Gridding power distribution network management method and system based on cloud edge fusion architecture

Abstract

The invention discloses a gridding power distribution network management method and system based on a cloud edge fusion architecture, and relates to the technical field of power distribution Internet of Things, and the method comprises the steps: constructing a four-stage node architecture comprising a central cloud platform, an edge grid control platform, a user side resource aggregation control platform and a user control terminal, and carrying out the deployment of the central cloud platform; synchronizing the resource information uploaded by all the platforms, collecting the resource information in the corresponding district by using a user control terminal, carrying out user side resource local control, and generating and issuing a regulation and control instruction; and executing the issued regulation and control instruction, and performing gridding power distribution network management based on the cloud edge fusion architecture according to the regulation and control instruction. According to the method, the efficient coordination management and control and overall calculation capability among the hierarchies can be improved, the current grid situation and the planning situation are analyzed, the combined project approval suggestions can be put forward in an integrated mode, the power grid planning construction work efficiency is improved, and the power grid repeated investment is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution Internet of Things, and in particular to a grid distribution network management method and system based on a cloud-edge fusion architecture. Background Art

[0002] With the access of a large proportion of distributed renewable energy and electric vehicles, the demand for flexible load energy diversity is growing, and the distribution network is changing from a traditional one-way power provider to a two-way energy flow and advanced services. Building a distribution network Internet of Things with cloud-edge-end as the system architecture can greatly improve the comprehensive perception of the distribution network's operating status, and on the other hand, it can meet the needs of large-scale connection of massive distributed resource access systems, promote two-way data interaction in distribution stations, and improve the efficiency of station management and control.

[0003] At present, the distribution network generally adopts a centralized optimization and dispatching method. After collecting information data from each terminal of the entire distribution network, it is uploaded to the distribution energy management system (EMS) of the dispatching center. The dispatching center centrally processes all the collected global information data, calculates the results, and then communicates them to each terminal for execution to achieve optimization and dispatching. However, with the formation of active distribution networks, the types and quantities of distributed energy that can be actively managed and dispatched are increasing. At this time, the traditional centralized optimization and dispatching will cause the optimization center to have a significant increase in the demand for hardware such as computers and storage devices, and the demand for communication bandwidth will also rise sharply, which will greatly reduce the computing efficiency and increase the economic cost, which is completely inconsistent with the requirements of power grid development. Another disadvantage of centralized optimization and dispatching is that the selection of optimization targets is inflexible. When distributed energy is widely penetrated, in such a huge distribution network, the optimization and dispatching targets of each region and each node are not the same. We should consider that each region or even each node may belong to different stakeholders. In the face of different situations, the optimization and dispatching of active distribution networks should realize the idea of ​​distributed autonomy and collaborative optimization in each region, while the traditional centralized optimization and dispatching can only set a unified optimization target for the whole world, and cannot achieve different optimization targets for each region. Summary of the invention

[0004] In view of the problems existing in the existing grid distribution network management method based on the cloud-edge fusion architecture, the present invention is proposed. Therefore, the problem to be solved by the present invention is how to provide a grid distribution network management method and system based on the cloud-edge fusion architecture.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] In the first aspect, the present invention provides a grid distribution network management method based on a cloud-edge fusion architecture, which includes constructing a four-level node architecture including a central cloud platform, an edge grid control platform, a user-side resource aggregation control platform and a user control terminal, and deploying the central cloud platform; synchronizing resource information uploaded by all platforms, using the user control terminal to collect resource information in the corresponding area to perform on-site control of user-side resources and generate and issue control instructions; executing the issued control instructions, and managing the grid distribution network based on the cloud-edge fusion architecture according to the control instructions.

[0007] As an optimal scheme of the grid distribution network management method based on cloud-edge fusion architecture described in the present invention, wherein: the control instructions include first-level control instructions, second-level control instructions, third-level control instructions and fourth-level control instructions; the user control terminal generates fourth-level control instructions according to resource information, the user-side resource aggregation control platform sends the third-level control instructions to all user control terminals, the edge grid control platform sends the second-level control instructions to all user-side resource aggregation control platforms, and the central cloud platform sends the first-level control instructions to all edge grid control platforms.

[0008] As an optimal scheme of the grid distribution network management method based on the cloud-edge fusion architecture described in the present invention, wherein: the first-level control instruction includes a grid area division command, and obtaining the grid area division command includes the following steps: dynamically generating grid units by comprehensively considering the structural and functional grid division index system; calculating the modularity index and branch flexibility margin index based on the electrical distance, calculating the connection strength between different network nodes, and defining the grid branch flexibility margin index to reflect the average load rate of the network branch; normalizing the electrical distance and branch flexibility margin index, and constructing an objective function for grid division; on the basis of grid division, assigning a grid number to each grid according to the geographic information data in the business data, the load monitoring data and the power supply points in the distribution network.

[0009] As an optimal scheme of the grid distribution network management method based on cloud-edge fusion architecture described in the present invention, wherein: the secondary control instructions include the user-side resource aggregation control instructions within the grid, which are calculated using the optimization model considering the source-load uncertainty, and an uncertainty set is constructed; if the adjustable uncertainty parameter of the unit is 0, it means that there is no uncertainty in the uncontrollable load, and the robust optimization model is converted into a deterministic model; if the adjustable uncertainty parameter of the unit is an upper limit number, it means that there is uncertainty in the uncontrollable load throughout the scheduling cycle, and the objective function of the optimization model considering source-load uncertainty is constructed and the constraints of the user-side resource aggregation optimization model within the grid are obtained, and the secondary control instructions are solved to perform user-side resource aggregation control within the grid.

[0010] As a preferred solution of the grid distribution network management method based on the cloud-edge fusion architecture described in the present invention, the constraint conditions of the user-side resource aggregation optimization model in the grid include distribution network flow constraints and safety constraints, and the expression of the flow constraints is:

[0011]

[0012] Where P ij,t , Q ij,t are respectively the active power and reactive power of branch ij in period t; P j,t , Q j,t are the net injected active power and reactive power at node j in period t, respectively; u(j) and v(j) are the set of branch end nodes with j as the first node and the set of branch head nodes with j as the last node, respectively; B is the set of distribution network nodes; r ij 、x ij are the resistance and reactance of branch ij respectively; I ij,t , L ij,t are the current flowing through branch ij and its square in period t, l is the set of distribution network branches; U j,t 、V j,t are the voltage at node j and its square during period t respectively; They are the output power of photovoltaic and wind turbine respectively; are respectively the active load and reactive load at node j in period t; the expression of the safety constraint is:

[0013]

[0014] In the formula, They represent the upper and lower limits of the current flowing through branch ij respectively; Respectively represent the upper and lower limits of the voltage of node i; It represents the maximum active power that can flow through branch ij.

[0015] As an optimal scheme of the grid distribution network management method based on the cloud-edge fusion architecture described in the present invention, wherein: the deployment of the central cloud platform includes the following steps: obtaining at least one node to be deployed information from the node storage pool through the cluster deployment service; automatically generating network configuration information corresponding to the node to be deployed according to the node to be deployed information; deploying the node to be deployed to the cloud platform according to the network configuration information corresponding to the node to be deployed; the third-level control instruction is the user control terminal executing the control instruction, sorting them according to the marginal cost of individual user adjustment as the control priority guidance indicator, decomposing and issuing them according to the total value of the second-level control instruction, monitoring the execution result of the control instruction, and selecting the user control terminal for adjustment; the fourth-level control instruction is the user device on-site control command to the user's own device on-site response.

[0016] As an optimal solution of the grid distribution network management method based on the cloud-edge fusion architecture described in the present invention, the execution of the issued control instructions includes the following steps: generating an initial control instruction; if the user control terminal detects a situation that requires control, a fourth-level control instruction is generated; if the fourth-level control instruction can meet the control requirements, the user control terminal directly executes the fourth-level control instruction; otherwise, a third-level control instruction is requested from the user-side resource aggregation control platform to evaluate and execute multi-level control instructions; if the system receives a third-level control instruction and meets the control requirements, the user control terminal executes the third-level control instruction; otherwise, a second-level control instruction is requested from the edge grid control platform; if the edge grid control platform receives a second-level control instruction and meets the control requirements, the second-level control instruction is executed; otherwise, a first-level control instruction is requested from the central cloud platform; if the central cloud platform receives a first-level control instruction, the user control terminal must execute the first-level control instruction, execute and feedback the control instruction, and start the execution timer at the same time, adjust the generation strategy of control instructions at all levels, and evaluate the execution effect after the control instruction is executed, end the current control cycle and start the next level of control instruction.

[0017] In the second aspect, the present invention provides a grid distribution network management system based on a cloud-edge fusion architecture, which includes: a construction module, which is used to construct a four-level node architecture including a central cloud platform, an edge grid control platform, a user-side resource aggregation control platform and a user control terminal, and deploy the central cloud platform; a generation module, which is used to synchronize the resource information uploaded by all platforms, and use the user control terminal to collect resource information in the corresponding area to perform on-site control of user-side resources and generate and issue control instructions; an execution management module, which is used to execute the issued control instructions, and perform grid distribution network management based on the cloud-edge fusion architecture according to the control instructions.

[0018] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the processor executes the computer program, it implements the steps of a grid distribution network management method based on a cloud-edge fusion architecture.

[0019] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, the steps of a grid distribution network management method based on a cloud-edge fusion architecture are implemented.

[0020] The beneficial effect of the present invention is that by setting up multi-level control, the pressure of cloud computing can be decentralized, local processing can be achieved, and efficient coordination and control and overall computing capabilities between various levels can be improved. The current status and planning of the grid can be analyzed, and suggestions for merging projects can be integrated to greatly improve the efficiency of grid planning and construction and reduce repeated investment in the grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 This is a flow chart of the grid distribution network management method based on cloud-edge fusion architecture.

[0023] Figure 2 This is a framework diagram of the grid distribution network management system based on the cloud-edge fusion architecture. DETAILED DESCRIPTION

[0024] In order to make the above-mentioned purposes, features and advantages of the present invention more understandable, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0025] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0026] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0027] Example 1

[0028] Reference Figure 1 , which is the first embodiment of the present invention, and provides a grid distribution network management method based on a cloud-edge fusion architecture, including:

[0029] S1: Build a four-level node architecture including the central cloud platform, edge grid control platform, user-side resource aggregation control platform, and user control terminal;

[0030] Specifically, the control instructions include first-level control instructions, second-level control instructions, third-level control instructions, and fourth-level control instructions;

[0031] The user control terminal generates four-level control instructions based on resource information. The user-side resource aggregation control platform sends three-level control instructions to all user control terminals. The edge grid control platform sends two-level control instructions to all user-side resource aggregation control platforms. The central cloud platform sends one-level control instructions to all edge grid control platforms.

[0032] The central cloud platform is the first-level node, the edge grid control platform is the second-level node, the user-side resource aggregation control platform is the third-level node, and the user control terminal is the fourth-level node. The first-level node, the second-level node, the third-level node and the fourth-level node communicate via one of the wireless, optical fiber or carrier.

[0033] Specifically, the central cloud platform is connected to multiple edge grid control platforms, each edge grid control platform is connected to multiple user-side resource aggregation control platforms, each user-side resource aggregation control platform is connected to multiple user control terminals, and the central cloud platform and the edge grid control platform, the edge grid control platform and the user-side resource aggregation control platform, and the user-side resource aggregation control platform and the user control terminal communicate through one of the wireless public networks, carriers or optical fibers according to data security requirements.

[0034] The central cloud platform is used to synchronize the resource information uploaded by all connected edge grid control platforms. The edge grid control platform is used to synchronize the resource information uploaded by all connected user-side resource aggregation control platforms and issue control instructions to the user-side resource aggregation control platform. The user-side resource aggregation control platform is used to synchronize the resource information on all connected user control terminals and issue user control terminal instructions. The user control terminal is used to collect resource information within the corresponding area and perform on-site control of user-side resources.

[0035] The central cloud platform is used to store various business data of existing business systems. The business data includes power grid management data and power grid operation data. The power grid management data is equipment status management data, and the power grid operation data is data at high, medium and low voltage levels.

[0036] Specifically, the user control terminal can generate four-level control instructions based on resource information. The user-side resource aggregation control platform sends the third-level control instructions to all user control terminals. The edge grid control platform sends the second-level control instructions to all user-side resource aggregation control platforms. The central cloud platform sends the first-level control instructions to all edge grid control platforms. All the third-level control instructions, second-level control instructions and first-level control instructions are generated by resource information.

[0037] S2: Synchronize the resource information uploaded by the platform, use the user control terminal to collect the resource information in the corresponding area, perform local control of user-side resources, generate and issue control instructions;

[0038] Specifically, the first-level control instruction is the grid area division command; the grid area division is used to dynamically generate grid units, and this dynamic grid unit is generated by comprehensively considering the structural and functional grid division index system. Structurally, the modularity index based on electrical distance is used to characterize the connection strength between different network nodes and effectively aggregate the devices with the closest electrical distance. Functionally, the branch flexibility sufficiency index is introduced to reflect the ability of flexible resources to be transmitted through branches.

[0039] Defining the grid branch flexibility index To reflect the average load rate of the network branch. The larger the value, the greater the load margin of each branch in grid c, and the stronger the ability to cope with the uncertainty changes in flexibility demand.

[0040]

[0041] In the formula, is the branch set of grid c; N b is the number of branches in the grid; is the load rate of branch l in the cth grid at time t; L l,t is the current flowing through branch l at time t; is the maximum value of the current allowed to flow through branch l.

[0042] The electrical distance and branch flexibility margin indicators are normalized and used as the objective function for grid division.

[0043] On the basis of grid division, each grid is assigned a grid number according to the geographic information data in the business data, the load monitoring data and the power supply points in the distribution network;

[0044] The secondary control command is the user-side resource aggregation control command within the grid; it is calculated using an optimization model that considers source-load uncertainty. The uncertainty set is as follows:

[0045]

[0046] In the formula, They are the uncertainty variables, predicted output and maximum prediction error value of the renewable distributed generation (R-DG) unit g at time t; An auxiliary variable indicating the R-DG output at the interval boundary, which is a binary variable; N R-DG is the number of R-DG units. R-DG refers to distributed photovoltaic PV, wind turbine WT and uncontrollable load. and So that the actual value of R-DG is within the uncertainty interval Inside. is the adjustable uncertainty parameter of the R-DG unit, and its value represents the number of time periods in which the R-DG can obtain the maximum value of the prediction interval during the scheduling optimization process. The size of can adjust the conservativeness of robust optimization;

[0047] like It means that R-DG has no uncertainty, and the robust optimization model is transformed into a deterministic model without conservatism; if Taking the upper limit means that R-DG has uncertainty in the entire scheduling cycle, and the robust optimization is most conservative. Its objective function model is as follows:

[0048]

[0049] Where: P t HV is the transaction power between the user-side resource aggregation within the grid and the upper-level grid at time t. A positive value indicates that the user-side resource aggregation within the grid purchases electricity from the upper-level grid, and a negative value indicates that the user-side resource aggregation within the grid sells electricity to the upper-level grid. is the corresponding transaction price; and are the charging and discharging power of ESS (energy storage) at time t, Characterize the energy storage operating costs. is the GT output power at time t, is its power generation cost coefficient; E D and G D They are the ESS and GT collection in the distribution network respectively; It is the transaction power between the user-side resource aggregation within the grid and other grids in real-time operation. A positive value indicates that the user-side resource aggregation within the grid sells electricity to other grids, and a negative value indicates that the user-side resource aggregation within the grid purchases electricity from other grids. is the corresponding transaction price; They are the upward flexibility (Flexible ramp-up, FRU) and downward flexibility (Flexible ramp-down, FRD) provided by other user-side resource aggregation in the grid at time t, is the corresponding price; n MG is the set of MGs in the distribution network, and T is the time period.

[0050] The constraints of the user-side resource aggregation optimization model within the grid include distribution network flow constraints and security constraints, as shown below: 1) AC flow constraints based on the second-order cone model:

[0051]

[0052] Where P ij,t , Q ij,tare respectively the active power and reactive power of branch ij in period t; P j,t , Q j,t are the net injected active power and reactive power at node j in period t, respectively; u(j) and v(j) are the set of branch end nodes with j as the first node and the set of branch head nodes with j as the last node, respectively; B is the set of distribution network nodes; r ij 、x ij are the resistance and reactance of branch ij respectively; I ij,t , L ij,t are the current flowing through branch ij and its square in period t, l is the set of distribution network branches; U j,t 、V j,t are the voltage at node j and its square during period t respectively; They are the output power of photovoltaic and wind turbine respectively; are the active load and reactive load at node j in period t respectively; Formula (8) is the second-order cone relaxation form of Formula (9).

[0053] 2) System security constraints:

[0054]

[0055]

[0056] Where: They represent the upper and lower limits of the current flowing through branch ij respectively; Respectively represent the upper and lower limits of the voltage of node i; It represents the maximum active power that can flow through branch ij.

[0057] The third-level control command is for the user to control the terminal to execute the control command;

[0058] The third-level control instructions are sorted based on the marginal cost of individual user adjustments as the control priority guidance indicator, and are decomposed and issued according to the total value of the second-level control instructions. The execution results of the control instructions are monitored. If the control instruction is not completed within 2 minutes, the unresponsive control instruction is cancelled and the user control terminal with the next priority is selected for adjustment.

[0059] The fourth-level control command is the local control command for user equipment;

[0060] The fourth-level control instructions are on-site responses of the user's own equipment, such as air conditioners, water heaters, household photovoltaics, energy storage and other resources.

[0061] When deploying cloud nodes in the central cloud platform, at least one node to be deployed information is obtained from the node storage pool through the cluster deployment service, and the network configuration information corresponding to the node to be deployed is automatically generated according to the node to be deployed information. According to the network configuration information corresponding to the node to be deployed, the node to be deployed is deployed to the cloud platform.

[0062] The edge grid control platform is controlled in grid units, and its nodes are configured with edge controllers and storage pools. The edge controller is used to process operation requests from end nodes of the user control end, package the operation requests into mirror ledgers and upload them to the central cloud platform, and read the mirror ledger information of the central cloud platform. According to the mirror ledger of the central cloud platform, operation requests are sent to end nodes for version updates and other maintenance. The storage pool is used to store data.

[0063] The end node of the user control terminal is configured with data collection, processing, storage, encryption and transmission functions. The user control terminal is used to control the two-way data transmission between the edge cloud and the user-side resource aggregation control platform according to the given user permissions.

[0064] The user-side resource aggregation control platform includes a data acquisition module, a grid division module, and a grid data collection and analysis module. The data acquisition module is used to collect business data obtained by the edge grid control platform from the central cloud platform.

[0065] S3: Execute the issued control instructions and manage the grid distribution network based on the cloud-edge fusion architecture according to the control instructions.

[0066] Specifically, an initial control instruction is generated. If the user control terminal detects that a control is required, a fourth-level control instruction is generated. If the fourth-level control instruction can meet the control requirements, the user control terminal directly executes the fourth-level control instruction.

[0067] Otherwise, request the third-level control instruction from the user-side resource aggregation control platform to evaluate and execute the multi-level control instruction;

[0068] If the system receives the third-level control instruction and can meet the control requirements, the user control terminal executes the third-level control instruction, otherwise it requests the second-level control instruction from the edge grid control platform.

[0069] If the edge grid control platform receives the second-level control instruction and can meet the control requirements, it will execute the second-level control instruction, otherwise it will request the first-level control instruction from the central cloud platform;

[0070] If the central cloud platform receives a first-level control instruction, the user control terminal must execute the first-level control instruction, execute and feedback the control instruction, start the execution timer at the same time, adjust the generation strategy of control instructions at all levels, and evaluate the execution effect after the control instruction is executed, end the current control cycle and start the next level of control instruction.

[0071] Furthermore, this embodiment also provides a grid distribution network management system based on a cloud-edge fusion architecture, including: a construction module, used to construct a four-level node architecture including a central cloud platform, an edge grid control platform, a user-side resource aggregation control platform and a user control terminal, and deploy the central cloud platform; a generation module, used to synchronize resource information uploaded by all platforms, and use the user control terminal to collect resource information in the corresponding area to perform on-site control of user-side resources and generate and issue control instructions; an execution management module, used to execute the issued control instructions, and perform grid distribution network management based on the cloud-edge fusion architecture according to the control instructions.

[0072] This embodiment also provides a computer device, which is suitable for a grid distribution network management method based on a cloud-edge fusion architecture, including: a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement all or part of the steps of the method described in the embodiment of the present invention as proposed in the above embodiment.

[0073] This embodiment also provides a storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method in any optional implementation of the above embodiment is executed. Wherein, the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, disk or optical disk.

[0074] The storage medium proposed in this embodiment and the data storage method proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be found in the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0075] As can be seen from the above, the present invention can decentralize the pressure of cloud computing by setting up multi-level control, realize local processing, and improve the efficient coordination and control and overall computing capabilities between various levels. The grid status and planning situation can be analyzed, and suggestions for combined project establishment can be integrated to greatly improve the efficiency of grid planning and construction and reduce repeated investment in the grid.

[0076] Example 2

[0077] Referring to Table 1, which is the second embodiment of the present invention, this embodiment provides a grid distribution network management method based on a cloud-edge fusion architecture. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0078] Table 1 Test data table

[0079]

[0080] As can be seen from the above, the present invention can decentralize the pressure of cloud computing by setting up multi-level control, realize local processing, and improve the efficient coordination and control and overall computing capabilities between various levels. The grid status and planning situation can be analyzed, and suggestions for combined project establishment can be integrated to greatly improve the efficiency of grid planning and construction and reduce repeated investment in the grid.

[0081] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A grid distribution network management method based on cloud-edge fusion architecture, characterized by: include, Build a four-level node architecture including the central cloud platform, edge grid control platform, user-side resource aggregation control platform, and user control terminal to deploy the central cloud platform; Synchronize resource information uploaded by all platforms, use user control terminals to collect resource information in the corresponding area, generate and issue control instructions for user-side resource local control; Execute the issued control instructions and manage the grid distribution network based on the cloud-edge fusion architecture according to the control instructions.

2. The grid distribution network management method based on the cloud-edge fusion architecture according to claim 1, characterized in that: The control instructions include first-level control instructions, second-level control instructions, third-level control instructions and fourth-level control instructions; The user control terminal generates four-level control instructions based on resource information. The user-side resource aggregation control platform sends three-level control instructions to all user control terminals. The edge grid control platform sends two-level control instructions to all user-side resource aggregation control platforms. The central cloud platform sends one-level control instructions to all edge grid control platforms.

3. The grid distribution network management method based on the cloud-edge fusion architecture according to claim 2 is characterized in that: The first-level control instruction includes a grid area division control instruction, and obtaining the grid area division control instruction includes the following steps: dynamically generating grid units by comprehensively considering the structural and functional grid division indicator system; Calculate the modularity index and branch flexibility margin index based on electrical distance, calculate the connection strength between different network nodes, and define the grid branch flexibility margin index to reflect the average load rate of the network branch; The electrical distance and branch flexibility margin indicators are normalized, and the objective function is constructed for grid division; On the basis of grid division, each grid is assigned a grid number according to the geographic information data in the business data, the load monitoring data and the power supply points in the distribution network.

4. The grid distribution network management method based on the cloud-edge fusion architecture according to claim 3 is characterized in that: The secondary control instructions include a user-side resource aggregation control instruction within the grid, which is calculated using an optimization model that considers source-load uncertainty to construct an uncertainty set; If the adjustable uncertainty parameter of the unit is 0, it means that there is no uncertainty in the uncontrollable load, and the robust optimization model is transformed into a deterministic model; If the adjustable uncertainty parameter of the unit is at the upper limit, it means that there is uncertainty in the uncontrollable load throughout the entire scheduling cycle. The objective function of the optimization model considering source-load uncertainty is constructed, and the constraint conditions of the user-side resource aggregation optimization model within the grid are obtained. The secondary control instructions are solved to perform user-side resource aggregation control within the grid.

5. The grid distribution network management method based on the cloud-edge fusion architecture according to claim 4, characterized in that: The constraints of the user-side resource aggregation optimization model in the grid include distribution network flow constraints and safety constraints. The expression of the flow constraints is: Where P ij,t , Q ij,t are respectively the active power and reactive power of branch ij in period t; P j,t , Q j,t are the net injected active power and reactive power at node j in period t, respectively; u(j) and v(j) are the set of branch end nodes with j as the first node and the set of branch head nodes with j as the last node, respectively; B is the set of distribution network nodes; r ij 、x ij are the resistance and reactance of branch ij respectively; I ij,t , L ij,t are the current flowing through branch ij and its square in period t, l is the set of distribution network branches; U j,t 、V j,t are the voltage and its square at node j in period t respectively; They are the output power of photovoltaic and wind turbine respectively; are the active load and reactive load at node j in period t respectively; The expression of the safety constraint is: In the formula, They represent the upper and lower limits of the current flowing through branch ij respectively; Respectively represent the upper and lower limits of the voltage of node i; It represents the maximum active power that can flow through branch ij.

6. The grid distribution network management method based on cloud-edge fusion architecture according to claim 5, characterized in that: The deployment of the central cloud platform includes the following steps: Obtain information of at least one node to be deployed from the node storage pool through the cluster deployment service; Automatically generate network configuration information corresponding to the nodes to be deployed according to the information of the nodes to be deployed; Deploy the nodes to be deployed to the cloud platform according to the network configuration information corresponding to the nodes to be deployed; The third-level control instructions are executed by the user control terminal, sorted by the marginal cost of individual user adjustment as the control priority guidance indicator, decomposed and issued according to the total value of the second-level control instructions, monitoring the execution results of the control instructions, and selecting the user control terminal for adjustment; The four-level control instruction is a local response of the user equipment's local control instruction to the user's own equipment.

7. The grid distribution network management method based on cloud-edge fusion architecture according to claim 6, characterized in that: The execution of the issued control instructions includes the following steps: Generate an initial control instruction. If the user control terminal detects that a control is required, a fourth-level control instruction is generated. If the fourth-level control instruction can meet the control requirements, the user control terminal directly executes the fourth-level control instruction. Otherwise, request the third-level control instruction from the user-side resource aggregation control platform to evaluate and execute the multi-level control instruction; If the system receives the third-level control instruction and meets the control requirements, the user control terminal executes the third-level control instruction, otherwise it requests the second-level control instruction from the edge grid control platform; If the edge grid control platform receives the second-level control instruction and meets the control requirements, it will execute the second-level control instruction, otherwise it will request the first-level control instruction from the central cloud platform; If the central cloud platform receives a first-level control instruction, the user control terminal must execute the first-level control instruction, execute and feedback the control instruction, start the execution timer at the same time, adjust the generation strategy of control instructions at all levels, and evaluate the execution effect after the control instruction is executed, end the current control cycle and start the next level of control instruction.

8. A grid distribution network management system based on a cloud-edge fusion architecture, based on the grid distribution network management method based on a cloud-edge fusion architecture according to any one of claims 1 to 7, characterized in that: include, A construction module is used to build a four-level node architecture including a central cloud platform, an edge grid control platform, a user-side resource aggregation control platform, and a user control terminal to deploy the central cloud platform; The generation module is used to synchronize resource information uploaded by all platforms, collect resource information in the corresponding area using the user control terminal, generate local control of user-side resources, and issue control instructions; The execution management module is used to execute the issued control instructions and manage the grid distribution network based on the cloud-edge fusion architecture according to the control instructions.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the grid distribution network management method based on the cloud-edge fusion architecture as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the grid distribution network management method based on the cloud-edge fusion architecture described in any one of claims 1 to 7 are implemented.

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