A Method and System for Visualizing Power System Operation Data Based on Digital Twins

Abstract

This invention discloses a method and system for visualizing power system operation data based on digital twins, belonging to the field of data transmission technology. The method includes: Step S1: acquiring operation data of power equipment in the power system based on various sensors; Step S2: layering data nodes to generate multiple hierarchical structures, and connecting parent data points within different hierarchical structures to generate a transmission network; Step S3: re-dividing sub-data points in each hierarchical structure based on transmission delay values ​​and hierarchical delay estimates to generate advanced hierarchical structures; Step S4: generating an updated transmission network, and rapidly transmitting the operation data to a pre-built digital twin model on the control platform based on the updated transmission network to achieve visualization of power system operation data. This invention allows for real-time adjustment of sensor transmission methods, improving data transmission rates and preventing errors in data visualization caused by untimely power system operation data transmission.

Description

Technical Field

[0001] This invention belongs to the field of data transmission technology, specifically relating to a method and system for visualizing power system operation data based on digital twins. Background Technology

[0002] A complete digital twin model includes a physical layer, a data layer, a model layer, a functional layer, and a capability layer. The data in the data layer comes from the inherent data in the physical space, which is multi-mode and multi-type operational data collected in real time by various sensors. The transmission rate of the sensor data is a key factor in improving the efficiency of data twin technology applications.

[0003] For example, Chinese patent application "CN112069247B" discloses a power system operation data visualization system based on digital twin technology, including a data acquisition module, a control module, a digital twin model construction module, and a display module. The control module is communicatively connected to the data acquisition module; the control module contains a machine learning module; the input of the digital twin model construction module is connected to the output of the control module; and the input of the display module is connected to the output of the digital twin model construction module. This invention also proposes a power system operation data visualization method, in which the data acquisition module collects real-time power system operation data and sends it to the control module. The control module analyzes, identifies, and predicts the operation data using its internal machine learning module, then sends the analysis, identification, and prediction results to the digital twin model construction module to construct a three-dimensional digital twin model of the power system, and finally sends it to the display module to visualize the operation data. Another example is Chinese patent application "CN116108596A," which discloses a rapid reliability assessment method for distribution networks in a power system, including the following steps: matching the distribution network database in the power system with an external system database to achieve interconnection between the power system and different application scenarios. Leveraging digital twin technology, this invention addresses the siloed limitations between the power system and application systems in different scenarios, establishing a cross-disciplinary and cross-system distribution network characterization index system. This allows for differentiated reliability assessment calculations based on various application scenarios. By integrating the databases of the power system and actual application systems, this invention overcomes the existing problems of significant differences in power system evaluation systems and application system software, inconsistent application levels, and difficulties in unified data extraction and application. It improves data retrieval efficiency and addresses the challenges of data sharing between information systems, interface standardization, and poor integration of the Internet of Things and information technology.

[0004] However, the existing technologies mentioned above only propose the model building steps of the power system and the integration of power data. In practice, improving the transmission rate of power system operation data is a fundamental condition for evaluating and analyzing whether the power system operation data is transmitted stably, and further realizing the timeliness of power system operation data visualization. Summary of the Invention

[0005] To address the aforementioned problems, this invention provides a method and system for visualizing power system operation data based on digital twins, thereby resolving the issues in the prior art.

[0006] To achieve the aforementioned objectives, this invention proposes a method for visualizing power system operation data based on digital twins, comprising:

[0007] Based on various sensors, operational data of power equipment in the power system are acquired;

[0008] The sensor is set as a data node. The data nodes are layered based on the evaluation values ​​between each data node to generate multiple hierarchical structures. The data nodes contained in the hierarchical structure are divided into sub-data points and parent data points. Each hierarchical structure includes a data cluster composed of different parent data points. The parent data points in different hierarchical structures are connected to each other to generate a transmission network.

[0009] Obtain the transmission delay value of the data cluster in the transmission network and the estimated hierarchical delay of the corresponding hierarchical structure, and re-divide the sub-data points in each hierarchical structure based on the transmission delay value and the estimated hierarchical delay to generate an advanced hierarchical structure;

[0010] The advanced hierarchical structure updates the transmission network based on a preset first cycle to generate an updated transmission network. Based on the updated transmission network, the operating data is quickly transmitted to a digital twin model pre-built on the control platform to realize the visualization of the power system's operating data.

[0011] Furthermore, generating the transmission network includes the following steps:

[0012] The signal strength values ​​of communication transmission between the data node and other data nodes are obtained, the minimum signal strength value is set as the evaluation value, a first threshold is set, and the data nodes with evaluation values ​​greater than or equal to the first threshold are combined to generate multiple data clusters. One data node is extracted from the data cluster and set as the selection node. The evaluation values ​​between the selection node and the remaining data nodes are accumulated and defined as a first value. The selection node corresponding to the minimum first value is set as the parent data point, and the remaining data nodes in the data cluster are set as the child data points. The data cluster is defined as the hierarchical structure.

[0013] The hierarchical structure includes a top level, intermediate levels, and a bottom level. The sub-data points of the top level and each intermediate level are composed of the parent data points in the next lower level hierarchical structure. In the bottom level, each sub-data point receives a data request sent by the parent data point in the corresponding data cluster using a first channel, and then sends the stored running data to the parent data point. After collecting the running data for a preset second period, the parent data point sends the collected running data to the parent data point of the intermediate level using a second channel. This step is repeated to send the running data of each data node from the hierarchical structure to the top level to generate the transmission network.

[0014] Furthermore, obtaining the transmission delay value and the hierarchical delay estimate includes the following steps:

[0015] The transmission delay value of the i-th data cluster in the hierarchical structure is calculated based on the first formula. The first formula is: ,in, exist Greater than or equal to Set the value to 1 if the condition is met, otherwise set it to 0. The number of sub-data points in the i-th data cluster. and The average time required to collect each of the running data from the parent data point in the i-th and j-th data clusters, respectively. and The time from when the parent data point in the i-th and j-th data clusters sends the data request to the child data point to when the data reception is completed, respectively, is defined as the time from when the parent data point in the i-th and j-th data clusters sends the data request to the child data point, and n is the number of data clusters in the hierarchical structure. The number of sub-data points in the j-th data cluster. and These are the parent data points of the i-th and j-th data clusters, respectively. Let d be the y-th sub-data point in the i-th data cluster, and d be the evaluation value;

[0016] The hierarchical delay estimate W for each of the hierarchical structures is calculated based on the second formula, which is: .

[0017] Furthermore, generating the advanced hierarchical structure includes the following steps:

[0018] Set filtering conditions, extract the data clusters in the hierarchical structure based on the filtering conditions, define them as first sub-clusters, obtain the transmission range of the parent data point in the first sub-cluster, obtain the number of sub-data points located within the transmission range of the parent data point but not belonging to the first sub-cluster, define it as a second value, if the second value is greater than or equal to a preset second threshold, then the sub-data points are sequentially assigned to the first sub-cluster to generate a second sub-cluster, repeat this step until the first sub-cluster in the hierarchical structure is reassigned to the second sub-cluster, obtain the hierarchical delay estimate of the hierarchical structure corresponding to each second sub-cluster based on the second formula, obtain the hierarchical structure corresponding to the minimum hierarchical delay estimate, and set it as the advanced hierarchical structure.

[0019] Furthermore, generating an updated transport network includes the following steps:

[0020] If the number or position of each sensor changes during the first period, each sub-data point in the advanced hierarchical structure that is not set as the parent data point is set as a sub-data group. Based on a preset value, multiple sub-data points are extracted from the sub-data groups and set as a second sub-cluster. The sub-data points of the second sub-cluster are set as the parent data points of the advanced hierarchical structure. Based on the evaluation value, the remaining data nodes in the advanced hierarchical structure are combined with the parent data points to generate multiple updated data clusters. Based on the updated data clusters, the transmission delay value corresponding to the advanced hierarchical structure is obtained. This step is repeated until the number of extractions of each sub-data point in the sub-data group is greater than or equal to a preset second threshold to generate multiple transmission delay values. The advanced hierarchical structure corresponding to the smallest transmission delay value is obtained, and each advanced hierarchical structure is set as an update transmission network.

[0021] This invention also provides a power system operation data visualization system based on digital twins. This system is used to implement the aforementioned power system operation data visualization method based on digital twins. The system mainly includes:

[0022] The data acquisition module acquires the operating data of the corresponding power equipment based on each sensor;

[0023] The transmission construction module sets the sensor as a data node, divides the data nodes into layers based on the evaluation values ​​between each data node to generate multiple hierarchical structures, divides the data nodes contained in the hierarchical structure into sub-data points and parent data points, each hierarchical structure includes multiple parent data points, and connects the parent data points in different hierarchical structures to generate a transmission network.

[0024] The node setting module obtains the transmission delay value and the estimated level delay of each layer in the transmission network, and re-divides the sub-data points in each layer based on the transmission delay value and the estimated level delay to generate an advanced layer structure.

[0025] The data display module, wherein the advanced hierarchical structure updates the transmission network based on a preset first cycle to generate an updated transmission network, and transmits the operating data quickly to a digital twin model pre-built on the control platform based on the updated transmission network to realize the visualization of the power system's operating data.

[0026] Compared with the prior art, the beneficial effects of the present invention are at least as follows:

[0027] This invention first designates sensors in the power system as data nodes. Based on the evaluation values ​​of each data node, the data nodes in the power system are divided into multiple hierarchical structures to construct a transmission network for power system operation data. This can shorten the transmission path of operation data and expand the collection range of operation data. Then, by calculating the hierarchical delay estimate of the hierarchical structure, the data nodes are re-divided to generate an advanced hierarchical structure. This allows for timely detection of communication interruptions or delays among data nodes, and the transmission paths of data nodes are adjusted based on the advanced hierarchical structure to improve the transmission efficiency of each data node. Finally, if the number or location of sensors in the power system changes, an updated transmission network is generated by re-dividing the data nodes in the advanced hierarchical structure, which can promptly expand the transmission range of power system operation data.

[0028] The present invention also sets the data node partitioning method in the advanced hierarchical structure by considering channel interference factors, further determines the transmission delay value corresponding to different partitioning methods, and selects the partitioning result with the best transmission efficiency to improve the transmission rate of data nodes. Attached Figure Description

[0029] Figure 1 This is a flowchart illustrating the steps of the power system operation data visualization method based on digital twins according to the present invention.

[0030] Figure 2 This is a diagram of the power system operation data transmission network structure according to the present invention;

[0031] Figure 3 This is a structural diagram of the power system operation data visualization system based on digital twins according to the present invention. Detailed Implementation

[0032] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0033] It is understood that the terms "first," "second," etc., used in this application may be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are used only to distinguish one element from another. For example, without departing from the scope of this application, a first script may be referred to as a second script, and similarly, a second script may be referred to as a first script.

[0034] like Figure 1 As shown, a digital twin-based method for visualizing power system operation data includes:

[0035] Step S1: Acquire the operating data of power equipment in the power system based on various sensors.

[0036] Specifically, applying digital twin models to power systems enables monitoring of operational data status, performance analysis, and data visualization at each stage of the power system. In this embodiment, the power system consists of power plants, transmission and transformation lines, power distribution substations, and electricity consumption, and includes various types of power equipment. By setting different types of sensors and installing each sensor on the corresponding power equipment, the required operational data of the power equipment can be collected in real time, including but not limited to voltage, temperature, current, electricity consumption, and various signal data, as well as physical data such as the height and shape of the power equipment.

[0037] Step S2: Set the sensor as a data node, and divide the data nodes into layers based on the evaluation values ​​between each data node to generate multiple hierarchical structures. Divide the data nodes contained in the hierarchical structure into sub-data points and parent data points. Each hierarchical structure includes a data cluster composed of different parent data points. Connect the parent data points in different hierarchical structures to generate a transmission network.

[0038] Specifically, in this embodiment, in order to quickly analyze various operating data of the power system, the data collected by each sensor can be set as data nodes. The evaluation value refers to the strength of the wireless transmission signal between each data node. The hierarchical structure refers to the hierarchical transmission of each data node in the form of an irregular tree structure. Each hierarchical structure contains multiple sub-data points and parent data points. Sub-data points and parent data points are combined to generate a data cluster. The operating data is transmitted from the sub-data points to the corresponding parent data points. Through the connection method of the parent data points, communication and transmission can be carried out between different hierarchical structures to build a transmission network. The specific connection method will be described later.

[0039] Step S3: Obtain the transmission delay value of the data cluster in the transmission network and the hierarchical delay estimate of the corresponding hierarchical structure. Based on the transmission delay value and the hierarchical delay estimate, re-divide the sub-data points in each hierarchical structure to generate the advanced hierarchical structure.

[0040] Specifically, in this embodiment, when the data nodes corresponding to each sensor communicate and transmit data, there are communication collisions or communication delays. Therefore, it is necessary to calculate the transmission delay value between the data nodes contained in the hierarchical structure of the transmission network, and further calculate the hierarchical delay estimate of the hierarchical structure. If the hierarchical delay estimate is high, the data nodes in the hierarchical structure can be re-divided and the transmission path of the data nodes can be changed to generate an advanced hierarchical structure, thereby reducing the hierarchical delay estimate of the hierarchical structure. That is, the hierarchical delay estimate of the advanced hierarchical structure is lower than that of the hierarchical structure.

[0041] Step S4: The advanced hierarchical structure generates an updated transmission network based on the preset first-cycle update transmission network. Based on the updated transmission network, the operating data is quickly transmitted to the digital twin model pre-built on the control platform to realize the visualization of the power system's operating data.

[0042] Specifically, in this embodiment, for example, the first cycle is set to 24 hours. Every 24 hours, the communication method of each data node in the advanced hierarchical structure is updated and judged. If the sensor of a certain power equipment has a positional offset or the number of sensors is increased, the corresponding transmission network needs to be updated to generate an updated transmission network. The specific generation method will be described later. It can efficiently transmit various operating data. The control platform refers to the data collection terminal, which includes the construction method of the digital twin model. It can quickly input various operating data into the digital twin model to realize the operation data visualization function of the power system.

[0043] Generating a transport network includes the following steps:

[0044] The signal strength values ​​of communication transmission between data nodes and other data nodes are obtained. The minimum signal strength value is set as the evaluation value. A first threshold is set. Data nodes with evaluation values ​​greater than or equal to the first threshold are combined to generate multiple data clusters. A data node is extracted from the data cluster and set as the selection node. The evaluation values ​​between the selection node and the remaining data nodes are accumulated and defined as the first value. The selection node corresponding to the minimum first value is set as the parent data point. The remaining data nodes in the data cluster are set as child data points. The data cluster is defined as a hierarchical structure.

[0045] The hierarchical structure includes a top level, intermediate levels, and a bottom level. The sub-data points of the top level and each intermediate level are composed of parent data points in the next lower level of the hierarchical structure. In the bottom level, each sub-data point receives a data request sent by the parent data point in the corresponding data cluster using the first channel, and then sends the stored running data to the parent data point. After the parent data point collects the running data for a preset second period, it sends the collected running data to the parent data point of the intermediate level using the second channel. This step is repeated to send the running data of each data node from the hierarchical structure to the top level to generate a transmission network.

[0046] Specifically, in this embodiment, the signal strength value refers to the radio wave strength of the two sensors communicating wirelessly. The signal strength value is related to the transmission distance, data transmission capacity, and sensor performance. When the data transmission capacity and sensor performance do not change, the signal strength value will change with the transmission distance. The signal strength value can be used as the identification standard for the farthest transmission distance of the sensor. Therefore, by setting the signal strength value as the evaluation value, the data nodes can be clustered and combined to generate a data cluster. For example, if the signal strengths of data node 1 with data node 2 and data node 3 are 5 and 1 respectively, and the first threshold is set to 3, then data node 1 and data node 2 are divided into the same data cluster.

[0047] To enable effective data transmission among data nodes in a data cluster, it is necessary to set transmission objects to improve the transmission rate of running data. This is achieved by setting the extraction node as the parent data point and setting the parent data point as the transmission object for the child data points. For example, in a data cluster, each child data point collects and stores running data. After receiving a data request from the parent data point, it transmits the running data to the parent data point in sequence. The hierarchical structure contains one or more data clusters.

[0048] In this embodiment, the highest level refers to the terminal used to receive all set operational data, including but not limited to the power system control platform; the lowest level refers to each sensor used only to collect and transmit its own operational data and not to receive other operational data; the intermediate level refers to the hierarchical structure that does not include the highest and lowest levels. The hierarchical structure in the power system must have a highest and lowest level to achieve operational data transmission. The hierarchical structure is arranged from the highest level to the lowest level, and the number of hierarchical structures also represents the increasing number of times operational data is transmitted from the sensors. The first channel and the second channel refer to different communication channels, which can reduce channel interference between channels transmitting data. Figure 2As shown, the connection between each hierarchical structure is that the parent data point of the current hierarchical structure connects to the child data point of the higher-level hierarchical structure. In order to reduce signal interference between sensors when transmitting running data, different transmission channels can be set for different hierarchical structures. For example, the child data point of the data cluster in hierarchical structure L3 uses channel 1 to transmit running data to the parent data point E31. The parent data point E31 uses channel 1 to transmit each running data and its own running data to the child data point e21 in hierarchical structure L2. The child data point e21 uses channel 2 to transmit the summarized running data and its own running data to the parent data point E21. This step is repeated to set the transmission method of each hierarchical structure as a transmission network.

[0049] Obtaining transmission delay values ​​and tier delay estimates involves the following steps:

[0050] The transmission delay value of the i-th data cluster in the hierarchical structure is calculated based on the first formula. The first formula is: ,in, exist Greater than or equal to Set the value to 1 if the condition is met, otherwise set it to 0. Let i be the number of sub-data points in the i-th data cluster. and Let be the average time required to collect each running data point from the parent data point in the i-th and j-th data clusters, respectively. and These represent the time from when the parent data point in the i-th and j-th data clusters sends a data request to the child data point until the data is received, respectively, where n is the number of data clusters in the hierarchical structure. Let j be the number of sub-data points in the j-th data cluster. and These are the parent data points of the i-th and j-th data clusters, respectively. Let d be the y-th sub-data point in the i-th data cluster, and d be the evaluation value;

[0051] The hierarchical delay estimate W for each level of the structure is calculated based on the second formula, which is: .

[0052] Specifically, in this embodiment, the transmission delay value refers to the delay in transmitting running data between various data nodes in the data cluster. The delay of each data cluster in the hierarchical structure is evaluated using a first formula. In the first formula, within the same data cluster, T refers to the time required from when the parent data point starts sending data requests to each child data point until the parent data point receives all running data, and t refers to the average time required from when the parent data point starts sending data requests to each child data point until the parent data point receives each running data sequentially. For example, if the time required for the parent data point to receive running data from each child data point is 4, 6, and 8 seconds respectively, and the parent data point completes receiving running data from all child data points at the 8th second, then T is 8, and t is (4+6+8) / 3=6. Therefore, This refers to the probability value of communication interference that may occur when each child data point in the same data cluster transmits data to its parent data point. This refers to the normal delay time when the parent data point receives running data without communication interference. The first formula estimates the transmission delay value of the data cluster by calculating the probability of collision when each child data point transmits running data to the parent data point and its own delay time. This can indirectly evaluate the transmission performance of the data cluster. The smaller the transmission delay value, the better the transmission performance of the data cluster.

[0053] like Figure 2 As shown, the hierarchical structure L3 contains two data clusters, I and J. Data cluster I contains three child data points and one parent data point, E31, while data cluster J contains two child data points and one parent data point, E32. The parent data point E31 sends data requests to its corresponding child data points based on a preset 10-second time interval. (The formula is incomplete in the original text.) It is used to determine sub-data points With two other sub-data points and For example, the magnitude of the evaluation values ​​between them. Figure 2 In the process, the evaluation values ​​of sub-data points in data cluster I and other sub-data points in the same hierarchical structure are judged respectively. The transmission delay values ​​of data clusters I and J can be calculated separately using the second formula. The hierarchical delay estimate of the hierarchical structure L3 is calculated by accumulating the transmission delay values ​​of each data cluster. The smaller the hierarchical delay estimate, the less interference there is between the data nodes and the higher the transmission rate of the running data.

[0054] Generating an advanced hierarchy involves the following steps:

[0055] Set filtering conditions, extract data clusters in the hierarchical structure based on the filtering conditions, define them as the first sub-cluster, obtain the transmission range of the parent data point in the first sub-cluster, obtain the number of sub-data points that are within the transmission range of the parent data point but do not belong to the first sub-cluster, define it as the second value, if the second value is greater than or equal to the preset second threshold, then the sub-data points are sequentially assigned to the first sub-cluster to generate the second sub-cluster. Repeat this step until the first sub-cluster in the hierarchical structure is reassigned to the second sub-cluster. Obtain the hierarchical delay estimate of the hierarchical structure corresponding to each second sub-cluster based on the second formula, obtain the hierarchical structure corresponding to the minimum hierarchical delay estimate, and set it as the advanced hierarchical structure.

[0056] Specifically, in this embodiment, setting filtering conditions can reduce the number of times the hierarchical structure is updated to an advanced hierarchical structure, making the transmission network more stable and faster. The filtering conditions are set as follows: in the hierarchical structure, the number of data nodes in the data cluster must be greater than or equal to 1, that is, the data cluster has at least one sensor, and the data node can receive communication from other sub-data points in the same data cluster or from other data clusters, or the data node can receive communication from a parent data point in another data cluster when the hierarchical structure has not changed; the transmission range refers to the signal transmission range of the parent data point, and the second value refers to the number of sub-data points that can receive communication from more than one parent data point. The second threshold is set to 1, then the sub-data point establishes communication connections with each parent data point to divide it into a new data cluster, and further generates a new hierarchical structure, for example. Figure 2 In this case, sub-data point e321 is simultaneously within the transmission range of parent data points E31 and E32. Therefore, it is necessary to calculate and determine the data cluster partitioning of sub-data point e321. Based on the second formula, the hierarchical delay estimate of the new hierarchical structure is calculated respectively. The new hierarchical structure corresponding to the minimum hierarchical delay estimate is set as the advanced hierarchical structure, which can effectively allocate the transmission objects of each data node and further improve the transmission rate.

[0057] Generating an updated transport network includes the following steps:

[0058] If the number or location of each sensor changes during the first cycle, each sub-data point in the advanced hierarchical structure that is not set as a parent data point is set as a sub-data group. Based on a preset value, multiple sub-data points are extracted from the sub-data groups and set as a second sub-cluster. The sub-data points of the second sub-cluster are set as parent data points of the advanced hierarchical structure. Based on the evaluation value, the remaining data nodes in the advanced hierarchical structure are combined with the parent data points to generate multiple updated data clusters. Based on the updated data clusters, the transmission delay value of the corresponding advanced hierarchical structure is obtained. This step is repeated until the number of extractions of each sub-data point in the sub-data group is greater than or equal to the preset second threshold to generate multiple transmission delay values. The advanced hierarchical structure corresponding to the minimum transmission delay value is obtained, and each advanced hierarchical structure is set as the update transmission network.

[0059] Specifically, in this embodiment, considering that changes in the number or location of sensors may affect the transmission efficiency of operational data, the transmission network is updated based on a preset first cycle to generate an updated transmission network. For example, if the first cycle is set to 24 hours, the power system operational data is transmitted via the updated transmission network every 24 hours. If the number of sensors increases, the sensor is also set as a data node, and the data nodes in the advanced hierarchical structure are re-divided and combined. Since changes in the number or location of sensors are unknown, the re-division steps of each advanced hierarchical structure need to be executed sequentially from the lowest level to the highest level. The preset value refers to the number of data clusters contained in the advanced hierarchical structure. By re-dividing the data clusters contained in the advanced hierarchical structure, the advanced hierarchical structure selects a data node that is not a parent data point in any other advanced hierarchical structure as the parent data point, which can reduce channel interference. For example, if the parent data point is repeatedly selected from the child data points in the advanced hierarchical structure, the parent data point needs to use multiple communication channels or switch back and forth between communication channels to receive the operational data of all child data points from the lowest level to this level, which will cause channel congestion and make the communication channel setting process complicated.

[0060] This invention first designates sensors in the power system as data nodes. Based on the evaluation values ​​of each data node, the data nodes in the power system are divided into multiple hierarchical structures to construct a transmission network for power system operation data. This can shorten the transmission path of operation data and expand the collection range of operation data. Then, by calculating the hierarchical delay estimate of the hierarchical structure, the data nodes are re-divided to generate an advanced hierarchical structure. This allows for timely detection of communication interruptions or delays among data nodes, and the transmission paths of data nodes are adjusted based on the advanced hierarchical structure to improve the transmission efficiency of each data node. Finally, if the number or location of sensors in the power system changes, an updated transmission network is generated by re-dividing the data nodes in the advanced hierarchical structure, which can promptly expand the transmission range of power system operation data.

[0061] The present invention further determines the transmission delay value corresponding to different partitioning methods by setting the partitioning method of each data node in the advanced hierarchical structure, and selects the partitioning result with the best transmission efficiency to improve the transmission rate of the data nodes.

[0062] Of particular note is that this invention allows for real-time adjustment of the sensor's transmission method, improving the data transmission rate and thus preventing errors in the display of the digital twin model when used for data visualization due to untimely data transmission during power system operation.

[0063] like Figure 3 As shown, the present invention also provides a power system operation data visualization system based on digital twins. This system is used to implement the aforementioned power system operation data visualization method based on digital twins. The system mainly includes:

[0064] The data acquisition module acquires operational data of power equipment in the power system based on various sensors;

[0065] The transmission construction module sets the sensor as a data node, and divides the data nodes into layers based on the evaluation values ​​between each data node to generate multiple hierarchical structures. The data nodes contained in the hierarchical structure are divided into sub-data points and parent data points. Each hierarchical structure includes multiple parent data points. The parent data points in different hierarchical structures are connected to each other to generate a transmission network.

[0066] The node setting module obtains the transmission delay value and the estimated level delay of each layer in the transmission network, and re-divides the sub-data points in each layer based on the transmission delay value and the estimated level delay to generate the advanced layer structure.

[0067] The data display module, with its advanced hierarchical structure, generates an updated transmission network based on a preset first-cycle update transmission network. Based on this updated transmission network, the operational data is rapidly transmitted to a pre-built digital twin model on the control platform to achieve visualization of the power system's operational data.

[0068] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the various embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0069] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0070] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0071] The above embodiments merely illustrate several implementation methods of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this patent should be determined by the appended claims.

[0072] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for visualizing power system operation data based on digital twins, characterized in that, The method includes the following steps: Based on various sensors, acquire operational data of power equipment in the power system; The sensor is set as a data node. The data nodes are layered based on the evaluation values ​​between each data node to generate multiple hierarchical structures. The data nodes contained in the hierarchical structure are divided into sub-data points and parent data points. Each hierarchical structure includes a data cluster composed of different parent data points. The parent data points in different hierarchical structures are connected to each other to generate a transmission network. The generation of the transmission network includes the following steps: The signal strength values ​​of communication transmission between the data node and other data nodes are obtained, the minimum signal strength value is set as the evaluation value, a first threshold is set, and the data nodes with evaluation values ​​greater than or equal to the first threshold are combined to generate multiple data clusters. In any data cluster, one data node is selected as the selection node, the evaluation values ​​between the selection node and the remaining data nodes are accumulated and defined as a first value, the selection node corresponding to the minimum first value is set as the parent data point, and the remaining data nodes in the data cluster are set as the child data points. The data cluster is defined as the hierarchical structure. The hierarchical structure includes a top level, intermediate levels, and a bottom level. The top level refers to the terminal used to receive all the set operating data. The bottom level refers to each sensor used only to collect and transmit its own operating data and not to receive other operating data. The intermediate level refers to a hierarchical structure that does not include the top level and the bottom level. The sub-data points of the top level and each of the intermediate levels are composed of the parent data points in the next level hierarchical structure. Each sub-data point in the bottom level uses a first channel to receive a data request sent by the parent data point in the corresponding data cluster, and then sends the stored operating data to the parent data point. After the parent data point collects the operating data for a preset second period, it uses a second channel to send the collected operating data to the parent data point of the intermediate level. This step is repeated to send the operating data of each data node from the hierarchical structure to the top level to generate the transmission network. Obtain the transmission delay value of the data cluster in the transmission network and the estimated hierarchical delay of the corresponding hierarchical structure, and re-divide the sub-data points in each hierarchical structure based on the transmission delay value and the estimated hierarchical delay to generate an advanced hierarchical structure; The advanced hierarchical structure updates the transmission network based on a preset first cycle to generate an updated transmission network. Based on the updated transmission network, the operating data is quickly transmitted to a digital twin model pre-built on the control platform to realize the visualization of the power system's operating data. Obtaining the transmission delay value and the hierarchical delay estimate includes the following steps: The transmission delay value of the i-th data cluster in the hierarchical structure is calculated based on the first formula. The first formula is: ,in, exist Greater than or equal to Set the value to 1 if the condition is met, otherwise set it to 0. The number of sub-data points in the i-th data cluster. and The average time required to collect each of the running data from the parent data point in the i-th and j-th data clusters, respectively. and The time from when the parent data point in the i-th and j-th data clusters sends the data request to the child data point to when the data reception is completed, respectively, is defined as the time from when the parent data point in the i-th and j-th data clusters sends the data request to the child data point, and n is the number of data clusters in the hierarchical structure. The number of sub-data points in the j-th data cluster. and These are the parent data points of the i-th and j-th data clusters, respectively. Let d be the y-th sub-data point in the i-th data cluster, and d be the evaluation value; The hierarchical delay estimate W for each of the hierarchical structures is calculated based on the second formula, which is: .

2. The method for visualizing power system operation data based on digital twins according to claim 1, characterized in that, Generating the aforementioned hierarchical structure includes the following steps: Set filtering conditions, extract the data clusters in the hierarchical structure based on the filtering conditions, define them as first sub-clusters, obtain the transmission range of the parent data point in the first sub-cluster, obtain the number of sub-data points located within the transmission range of the parent data point but not belonging to the first sub-cluster, define it as a second value, if the second value is greater than or equal to a preset second threshold, then the sub-data points are sequentially assigned to the first sub-cluster to generate a second sub-cluster, repeat this step until the first sub-cluster in the hierarchical structure is reassigned to the second sub-cluster, obtain the hierarchical delay estimate of the hierarchical structure corresponding to each second sub-cluster based on the second formula, obtain the hierarchical structure corresponding to the minimum hierarchical delay estimate, and set it as the advanced hierarchical structure.

3. The method for visualizing power system operation data based on digital twins according to claim 1, characterized in that, Generating an updated transport network includes the following steps: If the number or position of each sensor changes during the first period, each sub-data point in the advanced hierarchical structure that is not set as the parent data point is set as a sub-data group. Based on a preset value, multiple sub-data points are extracted from the sub-data groups and set as a second sub-cluster. The sub-data points of the second sub-cluster are set as the parent data points of the advanced hierarchical structure. Based on the evaluation value, the remaining data nodes in the advanced hierarchical structure are combined with the parent data points to generate multiple updated data clusters. Based on the updated data clusters, the transmission delay value corresponding to the advanced hierarchical structure is obtained. This step is repeated until the number of extractions of each sub-data point in the sub-data group is greater than or equal to a preset second threshold to generate multiple transmission delay values. The advanced hierarchical structure corresponding to the smallest transmission delay value is obtained, and each advanced hierarchical structure is set as an update transmission network.

4. A power system operation data visualization system based on digital twins, used to implement the power system operation data visualization method based on digital twins as described in any one of claims 1-3, characterized in that, The system includes the following modules: The data acquisition module acquires the operating data of the corresponding power equipment based on each sensor; The transmission construction module sets the sensor as a data node, divides the data nodes into layers based on the evaluation values ​​between each data node to generate multiple hierarchical structures, divides the data nodes contained in the hierarchical structure into sub-data points and parent data points, each hierarchical structure includes multiple parent data points, and connects the parent data points in different hierarchical structures to generate a transmission network. The node setting module obtains the transmission delay value and the estimated level delay of each layer in the transmission network, and re-divides the sub-data points in each layer based on the transmission delay value and the estimated level delay to generate an advanced layer structure. The data display module, wherein the advanced hierarchical structure updates the transmission network based on a preset first cycle to generate an updated transmission network, and transmits the operating data quickly to a digital twin model pre-built on the control platform based on the updated transmission network to realize the visualization of the power system's operating data.

Images