Control method and system for virtual power plant, and transaction system

Abstract

The present application relates to the technical field of virtual power plant control, and discloses a plant control method and system for a virtual power, and a transaction system. The method comprises: sending a network formation completion instruction to a fog computing layer, so that the fog computing layer sends a data reporting instruction to a corresponding networking device on the basis of the network formation completion instruction, and then provides feedback; acquiring target data fed back by the fog computing layer, the target data being calculated on the basis of reporting data submitted by the networking device; sending the target data to a virtual power plant management center, and receiving a scheduling instruction generated by the virtual power plant management center on the basis of the target data; and performing device control according to the scheduling instruction, thereby quickly processing, by means of the fog computing layer, an instruction sent by a cloud computing center, and therefore addressing the problems of high network latency and high bandwidth overhead in current mainstream cloud computing models based on distributed control frameworks.

Description

Control method, system and transaction system of virtual power plant

[0001] Priority information

[0002] The present application claims priority to the Chinese patent application No. 202411364582.1, filed on September 27, 2024, the whole content of which is incorporated herein by reference. TECHNICAL FIELD

[0003] The present application relates to the technical field of virtual power plant control, in particular to a control method, system and transaction system of virtual power plant. BACKGROUND

[0004] At present, in the calculation and control architecture of virtual power plant, most of the technical solutions adopt cloud computing framework or edge computing, and the mainstream way is through cloud computing: through device end data collection, and uploading data to cloud server through gateway for centralized data processing, through big data and computer technology, generating corresponding control instructions of each device, to realize the control of virtual power plant on the access energy with the goal of maximizing economic benefit, the calculation cost and maintenance cost are high.

[0005] SUMMARY

[0006] The main purpose of the present application is to provide a control method, system and transaction system of virtual power plant, which aims to solve the technical problem of high calculation cost and maintenance cost in the prior art through cloud computing.

[0007] In a first aspect, the present application provides a control method of virtual power plant, which is applied to a cloud computing center, and the method comprises the following steps:

[0008] sending a networking completion instruction to a fog computing layer, so that the fog computing layer sends a data reporting instruction to corresponding networking devices based on the networking completion instruction and feeds back;

[0009] obtaining target data fed back by the fog computing layer, the target data being calculated from reporting data reported by the networking devices;

[0010] sending the target data to a virtual power plant management center, and receiving a dispatching instruction generated by the virtual power plant management center based on the target data;

[0011] controlling the devices according to the dispatching instruction.

[0012] In the scheme, a networking completion instruction is sent to the fog computing layer, so that the fog computing layer sends corresponding instructions to the networking devices that have successfully networked with it. The fog computing layer performs calculation based on the reported data reported by the networking devices, so as to send target data to the cloud computing center. The cloud computing center undertakes secondary calculation tasks and data synchronization aggregation, system scheduling functions. The fog computing layer mainly undertakes the main calculation function, so as to reduce the data calculation cost in the control of the virtual power plant, and solve the problems of large network delay and high bandwidth cost in the cloud computing mode of the current mainstream distributed control framework.

[0013] In some embodiments, the step of performing device control according to the scheduling instruction comprises:

[0014] According to the scheduling instruction, power demand data and schedulable data are obtained.

[0015] The power demand data and the schedulable data are calculated to obtain a fog computing unit power participation strategy.

[0016] The fog computing unit power participation strategy is sent to each fog computing unit in the fog computing layer, so that the fog computing unit calculates a networking device participation strategy based on the fog computing unit power participation strategy, and controls the networking device according to the networking device participation strategy.

[0017] In the technical scheme of the embodiments of the application, the schedulable resources are determined according to the analysis of the scheduling instruction sent by the virtual power plant management center. The cloud computing center can generate a corresponding fog computing unit power participation strategy according to the schedulable resources, and control each fog computing unit in the fog computing layer to schedule and distribute the networking devices through the fog computing unit power participation strategy. Through the interaction between the cloud computing center and the fog computing layer, the delay is reduced, and the calculation efficiency and response speed are improved.

[0018] In some embodiments, the step of calculating the fog computing unit power participation strategy based on the power demand data and the schedulable data comprises:

[0019] A first target function is obtained, and a constraint condition is obtained based on the power demand data and the schedulable data.

[0020] According to the economic scheduling model, the first target function and the constraint condition are solved to obtain the fog computing unit power participation strategy.

[0021] In the technical scheme of the embodiment, the cloud computing center adopts an economic scheduling model with security constraints to perform optimal solution on the first target function and the constraint condition, so that the optimal result of power participation of each fog computing unit is obtained, the effect of fog computing unit calculation is improved, the economic and security scheduling under the constraint condition can be performed on the virtual power plant system level, and the scheduling effect is improved.

[0022] In some embodiments, before the step of sending the networking completion instruction to the fog computing layer, the method further includes

[0023] Receiving initial device operation data sent by the fog computing layer, the initial device operation data being sent to the fog computing layer by the terminal device layer;

[0024] Networking the fog computing layer and the terminal device layer based on the initial device operation data;

[0025] In the case of detecting that the networking is completed, a networking completion instruction is generated.

[0026] In the scheme, the cloud computing center performs networking on the fog computing layer and the terminal device layer based on the initial device operation data sent by the fog computing layer, and can perform automatic networking before controlling the virtual power plant, facilitates management of each fog computing unit in the fog computing layer and the terminal device layer, and improves the management effect.

[0027] In some embodiments, the step of networking the fog computing layer and the terminal device layer based on the initial device operation data includes:

[0028] Decoding the initial device operation data to obtain at least one of device information, device state information, and routing topology information;

[0029] Creating a topology graph network based on at least one of the device information, the device state information, and the routing topology information;

[0030] Optimizing the topology graph network by a preset optimization strategy to obtain an optimized topology graph network;

[0031] Obtaining a plurality of data pairs between fog computing units and edge devices according to the optimized topology graph network, the data pair being composed of one fog computing unit and a plurality of edge devices;

[0032] Generating a networking scheme and a networking instruction according to the plurality of data pairs;

[0033] Sending the networking scheme and the networking instruction to each fog computing unit in the fog computing layer to network the fog computing layer and the terminal device layer.

[0034] In the scheme, the information of the terminal device layer is obtained by decoding the initial device operation data, and the cloud computing center creates and optimizes the network topology structure in the entire control system according to the information of the terminal device layer, so as to bind and associate the fog computing units and the edge devices according to the optimized topology network, generate the optimal networking scheme, and ensure that the fog computing layer and the terminal device layer can efficiently and stably network according to the networking scheme, thereby providing a solid network foundation for subsequent data processing, energy management and control tasks.

[0035] In some embodiments, the step of sending the networking scheme and the networking instruction to each fog computing unit in the fog computing layer to network the fog computing layer and the terminal device layer comprises:

[0036] sending the networking scheme and the networking instruction to each fog computing unit in the fog computing layer, and receiving the binding information fed back by the fog computing unit according to the networking scheme and the networking instruction, the binding information being generated by the fog computing unit after networking with the corresponding device in the terminal device layer according to the networking scheme and the networking instruction;

[0037] after detecting that each fog computing unit in the fog computing layer feeds back the binding information, storing the binding information, and sending the optimized topology network to the fog computing unit, completing the networking.

[0038] In the technical scheme of the embodiments of the application, the prepared networking scheme and networking instruction are sent to each fog computing unit in the fog computing layer, thereby guiding the fog computing unit to connect and configure with the devices in the terminal device layer. After successful networking, the fog computing unit generates and feeds back the binding information, and the cloud computing center stores the received binding information, so as to facilitate subsequent rapid tracing according to the stored binding information in case of failure.

[0039] In some embodiments, the method further comprises:

[0040] determining abnormal data based on the device state information and the device information;

[0041] labeling the abnormal data to obtain a labeling result;

[0042] updating the topology network according to the labeling result.

[0043] In the scheme, the abnormal data can be quickly determined based on the device state information and the device information, and the abnormal data is labeled and the topology network is updated at the same time, so that the device state in the topology network is updated in time, thereby facilitating the rapid identification and processing of abnormal devices.

[0044] In some embodiments, the method further comprises:

[0045] selecting, by a path planning strategy, a preset number of fog computing units from the plurality of fog computing units as target fog computing units;

[0046] communicating with the target fog computing units as backup routing, and adding the target fog computing units to the optimized topology network.

[0047] In this scheme, when the device is networked, multiple fog computing units are selected as backup bridge links at the same time, and the real-time smoothness of control links and data links is guaranteed in the case of failure by constructing backup link routing.

[0048] Secondly, in order to achieve the above-mentioned purpose, the application further provides a virtual power plant control method, which is applied to a fog computing layer, and the method comprises the following steps:

[0049] In the case of receiving the network completion instruction sent by the cloud computing center, a data reporting instruction is sent to the corresponding network device according to the network completion instruction, so that the network device feeds back the reported data according to the data reporting instruction;

[0050] The reported data is calculated to obtain target data;

[0051] The target data is sent to the cloud computing center, so that the cloud computing center sends the target data to the virtual power plant management center, receives a scheduling instruction, and feeds back a fog computing unit power participation strategy according to the scheduling instruction;

[0052] In the case of receiving the fog computing unit power participation strategy, the network device is controlled according to the fog computing unit power participation strategy.

[0053] In this scheme, the concept of "semi-centralization" is adopted, the fog computing layer is used to replace part of the scheduling function in the cloud computing layer, the computing pressure and storage pressure are transferred to the decentralized "fog computing layer", the reported data reported by the edge device is calculated by the fog computing layer, the link transmission between the edge device and the cloud computing center is reduced, thereby reducing the bandwidth pressure and computing pressure caused by the corresponding data transmission, and after receiving the corresponding strategy, the network device can be scheduled according to the corresponding strategy, reducing the time delay risk caused by the Internet, solving the problems of large network time delay and high bandwidth cost in the current mainstream distributed control framework cloud computing mode.

[0054] In some embodiments, the step of calculating the reported data to obtain target data comprises:

[0055] The reported data is analyzed to obtain a networking device running state, a networking device performance index, and an environmental parameter;

[0056] Data is classified according to at least one of the networking device running state, the networking device performance index, and the environmental parameter to obtain classified data;

[0057] The classified data is aggregated and calculated to obtain target data.

[0058] Through a large number of dispersed central nodes arranged in the fog computing layer, each central node is responsible for the calculation of the reported data of the networking device in its network, and the efficiency of data calculation is improved through distributed calculation.

[0059] In some embodiments, the step of controlling the networking device according to the fog computing unit power participation strategy in the case of receiving the fog computing unit power participation strategy comprises:

[0060] In the case of receiving the fog computing unit power participation strategy, a networking device participation strategy is calculated based on the fog computing unit power participation strategy;

[0061] The networking device is controlled according to the networking device participation strategy.

[0062] In the technical scheme of the embodiments of the present application, according to the power participation strategy, the fog computing unit evaluates the power demand and availability of each device in the network, thereby calculating the optimal power usage mode of each device under different conditions. Based on the above analysis, the fog computing unit generates a specific networking device participation strategy, thereby accurately controlling how the device operates according to the power supply and demand, so that the fog computing unit can effectively manage and control the networking device according to the power participation strategy.

[0063] In some embodiments, the step of calculating a networking device participation strategy based on the fog computing unit power participation strategy in the case of receiving the fog computing unit power participation strategy comprises:

[0064] In the case of receiving the fog computing unit power participation strategy, a target power participation fog computing unit is obtained based on the fog computing unit power participation strategy;

[0065] A constraint condition is obtained according to the networking device and the target power participation fog computing unit, and a second target function is obtained;

[0066] The constraint condition and the second target function are input into a unit commitment model for solving to obtain a networking device participation strategy.

[0067] The scheme solves the optimization of the constraint condition and the target power participating in the fog computing unit by using the unit combination model of each fog computing unit in the fog computing layer, and obtains the best result of the participation of each device or energy management platform in energy aggregation under the guarantee of the safety of each device or energy management platform.

[0068] In some embodiments, the step of controlling the networking device according to the networking device participation strategy comprises:

[0069] Determining the networking device to be managed according to the networking device participation strategy;

[0070] Sending an instruction to the networking device to be managed, so that the networking device to be managed reports data based on the instruction.

[0071] The scheme determines the networking device that can be managed through the networking device participation strategy, so as to ensure that the networking device to be managed reports data according to the established strategy, provides necessary information support for the optimization and management of the network, and realizes the data interaction between the fog computing layer and the networking device and the effective management of the networking device.

[0072] In some embodiments, before the step of sending a data reporting instruction to the corresponding networking device according to the networking completion instruction sent by the cloud computing center, the step further comprises:

[0073] Receiving the initial device running data reported by the terminal device layer, and sending the initial device running data to the cloud computing center, so that the cloud computing center feeds back the networking scheme and the networking instruction based on the initial device running data;

[0074] According to the networking scheme and the networking instruction, the terminal device layer is networked, and binding information is generated;

[0075] The binding information is stored, and the binding information is sent to the cloud computing center, so that the cloud computing center determines the networking completion according to the binding information.

[0076] By sending the initial device running data to the cloud computing center, the cloud computing center sends the networking scheme and the networking instruction, the fog computing layer is networked with the terminal device layer according to the received networking scheme and instruction. In the networking process, the fog computing layer generates binding information, which reflects the connection and configuration state between the fog computing unit and the devices in the terminal device layer, and the binding information is stored for subsequent query and use.

[0077] In some embodiments, the step of networked with the terminal device layer according to the networking scheme and the networking instruction, and generating binding information comprises:

[0078] determining network and clock synchronization according to the network instruction;

[0079] After the network determination and clock synchronization are completed, the network scheme is used to bind and communicate with the devices in the corresponding jurisdictional area in the terminal device layer, and binding information is generated.

[0080] In the technical scheme of the embodiment, network determination is performed according to the network instruction and local data, so as to determine which devices need to participate in network, and clock synchronization is performed, so as to ensure that all devices operate under the same time reference. After the network determination and clock synchronization are completed, the network scheme can be used to bind and communicate with the devices in the logical jurisdictional area, automatic network can be realized, and network efficiency is improved.

[0081] In some embodiments, the method further comprises:

[0082] In the case where it is detected that the transmission link between the cloud computing center fails, an optimized topology network is acquired;

[0083] A target fog computing unit is determined from the optimized topology network, and the target fog computing unit is used to communicate with the cloud computing center.

[0084] The scheme can timely determine a backup fog computing unit as a “relay” backup bridge link from the optimized topology network when it is detected that the transmission link between the cloud computing center fails, and can quickly perform automatic repair, so as to ensure the real-time performance of virtual power plant control.

[0085] In a third aspect, to achieve the above object, the application further provides a virtual power plant control device, which is applied to a cloud computing center, and comprises:

[0086] A first sending module is configured to send a network completion instruction to a fog computing layer, so that the fog computing layer sends a data reporting instruction to corresponding network devices based on the network completion instruction and feeds back.

[0087] An acquisition module is configured to acquire target data fed back by the fog computing layer, wherein the target data is obtained by calculating reported data reported by the network devices after each fog computing unit in the fog computing layer sends a data reporting instruction to the corresponding network devices.

[0088] The first sending module is further configured to send the target data to a virtual power plant management center, and receive a scheduling instruction generated by the virtual power plant management center based on the target data.

[0089] A control module is configured to control devices according to the scheduling instruction.

[0090] In a fourth aspect, to achieve the above object, the present application further provides a virtual power plant control device, which is applied to a fog computing layer, and comprises:

[0091] a receiving module, configured to send a data reporting instruction to a corresponding networking device according to a networking completion instruction sent by the cloud computing center, so that the networking device feeds back reported data according to the data reporting instruction when the networking completion instruction is received;

[0092] a computing module, configured to compute the reported data to obtain target data;

[0093] a second sending module, configured to send the target data to the cloud computing center, so that the cloud computing center sends the target data to a virtual power plant management center, and receives a dispatching instruction and feeds back a fog computing unit power participation strategy according to the dispatching instruction;

[0094] The receiving module is further configured to control the networking device according to the fog computing unit power participation strategy when the fog computing unit power participation strategy is received.

[0095] In a fifth aspect, to achieve the above object, the present application further provides a virtual power plant control system, which comprises a terminal device layer, a cloud computing center and a fog computing layer.

[0096] In a sixth aspect, to achieve the above object, the present application further provides a virtual power plant transaction system, which comprises a terminal device layer, a power grid dispatching center, a virtual power plant management center, a cloud computing center and a fog computing layer, and executes the virtual power plant control method described above when performing power grid transaction.

[0097] The above description is only a summary of the technical scheme of the present application, in order to make the technical means of the present application more clearly understood and implemented according to the content of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the following specific embodiments of the present application are described. BRIEF DESCRIPTION OF DRAWINGS

[0098] Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The accompanying drawings are intended to only illustrate preferred embodiments and are not considered limiting of the present application. Moreover, like reference numerals are intended to denote like parts throughout the various drawings. In the drawings:

[0099] Figure 1 is a flowchart of an embodiment of a control method of a virtual power plant applied to a cloud computing center according to the present application;

[0100] Figure 2 is a structural diagram of a control system of a virtual power plant according to the present application;

[0101] Figure 3 is a flowchart of an embodiment of a control method of a virtual power plant according to the present application;

[0102] Figure 4 is a signaling diagram of an interaction between a cloud computing center and a fog computing layer in an embodiment of a control method of a virtual power plant according to the present application;

[0103] Figure 5 is another flowchart of an embodiment of a control method of a virtual power plant applied to a cloud computing center according to the present application;

[0104] Figure 6 is another flowchart of an embodiment of a control method of a virtual power plant applied to a cloud computing center according to the present application;

[0105] Figure 7 is a flowchart of an embodiment of a control method of a virtual power plant applied to a fog computing layer according to the present application;

[0106] Figure 8 is another flowchart of an embodiment of a control method of a virtual power plant applied to a fog computing layer according to the present application;

[0107] Figure 9 is a process diagram of data synchronization and communication control between a cloud computing center and each fog computing unit in a control method of a virtual power plant according to the present application;

[0108] Figure 10 is another flowchart of an embodiment of a control method of a virtual power plant applied to a fog computing layer according to the present application;

[0109] Figure 11 is a diagram of a normal connection between a cloud computing center and each unit in a fog computing layer in an embodiment of a control method of a virtual power plant applied to a fog computing layer according to the present application;

[0110] Figure 12 is a diagram of a switching when a communication link between a cloud computing center and a fog computing layer fails in an embodiment of a control method of a virtual power plant applied to a fog computing layer according to the present application;

[0111] Figure 13 is a structural diagram of an embodiment of a control device of a virtual power plant applied to a cloud computing center according to the present application;

[0112] Figure 14 is a structural diagram of an embodiment of a control device of a virtual power plant applied to a fog computing layer according to the present application.

[0113] Explanation of reference signs:

[0114] Terminal device layer 11, cloud computing center 12, fog computing layer 13.

[0115] The purposes, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0116] The embodiments of the technical solutions of the present application will be described in detail below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present application, and therefore only serve as examples, and cannot limit the protection scope of the present application.

[0117] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of this application; the terms "include" and "have" and any variations thereof used in the specification and the claims and the above description of the drawings are intended to cover the inclusion not the exclusion of one or more elements.

[0118] In the description of the embodiments of the present application, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "multiple" is more than two, unless otherwise explicitly and specifically limited.

[0119] Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present application. The appearance of the phrase in various places in the specification does not necessarily all refer to the same embodiment, nor is it necessarily independent or alternative embodiments to each other. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0120] In the description of the embodiments of the present application, the term "and / or" is only a description of the association relationship between the associated objects, which means that there can be three relationships, for example, A and / or B, which can represent the three cases of A alone, A and B together, and B alone. In addition, the character " / " in this paper generally represents that the front and rear associated objects are a "or" relationship.

[0121] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two), and similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0122] In the description of the embodiments of the present application, the orientations or positional relationships indicated by the technical terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like are based on the orientations or positional relationships shown in the drawings, and are only for the convenience of describing the embodiments of the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the embodiments of the present application.

[0123] In the description of the embodiments of the present application, unless otherwise explicitly specified and limited, the technical terms "mounting", "connecting", "connecting", "fixing" and the like should be understood broadly, for example, can be fixedly connected, or can be detachably connected, or can be integrated; can be mechanically connected, or can be electrically connected; can be directly connected, or can be indirectly connected through an intermediate medium, or can be the internal communication of two elements or the interaction relationship between two elements. For those skilled in the art, the specific meanings of the above terms in the embodiments of the present application can be understood according to the specific circumstances.

[0124] At present, in the calculation and control architecture of virtual power plant, most of the technical solutions adopt cloud computing framework or edge computing, etc. Based on the limited computing power of the current embedded chip, the mainstream way is still through cloud computing: through the device end to collect data, and upload the data to the cloud server through the gateway for centralized data processing, through big data and computer technology, to generate the control instructions of each device, to realize the control of virtual power plant to the connected energy from the target of maximizing economic benefit. In the current cloud computing scheme, all the communication and calculation between the device side need to upload the data back to the cloud computing center, and the calculation resources of the cloud computing center are used for calculation and control of the device side. The current mode needs the cloud computing center to have rich bandwidth resources and rich computing resources, which has high investment cost for the cloud computing center, and is easily affected by network resources. Once the data volume is too large, it is easy to cause data congestion, causing low cloud computing efficiency.

[0125] Therefore, it is necessary to improve the efficiency of cloud computing and reduce the cost of calculation and control of virtual power plants. The embodiments of the present application provide a control method of a virtual power plant. Compared with cloud computing and edge computing, there is an additional fog computing layer. The cloud computing center undertakes secondary computing tasks and data synchronization aggregation and system scheduling functions. The fog computing layer mainly undertakes corresponding data aggregation and main calculation and data storage functions. In the fog computing mode, a large number of dispersed center nodes, i.e. fog computing units, are arranged. Each fog computing unit is responsible for the calculation, data storage and device control of the corresponding edge device layer device. Then, the fog computing unit performs data synchronization and system scheduling of the calculation framework with the cloud computing center. Therefore, the data calculation cost in the control of the virtual power plant can be reduced, and the problems of large network delay and high bandwidth cost in the cloud computing mode of the current mainstream distributed control framework can be solved.

[0126] In actual applications, the control of the virtual power plant is usually to respond to the power regulation demand of the power grid, such as peak regulation demand and frequency regulation demand, so as to balance the power grid load, optimize power supply, improve the stability and reliability of the power system. Based on the above consideration, the embodiments described in the present application are applied to the scene of power resource scheduling.

[0127] The present application aims at the technical problem that the calculation cost and maintenance cost are high when calculation and control are performed by the cloud computing mode. A control method of a virtual power plant is provided. The control method of the virtual power plant is applied to a cloud computing center. Referring to FIG. 1, in the present example, the control method of the virtual power plant applied to the cloud computing center comprises the following steps.

[0128] Step S10: sending a networking completion instruction to the fog computing layer, so that the fog computing layer sends a data reporting instruction to the corresponding networking device based on the networking completion instruction and feeds back.

[0129] It should be noted that the execution subject of the embodiment is a cloud computing center, as shown in FIG. 2, which is a structural schematic diagram of a control system of a virtual power plant. The control system of the virtual power plant includes a terminal device layer 11, a cloud computing center 12, and a fog computing layer 13. The terminal device layer 11 includes a plurality of devices, such as device 1, device 2, device M, and the like. The fog computing layer 13 includes a plurality of fog computing units, each of which includes a fog computing module, a control module, a data aggregation module, a data storage module, and a communication module. The cloud computing center 12 includes a computing module, a data aggregation module, a communication module, a data storage module, a resource scheduling module, and a monitoring module. The cloud computing center 12 is deployed on the virtual power plant platform side and mainly includes computing servers, storage servers, resource scheduling servers, switches, firewalls, and the like. The fog computing layer 13 communicates with the cloud computing center through a backbone network and communicates and conveys control instructions with edge devices through the Internet. The fog computing layer 13 is mainly deployed near the switches in the area close to the terminal device layer 11. Each fog computing unit includes a computing server and a storage server, and a plurality of switches.

[0130] In a specific implementation, before performing resource scheduling of the edge devices of the virtual power plant, the fog computing units in the fog computing layer and the devices in the edge device layer need to be networked first, so as to facilitate subsequent device management and data calculation. After the networking is completed, data interaction and communication can be performed. Therefore, after the cloud computing center detects that the networking is completed, a networking completion instruction can be sent to the fog computing layer. Specifically, the computing module in the cloud computing center can generate and send the networking completion instruction to each fog computing unit in the fog computing layer.

[0131] After each fog computing unit receives the networking completion instruction, it sends a data reporting instruction to the networked devices corresponding thereto. For example, the fog computing unit 1 corresponds to the devices 1, 2, and 3. The fog computing unit 1 generates a data reporting instruction to the devices 1, 2, and 3.

[0132] Step S20: Obtain target data fed back by the fog computing layer. The target data is calculated from the reporting data reported by the networked devices.

[0133] It can be understood that after each fog computing unit in the fog computing layer sends a data reporting instruction to the corresponding networked devices, the networked devices will report the status of their own devices to each fog computing unit as reporting data. The reporting data can include device start-stop state, device voltage, current, temperature parameter, upper and lower limits of available power, device constraint condition, and the like. In addition, the reporting data can also include total platform start-stop state, total voltage, current, temperature, upper and lower limits of available power, platform constraint condition, platform regulation and maintenance plan, and the like provided by the energy management platform.

[0134] Each fog computing unit aggregates and stores the received reported data, and periodically feeds back the target data to the cloud computing center, so as to synchronize the data.

[0135] Step S30: sending the target data to the virtual power plant management center, and receiving the scheduling instruction generated by the virtual power plant management center based on the target data.

[0136] It should be noted that after the cloud computing center receives the target data fed back by each fog computing unit, the target data reported by each fog computing unit is summarized, and the data is periodically uploaded to the virtual power plant management center. After the virtual power plant management center receives the data uploaded by the cloud computing center, the scheduling instruction is generated in combination with the power grid power demand and the schedulable resources, and is sent to the cloud computing center.

[0137] Step S40: controlling the equipment according to the scheduling instruction.

[0138] In a specific implementation, after the cloud computing center receives the scheduling instruction sent by the virtual power plant management center, the equipment can be controlled by the fog computing layer according to the scheduling instruction, so as to control the equipment to perform the behavior of selling power or buying power to the power grid. As shown in FIG. 3, FIG. 3 is a schematic diagram of the overall flow of the control method of the virtual power plant. The virtual power plant management center and the power grid dispatching center perform data synchronization through data interaction, do not participate in the direct delivery of power, the power grid dispatching center proposes a scheduling demand to the virtual power plant management center, the virtual power plant management center sends a scheduling instruction to the cloud computing center, the cloud computing center sends a corresponding instruction to the fog computing layer, the terminal equipment layer is controlled through the fog computing layer, the terminal equipment layer performs the behavior of buying power and selling power to the power grid, and finally the power grid and the virtual power plant management center perform fee settlement, and the virtual power plant management center and the terminal equipment layer perform fee settlement, so as to realize normal operation. The cloud computing center can periodically report data to the virtual power plant management center.

[0139] As shown in FIG. 4, FIG. 4 is a signaling diagram of interaction between the cloud computing center and the fog computing layer. The cloud computing center sends a networking completion instruction to the fog computing layer, the fog computing layer sends a data reporting instruction to the networking equipment according to the networking completion instruction, the networking equipment reports data, the reported data is reported to the fog computing layer, the fog computing layer calculates the target data from the reported data, and sends the target data to the cloud computing center. The cloud computing center sends the target data to the virtual power plant management center, the virtual power plant management center generates a scheduling instruction to the cloud computing center according to the target data, and the cloud computing center controls the equipment through the fog computing layer according to the scheduling instruction.

[0140] In the scheme, a networking completion instruction is sent to the fog computing layer, so that the fog computing layer sends corresponding instructions to the networking devices that have successfully networked with it. The fog computing layer performs calculation based on the reporting data reported by the networking devices, so as to send target data to the cloud computing center. The cloud computing center undertakes secondary calculation tasks and data synchronization aggregation, system scheduling functions. The fog computing layer mainly undertakes the main calculation function, so as to reduce the data calculation cost in the control of the virtual power plant, and solve the problems of large network delay and high bandwidth cost in the current mainstream distributed control framework cloud computing mode.

[0141] In some embodiments, in order to improve the efficiency of resource scheduling, the scheduling instruction sent by the virtual power plant management center can be quickly controlled by the edge device. Referring to FIG. 5, step S40 specifically includes:

[0142] Step S401: obtaining power demand data and schedulable data according to the scheduling instruction.

[0143] It should be noted that since the scheduling instruction is generated by the virtual power plant management center in combination with the power grid power demand and schedulable resources after receiving the target data reported by the cloud computing center, the scheduling instruction can be analyzed to obtain the power demand data and the schedulable data. The power demand data is the real-time power demand of the power grid, such as power load prediction, historical power consumption mode, peak-valley electricity price information, and the schedulable data is the power resources in the edge device that can be adjusted or controlled.

[0144] Step S402: calculating the power demand data and the schedulable data to obtain a fog computing unit power participation strategy.

[0145] In specific implementation, the power demand data and the schedulable data can be calculated. The calculation method can be a heuristic algorithm, and can also be other solving methods, so as to obtain the fog computing unit power participation strategy, that is, the best solution for the fog computing unit to share the sold power or the purchased power.

[0146] In some embodiments, an economic scheduling model (SCED) with security constraints can be established in advance, the objective function and the constraint condition are included in the model, so as to use the economic scheduling model to solve the power demand data and the schedulable data. The step of calculating the power demand data and the schedulable data to obtain the fog computing unit power participation strategy includes: obtaining a first objective function, and obtaining a constraint condition according to the power demand data and the schedulable data; according to the economic scheduling model, the first objective function and the constraint condition are solved to obtain the fog computing unit power participation strategy.

[0147] It can be understood that the first target function is an index to be minimized or maximized, for example, minimizing energy cost, maximizing energy efficiency, and optimal economy. The embodiment takes the optimal economy as an example for illustration. In specific implementation, the power demand data and the schedulable data are taken as constraint conditions for solving, and the constraint conditions and the first target function are input into an economic scheduling model for solving, so that the optimal result of power participation of each fog computing unit can be obtained, and the power participation strategy of the fog computing unit, that is, the power use and scheduling strategy of the fog computing unit, is formulated, for example, when to start the generator, when to use the energy storage discharge, when to participate in demand response, and the like.

[0148] The cloud computing center adopts the economic scheduling model with security constraints to optimally solve the first target function and the constraint conditions, so that the optimal result of power participation of each fog computing unit is obtained, the effect of fog computing unit calculation is improved, the economic and security scheduling under the constraint condition can be performed on the virtual power plant system level, and the scheduling effect is improved.

[0149] In step S403, the fog computing unit power participation strategy is sent to each fog computing unit in the fog computing layer, so that the fog computing unit calculates the networking device participation strategy based on the fog computing unit power participation strategy, and controls the networking device according to the networking device participation strategy.

[0150] It should be noted that the fog computing unit power participation strategy can be sent to each fog computing unit in the fog computing layer, and each fog computing unit can calculate the networking device participation strategy based on the fog computing unit power participation strategy after receiving the SCED model solving result. Specifically, each fog computing unit can receive the power participation strategy and analyze it to understand the specific requirements, so as to generate the networking device participation strategy, which is the optimal result of each device or energy management platform participating in energy aggregation.

[0151] After generating the networking device participation strategy, the fog computing unit can generate corresponding instructions through the communication module, so as to control each device or energy management platform. The terminal device layer (edge device layer) executes the power selling or power purchasing to the power grid after receiving the control instruction of the fog computing layer.

[0152] In the technical scheme of the embodiment of the application, the schedulable resources are determined by analyzing the scheduling instruction sent by the virtual power plant management center, the cloud computing center can generate the corresponding fog computing unit power participation strategy according to the schedulable resources, and control each fog computing unit in the fog computing layer to schedule and distribute the networking device through the fog computing unit power participation strategy, so as to reduce the delay, improve the calculation efficiency and response speed through the interaction between the cloud computing center and the fog computing layer.

[0153] In some embodiments, before the edge device is controlled by the fog computing layer, each fog computing unit in the fog computing layer and the corresponding device also need to be networked, facilitating subsequent device management. As shown in FIG. 6, before step S10, it further includes:

[0154] Step S01: receiving initial device running data sent by the fog computing layer, the initial device running data being sent from the terminal device layer to the fog computing layer.

[0155] In a specific implementation, the communication module in the fog computing layer can communicate with the cloud computing center. In the networking stage, the communication module in the cloud computing center receives the initial device running data uploaded from all fog computing units in the fog computing layer. The initial device running data is obtained by the communication module in the edge device layer interacting with the communication module of each fog computing unit. The communication module in the edge device layer is mainly used for feeding back device running data and accepting downlink instructions.

[0156] The initial device running data includes device information, device state information, routing topology information, etc.

[0157] Step S02: networking the fog computing layer and the terminal device layer based on the initial device running data.

[0158] It can be understood that after receiving the initial device running data, the communication module in the cloud computing center can decode the initial device running data and transmit it to the monitoring module, so that the fog computing layer and the terminal device layer are networked based on the decoded initial device running data by the monitoring module and the scheduling module in the cloud computing center. Specifically, a topology graph network can be created, and the fog computing units in the fog computing layer and the devices in the terminal device layer can be bound according to the topology graph network, so as to complete the networking and realize effective communication between devices and optimized allocation of resources.

[0159] In some embodiments, the step of networking the fog computing layer and the terminal device layer based on the initial device running data can include:

[0160] decoding the initial device running data to obtain at least one of device information, device state information, and routing topology information;

[0161] creating a topology graph network based on at least one of the device information, the device state information, and the routing topology information;

[0162] optimizing the topology graph network by a preset optimization strategy to obtain an optimized topology graph network;

[0163] obtaining a plurality of data pairs between the fog computing units and the edge devices according to the optimized topology graph network, each data pair consisting of one fog computing unit and a plurality of edge devices;

[0164] generate a networking scheme according to the plurality of data pairs, and generate networking instructions;

[0165] send the networking scheme and the networking instructions to each fog computing unit in the fog computing layer, so as to network the fog computing layer and the terminal device layer.

[0166] It should be noted that the communication module in the cloud computing center decodes the initial device operation data to obtain device information, device state information, and routing topology information, which refers to the connection mode and path information of each device in the edge device layer. The edge device layer is composed of the following two ways: 1. A plurality of edge devices and intelligent edge gateways, routers and other devices, 2. Energy management platform. The device information can include the information of edge devices, intelligent edge gateways, routers or energy management platforms.

[0167] In a specific implementation, after receiving the device information, the device state information and the routing topology information, the monitoring module in the cloud computing center can create a topology graph network according to at least one of the device information, the device state information and the routing topology information. Specifically, it can sort the routing topology information, clarify the connection relationship between devices, link attributes (such as bandwidth, delay), etc., and use a drawing tool to build a topology graph network. The routing topology refers to the logical structure of the connection mode and path selection of devices (such as routers, switches, etc.) in the network.

[0168] After obtaining the topology graph network, the topology graph network can be sent to the scheduling module. After receiving the topology graph network, the scheduling module can optimize the topology graph network according to the data fed back by the communication module. The preset optimization strategy includes but is not limited to heuristic algorithms such as particle swarm algorithm, genetic algorithm, reinforcement learning such as DDPG, A3C algorithm, GCN graph algorithm, etc. Specifically, the topology graph network can be optimized according to the network throughput speed, shortest path, fastest response speed, etc. in the device information and device state information, so as to obtain an optimized topology graph network.

[0169] By decoding the initial device operation data, the information of the terminal device layer is obtained. The cloud computing center creates and optimizes the network topology structure in the entire control system according to the information of the terminal device layer, so as to bind and associate the fog computing units and the edge devices according to the optimized topology graph network, generate the optimal networking scheme, and ensure that the fog computing layer and the terminal device layer can efficiently and stably network according to the networking scheme, providing a solid network foundation for subsequent data processing, energy management and control tasks.

[0170] In some embodiments, the monitoring module of the cloud computing center will also mark abnormal data when creating a topology graph network for the routing topology to avoid abnormal situations, thereby avoiding subsequent device unavailability, and thus the control method of the virtual power plant applied to the cloud computing center further comprises:

[0171] determining abnormal data based on the device state information and the device information;

[0172] marking the abnormal data to obtain a marking result;

[0173] updating the topology graph network according to the marking result.

[0174] It can be understood that the abnormal data can be determined using statistical methods, machine learning algorithms, or rule engines based on the device state and device information. The abnormality can be caused by device failure, performance degradation, or unexpected usage patterns. After determining the abnormal data, the abnormal data can be marked, such as adding a specific label or annotation, to obtain a marking result, and the topology graph network can be updated according to the marking result, such as adding the marking result to the corresponding device in the topology graph network, or removing the corresponding device in the topology graph network according to the marking result, thereby updating the topology graph network. The device state in the topology graph network can be updated in time to facilitate the rapid identification and processing of abnormal devices.

[0175] In some embodiments, to avoid communication link failures between the fog computing layer and the edge devices and the cloud computing center causing communication interruption, a backup link routing method can be used to ensure real-time smoothness of the control link and the data link in case of failure. In the networking stage, the method further comprises: selecting a preset number of fog computing units as target fog computing units from the plurality of fog computing units through a path planning strategy; and using the target fog computing units as backup routes for communication and adding the target fog computing units to the optimized topology graph network.

[0176] In specific implementations, the scheduling module in the cloud computing center can also select a preset number of fog computing units as target fog computing units from the plurality of fog computing units through a path planning strategy after generating a plurality of data pairs. The path planning strategy can be a shortest path algorithm, and the fog computing units with shorter paths to the networking devices are selected as backup fog computing units. The preset number can be 2, 3, etc. The target fog computing units are backup routes for communication with the cloud computing center and the networking devices. The selected target fog computing units are set as backup routes to quickly switch in case of problems with the main route and ensure the continuity and reliability of communication.

[0177] After obtaining the target fog computing unit, the monitoring module in the cloud computing center can also add the target fog computing unit to the optimized topology network or label the target fog computing unit in the optimized topology network, and at the same time, the storage module in the cloud computing center saves the updated optimized topology network, and the computing module in the cloud computing center generates networking instructions to the fog computing layer after receiving the updated optimized topology network.

[0178] When performing device networking, multiple fog computing units are selected as backup bridge links at the same time, and the real-time smoothness of the control link and the data link is ensured in the case of failure by constructing a backup link routing mode.

[0179] Step S03: In the case where it is detected that the networking is completed, a networking completion instruction is generated.

[0180] It should be noted that after the cloud computing center detects that the networking is completed, the cloud computing center generates and sends a networking completion instruction through the computing module, so that the fog computing units and the networking devices in the fog computing layer after networking can interact and report data.

[0181] In the present scheme, the cloud computing center receives the initial device running data sent by the fog computing layer, and according to the initial device running data, the fog computing layer and the terminal device layer are networked, which can automatically network before controlling the virtual power plant, facilitating the management of each fog computing unit in the fog computing layer and the terminal device layer, and improving the management effect.

[0182] The present application aims at the technical problem that the calculation cost and maintenance cost are high when calculating and controlling by cloud computing, and proposes a virtual power plant control method, which is applied to the fog computing layer. Referring to FIG. 7, in the present example, the virtual power plant control method applied to the fog computing layer includes:

[0183] Step S50: In the case where the networking completion instruction sent by the cloud computing center is received, a data reporting instruction is sent to the corresponding networking device according to the networking completion instruction, so that the networking device feeds back the reporting data according to the data reporting instruction.

[0184] It should be noted that after each fog computing unit in the fog computing layer receives the networking completion instruction sent by the cloud computing center, the computing module in the fog computing unit triggers the generation of the data reporting instruction according to the networking completion instruction, and sends the data reporting instruction to the networking device networked therewith through the communication module. For example, the networking devices of unit1 are device1, device2 and device3, the networking devices of unit2 are device4, device5 and device6, then the computing module of unit1 sends the data reporting instruction to device1, device2 and device3, and the computing module of unit2 sends the data reporting instruction to device4, device5 and device6.

[0185] In a specific implementation, after the networking device receives the data reporting instruction, the information of the device is summarized into reporting data and fed back to the corresponding fog computing unit. The networking device can report the state of the device, such as the start-stop state of the device, the voltage, current, temperature parameter of the device, the upper and lower limits of the power that can be provided, the device constraint condition and other parameters. The energy management platform provides the total platform start-stop state, total voltage, current, temperature, upper and lower limits of the power that can be provided, platform constraint condition, platform regulation and maintenance plan and other information to obtain the reporting data.

[0186] Step S60: Calculate the reporting data to obtain target data.

[0187] It should be understood that the target data can be obtained by aggregating and calculating the reporting data. Specifically, the reporting data can be aggregated by a data aggregation module in each fog computing unit, so as to obtain the target data. After obtaining the target data, the data aggregation module also sends the target data to the storage module for storage.

[0188] Step S70: Send the target data to the cloud computing center, so that the cloud computing center sends the target data to the virtual power plant management center, receives the scheduling instruction, and feeds back the fog computing unit power participation strategy according to the scheduling instruction.

[0189] It can be understood that after the target data is calculated by each fog computing unit, the target data is sent to the cloud computing center through the communication module. The sending time can be set to send the target data to the cloud computing center periodically, for example, every 1h.

[0190] After the cloud computing center receives the target data sent by the communication module of each fog computing unit in the fog computing layer, all the target data is summarized, and the data is uploaded to the virtual power plant management center periodically. After receiving the target data uploaded by the cloud computing center, the virtual power plant management center generates a scheduling command in combination with the power grid power demand and the schedulable resources, and sends it to the cloud computing center. At the same time, the cloud computing center generates a fog computing unit power participation strategy according to the scheduling instruction.

[0191] Step S80: In the case of receiving the fog computing unit power participation strategy, control the networking device according to the fog computing unit power participation strategy.

[0192] It should be noted that the fog computing unit power participation strategy generated by the cloud computing center is sent to each fog computing unit through the communication module thereof. After receiving the fog computing unit power participation strategy, each unit can also use a heuristic algorithm to obtain the best result of each device or energy management platform participating in energy aggregation, so as to control the networking device.

[0193] In the present scheme, the concept of "semi-centralization" is adopted, which uses a fog computing layer to replace part of the scheduling function in the cloud computing layer, transfers part of the computing pressure and storage pressure to the decentralized "fog computing layer", calculates the reported data reported by the edge device through the fog computing layer, reduces the link transmission between the edge device and the cloud computing center, thereby reducing the bandwidth pressure and computing pressure caused by the corresponding data transmission, and after receiving the corresponding strategy, the networking device can be scheduled according to the corresponding strategy, reducing the time delay risk caused by the Internet, solving the problem of large network delay and high bandwidth cost in the current mainstream distributed control framework cloud computing mode.

[0194] In some embodiments, for computational efficiency, the reported data can be classified and aggregated for calculation. Referring to FIG. 8, step S60 specifically includes:

[0195] Step S601: Analyzing the reported data to obtain the networking device running state, networking device performance indicators, and environmental parameters.

[0196] It should be noted that the reported data includes device running state, networking device performance indicators, and corresponding environmental parameters, etc. Therefore, the reported data can be analyzed to obtain device start-stop state, device voltage, current, temperature parameters, upper and lower limits of available power, device constraint conditions, etc. The energy management platform provides total platform start-stop state, total voltage, current, temperature, upper and lower limits of available power, platform constraint conditions, platform regulation and maintenance plan, etc.

[0197] Step S602: Classifying the data according to at least one of the networking device running state, the networking device performance indicators, and the environmental parameters to obtain classified data.

[0198] In specific implementation, the data can be classified according to one or more of the networking device running state, the networking device performance indicators, and the environmental parameters. For example, the devices can be classified into "normal operation", "performance decline", "need maintenance", etc. to obtain classified data.

[0199] Step S603: Aggregating and calculating the classified data to obtain target data.

[0200] In specific implementation, the classified data is aggregated and calculated to obtain higher-level insights. For example, the number of devices in each category, average performance indicators, statistical data of environmental parameters, etc. can be calculated. The aggregation calculation can use time series aggregation, statistical aggregation, grouping aggregation, etc.

[0201] As shown in FIG. 9, FIG. 9 is a schematic diagram of the process of data synchronization and communication control between the cloud computing center and each fog computing unit. The computing module and the data storage module in the cloud computing center interact with each other. The communication module sends data to the data aggregation module, and sends the data to the computing module through the data aggregation module. The monitoring module and the communication module interact with each other. At the same time, the monitoring module and the scheduling module interact with each other. The communication modules in each fog computing unit can communicate with each other, and also communicate with the communication module of the cloud computing center. The control module, the data storage module, and the data aggregation module in each fog computing unit all communicate with the communication module. Each fog computing unit is connected to multiple edge devices.

[0202] Through the numerous dispersed central nodes arranged in the fog computing layer, each central node is responsible for the calculation of the reported data of the networking device in the network formed by the central node. Through distributed calculation, the efficiency of data calculation is improved.

[0203] In some embodiments, referring to FIG. 10, step S80 specifically includes:

[0204] Step S801: In the case where the fog computing unit power participation strategy is received, the networking device participation strategy is calculated based on the fog computing unit power participation strategy.

[0205] It should be noted that each unit can calculate the networking device participation strategy through the fog computing unit power participation strategy after receiving the fog computing unit power participation strategy. Specifically, the fog computing unit power participation strategy can be solved through the unit commitment model established in advance, so as to obtain the networking device participation strategy.

[0206] In some embodiments, step S801 can include: in the case where the fog computing unit power participation strategy is received, obtaining a target power participation fog computing unit based on the fog computing unit power participation strategy; obtaining a constraint condition according to the networking device and the target power participation fog computing unit, and obtaining a second target function; inputting the constraint condition and the second target function into the unit commitment model for solving, to obtain the networking device participation strategy.

[0207] It should be understood that after each unit receives the fog computing unit power participation strategy, the fog computing unit power participation strategy can be analyzed to obtain the target power participation fog computing unit, i.e., the fog computing unit that participates in subsequent calculation and data interaction. The unit commitment model is obtained by modeling each fog computing unit in advance using a model with safety constraints, and the edge devices under the jurisdiction of each unit and the target power participation fog computing unit can be used as constraint conditions.

[0208] The second objective function can be maximizing the participation of the networking device, minimizing the cost, or ensuring the safety of the networking device, etc., which can be selected according to actual needs. The second objective function and the constraint condition are input into a unit commitment model (SCUC), and a heuristic algorithm is used for optimal solution. Under the condition of ensuring the safety of each device or each energy management platform, the optimal scheme of each device or energy management platform participating in energy aggregation, i.e., the networking device participation strategy, is obtained. The constraint condition and the target power participating in the fog computing unit are optimized and solved by the unit commitment model used by each fog computing unit in the fog computing layer. Under the condition of ensuring the safety of each device or each energy management platform, the optimal result of each device or energy management platform participating in energy aggregation is obtained.

[0209] Step S802: controlling the networking device according to the networking device participation strategy.

[0210] After obtaining the networking device participation strategy, the networking device can be controlled according to the participation scheme of each networking device in the networking device participation strategy. Specifically, a related control instruction can be generated and sent to the networking device, so that the networking device performs data reporting and other operations according to the sent instruction.

[0211] In some embodiments, step S802 specifically includes: determining a to-be-managed networking device according to the networking device participation strategy; and sending an instruction to the to-be-managed networking device, so that the to-be-managed networking device performs data reporting based on the instruction.

[0212] It should be noted that the to-be-managed networking device can be determined according to the solved networking device participation strategy, so that a control instruction can be generated to the to-be-managed networking device, and the to-be-managed networking device collects its own data for data reporting through the sent control instruction. The to-be-managed networking device is determined through the networking device participation strategy, so that the to-be-managed networking device can ensure data reporting according to the established strategy, provide necessary information support for network optimization and management, realize data interaction between the fog computing layer and the networking device, and effectively manage the networking device.

[0213] In the technical scheme of the embodiment of the application, according to the power participation strategy, the fog computing unit evaluates the power demand and availability of each device in the networking, thereby calculating the optimal power use mode of each device under different conditions. Based on the above analysis, the fog computing unit generates a specific networking device participation strategy, thereby accurately controlling how the device operates according to the power supply and demand, so that the fog computing unit can effectively manage and control the networking device according to the power participation strategy.

[0214] In some embodiments, during the networking stage, the trigger condition for the cloud computing center to network is to receive the data reported by the fog computing layer. Therefore, before step S50, steps A41-A43 are further included.

[0215] Step A41: receiving the initial device operation data reported by the terminal device layer, and sending the initial device operation data to the cloud computing center, so that the cloud computing center feeds back the networking scheme and the networking instruction based on the initial device operation data.

[0216] In a specific implementation, after connecting with the plurality of terminal devices in the terminal device layer, the fog computing layer can receive the initial device operation data reported by the terminal device layer, the initial device operation data including device information, device state information, and routing topology information, and send the initial device operation data to the cloud computing center.

[0217] After receiving the initial device operation data, the cloud computing center can create a graph network for the routing topology according to the initial device operation data, update the topology graph network, and generate a final data pair between the fog computing unit and the edge device according to an algorithm and the initial device operation data, and generate the networking scheme and the networking instruction according to the data pair.

[0218] Step A42: networking with the terminal device layer according to the networking scheme and the networking instruction, and generating binding information.

[0219] It should be noted that after each fog computing unit receives the networking scheme and the networking instruction, it can determine to bind and communicate with the devices in its own logical jurisdiction area according to the networking scheme and the networking instruction, and generate binding information, the binding information including the fog computing unit and the corresponding networking device.

[0220] In some embodiments, the step of networking with the terminal device layer according to the networking scheme and the networking instruction, and generating binding information includes:

[0221] networking judgment and clock synchronization according to the networking instruction;

[0222] After the networking judgment and the clock synchronization are completed, binding and communication with the devices in the corresponding jurisdiction area in the terminal device layer according to the networking scheme, and generating binding information.

[0223] It should be noted that after listening to the networking instruction, the data aggregation module of the fog computing unit can pass the networking instruction to the fog computing module, and perform networking judgment and clock synchronization through the fog computing module, the networking judgment including determining which devices should join the network, how to configure the network connection, and allocating resources, and the clock synchronization mainly ensures that all participating devices or nodes are consistent in time.

[0224] After the networking judgment and the clock synchronization are completed, the control module of the fog computing unit binds and communicates with the devices in its own logical jurisdiction area in the terminal device layer according to the networking scheme, thereby generating the binding information.

[0225] In the technical solution of the embodiment of the application, network forming is determined according to the network forming instruction and the local data, so as to determine which devices need to participate in network forming and clock synchronization, and ensure that all devices operate under the same time reference. After network forming determination and clock synchronization are completed, the devices in the same logical jurisdiction area can be bound and communicated according to the network forming scheme, automatic network forming can be realized, and network forming efficiency is improved.

[0226] Step A43: The binding information is stored, and the binding information is sent to the cloud computing center, so that the cloud computing center determines that network forming is completed according to the binding information.

[0227] After the edge device is bound with the fog computing unit, the binding state is stored by the storage module of the fog computing unit computing module, and the state information is uploaded to the cloud computing center through the communication module, so that the cloud computing center determines that network forming is completed based on the binding information. Meanwhile, the cloud computing center can feed back the binding information to the monitoring module and aggregate the data together until all units complete network forming and store the data in the storage module. The system topology is synchronized to each unit through the relevant downlink by the computing module, and thus, the system network forming is completed.

[0228] In the embodiment, the initial device running data is sent to the cloud computing center, so as to receive the network forming scheme and the network forming instruction sent by the cloud computing center. The fog computing layer performs network forming operation with the terminal device layer according to the received network forming scheme and instruction. In the network forming process, the fog computing layer generates binding information reflecting the connection and configuration state between the fog computing unit and the devices in the terminal device layer. The binding information is stored for subsequent query and use.

[0229] In some embodiments, in order to improve data communication efficiency, when the data link fails, data communication can be performed through the backup link. Therefore, the control method of the virtual power plant applied to the fog computing layer includes the following steps.

[0230] In the case where it is detected that the transmission link between the cloud computing center fails, an optimized topology network is obtained, a target fog computing unit is determined from the optimized topology network, and communication is performed between the target fog computing unit and the cloud computing center.

[0231] It should be noted that according to the networking stage, each unit also maintains link monitoring with other g units except itself to ensure that the standby routing route is available, so when the link between the unit and the cloud computing center fails, the unit only needs to realize data interaction and forwarding through one of the g units to indirectly realize data synchronization and instruction transmission with the cloud data center, that is, to determine the target fog computing unit from the optimized topology network, for example, there are 3 target fog computing units, and the optimal fog computing unit can be determined as a standby communication route. As shown in FIG. 11, FIG. 11 is a schematic diagram of normal connection of the cloud computing center and the units in the fog computing layer, and unit4 and unit5 are backup standby bridge links of the unit. Under normal circumstances, unit1 only needs to monitor the links of unit4 and unit5 in real time. As shown in FIG. 12, FIG. 12 is a schematic diagram of switching when the communication link between the cloud computing center and the fog computing layer fails. When the unit and the cloud computing center fail to communicate, unit1 randomly selects one of unit4 and unit5 as a "relay" standby bridge link, that is, selects one of the red and blue links as a standby bridge link. Indirect communication is performed.

[0232] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the control method of the virtual power plant of the present application. More forms of simple transformation based on this technical concept are within the protection scope of the present application.

[0233] In addition, the embodiment of the present application also proposes a virtual power plant control system, which comprises a terminal device layer, a cloud computing center and a fog computing layer.

[0234] In addition, the embodiment of the present application also proposes a virtual power plant transaction system, which comprises a terminal device layer, a power grid dispatching center, a virtual power plant management center, a cloud computing center and a fog computing layer. The virtual power plant transaction system executes the above virtual power plant control method when performing power grid transaction.

[0235] Referring to FIG. 13, FIG. 13 is a structural block diagram of a first embodiment of a virtual power plant control device applied to a cloud computing center according to the present application.

[0236] As shown in FIG. 13, the virtual power plant control device applied to a cloud computing center according to the embodiment of the present application comprises:

[0237] A first sending module 110 is configured to send a networking completion instruction to the fog computing layer, so that the fog computing layer sends a data reporting instruction to the corresponding networking device based on the networking completion instruction and feeds back.

[0238] The acquisition module 120 is configured to acquire target data fed back by the fog computing layer, wherein the target data is obtained by calculating reported data reported by the networking device after each fog computing unit in the fog computing layer sends a data reporting instruction to the corresponding networking device.

[0239] The first sending module 110 is further configured to send the target data to a virtual power plant management center, and receive a scheduling instruction generated by the virtual power plant management center based on the target data.

[0240] The control module 130 is configured to perform device control according to the scheduling instruction.

[0241] In the scheme, the networking completion instruction is sent to the fog computing layer, so that the fog computing layer sends corresponding instructions to the networking device successfully networked therewith, the fog computing layer performs calculation based on the reported data reported by the networking device, and the target data is sent to the cloud computing center. The cloud computing center undertakes secondary calculation tasks and data synchronization aggregation and system scheduling functions, and the fog computing layer mainly undertakes primary calculation functions, so that the data calculation cost in the control of the virtual power plant can be reduced, and the problems of large network delay and high bandwidth cost in the cloud computing mode of the mainstream distributed control framework can be solved.

[0242] Referring to FIG. 14, FIG. 14 is a structural block diagram of a control device of a virtual power plant applied to a fog computing layer according to a first embodiment of the application.

[0243] As shown in FIG. 14, the control device of the virtual power plant applied to the fog computing layer according to the embodiment of the application comprises:

[0244] The receiving module 210 is configured to, in a case where the networking completion instruction sent by the cloud computing center is received, send a data reporting instruction to the corresponding networking device according to the networking completion instruction, so that the networking device feeds back reported data according to the data reporting instruction.

[0245] The calculation module 220 is configured to calculate the reported data to obtain target data.

[0246] The second sending module 230 is configured to send the target data to the cloud computing center, so that the cloud computing center sends the target data to a virtual power plant management center, and receives a scheduling instruction, and feeds back a fog computing unit power participation strategy according to the scheduling instruction.

[0247] The receiving module 230 is further configured to, in a case where the fog computing unit power participation strategy is received, control the networking device according to the fog computing unit power participation strategy.

[0248] In the present scheme, the concept of "semi-centralization" is adopted, the fog computing layer is used to replace part of the scheduling function in the cloud computing layer, and the computing pressure and storage pressure are transferred to the decentralized "fog computing layer". The fog computing layer calculates the reported data reported by the edge device, reduces the link transmission between the edge device and the cloud computing center, thereby reducing the bandwidth pressure and computing pressure caused by the corresponding data transmission, and after receiving the corresponding strategy, the networking device can be scheduled according to the corresponding strategy, reducing the time delay risk caused by the Internet, solving the problem of large network delay and high bandwidth cost in the current mainstream distributed control framework cloud computing mode.

[0249] It should be understood that the above is only illustrative, and does not constitute any limitation on the technical solutions of the present application. In specific applications, those skilled in the art can set it up according to the needs, and the present application does not limit it.

[0250] It should be noted that the above-described workflow is only illustrative and does not limit the scope of protection of the present application. In actual application, those skilled in the art can select part or all of them to achieve the purpose of the present embodiment scheme according to actual needs, which is not limited here.

[0251] In addition, technical details not described in detail in the present embodiment can be referred to the control method of the virtual power plant provided by any embodiment of the present application, which will not be repeated here.

[0252] Finally, it should be pointed out that: the above embodiments are only used to illustrate the technical solutions of the present application, but not to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application, and they should be covered in the scope of the claims and the description of the present application. Especially, as long as there is no structural conflict, each technical feature mentioned in each embodiment can be combined in any way. The present application is not limited to the specific embodiments disclosed in the text, but includes all technical solutions falling within the scope of the claims.

Claims

1. A control method of a virtual power plant, wherein, The method comprises: sending a networking completion instruction to the fog computing layer, so that the fog computing layer sends a data reporting instruction to the corresponding networking device based on the networking completion instruction and feeds back; obtaining target data fed back by the fog computing layer, the target data being calculated from reporting data reported by the networking device; sending the target data to a virtual power plant management center and receiving a scheduling instruction generated by the virtual power plant management center based on the target data; controlling the device according to the scheduling instruction.

2. The method of claim 1, wherein, The step of controlling the device according to the scheduling instruction comprises: obtaining power demand data and schedulable data according to the scheduling instruction; calculating the power demand data and the schedulable data to obtain a fog computing unit power participation strategy; sending the fog computing unit power participation strategy to each fog computing unit in the fog computing layer, so that the fog computing unit calculates a networking device participation strategy based on the fog computing unit power participation strategy and controls the networking device according to the networking device participation strategy.

3. The method of claim 2, wherein, The step of calculating the power demand data and the schedulable data to obtain a fog computing unit power participation strategy comprises: obtaining a first target function and a constraint condition according to the power demand data and the schedulable data; solving the first target function and the constraint condition according to an economic scheduling model to obtain a fog computing unit power participation strategy.

4. The method of any one of claims 1 to 3, wherein, Before the step of sending a networking completion instruction to the fog computing layer, the method further comprises receiving initial device operation data sent by the fog computing layer, the initial device operation data being sent by a terminal device layer to the fog computing layer; networking the fog computing layer and the terminal device layer based on the initial device operation data; generating a networking completion instruction when it is detected that the networking is completed.

5. The method of claim 4, wherein, The step of networking the fog computing layer and the terminal device layer based on the initial device operation data comprises: decoding the initial device operation data to obtain at least one of device information, device state information and routing topology information; creating a topology graph network based on at least one of the device information, the device state information and the routing topology information; optimizing the topology graph network through a preset optimization strategy to obtain an optimized topology graph network; obtaining a plurality of data pairs between the fog computing unit and the edge device according to the optimized topology graph network, the data pair being composed of one fog computing unit and a plurality of edge devices; generating a networking scheme and a networking instruction according to a plurality of the data pairs; sending the networking scheme and the networking instruction to each fog computing unit in the fog computing layer to network the fog computing layer and the terminal device layer.

6. The method of claim 5, wherein, The step of sending the networking scheme and the networking instruction to each fog computing unit in the fog computing layer to network the fog computing layer and the terminal device layer comprises: sending the networking scheme and the networking instruction to each fog computing unit in the fog computing layer, and receiving binding information fed back by the fog computing units according to the networking scheme and the networking instruction, the binding information being generated by the fog computing units after the fog computing units are networked with corresponding devices in a terminal device layer according to the networking scheme and the networking instruction; after detecting that each fog computing unit in the fog computing layer feeds back the binding information, storing the binding information, and sending the optimized topology graph network to the fog computing units, completing the networking.

7. The method of claim 5, wherein, The method further includes: determining abnormal data based on the device state information and the device information; labeling the abnormal data to obtain a labeling result; updating the topology graph network according to the labeling result.

8. The method of claim 5, wherein, The method further includes: filtering a preset number of fog computing units as target fog computing units from a plurality of fog computing units through a path planning strategy; communicating through the target fog computing units as backup routes, and adding the target fog computing units to the optimized topology graph network.

9. A control method of a virtual power plant, wherein The control method of the virtual power plant includes: in a case where a networking completion instruction sent by a cloud computing center is received, sending a data reporting instruction to corresponding networked devices according to the networking completion instruction, so that the networked devices feed back reported data according to the data reporting instruction; calculating the reported data to obtain target data; sending the target data to the cloud computing center, so that the cloud computing center sends the target data to a virtual power plant management center, and receives a dispatching instruction and feeds back a fog computing unit power participation strategy according to the dispatching instruction; in a case where the fog computing unit power participation strategy is received, controlling the networked devices according to the fog computing unit power participation strategy.

10. The method of claim 9, wherein, The step of calculating the reported data to obtain target data includes: analyzing the reported data to obtain networked device operating states, networked device performance indicators, and environmental parameters; classifying data according to at least one of the networked device operating states, the networked device performance indicators, and the environmental parameters to obtain classified data; aggregating and calculating the classified data to obtain target data.

11. The method of claim 9, wherein, The step of, in a case where the fog computing unit power participation strategy is received, controlling the networked devices according to the fog computing unit power participation strategy includes: in a case where the fog computing unit power participation strategy is received, calculating a networked device participation strategy based on the fog computing unit power participation strategy; controlling the networked devices according to the networked device participation strategy.

12. The method of claim 11, wherein, The step of, in a case where the fog computing unit power participation strategy is received, calculating a networked device participation strategy based on the fog computing unit power participation strategy includes: in a case where the fog computing unit power participation strategy is received, obtaining a target power participating fog computing unit based on the fog computing unit power participation strategy; obtaining a constraint condition according to a networked device and the target power participating fog computing unit, and obtaining a second target function; The constraint condition and the second target function are input into a unit commitment model for solving to obtain a networking device participation strategy.

13. The method of claim 11, wherein, The step of controlling the networking device according to the networking device participation strategy comprises: determining a to-be-managed networking device according to the networking device participation strategy; sending an instruction to the to-be-managed networking device to make the to-be-managed networking device report data based on the instruction.

14. The method of any one of claims 9 to 13, wherein, Before the step of sending a data reporting instruction to the corresponding networking device according to the networking completion instruction sent by the cloud computing center, the method further comprises: receiving initial device operation data reported by a terminal device layer and sending the initial device operation data to a cloud computing center to make the cloud computing center feed back a networking scheme and a networking instruction based on the initial device operation data; networking with the terminal device layer according to the networking scheme and the networking instruction and generating binding information; storing the binding information and sending the binding information to the cloud computing center to make the cloud computing center determine networking completion according to the binding information.

15. The method of claim 14, wherein, The step of networking with the terminal device layer according to the networking scheme and the networking instruction and generating binding information comprises: judging networking and synchronizing a clock according to the networking instruction; after the networking judgment and the clock synchronization are completed, binding and communicating with devices in a corresponding jurisdictional area in the terminal device layer according to the networking scheme to generate the binding information.

16. The method of any one of claims 9 to 15, wherein, The method further comprises: in a case where it is detected that a transmission link between the cloud computing center fails, obtaining an optimized topology network; determining a target fog computing unit from the optimized topology network, and communicating with the cloud computing center through the target fog computing unit.

17. A control system of a virtual power plant, wherein The control system of the virtual power plant comprises a terminal device layer, the cloud computing center of any one of claims 1 to 8, and the fog computing layer of any one of claims 9 to 16.

18. A trading system for a virtual power plant, wherein, The transaction system of the virtual power plant comprises a terminal device layer, a power grid dispatching center, a virtual power plant management center, the cloud computing center of any one of claims 1 to 8, and the fog computing layer of any one of claims 9 to 16, and the transaction system of the virtual power plant performs the control method of the virtual power plant of any one of claims 1 to 16 when performing power grid transactions.

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