Intelligent transformation method, system and equipment of traditional power distribution network, medium and product

Abstract

The invention belongs to the technical field of power distribution networks, and provides an intelligent transformation method, system and device for a traditional power distribution network, a medium and a product, and the method comprises the steps: constructing a ring main unit-branch incidence matrix based on nodes of the traditional power distribution network; obtaining a node adjacency matrix according to the ring main unit-branch incidence matrix; constructing a feeder incidence matrix based on a traditional power grid; identifying non-snowflake network nodes based on the node adjacency matrix and the feeder incidence matrix; a traditional power grid is transformed, so that non-snowflake network nodes meet the requirements of snowflake network nodes. According to the invention, node identification is carried out for an existing traditional power distribution network, a snowflake network is taken as an example, structural features of a future intelligent power distribution network are considered, and transformation of the existing traditional power distribution network is guided.

Description

Technical Field

[0001] This disclosure pertains to the field of power distribution network technology, and particularly relates to methods, systems, equipment, media, and products for the intelligent transformation of traditional power distribution networks. Background Technology

[0002] With the accelerating construction of my country's new power system, primarily based on new energy sources, the situation and tasks faced by the distribution network within this system have undergone significant changes. The distribution system will become more complex in terms of its components, topology, and operation. Therefore, it is necessary to transform the structure and operation of the distribution system, combining the characteristics and development needs of the new power system to realize a hierarchical and clustered intelligent distribution system. This will adapt to the new problems and challenges faced by the development of the new power system under the large-scale integration of new energy sources.

[0003] Existing research has explored new power grid structures to some extent, including attempts at hierarchical and clustered network structures in many advanced cities in China, honeycomb distribution network structures for future smart distribution networks, Singapore's petal-shaped power grid structure, and Paris's spindle-shaped power grid structure. However, related research has rarely focused on the transformation process from existing traditional power grids to new smart distribution networks, and no modeling research on the network structure of future smart distribution networks has yet been formed. Further summarization and generalization are needed for future smart distribution network models. Summary of the Invention

[0004] To address the aforementioned issues, this disclosure provides a method for transforming a distribution network into a snowflake network. It identifies nodes in the existing traditional distribution network and, taking a snowflake network (snowflake-shaped distribution network) as an example, considers meeting the structural characteristics of future smart distribution networks to guide the transformation of existing traditional power grids.

[0005] Firstly, this disclosure provides a method for the intelligent transformation of traditional power distribution networks, including: Based on the nodes of the traditional power grid, a ring network box-branch correlation matrix is ​​constructed; The node adjacency matrix is ​​obtained from the ring network box-branch correlation matrix; Construct a feeder correlation matrix based on the traditional power grid; Identify non-snowflake network nodes based on the node adjacency matrix and feeder correlation matrix; The traditional power grid is modified so that non-snowflake grid nodes meet the requirements of snowflake grid nodes.

[0006] Furthermore, Based on the nodes of a traditional power grid, a ring network box-branch correlation matrix is ​​constructed, including: Identify the nodes and their connections in the traditional power grid; Based on the connection relationships between nodes, a ring network box-branch association matrix is ​​established.

[0007] Furthermore, The node adjacency matrix is ​​obtained from the ring network box-branch correlation matrix, including: The node-branch correlation matrix is ​​obtained by expanding the ring network box-branch correlation matrix; Construct the node adjacency matrix based on the node-branch association matrix.

[0008] Furthermore, Based on the node adjacency matrix and feeder correlation matrix, non-snowflake network nodes are identified, including: Calculate the number of reachable paths for each node and define node redundancy; Identify traditional power grid nodes that are not part of the snowflake network based on the node threshold of the snowflake network.

[0009] Furthermore, Calculate the number of reachable paths for each node, including: Starting with the set of power nodes, perform a breadth-first search on the node adjacency matrix and feeder correlation matrix to count the number of available power sources for each node.

[0010] Furthermore, Upgrading traditional power grids includes: Based on the topological characteristics of the Snowflake network, the topological transformation from the traditional power grid to the Snowflake network is achieved by adding new intra-station or inter-station connection points, reconstructing some branches, and configuring flexible interconnection devices.

[0011] Secondly, based on the same inventive concept, this disclosure also provides a smart transformation system for traditional power distribution networks, including a ring network box-branch association matrix construction module, a node adjacency matrix acquisition module, a feeder association matrix construction module, a non-snowflake network node identification module, and a traditional power grid transformation module; The ring network box-branch correlation matrix construction module is used to construct the ring network box-branch correlation matrix based on the nodes of the traditional power grid; The node adjacency matrix acquisition module is used to obtain the node adjacency matrix based on the ring network box-branch association matrix; The feeder correlation matrix construction module is used to construct the feeder correlation matrix based on the traditional power grid. The non-snowflake network node identification module is used to identify non-snowflake network nodes based on the node adjacency matrix and feeder association matrix; Traditional power grid transformation modules are used to transform traditional power grids so that non-snowflake grid nodes meet the requirements of snowflake grid nodes.

[0012] Thirdly, based on the same inventive concept, this disclosure also provides an electronic device, including at least one processor and at least one memory electrically connected; The memory is electrically connected to the processor, wherein the memory stores instructions that can be executed by at least one of the processors, the instructions being executed by at least one of the processors to enable at least one of the processors to perform the intelligent transformation method for a conventional power distribution network as described above.

[0013] Fourthly, based on the same inventive concept, this disclosure also provides a computer storage medium storing a computer program. When the computer program is executed by the processor, it implements the intelligent transformation method of the traditional power distribution network as described above.

[0014] Fifthly, based on the same inventive concept, this disclosure also provides a computer program product, which is stored in at least one storage medium; The computer program product includes several instructions to cause at least one electronic device to perform the intelligent transformation method of the conventional power distribution network as described above.

[0015] Compared with the prior art, this disclosure provides a method for transforming a distribution network into a snowflake network, which has the following beneficial effects: Based on the existing traditional distribution network topology, node connection characteristics, and power supply path data, typical wiring patterns and key structural units are automatically identified, thereby revealing the structural characteristics and potential bottlenecks of the existing network structure. Simultaneously, by establishing a unified pattern recognition index system, the connectivity, redundancy, and flexible interconnection level of distribution networks at different voltage levels are quantitatively evaluated, providing a foundation for the abstract modeling of snowflake-shaped structures.

[0016] Other features and advantages of this disclosure will be set forth in the following description and will be apparent in part from the description or may be learned by practicing the disclosure. The objects and other advantages of this disclosure may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1a A schematic diagram of a single-side power supply radial wiring configuration in a high-voltage distribution network is shown. Figure 1b This diagram illustrates an abstracted schematic of a single-side power supply radial wiring configuration in a high-voltage distribution network. Figure 2a A schematic diagram of a single-ring network connection for a medium-voltage distribution network overhead line is shown. Figure 2b This diagram illustrates the simplified wiring diagram of a single-ring network for an overhead line in a medium-voltage distribution network. Figure 3a A schematic diagram of the wiring of a low-voltage AC / DC distribution network with power supply from both ends is shown. Figure 3b This diagram illustrates the wiring schematic of an abstract, two-terminal power supply type low-voltage AC / DC distribution network. Figure 4 A flowchart illustrating a method for intelligent transformation of a conventional power distribution network according to an embodiment of the present disclosure is shown. Figure 5 The diagram shows two sets of standard double-ring network connection structures for a traditional power grid; Figure 6 A schematic diagram of the ring network box circuit topology is shown; Figure 7 It shows Figure 5 The diagram shows the ring network box-branch correlation matrix of a traditional power grid. Figure 8 It shows Figure 5 The node-branch correlation matrix of the traditional power grid is shown below; Figure 9 It shows Figure 5 The node adjacency matrix of a traditional power grid is shown below. Figure 10 It shows Figure 5 The feeder correlation matrix of a traditional power grid is shown below; Figure 11 A schematic diagram of the structure of an electronic device according to an embodiment of the present disclosure is shown. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0020] Explanation of the basic concepts involved in the embodiments of this disclosure: 1. Radial wiring of single-side power supply in high-voltage distribution network.

[0021] Figure 1a Each load is powered by a single power source through a single path.

[0022] In this disclosure embodiment, Figure 1aThe wiring diagram shown is abstracted into a single radial power supply area containing only the power source, branches, and loads, such as... Figure 1b As shown.

[0023] 2. Single-ring network connection of overhead lines in medium-voltage distribution networks.

[0024] Figure 2a Each load is powered by two power sources through four paths. In this disclosure embodiment, Figure 2a The wiring diagram shown can be abstracted into a ring-shaped area with power supply at both ends, containing only the power source, branches, and load. Figure 2b As shown.

[0025] 3. Wiring of low-voltage AC / DC distribution networks with power supply at both ends.

[0026] Figure 3a Each load is powered by two power sources through two paths.

[0027] In this disclosure embodiment, Figure 3a The wiring diagram shown can be abstracted into a single area with power supply at both ends, containing only the power source, branch circuits, and load. Figure 3b As shown.

[0028] The "snowflake grid" structure is an evolution and upgrade of the existing traditional power grid. It only optimizes and adjusts the traditional grid structure without destroying or subverting the existing power grid. It is not a demolition and reconstruction of the existing power grid, and will not cause waste of power grid construction investment. Moreover, it is a new form of distribution network that is more adaptable to the new needs of the development of new power systems.

[0029] The embodiments disclosed herein use "Snowflake Network" as a preferred representative of smart distribution networks to illustrate the technical concept of "smart transformation of traditional distribution networks".

[0030] Figure 4 A flowchart illustrating a method for intelligent transformation of a conventional power distribution network according to an embodiment of the present disclosure is shown.

[0031] A method for intelligent transformation of a traditional power distribution network according to an embodiment of this disclosure includes the following steps: S1, based on the nodes of the traditional power grid, constructs a ring network box-branch correlation matrix.

[0032] S11, confirm the nodes of the traditional power grid and their connection relationships.

[0033] Based on traditional power grid GIS (Geographic Information System Data), SCADA (Supervisory Control and Data Acquisition) data and topology database, power grid nodes (substations / power sources, feeders, loads, tie switches) and their connection relationships are extracted.

[0034] Taking the existing two sets of standard double-ring networks as examples, as shown in the attached diagram. Figure 5 As shown, it includes 4 power sources (substation AD), 8 feeders (1-8), 8 loads (9-16), and 4 tie switches (17-20). Figure 5 The document also shows 16 branches B1-B16 and 8 fuse switches (F1-F8).

[0035] S12. Based on the connection relationship between nodes, establish a ring network box-branch association matrix to describe the association relationship between the ring network box and the branch.

[0036] Ring main units (RMUs) can be used for segmentation, interconnection, and load distribution of ring network nodes, and support the connection of distributed power sources and electric vehicle charging facilities. They typically use a single busbar connection. In terms of equipment selection, shared-enclosure RMUs are generally preferred. A "ring main unit" is a switchgear (outgoing switchgear) for each distribution branch, and the busbar of this switchgear is also part of the ring trunk line. In other words, the ring trunk line is formed by connecting the busbars of each outgoing switchgear.

[0037] Corresponding to Figure 5 The nodes and branches shown are shown; the ring network box nodes are the target of power supply (see attached diagram). Figure 5 (marked 9-20), while the branch is the carrier responsible for delivering electrical energy to the ring network box node, connecting different ring network box nodes.

[0038] Ring network box structure such as Figure 6 As shown, ring network box K i , K i+1 The branch numbering between them is defined as B. j Each ring main unit contains one busbar, and different types of loads can be connected to the busbar. (Ring main unit definition) K i The two switches contained therein are respectively S i,1 and S i,2 Ring mesh box K i+1 It contains two switches. S i+1,1 and Si+1,2 Ring network box K i The power supply depends on the switch S i,1 and S i,2 The open / closed state of the switch. S i,1 Close, switch S i,2 When opened, the ring network box K i The load is from the branch circuit B j-1 Power supply; switch S i,1 Turn on, switch S i,2 When closed, the ring network box K i The load is from the branch circuit B j powered by.

[0039] switch S i,2 and S i+1,1 The opening and closing state determines branch B j The on / off status of the switch. S i,2 and S i+1,1 When all are closed, branch B j Connected; when any switch in branch B is turned on, branch B is connected. j Disconnect. Define 0-1 variables. aB j Characterizing branch B j On / off status, 0-1 variables aS i,2 and aS i+1,1 Characterization switch S i,2 and S i+1,1 The open and closed states of the three elements are related by an AND logic: .

[0040] Each node is marked and numbered, and this information is reflected in the ring network box-branch association matrix. E In the matrix, the row numbers correspond one-to-one with the ring network box numbers, and the column numbers correspond one-to-one with the branch numbers. See Appendix. Figure 7 .

[0041] matrix E The ring network box contains only three elements: -1, 0, and 1, and does not consider the main transformer node. K iWith branch road B j When not connected, E ij =0; when the ring network box K i It is branch road B j At the starting point, E ij =1; when the ring network box K i It is branch road B j At the finish line, E ij =-1. Furthermore, the ring network box nodes at both ends of the tie line can be considered as the starting point of the tie line.

[0042] S2, the node adjacency matrix is ​​obtained from the ring network box-branch correlation matrix.

[0043] S21, the node-branch correlation matrix is ​​obtained by expanding the ring network box-branch correlation matrix.

[0044] Based on the ring network box-branch correlation matrix, and referring to the appendix Figure 5 , expanded Figure 8 The node-branch correlation matrix N is shown.

[0045] S22, construct based on the node-branch association matrix. Figure 9 The node adjacency matrix shown A : .

[0046] S3, based on the traditional power grid, constructs a feeder correlation matrix.

[0047] In traditional power grids, ring main units and branches together form each feeder. A feeder often contains multiple ring main units and multiple branches. A single feeder often operates in a radial pattern, and the feeders are connected to each other through intra-station and inter-station communication.

[0048] Appendix Figure 5 Feeder correlation matrix of two sets of standard double-ring networks F ,like Figure 10 As shown.

[0049] Feeder correlation matrix F It is a symmetric matrix, and its dimensions and the number of feed lines are the same. The matrix... F It contains two elements: 0 and 1. 1 indicates that the two feeders are related and there is a connecting line between them; 0 indicates that the two feeders are not related and there is no connecting line between them.

[0050] S4 identifies non-snowflake network nodes based on the node adjacency matrix and feeder correlation matrix.

[0051] S41, calculate the number of reachable paths for each node and define node redundancy.

[0052] Starting with the set of power supply nodes, perform a breadth-first search (BFS) on the node adjacency matrix and feeder association matrix to count the number of reachable power supplies s for each node.

[0053] Define node redundancy R = s - 1.

[0054] S42, based on the node threshold of the snowflake network, identify traditional power grid nodes that are not part of the snowflake network.

[0055] The criteria for determining "non-snowflake network node" are s<2 or R=0.

[0056] by Figure 5 Taking the network structure shown as an example, performing a breadth-first search (BFS) on N and F yields a redundancy of 0 for each load node, indicating that the original network structure is a non-snowflake network architecture.

[0057] S5 involves modifying traditional power grids to make non-snowflake grid nodes conform to the requirements of snowflake grid nodes.

[0058] Based on the topological characteristics of the Snowflake network (multi-source and multi-branch, ring network interconnection, and three-dimensional mutual backup), the topological conversion from traditional power grid to Snowflake network is achieved by adding intra-station or inter-station connection points, reconstructing some branches, and configuring flexible interconnection devices (such as circuit breakers or switches).

[0059] Snowflake Network follows the "closed-loop design, open-loop operation" model. The closed-loop design mainly refers to connecting the distribution network into a closed-loop network through the intra-station and inter-station tie lines. The tie switch is a normally open switch, which is generally in the open state. When a feeder fails or the load rate is heavy, part of the load of the ring network box can be transferred to other feeders by closing the tie switch.

[0060] In addition to the branches that are directly connected to the main transformer in the substation, each branch in the snowflake network is connected to a ring network box at both ends, and there must also be a branch between two adjacent ring network boxes.

[0061] Based on the same inventive concept as the method disclosed above, this disclosure also provides a smart transformation system for traditional power distribution networks, including a ring network box-branch association matrix construction module, a node adjacency matrix acquisition module, a feeder association matrix construction module, a non-snowflake network node identification module, and a traditional power grid transformation module; The ring network box-branch correlation matrix construction module is used to construct the ring network box-branch correlation matrix based on the nodes of the traditional power grid; The node adjacency matrix acquisition module is used to obtain the node adjacency matrix based on the ring network box-branch association matrix; The feeder correlation matrix construction module is used to construct the feeder correlation matrix based on the traditional power grid. The non-snowflake network node identification module is used to identify non-snowflake network nodes based on the node adjacency matrix and feeder association matrix; Traditional power grid transformation modules are used to transform traditional power grids so that non-snowflake grid nodes meet the requirements of snowflake grid nodes.

[0062] Based on the same inventive concept as the above-disclosed content, this disclosure also provides an electronic device. For example... Figure 11 As shown, the electronic device of this disclosure embodiment includes at least one processor and at least one memory electrically connected to the processor, wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the intelligent transformation method of the conventional power distribution network as described above.

[0063] It should be noted that the electrical connection between the above-mentioned units does not necessarily mean the connection between lines. The indirect connection method can be applied to the embodiments of this disclosure as long as it achieves the purpose of this disclosure.

[0064] Based on the same inventive concept, this disclosure also provides a computer storage medium storing a computer program, which, when executed by a processor, implements the intelligent transformation method for the traditional power distribution network as described above.

[0065] Based on the same inventive concept, this disclosure also provides a computer program product stored in at least one storage medium; the computer program product includes several instructions to cause at least one computer device to execute the intelligent transformation method of the conventional power distribution network as described above.

[0066] Although the present disclosure has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure.

Claims

1. A method for intelligent transformation of a traditional power distribution network, characterized in that, The method includes: Based on the nodes of the traditional power grid, a ring network box-branch correlation matrix is ​​constructed; The node adjacency matrix is ​​obtained from the ring network box-branch correlation matrix; Construct a feeder correlation matrix based on the traditional power grid; Identify non-snowflake network nodes based on the node adjacency matrix and feeder correlation matrix; The traditional power grid is modified so that non-snowflake grid nodes meet the requirements of snowflake grid nodes.

2. The method according to claim 1, characterized in that, Based on the nodes of a traditional power grid, a ring network box-branch correlation matrix is ​​constructed, including: Identify the nodes and their connections in the traditional power grid; Based on the connection relationships between nodes, a ring network box-branch association matrix is ​​established.

3. The method according to claim 2, characterized in that, The node adjacency matrix is ​​obtained from the ring network box-branch correlation matrix, including: The node-branch correlation matrix is ​​obtained by expanding the ring network box-branch correlation matrix; Construct the node adjacency matrix based on the node-branch association matrix.

4. The method according to any one of claims 1-3, characterized in that, Based on the node adjacency matrix and feeder correlation matrix, non-snowflake network nodes are identified, including: Calculate the number of reachable paths for each node and define node redundancy; Identify traditional power grid nodes that are not part of the snowflake network based on the node threshold of the snowflake network.

5. The method according to claim 4, characterized in that, Calculate the number of reachable paths for each node, including: Starting with the set of power nodes, perform a breadth-first search on the node adjacency matrix and feeder correlation matrix to count the number of available power sources for each node.

6. The method according to any one of claims 1-3 and 5, characterized in that, Upgrading traditional power grids includes: Based on the topological characteristics of the Snowflake network, the topological transformation from the traditional power grid to the Snowflake network is achieved by adding new intra-station or inter-station connection points, reconstructing some branches, and configuring flexible interconnection devices.

7. A smart transformation system for a traditional power distribution network, characterized in that, The system includes a ring network box-branch association matrix construction module, a node adjacency matrix acquisition module, a feeder association matrix construction module, a non-snowflake network node identification module, and a traditional power grid transformation module; The ring network box-branch correlation matrix construction module is used to construct the ring network box-branch correlation matrix based on the nodes of the traditional power grid; The node adjacency matrix acquisition module is used to obtain the node adjacency matrix based on the ring network box-branch association matrix; The feeder correlation matrix construction module is used to construct the feeder correlation matrix based on the traditional power grid. The non-snowflake network node identification module is used to identify non-snowflake network nodes based on the node adjacency matrix and feeder association matrix; Traditional power grid transformation modules are used to transform traditional power grids so that non-snowflake grid nodes meet the requirements of snowflake grid nodes.

8. An electronic device, characterized in that, Includes at least one processor and at least one memory electrically connected; The memory is electrically connected to the processor, wherein the memory stores instructions that can be executed by at least one of the processors, the instructions being executed by at least one of the processors to enable at least one of the processors to perform the intelligent transformation method for a conventional power distribution network as described in any one of claims 1-6.

9. A computer storage medium, characterized in that, The computer storage medium stores a computer program. When the computer program is executed by the processor, it implements the intelligent transformation method for the traditional power distribution network as described in any one of claims 1-6.

10. A computer program product, characterized in that, The computer program product is stored in at least one storage medium; The computer program product includes several instructions to cause at least one electronic device to execute the intelligent transformation method for a conventional power distribution network as described in any one of claims 1-6.

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