A method, device and equipment for modeling topology of AC / DC microgrid

Abstract

The application provides a topology modeling method of an AC / DC micro-grid, which comprises the following steps: after obtaining equipment data of a target grid, defining the equipment data based on graph database technology, generating a physical topology attribute graph and an electrical structure attribute graph corresponding to the target grid based on the definition result, and selecting an adaptive control unit group based on the control type of the target grid to control the electrical structure attribute graph of the target grid. Since the graph database is introduced in the process, the information can be efficiently stored, queried and analyzed based on the graph database, and the method has good scalability and interoperability, and meets the topology analysis requirements of the micro-grid.

Description

Technical Field

[0001] This invention relates to the field of smart grid technology, and specifically to a method, apparatus, and equipment for AC / DC microgrid topology modeling. Background Technology

[0002] AC / DC microgrids, as an important component of smart grid development, are complex dynamic networks with varying topologies. Traditional power grid topology data organization and analysis are based on traditional relational databases, which are insufficient in terms of storage capacity, query efficiency, and scalability to meet the topology analysis needs of microgrids. Summary of the Invention

[0003] In view of this, embodiments of the present invention provide an AC / DC microgrid topology modeling method, apparatus, and device to realize topology analysis of microgrids.

[0004] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:

[0005] A method for topology modeling of AC / DC microgrids includes:

[0006] Acquire device data of the target power grid, the device data including device identification data, physical connection data and network topology relationship data corresponding to the device identification data;

[0007] The device data is defined using a pre-defined image database;

[0008] Based on the definition results of the device data, a physical topology attribute map of the physical device is constructed. The physical topology attribute map includes at least: device ID, device type, geographical location, and port information.

[0009] Based on the definition results of the device data, an electrical structure attribute diagram of the target power grid is constructed;

[0010] Obtain the control type corresponding to the target power grid, wherein the control type is a system operation type or a service type;

[0011] Obtain a control unit group that matches the control type;

[0012] The electrical structure attribute diagram of the target power grid is controlled based on the control unit group.

[0013] Optionally, in the above AC / DC microgrid topology modeling method, the system operation type includes:

[0014] Joint grid connection, joint islanding, separate islanding, AC microgrid independent grid connection, DC microgrid independent grid connection;

[0015] The business type is established based on different operating conditions, load types, and renewable energy consumption among target power grid clusters.

[0016] Optionally, in the above AC / DC microgrid topology modeling method, the preset graph database is the Neo4j graph database.

[0017] Optionally, in the above AC / DC microgrid topology modeling method, the device data is defined using a preset graph database, including:

[0018] The device data is defined using a preset graph database, and physical node attributes are assigned to it. The defined content includes: vertices, edges, and attributes.

[0019] An AC / DC microgrid topology modeling device, comprising:

[0020] The data acquisition unit is used to acquire equipment data of the target power grid. The equipment data includes equipment identification data, as well as physical connection data and network topology relationship data corresponding to the equipment identification data.

[0021] A definition unit is used to define the device data using a preset graph database;

[0022] The topology graph construction unit is used to construct a physical topology attribute graph of the physical device based on the definition results of the device data. The physical topology attribute graph includes at least: device ID, device type, geographical location, and port information; and to construct an electrical structure attribute graph of the target power grid based on the definition results of the device data.

[0023] A control type acquisition unit is used to acquire the control type corresponding to the target power grid, wherein the control type is a system operation type or a service type; and to acquire a control unit group that matches the control type.

[0024] A control unit is used to control the electrical structure property diagram of the target power grid based on the control unit group.

[0025] Optionally, in the above-mentioned AC / DC microgrid topology modeling device, the system operation type includes:

[0026] Joint grid connection, joint islanding, separate islanding, AC microgrid independent grid connection, DC microgrid independent grid connection;

[0027] The business type is established based on different operating conditions, load types, and renewable energy consumption among target power grid clusters.

[0028] Optionally, in the above AC / DC microgrid topology modeling device, the preset graph database is the Neo4j graph database.

[0029] Optionally, in the above-mentioned AC / DC microgrid topology modeling device, when the definition unit defines the device data using a preset graph database, it is specifically used for:

[0030] The device data is defined using a preset graph database, and physical node attributes are assigned to it. The defined content includes: vertices, edges, and attributes.

[0031] An AC / DC microgrid topology modeling device, comprising:

[0032] A memory and a processor; the memory stores a program suitable for execution by the processor, the program being used for:

[0033] Acquire device data of the target power grid, the device data including device identification data, physical connection data and network topology relationship data corresponding to the device identification data;

[0034] The device data is defined using a pre-defined image database;

[0035] Based on the definition results of the device data, a physical topology attribute map of the physical device is constructed. The physical topology attribute map includes at least: device ID, device type, geographical location, and port information.

[0036] Based on the definition results of the device data, an electrical structure attribute diagram of the target power grid is constructed;

[0037] Obtain the control type corresponding to the target power grid, wherein the control type is a system operation type or a service type;

[0038] Obtain a control unit group that matches the control type;

[0039] The electrical structure property diagram of the target power grid is controlled based on the control unit group.

[0040] Based on the above technical solutions, the solutions provided in this embodiment of the invention, after obtaining the equipment data of the target power grid, define the equipment data based on graph database technology, generate the physical topology attribute map and electrical structure attribute map corresponding to the target power grid based on the definition results, and then select an appropriate control unit group to control the electrical structure attribute map of the target power grid based on the control type corresponding to the target power grid. Since a graph database is introduced in this process, information can be efficiently stored, queried and analyzed based on the graph database, which has good scalability and interoperability, and meets the topology analysis requirements of microgrids. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0042] Figure 1 This is a flowchart illustrating the AC / DC microgrid topology modeling method disclosed in the embodiments of this application;

[0043] Figure 2 This is a schematic diagram of the AC / DC microgrid topology modeling device disclosed in the embodiments of this application;

[0044] Figure 3 This is a schematic diagram of the AC / DC microgrid topology modeling device disclosed in an embodiment of this application. Detailed Implementation

[0045] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0046] The applicant's research revealed the following main problems with traditional power grid topology data organization and analysis schemes:

[0047] New energy sources, distributed power sources, electric vehicles, and energy storage devices are emerging in large numbers; the structure and operation mode of multi-station integrated AC / DC microgrids are becoming increasingly complex, and grid topology data is growing exponentially. Traditional grid topology data organization and analysis are based on traditional relational databases, which are difficult to meet the business needs of AC / DC microgrid topology analysis and operation control in new smart grids in terms of storage scale, query efficiency, and scalability.

[0048] As a crucial component of smart grid development, AC / DC microgrids are complex, dynamic networks with varying topologies. They can operate either grid-connected to a higher-level power grid or as isolated systems. During grid-connected operation, they can switch between power supply and consumption. Topology design must consider principles such as zoning and layering, maximizing resource utilization, ensuring power supply reliability, and AC / DC interconnection. Therefore, it is necessary to conduct targeted research on microgrid components and topologies based on traditional power grid topology modeling techniques and the structural characteristics of AC / DC microgrids.

[0049] As a typical representative of non-relational databases, graph databases offer several advantages over traditional relational databases' two-dimensional table storage method. These advantages include: the ability to store entities and their connections in graph form, making queries between nodes and relationships simpler and faster; the capacity to handle large, heterogeneous data, combining richer data with more efficient queries; minimizing coding decisions and repeatedly extracting complex structural information; and excellent scalability and interoperability, enabling efficient graph data utilization and analysis. Currently, there is extensive research on traditional power grid topology attribute graph modeling. However, research on topology modeling and analysis based on graph database technology is lacking in the field of AC / DC microgrid topology analysis.

[0050] This invention proposes a data modeling method for microgrid topology management based on graph database technology. Its advantage lies in introducing graph database technology, selecting basic primitives of the designed microgrid (the microgrid being the target grid in the following text), extracting the microgrid DG units and corresponding load information as nodes in the topology graph, and extracting the actual physical connections between nodes as edges in the topology graph, thereby completing microgrid data modeling based on graph database technology. This achievement can conveniently obtain the correct microgrid topology structure, intuitively display node connection relationships, and further support controller adjustment based on real-time topology identification, ensuring the safe and stable operation of the microgrid, and optimizing the consumption of distributed energy resources, among other business requirements.

[0051] For details, see Figure 1 The AC / DC microgrid topology modeling method disclosed in this application may include:

[0052] Step S101: Obtain device data of the target power grid, the device data including device identification data, physical connection data and network topology relationship data corresponding to the device identification data.

[0053] The target power grid can be an AC / DC microgrid: an AC / DC microgrid is a small-scale power generation and distribution system composed of distributed power sources, energy storage devices, energy conversion devices, related loads, and monitoring and protection devices. It is an autonomous system capable of self-control, protection, and management. With the continuous expansion of new energy power generation, the utilization and development of distributed generators (DG) are receiving increasing attention. Microgrids play a role in improving the utilization rate of new energy sources, fully leveraging the potential of DG, and reducing the negative impact of the intermittency and volatility of photovoltaic and wind power generation on the power grid. They are an important component of the future smart grid. Based on different bus voltages, AC / DC microgrids can be further divided into AC microgrids, DC microgrids, and hybrid AC / DC microgrids (HMG). Among them, hybrid AC / DC microgrids are convenient for simultaneously accepting AC and DC power sources and loads, and can potentially improve power supply reliability and continuity through mutual support between AC and DC buses. However, the operation and control of HMGs are relatively complex, bringing new challenges to control technology.

[0054] This solution first requires acquiring the equipment data corresponding to each power device included in the target power grid to be modeled. This power device includes not only power control equipment (such as transformers, charging piles, energy storage devices, and circuit breakers) but also power transmission equipment, such as busbars. The equipment data can include the equipment's own data, its physical connections and network topology, and even related power grid business data. The equipment's own data can include equipment identifiers, equipment types, equipment operating parameters, etc.

[0055] Step S102: Define the device data using a preset graph database.

[0056] Graph database technology: As a typical representative of non-relational databases, graph databases can store network data composed of concepts, entities, relations, and attributes in knowledge graphs. They also enable graph-based data storage, querying, and mining based on node, relation, and attribute data structures, and have given rise to a new graph-centric big data technology stack. As one of the mainstream tools for storing network data, it has shown broad application potential in highly interconnected fields with diverse node types, such as social networks and biomedical networks. It plays an increasingly important role in complex network analysis.

[0057] In this solution, the preset graph database can refer to the Neo4j graph database, or other graph databases can be selected. Neo4j was chosen because its main elements include nodes, relationships, attributes, and entity labels. These different elements are stored in different files with clearly defined storage responsibilities and are linked in the form of a graph. Edge information is stored as attributes. Neo4j primarily uses the Cypher query language. This language is a declarative graph database query language with rich expressiveness, enabling efficient querying and updating of graph data.

[0058] After obtaining the device data of the target power grid, the preset graph database is used to define all physical devices in the microgrid based on the device data, and assign them physical node attributes. The topology network is defined as an undirected graph, that is, a set of nodes and edges. Each node and edge has its own attributes, and the specific definition rules are as follows:

[0059] Vertex: Map the electrical equipment corresponding to the single-terminal electrical element to a vertex, number each vertex, and the vertex type constitutes a set Tv, which contains DG unit and corresponding load information;

[0060] Edge: Map electrical equipment with two electrical endpoints or multiple physical nodes to an edge, number each edge, and the types of two or more endpoints form a set Te, including switches, circuit breakers, etc.

[0061] Attributes: An attribute is a tuple (attribute name, value range), where the value range is the set of allowed values ​​for the attribute. In graph data, the set of all attributes is denoted as A. The set of all attributes for each vertex (or edge) is a subset of A. Each vertex (or edge) must have at least one primary attribute, serving as a unique identifier. Examples include the unique name of electrical equipment (primary attribute), voltage level, equipment object code, switch status, geographical location, and the name of the associated power plant. The attribute information on vertices and edges allows the graph data model to fully express the complex structure and semantics of the power grid topology, supporting the querying and analysis of power grid topology data based on graph database technology.

[0062] Step S103: Construct a physical topology attribute map of the physical device based on the definition results of the device data. The physical topology attribute map includes at least: device ID, device type, geographical location, and port information.

[0063] This step involves extracting and modeling the physical structure topology attributes of the target power grid based on the definition results of the preset graph database. Specifically, according to the attribute set corresponding to each power device defined in the preset graph database, the device attributes and physical connections of the power devices are extracted. A physical topology attribute graph is formed based on the attributes of the power devices. The physical topology attribute graph contains attributes such as device ID, model, geographical location, and port information corresponding to each power device.

[0064] Step S104: Construct the electrical structure attribute diagram of the target power grid based on the definition results of the device data.

[0065] This step involves performing a power grid topology analysis on the definition results of the preset graph database to extract and model the electrical structure topology attributes of the target power grid. Each DG unit in the target power grid is connected via lines and circuit breakers. When a fault occurs in the target power grid, causing a circuit breaker to open, the network topology of the target power grid will change. Therefore, it is necessary to acquire the target power grid topology information in real time. After distinguishing between the physical and electrical connections of the target power grid, terminals are set to store the electrical relationship attributes between each power device. By analyzing the electrical relationship attributes of each power device, an electrical structure attribute graph of the target power grid can be constructed. This attribute graph will subsequently be used to identify the circuit breaker switching status and determine the voltage, current, frequency, and power output of the DG units in the target power grid, thereby achieving real-time acquisition of the dynamic state of the target power grid topology.

[0066] Power grid topology analysis: The essence of power network topology analysis is to transform the physical model of the power grid into a computer-recognizable mathematical model based on the connection relationships of electrical components in the power grid. This model reflects the electrical wiring diagram and provides real-time information and data on switching states to the corresponding programs. The topology of an AC / DC microgrid specifically includes the internal electrical wiring network structure, power supply system (DC / AC power supply and three-phase / single-phase power supply), and the node locations of corresponding loads and distributed generation sources within the microgrid.

[0067] Step S105: Obtain the control type corresponding to the target power grid, wherein the control type is a system operation type or a service type.

[0068] In this scheme, there can be multiple control types for the target power grid. Different control types can be selected to control the target power grid according to different needs. Different control types correspond to different control unit groups, which are used to control the operating status of the power equipment in the target power grid under the corresponding control type.

[0069] Step S106: Obtain a control unit group that matches the control type.

[0070] For example, according to the system operating status, the target power grid can be divided into joint grid connection (active distribution network control, passive distribution network control), joint islanding, separate islanding, AC microgrid independent grid connection, DC microgrid independent grid connection and other system operating control unit groups. Each operating control unit group controls the target power grid to operate under the corresponding operating status. Business control unit groups are divided according to the different operating conditions, load types and renewable energy consumption principles within the target power grid and between target power grid clusters.

[0071] Step S107: Control the electrical structure attribute diagram of the target power grid based on the control unit group.

[0072] The relevant operation control unit group and business control unit group of the target power grid, combined with the electrical structure attribute diagram of the target power grid, can control the topology of the electrical structure attribute diagram of the target power grid. This allows control of the operation mode of the target power grid through the electrical structure attribute diagram. Furthermore, the control unit groups support flexible configuration and can be mutually inclusive and nested. This advantage enables subsequent support for data querying, data analysis, and decision optimization under the goal of flexible interconnection and unified control of different microgrids.

[0073] The technical solution disclosed in the above embodiments of this application defines the equipment data of the target power grid based on graph database technology after obtaining the equipment data of the target power grid. Based on the definition results, a physical topology attribute map and an electrical structure attribute map corresponding to the target power grid are generated. Then, an appropriate control unit group is selected based on the control type corresponding to the target power grid to control the electrical structure attribute map of the target power grid. Since a graph database is introduced in this process, information can be efficiently stored, queried and analyzed based on the graph database, which has good scalability and interoperability.

[0074] This embodiment discloses an AC / DC microgrid topology modeling device. For the specific working content of each unit in the device, please refer to the above method embodiment.

[0075] The AC / DC microgrid topology modeling device provided in the embodiments of the present invention is described below. The AC / DC microgrid topology modeling device described below and the AC / DC microgrid topology modeling method described above can be referred to each other.

[0076] See Figure 2 The aforementioned AC / DC microgrid topology modeling device may include:

[0077] Data acquisition unit A is used to acquire equipment data of the target power grid. The equipment data includes equipment identification data, as well as physical connection data and network topology relationship data corresponding to the equipment identification data.

[0078] Definition unit B is used to define the device data using a preset graph database;

[0079] The topology graph construction unit C is used to construct a physical topology attribute graph of the physical device based on the definition results of the device data. The physical topology attribute graph includes at least: device ID, device type, geographical location, and port information; and to construct an electrical structure attribute graph of the target power grid based on the definition results of the device data.

[0080] Control type acquisition unit D is used to acquire the control type corresponding to the target power grid, wherein the control type is a system operation type or a service type; and acquire the control unit group that matches the control type.

[0081] Control unit E is used to control the electrical structure property diagram of the target power grid based on the control unit group.

[0082] Figure 3 For a hardware structure diagram of the server provided in an embodiment of the present invention, see [link to diagram]. Figure 3 As shown, it may include: at least one processor 100, at least one communication interface 200, at least one memory 300 and at least one communication bus 400;

[0083] In this embodiment of the invention, the number of processor 100, communication interface 200, memory 300, and communication bus 400 is at least one, and the processor 100, communication interface 200, and memory 300 communicate with each other through the communication bus 400; obviously, Figure 3 The communication connections shown for the processor 100, communication interface 200, memory 300, and communication bus 400 are optional.

[0084] Optionally, the communication interface 200 can be an interface of a communication module, such as the interface of a GSM module;

[0085] Processor 100 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention.

[0086] The memory 300 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0087] Specifically, processor 100 is used for:

[0088] Acquire device data of the target power grid, the device data including device identification data, physical connection data and network topology relationship data corresponding to the device identification data;

[0089] The device data is defined using a pre-defined image database;

[0090] Based on the definition results of the device data, a physical topology attribute map of the physical device is constructed. The physical topology attribute map includes at least: device ID, device type, geographical location, and port information.

[0091] Based on the definition results of the device data, an electrical structure attribute diagram of the target power grid is constructed;

[0092] Obtain the control type corresponding to the target power grid, wherein the control type is a system operation type or a service type;

[0093] Obtain a control unit group that matches the control type;

[0094] The electrical structure property diagram of the target power grid is controlled based on the control unit group.

[0095] For ease of description, the above system is described by dividing it into various modules based on their functions. Of course, in implementing this application, the functions of each module can be implemented in one or more software and / or hardware.

[0096] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for system or system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and relevant parts can be referred to the descriptions in the method embodiments. The systems and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0097] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0098] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0099] It should also be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0100] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for topology modeling of AC / DC microgrids, characterized in that, include: Acquire device data of the target power grid, the device data including device identification data, physical connection data and network topology relationship data corresponding to the device identification data; The device data is defined using a pre-defined image database; Based on the definition results of the device data, a physical topology attribute map of the physical device is constructed. The physical topology attribute map is constructed by extracting the device attributes and physical connections of each power device according to the attribute set defined by the preset map database. The physical topology attribute map includes at least: device ID, device type, geographical location and port information. Based on the definition results of the device data, an electrical structure attribute diagram of the target power grid is constructed. This involves distinguishing between the physical and electrical connections of the target power grid, storing the electrical relationship attributes between various power devices using terminals, and analyzing these attributes to construct the electrical structure attribute diagram. This diagram can identify the voltage, current, frequency, and power output of the DG units in the target power grid by recognizing the circuit breaker switching status, thereby enabling real-time acquisition of the dynamic state of the target power grid topology. Obtain the control type corresponding to the target power grid, wherein the control type is a system operation type or a service type; the system operation type includes: joint grid connection, joint islanding, separate islanding, AC microgrid independent grid connection, and DC microgrid independent grid connection; the service type is a service type established based on different operating conditions, load types, and renewable energy consumption among the target power grid clusters. Obtain a control unit group that matches the control type; The electrical structure attribute diagram of the target power grid is controlled based on the control unit group. The relevant operation control unit group and business control unit group of the target power grid are combined with the electrical structure attribute diagram of the target power grid to control the topology of the electrical structure attribute diagram of the target power grid.

2. The AC / DC microgrid topology modeling method according to claim 1, characterized in that, The preset graph database is the Neo4j graph database.

3. The AC / DC microgrid topology modeling method according to claim 1, characterized in that, The device data is defined using a preset graph database, including: The device data is defined using a preset graph database, and physical node attributes are assigned to it. The defined content includes: vertices, edges, and attributes.

4. A device for modeling AC / DC microgrid topology, characterized in that, include: The data acquisition unit is used to acquire equipment data of the target power grid. The equipment data includes equipment identification data, as well as physical connection data and network topology relationship data corresponding to the equipment identification data. A definition unit is used to define the device data using a preset graph database; The topology graph construction unit is used to construct a physical topology attribute graph of physical devices based on the definition results of the device data. This involves extracting the device attributes and physical connections of each power device according to the attribute set defined in the preset graph database, and constructing the physical topology attribute graph, which includes at least: device ID, device type, geographical location, and port information. The unit also constructs an electrical structure attribute graph of the target power grid based on the definition results of the device data. This is achieved by distinguishing between the physical and electrical connections of the target power grid, storing the electrical relationship attributes between each power device using terminals, and analyzing these attributes to construct the electrical structure attribute graph of the target power grid. The electrical structure attribute graph can identify the voltage, current, frequency, and power output of the DG unit in the target power grid by recognizing the circuit breaker switching status, thereby enabling real-time acquisition of the dynamic state of the target power grid topology. The control type acquisition unit is used to acquire the control type corresponding to the target power grid, wherein the control type is a system operation type or a service type; and to acquire a control unit group that matches the control type; the system operation type includes: joint grid connection, joint islanding, separate islanding, AC microgrid standalone grid connection, and DC microgrid standalone grid connection; the service type is a service type established based on different operating conditions, load types, and renewable energy consumption among the target power grid clusters; A control unit is used to control the electrical structure attribute diagram of the target power grid based on the control unit group, wherein the relevant operation control unit group and business control unit group of the target power grid are combined with the electrical structure attribute diagram of the target power grid to control the topology of the electrical structure attribute diagram of the target power grid.

5. The AC / DC microgrid topology modeling device according to claim 4, characterized in that, The preset graph database is the Neo4j graph database.

6. The AC / DC microgrid topology modeling device according to claim 4, characterized in that, When the definition unit defines the device data using a preset graph database, it is specifically used for: The device data is defined using a preset graph database, and physical node attributes are assigned to it. The defined content includes: vertices, edges, and attributes.

7. An AC / DC microgrid topology modeling device, characterized in that, include: A memory and a processor; the memory stores a program suitable for execution by the processor, the program being used for: Acquire device data of the target power grid, the device data including device identification data, physical connection data and network topology relationship data corresponding to the device identification data; The device data is defined using a pre-defined image database; Based on the definition results of the device data, a physical topology attribute map of the physical device is constructed. The physical topology attribute map is constructed by extracting the device attributes and physical connections of each power device according to the attribute set defined by the preset map database. The physical topology attribute map includes at least: device ID, device type, geographical location and port information. Based on the definition results of the device data, an electrical structure attribute diagram of the target power grid is constructed. This involves distinguishing between the physical and electrical connections of the target power grid, storing the electrical relationship attributes between various power devices using terminals, and analyzing these attributes to construct the electrical structure attribute diagram. This diagram can identify the voltage, current, frequency, and power output of the DG units in the target power grid by recognizing the circuit breaker switching status, thereby enabling real-time acquisition of the dynamic state of the target power grid topology. Obtain the control type corresponding to the target power grid, wherein the control type is a system operation type or a service type; the system operation type includes: joint grid connection, joint islanding, separate islanding, AC microgrid independent grid connection, and DC microgrid independent grid connection; the service type is a service type established based on different operating conditions, load types, and renewable energy consumption among the target power grid clusters. Obtain a control unit group that matches the control type; The electrical structure attribute diagram of the target power grid is controlled based on the control unit group. The relevant operation control unit group and business control unit group of the target power grid are combined with the electrical structure attribute diagram of the target power grid to control the topology of the electrical structure attribute diagram of the target power grid.

Images