A method and system for constructing a graph database based on power data

Abstract

The application provides a kind of based on power data's graph database construction method and system, this method includes: with power dispatch center, power generation equipment, power equipment and power user as graph node;Establish the node edge between power dispatch center and its corresponding power generation equipment, establish the first node edge according to the coordination between power generation equipment under power dispatch center, obtain first subgraph;Establish the node edge between target power generation equipment and its corresponding power equipment, establish the second node edge according to the correlation between power equipment under target power generation equipment, construct second subgraph;Establish the node edge between target power equipment and its corresponding power user, and establish the third node edge according to the similarity between power user under target power equipment, construct third subgraph;According to the first subgraph, second subgraph and third subgraph of power dispatch center, construct the graph database of power dispatch center.The application improves the stability and reliability of the entire power system data processing.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method and system for constructing a graph database based on power data. Background Art

[0002] In the operation and management of power systems, the effective organization and utilization of power data is crucial. With the acceleration of power informatization, a large amount of power data is collected and stored.

[0003] Existing methods for constructing power databases are primarily based on traditional relational database models. Relational databases have relatively fixed schemas and are poorly adaptable to the ever-changing business needs and data structures within power systems. For example, when power networks undergo upgrades, new types of power equipment are added, or the connections between devices change, complex modifications to the database table structure are required, which can easily introduce data inconsistencies. Furthermore, power data is extensively interconnected, such as the electrical connections between devices and the power supply relationships between devices and users. Querying this related data in a relational database often requires multi-table joins. As data volume increases, the performance of these multi-table joins plummets, resulting in lengthy query response times. Furthermore, relational databases lack scalability for the storage and management of large-scale power data. As power data grows exponentially, relational databases face challenges in hardware resource expansion and data distribution, making system bottlenecks more likely.

[0004] Therefore, the existing power database construction methods are difficult to efficiently handle the complexity, dynamics and large scale of power data, affecting the stability and reliability of data processing in the entire power system. Summary of the Invention

[0005] The present invention provides a method and system for constructing a graph database based on power data, which is used to efficiently process the complexity, dynamics and large scale of power data and improve the stability and reliability of data processing in the entire power system.

[0006] In a first aspect, the present invention provides a method for constructing a graph database based on power data, comprising:

[0007] Collect data on power generation equipment, power equipment and power users under the power dispatching center in the power system, and use the power dispatching center, the power generation equipment, power equipment and power users under the power dispatching center as graph nodes;

[0008] Establishing a node edge between the power dispatching center and its corresponding power generation equipment, and establishing a first node edge based on the collaborative relationship between the power generation equipment under the power dispatching center to obtain a first subgraph;

[0009] Establishing a node edge between a target power generation device and its corresponding power equipment, and establishing a second node edge based on the degree of association between the power equipment under the target power generation device, to construct a second subgraph; the target power generation device is any power generation device in the power dispatching center;

[0010] Establishing a node edge between a target power device and its corresponding power user, and establishing a third node edge based on the similarity between the power users under the target power device, to construct a third subgraph; the target power device is any power device of the target power generation device;

[0011] A graph database of the power dispatching center is constructed according to the first subgraph, the second subgraph and the third subgraph of the power dispatching center.

[0012] According to an embodiment of the present invention, a method for constructing a graph database based on power data is provided, wherein a first node edge is established based on the collaborative relationship between power generation equipment under a power dispatching center to obtain a first subgraph, including:

[0013] Obtain the power generation power of any two power generation devices under the power dispatching center at the target time within the preset observation time period, as well as the most recent start-stop time interval of any two power generation devices, and the regulation rate of any two power generation devices;

[0014] Calculate the synergy coefficient between any two power generation devices based on their power generation at the target time, the most recent start-stop interval, and the regulation rate;

[0015] If the synergy relationship coefficient between any two power generation devices is greater than or equal to a preset synergy relationship threshold, a first node edge between the any two power generation devices is established to obtain the first subgraph.

[0016] According to the method for constructing a graph database based on power data provided by an embodiment of the present invention, the calculation formula for the synergy relationship coefficient between any two power generation devices is as follows:

[0017]

[0018] Among them, S GG (g i ,g j ) represents the synergy coefficient between the i-th power generation equipment and the j-th power generation equipment, gi represents the i-th power generation equipment, g j represents the jth power generation equipment, T represents the preset observation time period, t represents the target time, represents the power generation of the i-th power generation equipment at the target time, represents the power generation of the jth power generation equipment at the target time, represents the latest start-stop time interval of the i-th power generation device and the j-th power generation device, T max represents a preset maximum time interval reference value, represents the regulation rate of the i-th power generation device, represents the regulation rate of the j-th power generation device, Q max represents a preset maximum regulation rate value.

[0019] According to the power data-based graph database construction method provided by the embodiment of the present application, a second node edge is established according to the correlation degree between the power devices under the target power generation device, and a second subgraph is constructed, comprising:

[0020] The number of power transmission paths and the number of electrical connections jointly participated by any two power devices under the target power generation device, the current value on the electrical connection associated with the target moment within a preset observation time period, and the influence coefficient of one power device on another power device when one of the two power devices fails are obtained;

[0021] According to the number of power transmission paths and the number of electrical connections jointly participated by any two power devices, the current value on the electrical connection associated with the two power devices, and the influence coefficient between the two power devices, the correlation degree coefficient between the two power devices is calculated.

[0022] If the correlation degree coefficient between any two power devices is greater than or equal to a preset correlation degree threshold, a second node edge is established between the two power devices, and the second subgraph is constructed.

[0023] According to the power data-based graph database construction method provided by the embodiment of the present application, the calculation formula of the correlation degree coefficient between any two power devices is as follows:

[0024]

[0025] ω1+ω2=1;

[0026] wherein S EE (e i , e j ) represents the correlation degree coefficient between the i-th power device and the j-th power device, e i represents the i-th power device, e j represents the j-th power device, N common (e i , e j ) represents the number of power transmission paths jointly participated by the i-th power device and the j-th power device, N total represents the maximum reference number of power transmission paths, Mcommon (e i , e j ) represents the number of electrical connections in which the i-th power device participates together with the j-th power device, M total represents the maximum reference number of electrical connections, T represents a preset observation time period, t represents a target time, represents the current value on the electrical connection associated with the i-th power device and the j-th power device at the target time, I max represents a preset maximum current reference value, represents the influence coefficient of the j-th power device when the i-th power device fails, F amx represents a preset maximum influence degree reference coefficient, e represents the base number of an exponential function, and ω1 and ω2 represent preset weight values.

[0027] The method for constructing a graph database based on power data provided by the embodiment of the application establishes a third node edge according to the similarity degree between power users under a target power device, and constructs a third subgraph, which comprises the following steps:

[0028] Obtaining the power consumption of any two power users under the target power device at a target time within a preset observation time period, and the power consumption of any two power users within a preset time period;

[0029] According to the power consumption of any two power users at a target time and the power consumption of any two power users within a preset time period, a similarity degree coefficient between any two power users is calculated;

[0030] If the similarity degree coefficient between any two power users is greater than or equal to a preset similarity degree threshold, a third node edge between any two power users is established, and the third subgraph is constructed.

[0031] According to the method for constructing a graph database based on power data provided by the embodiment of the application, the calculation formula of the similarity degree coefficient between any two power users is as follows:

[0032]

[0033] Wherein, S UU (u i , u j ) represents the similarity degree coefficient between the i-th power user and the j-th power user, u i represents the i-th power user, u j represents the j-th power user, T represents a preset observation time period, t represents a target time, represents the power consumption of the i-th power user at the target time, represents the power consumption of the j-th power user at the target time, represents the power factor of the i-th power user at the target time, represents the power factor of the jth power user at the target time, represents the electricity consumption of the i-th electricity user in the preset time period, represents the power consumption of the i-th power user in the preset time period, log() represents the logarithmic function, and λ1 and λ2 represent the preset weight factors.

[0034] According to the method for constructing a graph database based on power data provided by an embodiment of the present invention, after constructing the graph database of the power dispatching center according to the first subgraph, the second subgraph, and the third subgraph of the power dispatching center, the method further includes:

[0035] According to the jurisdiction information and dispatching strategy information of each power dispatching center, a graph index between power dispatching centers is established;

[0036] A graph database of the power system is constructed based on the graph indexes between the power dispatching centers and the graph database of each power dispatching center.

[0037] In a second aspect, the present invention further provides a graph database construction system based on power data, which is applied to the graph database construction method based on power data as described in the first aspect. The graph database construction system based on power data includes:

[0038] The collection module is used to collect data on power generation equipment, power equipment and power users under the power dispatching center in the power system, and uses the power dispatching center, the power generation equipment, power equipment and power users under the power dispatching center as graph nodes;

[0039] A first subgraph construction module is used to establish a node edge between the power dispatching center and its corresponding power generation equipment, and to establish a first node edge based on the collaborative relationship between the power generation equipment under the power dispatching center to obtain a first subgraph;

[0040] A second subgraph construction module is configured to establish a node edge between a target power generation device and its corresponding power equipment, and to establish a second node edge based on the degree of association between the power equipment under the target power generation device, thereby constructing a second subgraph; the target power generation device is any power generation device in the power dispatching center;

[0041] a third subgraph construction module, configured to establish a node edge between a target power device and its corresponding power user, and to establish a third node edge based on the similarity between the power users under the target power device, thereby constructing a third subgraph; the target power device being any power device of the target power generation device;

[0042] The graph database construction module is used to construct the graph database of the power dispatching center based on the first subgraph, the second subgraph and the third subgraph of the power dispatching center.

[0043] In a third aspect, the present invention also provides an electronic device comprising: a memory for storing a computer software program; and a processor for reading and executing the computer software program, thereby implementing any of the above-mentioned methods for constructing a graph database based on power data.

[0044] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium, in which a computer software program is stored. When the computer software program is executed by a processor, it implements any of the above-mentioned methods for constructing a graph database based on power data.

[0045] In a fifth aspect, the present invention further provides a computer program product, comprising a computer program, which, when executed by a processor, implements any of the above methods for constructing a graph database based on power data.

[0046] The method for constructing a graph database based on power data provided by an embodiment of the present invention establishes a power system database using a graph model. The nodes and edges of the graph model can be flexibly defined and expanded. When the power system changes, only the corresponding nodes and edges need to be added to the graph model, eliminating the need to modify the complex table structure required by relational databases. Secondly, because the graph database directly stores the relationships between power data in the form of nodes and edges, queries do not require complex multi-table join operations. Simply starting from the node representing the power dispatch center and traversing along the edges can quickly obtain the nodes of all relevant power users, significantly reducing query time complexity. Furthermore, by constructing a graph database using multiple subgraphs, it can be understood as distributing large-scale power data across multiple storage nodes or computing units. When the number of power users increases significantly, causing the data volume to exceed the processing capacity of the original system, a graph partitioning algorithm is used to redistribute the graph data to newly added storage nodes. Each storage node is responsible for processing a portion of the subgraph data, thereby avoiding the occurrence of system bottlenecks. Therefore, the embodiments of the present invention achieve efficient processing of the complexity, dynamics, and large-scale nature of power data, improving the stability and reliability of data processing across the entire power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a flowchart of a method for constructing a graph database based on power data provided by an embodiment of the present invention;

[0048] Figure 2 is a schematic diagram of a first subgraph provided by an embodiment of the present invention;

[0049] Figure 3 is a schematic diagram of a second subgraph provided by an embodiment of the present invention;

[0050] Figure 4 is a schematic diagram of a second subgraph provided by an embodiment of the present invention;

[0051] Figure 5 is a schematic diagram of a graph database of a power system provided by an embodiment of the present invention;

[0052] Figure 6 This is a structural diagram of a system for building a graph database based on power data provided by an embodiment of the present invention;

[0053] Figure 7 An embodiment diagram of an electronic device provided by an embodiment of the present invention;

[0054] Figure 8 A diagram of an embodiment of a computer-readable storage medium provided for an embodiment of the present invention. DETAILED DESCRIPTION

[0055] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0056] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Therefore, a feature specified as "first" or "second" may explicitly or implicitly include one or more of the specified features. In the description of the present invention, "plurality" means two or more, unless otherwise specifically defined.

[0057] In the description of the present invention, the term "for example" is used to mean "used as an example, illustration or illustration". Any embodiment of the present invention described as "for example" is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any person skilled in the art to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes are not elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed herein.

[0058] Optional, see Figure 1 As shown, Figure 1This is a flowchart of the method for constructing a graph database based on power data provided by the present invention. In the embodiment of the present invention, the execution subject of the method for constructing a graph database based on power data is a database construction system. Therefore, the method for constructing a graph database based on power data includes:

[0059] Step 10: Collect the power generation equipment, power equipment and power users under the power dispatching center in the power system, and use the power dispatching center, the power generation equipment, power equipment and power users under the power dispatching center as graph nodes.

[0060] Optionally, the database construction system is connected to the power system, so it can interface with the monitoring system, management information system (MIS), etc. of the power dispatching center of the power system to obtain the data source within the jurisdiction of each power dispatching center. The data source includes power generation equipment information, such as relevant parameters, location, operating status, etc. of thermal power generating units, hydropower generating units, wind power generating units, etc.; power equipment information, such as specifications, connection relationships, real-time flow data, etc. of substations, transmission lines, distribution equipment, etc.; and power user information, such as the electricity consumption scale, electricity consumption characteristics, and location of different types of users.

[0061] Furthermore, the database construction system extracts the power dispatching center, as well as the power generation equipment, power equipment and power users under the power dispatching center from the data source, wherein the power equipment includes substation equipment and transmission equipment, and the power users include industrial users and residential users.

[0062] Furthermore, the database construction system defines the power dispatching center, the power generation equipment, power equipment and power users under the power dispatching center as graph nodes. Each graph node has a unique identifier and contains corresponding attribute information, such as the user number, power consumption, power consumption time and other attribute information of the power user. Among them, the power dispatching center set of the power system can be expressed as C = {c1, c2, ..., c s}, c s represents the sth power dispatching center. The power generation equipment set under each power dispatching center can be expressed as G = {g1, g2, ..., g n}, g n The set of power equipment under each power generation equipment can be expressed as E = {e1, e2, ..., e m}, e m The set of power users under each power device can be expressed as U = {u1, u2, ..., u k},u k represents the kth electricity user.

[0063] Step 20: Establish a node edge between the power dispatching center and its corresponding power generation equipment, and establish a first node edge based on the collaborative relationship between the power generation equipment under the power dispatching center to obtain a first subgraph.

[0064] It should be noted that the graph in the embodiment of the present invention is an unweighted graph. Therefore, if there is an edge between two nodes, the default value of the edge between the nodes is 1.

[0065] Optionally, for each power dispatch center c i , determine each power dispatch center c i and its corresponding power generation equipment g i The connection relationship between them can be determined based on the communication link and the dispatch instruction issuing channel. If there is an effective connection so that the power dispatch center c i Can be used for power generation equipment i To conduct dispatching control, a power dispatching center c i and power generation equipment i The node edges between them. Among them, the connection relationship can be expressed as a function f CE (c i , g i ), whose value is:

[0066]

[0067] When f CE (c i , g i )=1, build slave node c i To node g i Node edges.

[0068] Furthermore, the database construction system establishes a first node edge according to the collaborative relationship between any two power generation devices under the power dispatching center to obtain a first subgraph, as specifically described in steps 201 to 203 .

[0069] Step 30: Establish a node edge between the target power generation equipment and its corresponding power equipment, and establish a second node edge according to the degree of association between the power equipment under the target power generation equipment to construct a second subgraph.

[0070] Optionally, for each power generation device, from the perspective of power flow, it is determined whether the electric energy generated by the power generation device is transmitted, converted, etc. through a specific power device. For example, the power generation device g i The generated electricity is sent to the power equipment through a specific transmission line i , then build power generation equipment g i With power equipment i The node edges between them. Among them, the connection relationship can be expressed as a function fCE (g i , e i ), whose value is:

[0071]

[0072] When f CE (g i , e i )=1, build slave node g i To node e i Node edges.

[0073] Furthermore, the database construction system establishes a second node edge according to the degree of association between any two power equipment under the target power generation equipment, and constructs a second subgraph, as specifically described in steps 301 to 303 .

[0074] Step 40: Establish a node edge between the target power equipment and its corresponding power user, and establish a third node edge based on the similarity between the power users under the target power equipment to construct a third subgraph.

[0075] Optionally, for each power device, it is determined whether the power device directly or indirectly supplies power to the power user based on the power distribution relationship. i For residential users i Power supply, then build power equipment e i With residential users i The node edges between them. Among them, the connection relationship can be expressed as a function f CE (e i ,u i ), whose value is:

[0076]

[0077] When f CE (e i ,u i )=1, construct the slave node e i To node u i Node edges.

[0078] Furthermore, the database construction system establishes a third node edge according to the similarity between any two power users under the target power equipment, and constructs a third subgraph, as specifically described in steps 401 to 403 .

[0079] Step 50: construct a graph database of the power dispatching center based on the first subgraph, the second subgraph, and the third subgraph of the power dispatching center.

[0080] Furthermore, for each power dispatching center, the database construction system integrates the first subgraph, second subgraph and third subgraph constructed by each power dispatching center, that is, taking each power dispatching center as the core, all relevant power generation equipment, power equipment and power users and their edge relationships are summarized together, and a suitable graph database management system (such as Neo4j) is used to store graph structure information, and finally a complete graph database for each power dispatching center is formed.

[0081] It should be noted that in a graph database, each node and edge can be associated with corresponding attributes (such as real-time parameters of the device, detailed information of the user, etc.), which facilitates subsequent queries, analysis, and the application of graph-based algorithms (such as the shortest path algorithm for finding the optimal recovery path during troubleshooting, and the community discovery algorithm for analyzing different closely related user groups).

[0082] The embodiments of the present invention establish a database for the power system using a graph model. The nodes and edges of the graph model can be flexibly defined and expanded. When the power system changes, only the corresponding nodes and edges need to be added to the graph model, eliminating the need to modify the complex table structure as in a relational database. Secondly, because the graph database directly stores the relationships between power data in the form of nodes and edges, queries do not require complex multi-table join operations. Simply starting from the node representing the power dispatch center and traversing along the edges can quickly obtain the nodes of all relevant power users, significantly reducing query time complexity. Furthermore, by constructing a graph database using multiple subgraphs, it can be understood as distributing large-scale power data across multiple storage nodes or computing units. When the number of power users increases significantly, causing the data volume to exceed the processing capacity of the original system, a graph partitioning algorithm is used to redistribute the graph data to newly added storage nodes. Each storage node is responsible for processing a portion of the subgraph data, thereby avoiding the occurrence of system bottlenecks. Therefore, the embodiments of the present invention achieve efficient processing of the complexity, dynamics, and large-scale nature of power data, improving the stability and reliability of data processing across the entire power system.

[0083] In one embodiment, steps 201 to 203 are described as follows:

[0084] Step 201: Obtain the power generation power of any two power generation devices under the power dispatching center at the target time within a preset observation time period, the most recent start-stop time interval of any two power generation devices, and the regulation rate of any two power generation devices.

[0085] Among them, the collaborative relationship between power generation equipment can be considered from multiple dimensions, such as the complementarity of power generation (for example, the power coordination between hydropower and thermal power in the dry season and the wet season), and the coordination of start and stop times (different types of units reasonably arrange the start and stop sequence according to the peak and valley periods of electricity consumption).

[0086] Therefore, the database construction system obtains the power generation power of any two power generation equipment under the power dispatching center at the target moment within the preset observation time period, as well as the most recent start-stop time interval of any two power generation equipment, and the regulation rate of any two power generation equipment, where the preset observation time period is such as the past day, the past week, etc.

[0087] Step 202 : Calculate the synergy coefficient between any two power generation devices according to the power generation of the any two power generation devices at the target time, the most recent start-stop time interval, and the regulation rate.

[0088] Furthermore, the database construction system calculates the synergy coefficient between any two power generation devices based on their power generation at the target time, the most recent start-stop time interval, and the regulation rate. The calculation formula for the synergy coefficient between any two power generation devices is as follows:

[0089]

[0090] Among them, S GG (g i , g j ) represents the synergy coefficient between the i-th power generation equipment and the j-th power generation equipment, g i represents the i-th power generation equipment, g j represents the jth power generation equipment, T represents the preset observation time period, t represents the target time, represents the power generation of the i-th power generation equipment at the target time, represents the power generation of the jth power generation equipment at the target time, T represents the time interval between the most recent start and stop of the i-th power generation equipment and the j-th power generation equipment. max Indicates the preset maximum time interval reference value, represents the regulation rate of the i-th power generation equipment, Q gj represents the regulation rate of the jth power generation equipment, Q max Indicates the preset maximum value of the regulation rate.

[0091] Step 203: If the synergy relationship coefficient between any two power generation devices is greater than or equal to a preset synergy relationship threshold, a first node edge is established between the any two power generation devices to obtain a first subgraph.

[0092] Furthermore, if the synergy relationship coefficient between any two power generation devices is greater than or equal to the preset synergy relationship threshold, the database construction system establishes a first node edge between any two power generation devices to obtain a first subgraph, wherein the preset synergy relationship threshold θ GG According to actual settings.

[0093] Therefore, it can be understood that if the synergy coefficient S between the i-th power generation equipment and the j-th power generation equipment is GG (g i , g j )≥θ GG , then establish a slave node g in the graph i To node g j Node edges.

[0094] In one embodiment, the power dispatching center 1 has power generation equipment 1, power generation equipment 2, power generation equipment 3, power generation equipment 4, power generation equipment 5 and power generation equipment 6, and all power generation equipment are effectively connected to the power dispatching center 1. The synergy relationship coefficient between power generation equipment 1 and power generation equipment 5, the synergy relationship coefficient between power generation equipment 2 and power generation equipment 6, and the synergy relationship coefficient between power generation equipment 3 and power generation equipment 4 are all greater than the preset synergy relationship threshold. Therefore, the first subgraph constructed is as follows: Figure 2 shown.

[0095] The embodiment of the present invention constructs a first subgraph to provide a data basis for the subsequent construction of a graph database, so that the complexity, dynamics and large-scale nature of power data can be efficiently processed through the graph database, thereby improving the stability and reliability of data processing in the entire power system.

[0096] In one embodiment, steps 301 to 303 are described as follows:

[0097] Step 301: Obtain the number of power transmission paths and electrical connections jointly participated by any two power devices under the target power generation device, as well as the current values ​​on the electrical connections associated with any two power devices at the target time within a preset observation time period, and the impact coefficient of a failure of one of the two power devices on the other power device.

[0098] The degree of correlation between power equipment can be considered by factors such as the tightness of electrical connections and the impact range of equipment failures. For example, adjacent towers on the same transmission line and equipment in different electrical bays within the same substation have a high degree of correlation.

[0099] Therefore, the database construction system obtains the number of power transmission paths and the number of electrical connections jointly participated by any two power devices under the target power generation device, as well as the current values ​​on the electrical connections associated with any two power devices at the target moment within a preset observation time period, and the impact coefficient of one power device on the other power device when any two power devices fail.

[0100] In one embodiment, the specific process of obtaining the influence coefficient is as follows:

[0101] First, the power equipmenti and power equipment j Perform failure mode analysis.

[0102] The failure modes of power equipment can be categorized into short circuit failure, open circuit failure, and performance degradation due to equipment aging. Different types of equipment have different failure modes. For example, a short circuit failure in a transmission line (which is power equipment) may be caused by lightning strikes, tree branches, etc.; for a transformer, it may be caused by a winding short circuit, iron core failure, etc. i The set of all possible failure modes F i ={f i1 , f i2 ,...,f in}, f in Indicates electrical equipment e i The nth failure mode of the power equipment e j The set of all possible failure modes F j ={f j1 , f j2 ,...,f jm}, f jm Indicates electrical equipment e j The mth failure mode.

[0103] Further, the analysis of the power equipment i Failure to affect power equipment j The topology of the power system needs to be considered, including the connection between transmission lines, substations and other equipment.

[0104] Construct the topology matrix X of the power system, where the element x in the topology matrix X is pq Indicates whether there is a direct electrical connection between power equipment p and power equipment q (if yes, x pq =1; otherwise, x pq =0). By searching the topology matrix, the power equipment e i Start by finding all possible electrical equipment j The path set Q ij ={q1, q2, ..., q k}, where path q l ={e l1 , e l2 ,...,e ln}, indicating that the power equipment e i After a series of power equipment l1 , e l2 ,...,e ln Reaching power equipment j .

[0105] Furthermore, for each propagation path q l ∈Q ij , when the power equipment e i When a fault occurs, the power flow changes of each device on the path are calculated according to the power flow calculation method. The power flow calculation can be based on the node voltage equation and branch power equation of the power system, as follows:

[0106] Assume that the node admittance matrix of the power system is Y, the node voltage vector is V, and the branch power vector is S. For normal operation, the equations I = YV and S = VI are satisfied. * , where I represents the node injection current vector and I * Represents the conjugate vector of I. When the power device e i A fault occurs (assuming it is a short circuit fault with a short circuit impedance of Z f ), modify the node admittance matrix Y to Y * The specific modification method depends on the fault type and location, and the node voltage vector V is recalculated. * and branch power vector S * . Further, calculate the power equipment e i The change of the power flow ΔS ej , for example, for transmission line equipment, in, Indicates the branch power after the fault, S ej Indicates normal branch power.

[0107] Furthermore, reliability indicators are used to quantify the impact of failures. Commonly used reliability indicators include under-power probability (LOLP) and expected short supply (EENS).

[0108] Therefore, the calculation of the power equipment e i The reliability index R1 of the power system during normal operation, for example, is obtained by performing a large number of random state sampling on the power system through methods such as Monte Carlo simulation, calculating the power supply situation in each state, and obtaining the reliability index statistically. i When a fault occurs, the reliability index R2 of the power system is recalculated. The change in the reliability index ΔR = |R2-R1| is calculated.

[0109] According to the power equipment i The position and role of the power system, the reliability index change is distributed to the power equipment j Get the power equipment j The reliability impact For example, if the electrical equipment e j It is a key transmission line that contributes more to the reliability index and has a greater impact on distribution.

[0110] Furthermore, the power equipment is evaluated by integrating the changes in power flow and reliability indicators. i When a fault occurs, the power equipment j Degree of impact The details are as follows:

[0111] Assume that the weight of the power flow change is μ1, the weight of the reliability index change is μ2, and μ1+μ2=1, then the impact degree is It can be expressed as:

[0112]

[0113] in, Indicates electrical equipment e j The maximum allowable branch power is used to normalize the power flow variation.

[0114] Step 302, calculate the correlation coefficient between any two power devices based on the number of power transmission paths and the number of electrical connections in which any two power devices participate, the current values ​​on the electrical connections associated with any two power devices, and the influence coefficient between any two power devices.

[0115] Furthermore, the database construction system calculates the correlation coefficient between any two power devices based on the number of power transmission paths and electrical connections in which any two power devices participate, the current values ​​on the electrical connections associated with any two power devices, and the influence coefficient between any two power devices. The calculation formula for the correlation coefficient between any two power devices is as follows:

[0116]

[0117] ω1+ω2=1;

[0118] Among them, S EE (e i , e j ) represents the correlation coefficient between the i-th power equipment and the j-th power equipment, e i represents the i-th power equipment, e j represents the jth power device, N common (e i , e j ) represents the number of power transmission paths in which the i-th power device and the j-th power device participate together, N total Indicates the maximum reference number of power transmission paths, M common (e i , e j) represents the number of electrical connections between the i-th power equipment and the j-th power equipment, M total represents the maximum reference number of electrical connections, T represents the preset observation time period, and t represents the target time. represents the current value of the electrical connection between the i-th power device and the j-th power device at the target time, I max Indicates the preset maximum current reference value, F represents the impact coefficient of the i-th power equipment failure on the j-th power equipment, amx represents the preset maximum influence reference coefficient, e represents the base of the exponential function, and ω1 and ω2 represent the preset weight values.

[0119] Step 303: If the correlation coefficient between any two power devices is greater than or equal to a preset correlation threshold, a second node edge is established between the any two power devices to construct a second subgraph.

[0120] Furthermore, if the correlation coefficient between any two power devices is greater than or equal to a preset correlation threshold, the database construction system establishes a second node edge between any two power devices and constructs a second subgraph, wherein the preset correlation threshold θ EE According to actual settings.

[0121] Therefore, it can be understood that if the correlation coefficient S between the i-th power equipment and the j-th power equipment is EE (e i , e j )≥θ EE , then establish a slave node e in the graph i To node e j Node edges.

[0122] In one embodiment, power generation device 1 includes power device 1, power device 2, power device 3, power device 4, power device 5, and power device 6, and electric energy can flow from target power generation device 1 to all power devices. The correlation coefficient between power device 1 and power device 3, the correlation coefficient between power device 2 and power device 4, and the correlation coefficient between power device 5 and power device 6 are all greater than the preset correlation threshold. Therefore, the second subgraph is constructed as shown in FIG. Figure 3 shown.

[0123] The embodiment of the present invention constructs a second subgraph to provide a data basis for the subsequent construction of a graph database, so that the complexity, dynamics and large-scale nature of power data can be efficiently processed through the graph database, thereby improving the stability and reliability of data processing in the entire power system.

[0124] In one embodiment, steps 401 to 403 are described as follows:

[0125] Step 401: Obtain the power consumption of any two power users under the target power equipment at a target moment within a preset observation time period, and the power consumption of any two power users within the preset time period.

[0126] The similarity between electricity users can be measured from perspectives such as electricity consumption behavior (time distribution, power factor, etc.) and electricity consumption scale (daily electricity consumption, monthly electricity consumption, etc.). Therefore, the database construction system obtains the electricity consumption of any two electricity users under the target power equipment at the target time within the preset observation time period, as well as the electricity consumption of any two electricity users within the preset time period.

[0127] Step 402 : Calculate the similarity coefficient between any two power users based on their power consumption at the target time and their power consumption within a preset time period.

[0128] Furthermore, the database construction system calculates the similarity coefficient between any two power users based on their power consumption at the target time and their power consumption within a preset time period. The calculation formula for the similarity coefficient between any two power users is as follows:

[0129]

[0130] Among them, S UU (u i ,u j ) represents the similarity coefficient between the i-th electricity user and the j-th electricity user, u i represents the i-th electricity user, u j represents the jth electricity user, T represents the preset observation time period, t represents the target time, represents the power consumption of the i-th electricity user at the target time, represents the power consumption of the jth power user at the target time, represents the power factor of the i-th power user at the target time, represents the power factor of the jth power user at the target time, represents the electricity consumption of the i-th electricity user in the preset time period, represents the power consumption of the i-th power user in the preset time period, log() represents the logarithmic function, and λ1 and λ2 represent the preset weight factors.

[0131] Step 403: If the similarity coefficient between any two power users is greater than or equal to a preset similarity threshold, a third node edge is established between the any two power users to construct a third subgraph.

[0132] Further, if the similarity degree coefficient between any two power users is greater than or equal to a preset similarity degree threshold, the database construction system establishes a third node edge between any two power users, and constructs the third subgraph, wherein the preset similarity degree threshold is θ UU According to actual settings.

[0133] Therefore, it can be understood that if the similarity degree coefficient S UU (u i , u j ) ≥ θ UU , a node edge from node u i to node u j is established in the graph.

[0134] In an embodiment, there are power users 1, 2, 3, 4, 5 and 6 under the power equipment 1, and the power equipment 1 can supply power to all the power users. The similarity degree coefficient between the power user 1 and the power user 2, the similarity degree coefficient between the power user 1 and the power user 5, the similarity degree coefficient between the power user 1 and the power user 6, the similarity degree coefficient between the power user 2 and the power user 4, the similarity degree coefficient between the power user 2 and the power user 6, and the similarity degree coefficient between the power user 3 and the power user 4 are all greater than the preset similarity degree threshold. The third subgraph constructed is shown in FIG. 4. Figure 4

[0135] The embodiment of the present application constructs the third subgraph, provides a data basis for subsequent construction of the graph database, and enables efficient processing of the complexity, dynamics and large scale of the power data through the graph database, thereby improving the stability and reliability of the entire power system data processing.

[0136] In an embodiment, after the graph database of each power dispatching center is constructed, the graph database of the power system needs to be constructed according to the graph databases of all the power dispatching centers, and the specific process is as follows:

[0137] Step 60: According to the jurisdictional region information and the dispatching strategy information of each power dispatching center, the graph index between the power dispatching centers is established.

[0138] ​Specifically, the database construction system obtains the jurisdiction information of each power dispatching center, and the jurisdiction information includes jurisdiction range description information, voltage level coverage information and jurisdiction distribution information. Jurisdiction range description information includes geographical area range, such as which cities, districts and counties are covered, longitude and latitude boundaries, etc. Voltage level coverage information includes mainly responsible for 110kV and above voltage level grid dispatching, or includes specific low-voltage distribution network areas, etc. Jurisdiction distribution information includes the approximate distribution of power generation, transmission, and power consumption entities under its jurisdiction. In one embodiment, the set of power dispatching centers of the power system can be expressed as C = {c1, c2, ..., c s}, c s Represents the sth power dispatching center. For each power dispatching center, its jurisdiction information is quantified, such as defining the geographic area coverage vector as O i ={O i1 , O i2 ,...,O in}, where O ij It can represent the coverage status in a certain geographical dimension (such as a region divided by a grid with a certain precision) (the value can be 0 or 1, indicating no coverage or coverage); the voltage level coverage vector V i ={v i1 , v i2 ,...,v im}, v ik Indicates whether the corresponding voltage level is covered.

[0139] Furthermore, the database construction system obtains the dispatching strategy information of each power dispatching center. The dispatching strategy information includes power generation plan allocation strategy (how different power dispatching centers arrange the power generation power, start and stop time, etc. of power generation equipment according to the load forecast in their own area), fault emergency handling strategy (when facing power grid failure, how to coordinate with adjacent power dispatching centers to perform load transfer, fault isolation and other operations), and power mutual assistance strategy (rules for power support between different power dispatching centers during peak and valley periods).

[0140] Furthermore, the database construction system extracts and quantifies the characteristics of the scheduling strategy. For example, for the power generation plan allocation strategy, the strategy difference measurement function S is defined. P (c i , c j ), the calculation formula is as follows:

[0141]

[0142] Among them, T represents the planning period, G ij Indicates that it is in the power dispatching center c i and power dispatching centerj The collection of power generation equipment in the surrounding areas of the jurisdiction, and They represent the power generation equipment g in the power dispatching center c i and power dispatching center j The power generation plan is scheduled at the time t. Indicates the maximum power generation of the power generation equipment; ω g It represents the weight coefficient of power generation equipment g in the overall strategy consideration, which can be set according to factors such as power generation capacity and importance.

[0143] For the fault emergency handling strategy, define the fault coordination function S F (c i , c j ), the calculation formula is as follows:

[0144]

[0145] in, In the face of multiple preset fault scenarios, the power dispatch center c i and power dispatching center j The number of scenarios that can be effectively handled collaboratively (e.g., through reasonable load shifting, power restoration, etc.); represents the total number of preset fault scenarios, and α1 represents the weight coefficient of the number of scenarios; In the critical fault simulation, the power dispatch center c i and power dispatching center j The time difference in initiating effective emergency response measures; Indicates the maximum allowable time difference reference value, β1 indicates the time difference weight coefficient, E ij Indicates that it involves the power dispatching center c i and power dispatching center j Coordinate the collection of key power equipment within the region; and They represent the power equipment e in the power dispatch center c in the case of a fault. i and power dispatching center j The current change can be estimated through power flow calculation; I max represents the maximum reference current change; γ represents the current change weight coefficient, α1+β1+γ=1.

[0146] For the electric energy mutual aid strategy, define the electric energy mutual aid correlation function S E (c i , c j ), the calculation formula is as follows:

[0147]

[0148] Among them, T peak Indicates the peak and valley periods of electricity consumption. Indicates that at time t, the power dispatching center c i and power dispatching center j The expected mutual energy between the two (positive value indicates that the power dispatch center c i Flow to the power dispatching center c j , negative value is opposite); E max It represents the set maximum mutual aid power reference value, and α2 represents the mutual aid power weight coefficient; Indicates that after a long period of time, the power dispatch center c i and power dispatching center j The difference in the change of the power balance state (measured by the surplus or deficit of power), It represents the maximum balance difference value of the reference; β2 represents the power balance weight coefficient, α2+β2=1.

[0149] Furthermore, the database construction system calculates the power dispatch center c i and power dispatching center j The degree of correlation between D (c i , c j ), the specific calculation formula is as follows:

[0150]

[0151] Among them, O i ·O j Represents vector O i and vector O j The inner product of |O i | and |O j | respectively represent vector O i and vector O j The modulus of ; ε1, ε2, ε3, ε4 represent weight coefficients, ε1+ε2+ε3+ε4=1.

[0152] If the power dispatching center c i and power dispatching center j The degree of correlation between E (c i , c j ) is greater than the correlation threshold θ D , the database construction system establishes the power dispatching center c i and power dispatching center j The node edges between them, node edges, power dispatching center c i and power dispatching center j Constructs the graph index.

[0153] Step 70: construct a graph database of the power system based on the graph indexes between the power dispatching centers and the graph database of each power dispatching center.

[0154] Furthermore, the database construction system uses the established graph index between power dispatch centers as a framework to integrate the graph database of each power dispatch center (such as the graph database containing power generation equipment, power equipment, power users and the complex relationships between them built in the previous step). For each edge between power dispatch centers in the graph index (such as the one connecting power dispatch center c i and power dispatching center j edge).

[0155] It should be noted that in the graph database of the integrated power system, not only the power dispatching center c represented by this edge is retained i and the associated information of the power dispatching center cj (reflected by the above comprehensive correlation, etc.), and the power dispatching center cj also needs to be i and power dispatching center j The cross-region connection information in the graph database is sorted and associated. For example, if the power dispatch center c i In the graph database, there is a power generation device g connected to a transmission line (power equipment) e, and the transmission line is associated with the power equipment in the jurisdiction through the cross-regional connection line. j The power system diagram database needs to reflect the connection relationship of power equipment across dispatching centers.

[0156] Furthermore, in the constructed graph database of the power system, it is necessary to improve the structure of the graph. For example, according to the hierarchical and partitioning characteristics of the actual power system (such as provincial-level dispatching, municipal-level dispatching and other different levels and different geographical partitioning situations), the nodes and edges should be reasonably classified and labeled to facilitate subsequent query and analysis operations.

[0157] At the same time, more attribute information needs to be associated with the nodes and edges in the graph. For example, for the power dispatching center node, in addition to the above-mentioned jurisdiction and dispatching strategy related attributes, its historical dispatching operation records, personnel configuration and other information can also be associated; for the power generation equipment node, the equipment's full life cycle maintenance records, real-time operation status monitoring data, etc. can be associated; for the edge (whether it is the edge between the dispatching center or the edge between each internal device), attributes such as power transmission limit and reliability assessment value can be associated.

[0158] Continuing with the above embodiment, the degree of association between the power dispatching center 1 and the power dispatching center 2 in the power system is greater than the association threshold, so the graph database of the power system is as follows: Figure 5 shown.

[0159] The embodiment of the present invention constructs a graph database of the power system based on the graph database of the power dispatching center, so that the complexity, dynamics and large scale of power data can be efficiently processed through the graph database of the power system, thereby improving the stability and reliability of data processing of the entire power system.

[0160] Furthermore, the graph database construction system based on power data provided by the present invention is described below. The graph database construction system based on power data described below and the graph database construction method based on power data described above can be referenced to each other.

[0161] Optional, see Figure 6 , Figure 6 This is a structural diagram of a graph database construction system based on power data provided by the present invention. The graph database construction system based on power data includes:

[0162] The collection module 610 is used to collect information about power generation equipment, power equipment, and power users under the power dispatching center in the power system, and uses the power dispatching center, the power generation equipment, power equipment, and power users under the power dispatching center as graph nodes;

[0163] A first subgraph construction module 620 is configured to establish a node edge between the power dispatching center and its corresponding power generation equipment, and to establish a first node edge based on the collaborative relationship between the power generation equipment under the power dispatching center to obtain a first subgraph;

[0164] The second subgraph construction module 630 is configured to establish a node edge between the target power generation device and its corresponding power equipment, and to establish a second node edge based on the degree of association between the power equipment under the target power generation device, thereby constructing a second subgraph; the target power generation device is any power generation device in the power dispatching center;

[0165] A third subgraph construction module 640 is configured to establish a node edge between a target power device and its corresponding power user, and to establish a third node edge based on the similarity between the power users under the target power device, thereby constructing a third subgraph; the target power device is any power device of the target power generation equipment;

[0166] The graph database construction module 650 is used to construct a graph database of the power dispatching center according to the first subgraph, the second subgraph and the third subgraph of the power dispatching center.

[0167] The embodiments of the present invention establish a database for the power system using a graph model. The nodes and edges of the graph model can be flexibly defined and expanded. When the power system changes, only the corresponding nodes and edges need to be added to the graph model, eliminating the need to modify the complex table structure as in a relational database. Secondly, because the graph database directly stores the relationships between power data in the form of nodes and edges, queries do not require complex multi-table join operations. Simply starting from the node representing the power dispatch center and traversing along the edges can quickly obtain the nodes of all relevant power users, significantly reducing query time complexity. Furthermore, by constructing a graph database using multiple subgraphs, it can be understood as distributing large-scale power data across multiple storage nodes or computing units. When the number of power users increases significantly, causing the data volume to exceed the processing capacity of the original system, a graph partitioning algorithm is used to redistribute the graph data to newly added storage nodes. Each storage node is responsible for processing a portion of the subgraph data, thereby avoiding the occurrence of system bottlenecks. Therefore, the embodiments of the present invention achieve efficient processing of the complexity, dynamics, and large-scale nature of power data, improving the stability and reliability of data processing across the entire power system.

[0168] See also Figure 7 , Figure 7 This is a diagram of an embodiment of an electronic device provided by an embodiment of the present invention. Figure 7 As shown, an embodiment of the present invention provides an electronic device 700, including a memory 710, a processor 720, and a computer program 711 stored in the memory 710 and executable on the processor 720. When the processor 720 executes the computer program 711, the following steps are implemented:

[0169] Collect data on power generation equipment, power equipment and power users under the power dispatching center in the power system, and use the power dispatching center, the power generation equipment, power equipment and power users under the power dispatching center as graph nodes;

[0170] Establishing a node edge between the power dispatching center and its corresponding power generation equipment, and establishing a first node edge based on the collaborative relationship between the power generation equipment under the power dispatching center to obtain a first subgraph;

[0171] Establish a node edge between the target power generation equipment and its corresponding power equipment, and establish a second node edge based on the degree of association between the power equipment under the target power generation equipment to construct a second subgraph; the target power generation equipment is any power generation equipment in the power dispatching center;

[0172] Establishing a node edge between the target power equipment and its corresponding power user, and establishing a third node edge based on the similarity between the power users under the target power equipment, to construct a third subgraph; the target power equipment is any power equipment of the target power generation equipment;

[0173] A graph database of the power dispatching center is constructed according to the first subgraph, the second subgraph and the third subgraph of the power dispatching center.

[0174] See also Figure 8 , Figure 8 Detailed description of an embodiment of a computer-readable storage medium provided by an embodiment of the present invention. Figure 8 As shown, this embodiment provides a computer-readable storage medium 800 on which a computer program 711 is stored. When the computer program 711 is executed by a processor, the following steps are implemented:

[0175] Collect data on power generation equipment, power equipment and power users under the power dispatching center in the power system, and use the power dispatching center, the power generation equipment, power equipment and power users under the power dispatching center as graph nodes;

[0176] Establishing a node edge between the power dispatching center and its corresponding power generation equipment, and establishing a first node edge based on the collaborative relationship between the power generation equipment under the power dispatching center to obtain a first subgraph;

[0177] Establish a node edge between the target power generation equipment and its corresponding power equipment, and establish a second node edge based on the degree of association between the power equipment under the target power generation equipment to construct a second subgraph; the target power generation equipment is any power generation equipment in the power dispatching center;

[0178] Establishing a node edge between the target power equipment and its corresponding power user, and establishing a third node edge based on the similarity between the power users under the target power equipment, to construct a third subgraph; the target power equipment is any power equipment of the target power generation equipment;

[0179] A graph database of the power dispatching center is constructed according to the first subgraph, the second subgraph and the third subgraph of the power dispatching center.

[0180] On the other hand, the present invention further provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the method for constructing a graph database based on power data provided by the above methods, which includes:

[0181] Collect data on power generation equipment, power equipment and power users under the power dispatching center in the power system, and use the power dispatching center, the power generation equipment, power equipment and power users under the power dispatching center as graph nodes;

[0182] Establishing a node edge between the power dispatching center and its corresponding power generation equipment, and establishing a first node edge based on the collaborative relationship between the power generation equipment under the power dispatching center to obtain a first subgraph;

[0183] Establish a node edge between the target power generation equipment and its corresponding power equipment, and establish a second node edge based on the degree of association between the power equipment under the target power generation equipment to construct a second subgraph; the target power generation equipment is any power generation equipment in the power dispatching center;

[0184] Establishing a node edge between the target power equipment and its corresponding power user, and establishing a third node edge based on the similarity between the power users under the target power equipment, to construct a third subgraph; the target power equipment is any power equipment of the target power generation equipment;

[0185] A graph database of the power dispatching center is constructed according to the first subgraph, the second subgraph and the third subgraph of the power dispatching center.

[0186] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0187] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0188] Finally, 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 aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for constructing a graph database based on power data, characterized in that: include: Collect data on power generation equipment, power equipment and power users under the power dispatching center in the power system, and use the power dispatching center, the power generation equipment, power equipment and power users under the power dispatching center as graph nodes; Establishing a node edge between the power dispatching center and its corresponding power generation equipment, and establishing a first node edge based on the collaborative relationship between the power generation equipment under the power dispatching center to obtain a first subgraph; Establishing a node edge between a target power generation device and its corresponding power equipment, and establishing a second node edge based on the degree of association between the power equipment under the target power generation device, to construct a second subgraph; the target power generation device is any power generation device in the power dispatching center; Establishing a node edge between the target power device and its corresponding power user, and establishing a third node edge based on the similarity between the power users under the target power device to construct a third subgraph; The target power equipment is any power equipment of the target power generation equipment; Constructing a graph database of the power dispatching center according to the first subgraph, the second subgraph, and the third subgraph of the power dispatching center; The step of establishing a first node edge based on the collaborative relationship between power generation equipment under the power dispatching center to obtain a first subgraph includes: Obtain the power generation power of any two power generation devices under the power dispatching center at the target time within the preset observation time period, as well as the most recent start-stop time interval of any two power generation devices, and the regulation rate of any two power generation devices; Calculate the synergy coefficient between any two power generation devices based on their power generation at the target time, the most recent start-stop interval, and the regulation rate; If the synergy relationship coefficient between any two power generation devices is greater than or equal to a preset synergy relationship threshold, a first node edge is established between the any two power generation devices to obtain the first subgraph; The calculation formula of the synergy coefficient between any two power generation equipment is as follows: Among them, S GG (g i ,g j ) represents the synergy coefficient between the i-th power generation equipment and the j-th power generation equipment, g i represents the i-th power generation equipment, g j represents the jth power generation equipment, T represents the preset observation time period, t represents the target time, represents the power generation of the i-th power generation equipment at the target time, represents the power generation of the jth power generation equipment at the target time, T represents the time interval between the most recent start and stop of the i-th power generation equipment and the j-th power generation equipment. max Indicates the preset maximum time interval reference value, represents the regulation rate of the i-th power generation equipment, represents the regulation rate of the jth power generation equipment, Q max Indicates the preset maximum value of the regulation rate.

2. The method for constructing a graph database based on power data according to claim 1, characterized in that: The step of establishing a second node edge according to the degree of association between the power equipment under the target power generation equipment to construct a second subgraph includes: Obtaining the number of power transmission paths and electrical connections jointly participated in by any two power devices under the target power generation device, as well as the current values ​​of the electrical connections associated with the two power devices at target times within a preset observation time period, and the impact coefficient of a failure of one of the two power devices on the other power device; Calculate the correlation coefficient between any two power devices based on the number of power transmission paths and electrical connections in which the two power devices participate, the current values ​​on the electrical connections associated with the two power devices, and the influence coefficient between the two power devices; If the correlation coefficient between any two power devices is greater than or equal to a preset correlation threshold, a second node edge is established between the any two power devices to construct the second subgraph.

3. The method for constructing a graph database based on power data according to claim 2, characterized in that: The calculation formula for the correlation coefficient between any two power devices is as follows: ω1+ω2=1; Among them, S EE (e i ,e j ) represents the correlation coefficient between the i-th power equipment and the j-th power equipment, e i represents the i-th power equipment, e j represents the jth power device, N common (e i ,e j ) represents the number of power transmission paths in which the i-th power device and the j-th power device participate together, N total Indicates the maximum reference number of power transmission paths, M common (e i ,e j ) represents the number of electrical connections between the i-th power equipment and the j-th power equipment, M total represents the maximum reference number of electrical connections, T represents the preset observation time period, and t represents the target time. represents the current value of the electrical connection between the i-th power device and the j-th power device at the target time, I max Indicates the preset maximum current reference value, F represents the impact coefficient of the i-th power equipment failure on the j-th power equipment, amx represents the preset maximum influence reference coefficient, e represents the base of the exponential function, and ω1 and ω2 represent the preset weight values.

4. The method for constructing a graph database based on power data according to claim 1, characterized in that: The step of establishing a third node edge based on the similarity between the power users under the target power equipment and constructing a third subgraph includes: Obtaining the power consumption of any two power users under the target power equipment at a target time within a preset observation time period, and the power consumption of any two power users within the preset time period; Calculate the similarity coefficient between any two electricity users based on their electricity consumption at the target time and their electricity consumption within a preset time period; If the similarity coefficient between any two power users is greater than or equal to a preset similarity threshold, a third node edge is established between the any two power users to construct the third subgraph.

5. The method for constructing a graph database based on power data according to claim 4, characterized in that: The calculation formula of the similarity coefficient between any two electricity users is as follows: Among them, S UU (u i ,u j ) represents the similarity coefficient between the i-th electricity user and the j-th electricity user, u i represents the i-th electricity user, u j represents the jth electricity user, T represents the preset observation time period, t represents the target time, represents the power consumption of the i-th electricity user at the target time, represents the power consumption of the jth power user at the target time, represents the power factor of the i-th power user at the target time, represents the power factor of the jth power user at the target time, represents the electricity consumption of the i-th electricity user in the preset time period, represents the power consumption of the i-th power user in the preset time period, log() represents the logarithmic function, and λ1 and λ2 represent the preset weight factors.

6. The method for constructing a graph database based on power data according to any one of claims 1 to 5, characterized in that: After constructing the graph database of the power dispatching center according to the first subgraph, the second subgraph, and the third subgraph of the power dispatching center, the method further includes: According to the jurisdiction information and dispatching strategy information of each power dispatching center, a graph index between power dispatching centers is established; A graph database of the power system is constructed based on the graph indexes between the power dispatching centers and the graph database of each power dispatching center.

7. A graph database construction system based on power data, characterized in that: The method for constructing a graph database based on electric power data according to any one of claims 1 to 6, wherein the system for constructing a graph database based on electric power data comprises: The collection module is used to collect data on power generation equipment, power equipment and power users under the power dispatching center in the power system, and uses the power dispatching center, the power generation equipment, power equipment and power users under the power dispatching center as graph nodes; A first subgraph construction module is used to establish a node edge between the power dispatching center and its corresponding power generation equipment, and to establish a first node edge based on the collaborative relationship between the power generation equipment under the power dispatching center to obtain a first subgraph; A second subgraph construction module is configured to establish a node edge between a target power generation device and its corresponding power equipment, and to establish a second node edge based on the degree of association between the power equipment under the target power generation device, thereby constructing a second subgraph; the target power generation device is any power generation device in the power dispatching center; a third subgraph construction module, configured to establish a node edge between a target power device and its corresponding power user, and to establish a third node edge based on the similarity between the power users under the target power device, thereby constructing a third subgraph; the target power device being any power device of the target power generation device; A graph database construction module, configured to construct a graph database of the power dispatching center based on the first subgraph, the second subgraph, and the third subgraph of the power dispatching center; The step of establishing a first node edge based on the collaborative relationship between power generation equipment under the power dispatching center to obtain a first subgraph includes: Obtain the power generation power of any two power generation devices under the power dispatching center at the target time within the preset observation time period, as well as the most recent start-stop time interval of any two power generation devices, and the regulation rate of any two power generation devices; Calculate the synergy coefficient between any two power generation devices based on their power generation at the target time, the most recent start-stop interval, and the regulation rate; If the synergy relationship coefficient between any two power generation devices is greater than or equal to a preset synergy relationship threshold, a first node edge is established between the any two power generation devices to obtain the first subgraph; The calculation formula of the synergy coefficient between any two power generation equipment is as follows: Among them, S GG (g i ,g j ) represents the synergy coefficient between the i-th power generation equipment and the j-th power generation equipment, g i represents the i-th power generation equipment, g j represents the jth power generation equipment, T represents the preset observation time period, t represents the target time, represents the power generation of the i-th power generation equipment at the target time, represents the power generation of the jth power generation equipment at the target time, T represents the time interval between the most recent start and stop of the i-th power generation equipment and the j-th power generation equipment. max Indicates the preset maximum time interval reference value, represents the regulation rate of the i-th power generation equipment, represents the regulation rate of the jth power generation equipment, Q max Indicates the preset maximum value of the regulation rate.

8. A non-transitory computer-readable storage medium storing a computer software program, characterized in that: When the computer software program is executed by a processor, the method for constructing a graph database based on power data as described in any one of claims 1 to 6 is implemented.

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