apparatus, storage medium, and computer equipment based on a virtual power plant, which can solve the problem of how to schedule resources while satisfying the benefits of the virtual power plant. The technical solution is as follows:

[0005] In a first aspect, embodiments of this application provide a resource scheduling method based on a virtual power plant, the method comprising:

[0006] Receive transaction requests from the scheduler; wherein the transaction requests carry transaction type and transaction indicator requirements;

[0007] A target resource pool is determined from a set of preset resource pools based on the transaction type; wherein, the target resource pool includes multiple resources;

[0008] Performance parameters are obtained by monitoring the performance of each resource according to the aforementioned transaction indicator requirements.

[0009] With the constraint of maximizing overall benefit, an evaluation value is obtained by comprehensively evaluating each resource based on the performance parameters.

[0010] Based on the evaluation value, the resources in the target resource pool are sorted in ascending order, and the search starts from the first resource until the transaction indicator requirements are met;

[0011] A resource set is generated based on the searched resources, and control commands are sent to the resource set.

[0012] Secondly, embodiments of this application provide a resource scheduling device based on a virtual power plant, the device comprising:

[0013] The transceiver unit is used to receive transaction requests from the scheduler; wherein the transaction request carries the transaction type and transaction indicator requirements;

[0014] A determining unit is configured to determine a target resource pool from a set of preset resource pools based on the transaction type; wherein the target resource pool includes multiple resources;

[0015] The evaluation unit is used to monitor the performance of each resource according to the transaction indicator requirements to obtain performance parameters; and to comprehensively evaluate each resource according to the performance parameters with the constraint of maximizing overall revenue to obtain an evaluation value.

[0016] The search unit is used to sort the resources in the target resource pool in ascending order according to the evaluation value, and to search from the first resource until the transaction indicator requirements are met.

[0017] The scheduling unit is used to generate a resource set based on the searched resources and to send control commands to the resource set.

[0018] Thirdly, embodiments of this application provide a computer storage medium storing a plurality of instructions adapted for loading by a processor and executing the above-described method steps.

[0019] Fourthly, embodiments of this application provide a computer device, which may include: a processor and a memory; wherein the memory stores a computer program, the computer program being adapted to be loaded by the processor and to execute the above-described method steps.

[0020] The beneficial effects of the technical solutions provided in some embodiments of this application include at least the following:

[0021] Adaptable to various trading scenarios, it fully considers the specific indicators of various resources, including resource type, response rate, upper and lower limits of power output, and performance indicators such as regulation response reliability. Based on the requirements of different trading scenarios in terms of trading volume, response time, and response rate, it adopts aggregation management methods such as resource aggregation classification, resource evaluation and ranking, and resource optimization screening. While meeting the requirements of virtual power plant trading indicators, it can minimize the overall cost of virtual power plant trading regulation, thereby optimizing the operational efficiency of virtual power plants. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a schematic diagram of the system architecture provided in the embodiments of this application;

[0024] Figure 2 This is a flowchart illustrating the resource scheduling method based on a virtual power plant provided in an embodiment of this application;

[0025] Figure 3 This is a schematic diagram of the structure of a resource scheduling device based on a virtual power plant provided in this application;

[0026] Figure 4 This is a schematic diagram of the structure of a computer device provided in this application. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0028] It should be noted that the resource scheduling method based on virtual power plants provided in this application is generally executed by computer equipment, and correspondingly, the resource scheduling device based on virtual power plants is generally installed in the computer equipment.

[0029] Figure 1 An exemplary system architecture is shown that can be applied to the resource scheduling method or apparatus based on a virtual power plant in this application.

[0030] like Figure 1As shown, the system architecture may include: a scheduling device 101, a computer device 102, and a resource pool 103. The terminal device 101, computer device 102, and resource pool can communicate via a network, which serves as the medium for providing communication links between these units. The network may include various types of wired or wireless communication links, such as: wired communication links including fiber optic cables, twisted-pair cables, or coaxial cables; and wireless communication links including Bluetooth communication links, Wi-Fi communication links, or microwave communication links.

[0031] The dispatcher device 101 can be a device deployed by the power grid or power trading center to issue trading requests, which specify the trading type and trading indicator requirements. The computer device 102 is equipped with a virtual power plant, which is used to select suitable resources from the resource pool 103 in response to the trading requests to form a resource set, and then send control commands to the resource set to control the above resources to perform power regulation and other operations. The computer device 102 monitors the scheduling results of the resources and then returns the scheduling results to the dispatcher device 101.

[0032] It should be noted that the computer device 102 can be either hardware or software. When the computer device 102 is hardware, it can be implemented as a distributed server cluster composed of multiple computer devices, or as a single server. When the computer device 102 is software, it can be implemented as multiple software programs or software modules (for example, used to provide distributed services), or as a single software program or software module; no specific limitations are made here.

[0033] It should be understood that Figure 1 The number of scheduling devices 101, network devices, and computer devices 102 shown is merely illustrative. Depending on implementation needs, there can be any number of scheduling devices, network devices, and computer devices.

[0034] The following will be combined with the appendix Figure 2 This application provides a detailed description of the resource scheduling method based on a virtual power plant, as provided in the embodiments of this application. The resource scheduling device based on a virtual power plant in the embodiments of this application can be... Figure 1 The terminal device shown.

[0035] Please see Figure 2 This document provides a flowchart illustrating a resource scheduling method based on a virtual power plant, as described in an embodiment of this application. Figure 2 As shown, the method described in this application embodiment may include the following steps:

[0036] S201, Receive transaction requests from the scheduler.

[0037] The dispatcher can be the power grid or the power trading management center, and the trading request can carry attribute values ​​such as trading type and trading indicator requirements. The trading type indicates the trading scenario, including: demand response (i.e., non-real-time response, requiring advance invitation), real-time response, peak-shaving ancillary services, and power trading; the trading indicator requirements indicate the technical indicator values ​​required for the transaction, and different trading types correspond to different trading indicator requirements.

[0038] For example, for demand response, the corresponding transaction metrics requirements include: load demand, response duration, and response time period.

[0039] For real-time response, the corresponding transaction metrics requirements include: response reliability, response rate, and response cost.

[0040] For peak shaving ancillary services, the corresponding transaction metrics requirements include: load demand, response duration, response time period, and response cost.

[0041] For electricity trading, the corresponding trading indicators include load demand, response duration, response time period, and response cost.

[0042] S202. Determine the target resource pool from multiple resource pools based on the transaction type.

[0043] The computer equipment is pre-configured with associations between transaction types and resource pools. Based on these associations, the target resource pool corresponding to the transaction type in S201 is determined. For example, the associations are: demand response is associated with the demand response resource pool, real-time response with the real-time response resource pool, peak-shaving ancillary services with the peak-shaving ancillary service resource pool, and electricity trading with the electricity trading resource pool. Each resource pool contains multiple resources, and resources within different resource pools may overlap.

[0044] In one or more possible embodiments, the process of partitioning multiple resource pools includes:

[0045] The virtual power plant manages all resources and obtains the performance indicators for each resource, including: resource type, controllability, response time, response rate, adjustment limits, response reliability, advance notice time, and response cost. Resource type refers to the type of resource, including distributed generation equipment, energy storage equipment, charging piles, and loads (i.e., electrical equipment). Controllability indicates whether the resource involved in adjustment can be directly controlled; controllability determines the resource's response speed and reliability, and determines whether the resource can participate in application scenarios with high time and reliability. Response time indicates the time period during which the resource can participate in the response; the resource's response capability varies in different time periods. Response rate indicates the time from receiving a response request to reaching the response target through adjustment (i.e., the speed of the response); resources with different response rates can be applied to different application scenarios (i.e., demand types). Adjustment limits indicate the maximum upward and downward adjustment values ​​of the resource output. Response reliability indicates the probability that the resource will achieve the response target through adjustment. Advance notice time indicates the time during which the resource notifies users in advance to facilitate adjustments to their production and life plans. Response cost represents the cost that resources need to compensate for participating in the adjustment process, for example, in yuan per kilowatt-hour.

[0046] Different transaction types have different performance metric requirements.

[0047] For example: See Table 1 for the performance metric requirements corresponding to the four transaction types:

[0048] Table 1

[0049]

[0050] Different transaction types correspond to different resource pools. Based on the performance index requirements of the transaction type, all resources managed by the virtual power plant are clustered to obtain multiple resource pools.

[0051] For example, when the transaction type is demand response, based on the performance requirements of demand response—resource types being industrial load and electric vehicle charging piles, requiring controllability, advance notification, slower response rates, and lower response costs—resources meeting the performance requirements are selected from all resources, and a demand response resource pool is generated based on these selected resources. Following this method, a real-time response resource pool is associated with the real-time response resource pool, a peak-shaving ancillary service resource pool is associated with the peak-shaving ancillary service resource pool, and an electricity trading resource pool is associated with the electricity trading resource pool.

[0052] S203. Based on the transaction indicator requirements, perform performance monitoring on each resource in the target resource pool to obtain performance parameters.

[0053] Different types of resources require different performance monitoring methods, which are explained below. Computer equipment can periodically monitor the performance parameters of various resources.

[0054] For car charging stations, the performance monitoring process includes:

[0055] 1) The upper limit of the charging pile adjustment is the maximum charging power of the charging pile; the lower limit of the charging pile adjustment is 0.

[0056] 2) The response time of the charging pile is determined by the charging plan of the charging pile. It is determined whether there is a time period that must be charged. If so, the time period needs to be excluded from the response time.

[0057] 3) The response cost of a charging station is the cost of charging during the response period, which depends on the charging price standard of the charging station.

[0058] 4) The controllability of a charging station is determined by whether it has remote control and adjustment capabilities.

[0059] 5) The response rate of charging piles is generally in the millisecond range.

[0060] For energy storage devices (e.g., rechargeable batteries), the performance monitoring process includes:

[0061] 1) When the transaction type is demand response, the upper limit of the energy storage device's adjustment is the maximum charging power; the lower limit of the energy storage device's adjustment is the discharging power. When the transaction type is real-time response, the upper and lower limits of adjustment depend on the energy storage device's state of charge (SOC). When the SOC is below the threshold, the energy storage device can only charge and cannot discharge; when the SOC is above the threshold, the energy storage device can only discharge and cannot charge.

[0062] 2) The response period is determined based on the charging and discharging plan of the energy storage device to determine whether there is a period that must be charged and discharged. If so, the period can be excluded from the response period.

[0063] 3) The response cost is determined by the cost of charging and discharging the energy storage device once, which specifically depends on the cost of the battery energy storage and the number of charge-discharge cycles:

[0064] Cost per response = Cost of construction / Maximum number of charge-discharge cycles.

[0065] 4) Controllability is determined by whether the energy storage device has remote control and regulation capabilities;

[0066] 5) The response rate is typically in the millisecond range.

[0067] For distributed generation equipment, the focus is on monitoring its operating status, power generation, and projected power generation for future periods. The performance monitoring process includes:

[0068] 1) The upper limit of adjustment is the predicted power generation of distributed generation equipment in the future period; the lower limit of adjustment for distributed generation equipment is 0.

[0069] 2) The response time of distributed generation is determined by the generation plan of the distributed generation equipment, and the response time excludes the period when there is a generation plan.

[0070] 3) The response cost of distributed generation equipment is the reduced power generation revenue of distributed generation equipment in the future period, and the unit response cost is the unit power generation price of distributed generation equipment in the future period.

[0071] 4) The controllability of distributed power generation equipment is determined by whether the charging pile has remote control and adjustment capabilities.

[0072] 5) The response rate of distributed generation equipment is generally in the millisecond range.

[0073] For adjustable loads, the performance monitoring process includes monitoring their operating status, power, and predicted power for future periods.

[0074] 1) The upper limit of adjustable load is the predicted load power in the future period; the lower limit is 0, and for some loads with a minimum allowable load, it is the minimum allowable load.

[0075] 2) The response time of adjustable load is determined by the load operation plan, and the response time should exclude the period when the load is forced to operate;

[0076] 3) The response cost of adjustable load is the unit compensation requirement for users to reduce or increase load during the future period, which is mainly determined by the users.

[0077] 4) The controllability of adjustable loads is determined by whether the adjustable loads have remote control and adjustment capabilities.

[0078] 5) The response rate of an adjustable load is determined by the characteristics of the load.

[0079] The methods for obtaining performance parameters by monitoring the performance of various types of resources are summarized in Table 2. The performance parameters of each resource include one or more of the seven indicators in Table 2.

[0080] Table 2

[0081]

[0082]

[0083] S204. Based on the performance parameters, a comprehensive evaluation of each resource in the target resource pool is performed to obtain the evaluation value.

[0084] Specifically, based on the specific transaction type, the resource pools corresponding to different transaction types fully consider key indicators such as response rate, response reliability, and response cost for each participating virtual power plant. Based on these indicators, a comprehensive evaluation is performed on all resources in the resource pool to obtain an evaluation value. This allows virtual power plants to form a selection queue by arranging resources in ascending order according to their evaluation values ​​in specific transaction scenarios, with resources having higher evaluation values ​​ranked first.

[0085] When conducting a comprehensive evaluation of resources, considering the operational and management objectives of virtual power plants, different transaction types have different emphases on resource transaction indicators. Therefore, the indicators considered in the comprehensive evaluation of various resources differ across different transaction scenarios:

[0086] For demand response scenarios, in addition to response cost requirements, the reliability of resource response is also a key consideration, given that the trading center has certain requirements for response probability. Apart from these factors, adjustment volume and response rate are relatively less important.

[0087] For real-time response scenarios, in addition to requirements such as response cost and response reliability, response rate also needs to be given priority due to the time requirements of real-time response.

[0088] For peak shaving auxiliary services, response cost and response reliability need to be considered.

[0089] For electricity trading scenarios, response costs are the primary consideration.

[0090] The requirements for resource adjustment characteristics in different transaction scenarios are summarized in Table 3.

[0091] Table 3 provides a qualitative description of the importance of indicators for different types of resources under various transaction types.

[0092]

[0093]

[0094] To achieve comprehensive evaluation of different types of indicators and realize unified ranking and scheduling of resources, a comprehensive evaluation based on resource characteristics is required. This invention adopts a hierarchical evaluation method to comprehensively evaluate resources, establishing a target graph with the overall benefit of the virtual power plant as the constraint. The sub-objective is to minimize the comprehensive scheduling cost of the virtual power plant under different trading scenarios. Specific indicators include: resource type, adjustment upper and lower limits, response reliability, response rate, advance notice time, and response cost.

[0095] To obtain the weight values ​​of each indicator item in the comprehensive evaluation, the following steps are used to analyze its comprehensive weight:

[0096] 1) First, determine the evaluation index system for the evaluation object:

[0097] Resource X = (Resource type, adjustment limits, response rate, response reliability, advance notice time, response cost);

[0098] Construct a pairwise comparison matrix. Based on the importance of resource characteristics under different transaction types, construct a pairwise comparison matrix for each performance index of the resource and scales from 1 to 9. Let the resource have n performance indices, X = {x1, x2, ..., xn}. n To compare their impact on the target at the next higher level, we need to determine their relative weight to a specific target at that level. In other words, we need to rank the impact of the n performance indicators on a specific target at the next higher level.

[0099] The above comparisons are pairwise comparisons between performance indicators, using scales from 1 to 9. Let ai,j represent the comparison result of the i-th performance indicator relative to the j-th performance indicator; then A is called the pairwise comparison matrix.

[0100]

[0101] The criteria for the values ​​of elements in matrix A are as follows:

[0102] Table 4 shows the values ​​of the elements in the target importance judgment matrix A.

[0103]

[0104] 3) Calculate the single ranking weight vector for each resource indicator relative to different scenarios. For each pairwise comparison matrix, calculate the largest eigenvalue and its corresponding eigenvector, and perform consistency checks using the consistency index, random consistency index, and consistency ratio. If the checks pass, calculate the weight value of each indicator using the root square method. The specific calculation method is as follows:

[0105] ① The product of each row of elements in A and the nth root are obtained as a vector. in,

[0106] ②For W * After normalization, the weight vector is obtained. in

[0107] 4) Perform a consistency check. The specific check process is as follows:

[0108] ① Summing the elements of each column in matrix A yields a vector S = (s1, s2, ..., sn), where

[0109] ② Calculate λ max The value,

[0110] ③Calculation

[0111] When the CI value is less than 0.1, the consistency check can be considered to have passed. If the check passes, the decision can be made according to the result represented by the total ranking weight vector. Otherwise, the model needs to be reconsidered or the pairwise comparison matrices with larger consistency ratios (CR) need to be reconstructed.

[0112] 4) Comprehensive evaluation. When obtaining the weights of each resource, there are usually multiple weights for each resource. The final evaluation value is obtained by normalizing the weighted average of multiple weights, so that the evaluation values ​​of each resource are within the same range. This evaluation value serves as the basis for the unified evaluation of resources.

[0113] S205. Sort each resource in the target resource pool in ascending order according to the evaluation value, and start searching from the first resource until the transaction indicator requirements are met.

[0114] S206. Generate a resource set based on the searched resources, and send scheduling instructions to the resource set.

[0115] In this process, resources with higher evaluation values ​​are ranked first, and resources with lower evaluation values ​​are ranked last. After being sorted in ascending order, a selection queue is formed. Then, the search starts from the first resource in the selection queue. The performance indicators of the searched resources are summarized. When the summarized values ​​meet the requirements of the transaction indicators (such as transaction volume, response time, response rate, etc.), the search stops, the searched resources are formed into a resource set, and control commands are sent to the resource set.

[0116] This application is applicable to various specific trading scenarios, such as demand response, real-time response, peak shaving ancillary services, and power trading. It fully considers the specific indicators of various resources, including resource type, response rate, upper and lower limits of power output, and performance indicators such as regulation response reliability. Based on the requirements of different trading scenarios in terms of trading volume, response time, and response rate, it adopts aggregation management methods such as resource aggregation classification, resource evaluation and ranking, and resource optimization screening. While meeting the trading indicator requirements of virtual power plants, it can minimize the overall trading and regulation costs of virtual power plants, thereby optimizing the operational efficiency of virtual power plants.

[0117] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in this application.

[0118] Please see Figure 3This illustration shows a schematic diagram of a resource scheduling device based on a virtual power plant provided in an exemplary embodiment of this application, hereinafter referred to as device 4. Device 3 can be located in a computer device. Device 3 can be implemented as all or part of a terminal device through software, hardware, or a combination of both. Device 3 includes: a transceiver unit 301, a determination unit 302, an evaluation unit 303, a search unit 304, and a scheduling unit 305.

[0119] The transceiver unit 301 is used to receive transaction requests from the scheduler; wherein the transaction request carries transaction type and transaction indicator requirements;

[0120] The determining unit 302 is configured to determine a target resource pool from a preset plurality of resource pools according to the transaction type; wherein the target resource pool includes a plurality of resources;

[0121] Evaluation unit 303 is used to monitor the performance of each resource according to the transaction indicator requirements to obtain performance parameters; and to conduct a comprehensive evaluation of each resource based on the performance parameters with the constraint of maximizing overall revenue to obtain an evaluation value.

[0122] Search unit 304 is used to sort each resource in the target resource pool in ascending order according to the evaluation value, and to search from the first resource until the transaction indicator requirements are met;

[0123] The scheduling unit 305 is used to generate a resource set based on the searched resources and to send control commands to the resource set.

[0124] In one or more possible embodiments, it also includes:

[0125] Clustering units are used to identify all resources managed by the virtual power plant;

[0126] Obtain the performance metrics of each resource;

[0127] Based on the performance metrics, the resources are clustered to obtain multiple resource pools.

[0128] In one or more possible embodiments, the performance metrics include one or more of the following: resource type, controllability, response time, response rate, adjustment upper and lower limits, response reliability, advance notice time, and response cost; the transaction types include: demand response, real-time response, power trading, and peak shaving ancillary services; the multiple resource pools include: demand response source pool, real-time response resource pool, power trading resource pool, and peak shaving ancillary service resource pool.

[0129] In one or more possible embodiments, when the resource is a car charging station, the upper limit of adjustment is the maximum charging power of the charging station, and the lower limit of adjustment is 0; the response cost is the charging cost during the response period.

[0130] When the resource is an energy storage device, its upper limit of regulation is the maximum charging power, and its lower limit of regulation is the discharging power; single response cost = cost / maximum number of charge-discharge cycles;

[0131] When the resource is distributed generation equipment, its upper limit of regulation is the predicted power generation in the future period; the lower limit of regulation is 0.

[0132] When the resource is an adjustable load, its upper limit of adjustment is the predicted load power for the future period; the lower limit of adjustment is 0.

[0133] In one or more possible embodiments, the step of comprehensively evaluating each resource based on the performance parameters to obtain an evaluation value includes:

[0134] The weights of each performance index of a resource are calculated using the analytic hierarchy process (AHP).

[0135] The evaluation value is obtained by normalizing the weights of each resource.

[0136] In one or more possible embodiments, the normalization process includes: weighting the various weights of the resources.

[0137] In one or more possible embodiments, the resources include: energy storage devices, distributed generation devices, loads, or charging piles.

[0138] It should be noted that the above-described embodiment of the device 3, when executing the resource scheduling method based on a virtual power plant, only illustrates the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the above functions. Furthermore, the resource scheduling device based on a virtual power plant and the resource scheduling method embodiment based on a virtual power plant are based on the same concept, and their implementation process is detailed in the method embodiment, which will not be repeated here.

[0139] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0140] This application also provides a computer storage medium that can store multiple instructions, which are adapted to be loaded and executed by a processor as described above. Figure 2 The method steps of the illustrated embodiment can be found in the following documentation for detailed execution. Figure 2 The specific details of the illustrated embodiments will not be elaborated here.

[0141] This application also provides a computer program product that stores at least one instruction, which is loaded and executed by the processor to implement the resource scheduling method based on the virtual power plant as described in the above embodiments.

[0142] Please see Figure 4 This document provides a schematic diagram of the structure of a computer device according to an embodiment of this application. Figure 4 As shown, the computer device 400 may include: at least one processor 401, at least one network interface 404, memory 405, and at least one communication bus 402.

[0143] The communication bus 402 is used to enable communication between these creations.

[0144] Optionally, the computer device of this application may further include: a user interface 403, which is used to perform human-computer interaction operations, including a display screen and a camera. Furthermore, the user interface 403 may also include a standard wired interface and a wireless interface.

[0145] The network interface 404 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0146] The processor 401 may include one or more processing cores. The processor 401 connects to various parts of the computer device 400 using various interfaces and lines, and performs various functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 405, and by calling data stored in memory 405. Optionally, the processor 401 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 401 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content to be displayed on the screen; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 401 and may be implemented as a separate chip.

[0147] The memory 405 may include random access memory (RAM) or read-only memory. Optionally, the memory 405 may include a non-transitory computer-readable storage medium. The memory 405 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 405 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 405 may also be at least one storage device located remotely from the aforementioned processor 401. Figure 4 As shown, the memory 405, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and application programs.

[0148] exist Figure 4 In the computer device 400 shown, the user interface 403 is mainly used to provide an input interface for the user and to obtain the user's input data; while the processor 401 can be used to call the application program stored in the memory 405 and specifically execute, such as Figure 2 The method shown can be referred to for details. Figure 2 As shown, it will not be elaborated further here.

[0149] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory, or random access memory, etc.

[0150] The above-disclosed embodiments are merely preferred embodiments of this application and should not be construed as limiting the scope of this application. Therefore, any equivalent variations made in accordance with the claims of this application shall still fall within the scope of this application.

Claims

1. A resource scheduling method based on a virtual power plant, characterized in that, include: Identify all resources managed by the virtual power plant; The resources include: energy storage devices, distributed generation equipment, loads or charging piles; Obtain the performance metrics of each resource; the performance metrics include one or more of the following: resource type, controllability, response time, response rate, adjustment upper and lower limits, response reliability, advance notice time, and response cost. Based on the performance indicators, the various resources are clustered to obtain multiple resource pools; the multiple resource pools include: a demand response resource pool, a real-time response resource pool, a power trading resource pool, and a peak-shaving ancillary service resource pool; The system receives transaction requests from the dispatcher; wherein the transaction requests carry transaction type and transaction indicator requirements; different transaction types correspond to different transaction indicator requirements; the transaction types include: demand response, real-time response, power trading, and peak shaving ancillary services; A target resource pool is determined from a set of preset resource pools based on the transaction type; wherein, the target resource pool includes multiple resources; Performance parameters are obtained by monitoring the performance of each resource according to the aforementioned transaction indicator requirements. With the constraint of maximizing overall benefit, an evaluation value is obtained by comprehensively evaluating each resource based on the performance parameters. Based on the evaluation value, the resources in the target resource pool are sorted in ascending order, and the search starts from the first resource until the transaction indicator requirements are met; A resource set is generated based on the searched resources, and control commands are sent to the resource set.

2. The method according to claim 1, characterized in that, When the resource is a car charging pile, its adjustment upper limit is the maximum charging power of the charging pile, and the adjustment lower limit is 0; the response cost is the charging cost during the response period. When the resource is an energy storage device, its upper limit of regulation is the maximum charging power, and its lower limit of regulation is the discharging power; single response cost = cost / maximum number of charge-discharge cycles; When the resource is distributed generation equipment, its upper limit of regulation is the predicted power generation in the future period; the lower limit of regulation is 0. When the resource is an adjustable load, its upper limit of adjustment is the predicted load power for the future period; the lower limit of adjustment is 0.

3. The method according to claim 1 or 2, characterized in that, The process of comprehensively evaluating each resource based on the performance parameters to obtain the evaluation value includes: The weights of each performance index of a resource are calculated using the analytic hierarchy process (AHP). The evaluation value is obtained by normalizing the weights of each resource.

4. The method according to claim 3, characterized in that, Normalization includes weighted evaluation of each resource's weight.

5. A resource scheduling device based on a virtual power plant, characterized in that, include: Clustering units identify all resources managed by the virtual power plant; The resources include: energy storage devices, distributed generation devices, loads or charging piles; obtain the performance indicators of each resource; the performance indicators include one or more of the following: resource type, controllability, response time period, response rate, adjustment upper and lower limits, response reliability, advance notice time, and response cost; Based on the performance indicators, the various resources are clustered to obtain multiple resource pools; the multiple resource pools include: a demand response resource pool, a real-time response resource pool, a power trading resource pool, and a peak-shaving ancillary service resource pool; The transceiver unit is used to receive transaction requests from the dispatcher; wherein the transaction request carries the transaction type and transaction indicator requirements; different transaction types correspond to different transaction indicator requirements; the transaction types include: demand response, real-time response, power trading, and peak shaving ancillary services; A determining unit is configured to determine a target resource pool from a set of preset resource pools based on the transaction type; wherein the target resource pool includes multiple resources; The evaluation unit is used to monitor the performance of each resource according to the transaction indicator requirements to obtain performance parameters; and to comprehensively evaluate each resource according to the performance parameters with the constraint of maximizing overall revenue to obtain an evaluation value. The search unit is used to sort the resources in the target resource pool in ascending order according to the evaluation value, and to search from the first resource until the transaction indicator requirements are met. The scheduling unit is used to generate a resource set based on the searched resources and to send control commands to the resource set.

6. A computer storage medium, characterized in that, The computer storage medium stores a plurality of instructions adapted for loading by a processor and executing the method steps as claimed in any one of claims 1 to 4.

7. A computer device, characterized in that, include: A processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and executed the method steps as claimed in any one of claims 1 to 4.

Images