System logic topological graph automatic generation method for power grid business

Abstract

The invention discloses a system logic topological graph automatic generation method for power grid business, which belongs to the technical field of power grids, and comprises a data layer, a business layer and a UI layer, and is characterized in that power information data in a power distribution network is imported into a database to form the data layer; the business layer comprises a data simulation module, a data management module, a visual layout module and an interaction control module, and the data simulation module extracts desired data from the business layer; and the data management module processes the sample data generated by the data simulation module and provides data support for the visual layout module and the interaction control module. The automatic drawing technology can greatly shorten the generation time of the topological graph and improve the updating speed, and the automatically generated power system topological graph can accurately reflect the latest state of the power grid.

Description

Technical Field

[0001] The present invention relates to the technical field of power grids, and in particular to a method for automatically generating a system logic topology diagram for power grid services. Background Art

[0002] In the digital planning, the need for integrated innovation around business and digital technologies is clarified, the development trends of basic and forward-looking digital technologies are closely tracked, the transformation of traditional power grids to energy Internet is accelerated, research and construction of digital twin technology applications are carried out, and synchronous technical research and development of twin reconstruction of power grid environments are promoted to achieve cross-temporal and spatial association and mapping collaboration with business platforms.

[0003] In the power grid, in order to better and intuitively display the power grid structure, a power system topology diagram will be drawn in the power grid. The power system topology diagram is a graphical representation of the automatic generation method of the system logic topology diagram for power grid business. It shows the connection method of various components in the power grid such as generators, transformers, transmission lines and loads. This topology structure not only helps to analyze the operating status of the power system and optimize energy distribution, but also can quickly locate the problem when a fault occurs.

[0004] At present, there are situations where manual drawing exists. Not only does manual drawing of topology maps take a lot of time, resulting in a slow update speed and possibly failing to timely reflect the latest status of the power grid, but there may also be omissions or errors in the manual drawing process, affecting the accuracy and reliability of the topology map. Summary of the invention

[0005] The purpose of the present invention is to provide a method for automatically generating a system logic topology diagram for power grid business, which effectively solves the problem that in the existing process of drawing a power system topology diagram, the manual drawing takes a long time and is prone to omissions or errors, affecting the accuracy and reliability of the topology diagram.

[0006] The technical solution of the present invention is as follows:

[0007] A method for automatically generating a system logic topology diagram for power grid business, including a data layer, a business layer, and a UI layer.

[0008] The first step: importing the power information data in the distribution network into the database to form a data layer;

[0009] Step 2: The business layer includes a data simulation module, a data management module, a visualization layout module and an interactive control module, and the data simulation module extracts the desired data from the business layer;

[0010] Step 3: The data management module processes the sample data generated by the data simulation module and provides data support to the visualization layout module and the interactive control module;

[0011] Step 4: the visual layout module calculates the positions of the nodes in the data management module, determines the final positions of the nodes in the layout and draws a graph to provide to the interactive control module;

[0012] Step 5: The UI layer displays the topology map generated by the mutual control module in the business layer. The UI layer provides an operation interface to the user and displays the network topology results to the user in a friendly, clear and interactive manner.

[0013] Preferably, the data layer includes an Oracle storage data simulator, and the data generated by the Oracle storage data simulator is converted into ison format through middleware and stored in MongoDB. MongoDB stores all processed data and data relationships that meet the needs of the front-end display layer.

[0014] Preferably, the data simulation module includes a data simulator, which can generate sample data simulating real-life scenarios required by the network topology visualization system. The simulated data will be stored in Oracle, which will convert the data into json format through a pattern and then store it in MongoDB. MongoDB provides an interface for adding, deleting, modifying and checking to the server and front end.

[0015] Preferably, the data management module processes the data stored in the data simulator. The module includes topological data preprocessing, that is, converting the data mode and updating it in real time, and retrieving data that meets the front-end request from MongoDB. However, the data format does not meet the requirements, so the data needs to be preprocessed. The system has the function of real-time update. When the system is running, the front end requests data from the server every 2 seconds through Aiax. If the background data changes, the merged data will update the changed data into the stored page.

[0016] Preferably, the visualization layout module includes layout algorithm optimization, D3.js library optimization and D3.js drawing of topology map, and the topology map generated by the visualization layout module needs to provide interactive functions to users.

[0017] Preferably, the interactive control module includes six parts: connection filtering, topology map expansion and contraction control, page synchronization, property modification, topology submap and traffic viewing.

[0018] Preferably, the UI layer is divided into a topology map and a property panel. The topology map is the main map for front-end visualization, which mainly draws nodes and node contact data obtained from the background. Nodes include routers, network segments, and hosts: business connections include E-Mail, SENT-MESSAGE, and Download-file. The protocol connection relationships are ICMP, DNS, FTP, and HTTP. The property panel contains detailed information on node attributes, the number of each node, and filter label flags.

[0019] Preferably, there are three types of nodes in the topology diagram, namely, routers, network segments and hosts. Routers distribute network segments, and there are multiple hosts in each network segment. There may be business connections and protocol connections between hosts. There are two types of connection relationships in the topology diagram, namely, business connection relationships (E-Mai1, SENT-MESSAGE, Download-file) and protocol connection relationships (ICMP, DNS, FTP, HTTP).

[0020] The advantages of the present invention are:

[0021] 1. The present invention uses automatic generation technology to calculate and draw based on real-time data and algorithms of the power grid, reducing interference and errors caused by human factors. The generated topology map can accurately reflect the actual situation of the power grid, which not only improves the accuracy of automatically drawn topology maps, but also the automatic generation technology can quickly generate topology maps based on real-time data of the power grid, greatly improving work efficiency. With the expansion of the scale of the power grid and the increase of data, this advantage becomes more obvious.

[0022] 2. The present invention studies a hybrid layout algorithm for visualization elements. According to the different characteristics of each system structure relationship, an appropriate layout algorithm is applied to solve the difficulty of displaying complex and diverse system structure relationships, and realizes a "one system picture" display and operation monitoring standard for panoramic penetration of the business system, thereby improving the interactive and linked interface display effect, promoting managers to clearly understand the system, and assisting in business application evaluation and governance.

[0023] 3. The present invention facilitates system managers to understand large and complex business system architectures, reduces learning costs, drives more efficient and standardized completion of system management work, reduces the complexity of integration between application systems, and provides more convenient and extensive application access and capability sharing.

[0024] 4. The present invention studies the automatic generation method of service topology. By checking a single service call chain and performing aggregate analysis on multiple call chains, it can achieve three-dimensional observation at each granularity and support efficient management of business system services. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1The system logic topology diagram of the present invention automatically generates an overall framework diagram;

[0026] Figure 2 is a flow chart of the data simulator in the present invention;

[0027] Figure 3 It is a schematic diagram of the code of the data simulator operation part in the structure of the present invention;

[0028] Figure 4 It is a data conversion flow chart in topological data preprocessing in the present invention;

[0029] Figure 5 It is a real-time update flow chart in topology data preprocessing in the present invention;

[0030] Figure 6 It is a flow chart of drawing a topology map in the visualization layout module of the present invention;

[0031] Figure 7 is a flow chart of the force-directed layout of the present invention;

[0032] Figure 8 It is the data displayed in the topological diagram of the present invention and a schematic diagram showing the form of a topological connection diagram. DETAILED DESCRIPTION

[0033] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0034] like Figures 1 to 8 As shown, the present invention provides a method for automatically generating a system logical topology diagram for power grid business, which includes a data layer, a business layer, and a UI layer.

[0035] The first step: importing the power information data in the distribution network into the database to form a data layer;

[0036] Step 2: The business layer includes a data simulation module, a data management module, a visualization layout module and an interactive control module, and the data simulation module extracts the desired data from the business layer;

[0037] Step 3: The data management module processes the sample data generated by the data simulation module and provides data support to the visualization layout module and the interactive control module;

[0038] Step 4: the visual layout module calculates the positions of the nodes in the data management module, determines the final positions of the nodes in the layout and draws a graph to provide to the interactive control module;

[0039] Step 5: The UI layer displays the topology map generated by the mutual control module in the business layer. The UI layer provides an operation interface to the user and displays the network topology results to the user in a friendly, clear and interactive manner.

[0040] It should be noted that the automatic generation technology is used to calculate and draw based on the real-time data and algorithms of the power grid, which reduces the interference and errors of human factors. The generated topology map can accurately reflect the actual situation of the power grid. It not only improves the accuracy of the automatic drawing of the topology map, but also the automatic generation technology can quickly generate the topology map according to the real-time data of the power grid, greatly improving the work efficiency. With the expansion of the scale of the power grid and the increase of data, this advantage is more obvious.

[0041] Preferably, the data layer includes an Oracle storage data simulator, and the data generated by the Oracle storage data simulator is converted into ison format through middleware and stored in MongoDB. MongoDB stores all processed data and data relationships that meet the needs of the front-end display layer.

[0042] Preferably, the data simulation module includes a data simulator, which can generate sample data simulating real-life scenarios required by the network topology visualization system. The simulated data will be stored in Oracle, which will convert the data into json format through a pattern and then store it in MongoDB. MongoDB provides an interface for adding, deleting, modifying and checking to the server and front end.

[0043] It should be noted that the data simulator is a script written in Python, which randomly deletes or modifies existing data within a certain time range and randomly generates new data, thereby driving the normal display and operation of the visualization system;

[0044] Specifically, the data simulator first simulates host detection, which simulates the network topology visualization system detecting hosts in the network, and then continues to detect the gateway where the host is located. When detecting the gateway, a dynamic icon will appear on the front-end page to represent that it is being detected, and then the route will be detected. Finally, the relationship between all hosts under the route and each host will be known. At this time, the front-end page will connect the related hosts with lines. At this time, the multiple detected routes are actually one route, and at this time, you only need to merge them;

[0045] Subsequently, the data simulator will simulate attacks, with one host attacking other hosts or multiple hosts attacking other hosts. Each attacked host will have two situations: the host has a defense system or not. When the attacked host has a defense system, the attack fails; when the attacked host does not have a defense system, the attack is successful, and this process is repeated.

[0046] The data simulator will store the data generated by the above operations in an Oracle database. Users can configure the running time interval of the data simulator, the duration of each step of the attack and defense tasks, the duration of the opening tasks, the time interval of each routing communication restoration, etc. The data simulator will update the status of the entire process from program startup to page rendering in real time, including data preparation, data preparation completion, pre-loading of hosts and network segments, dynamic addition of data, step rotation, instruction transmission tasks, file transfer tasks, added services, and completion of protocol execution.

[0047] Preferably, the data management module processes the data stored in the data simulator. The module includes topological data preprocessing, that is, converting the data mode and updating it in real time, and retrieving data that meets the front-end request from MongoDB. However, the data format does not meet the requirements, so the data needs to be preprocessed. The system has the function of real-time update. When the system is running, the front end requests data from the server every 2 seconds through Aiax. If the background data changes, the merged data will update the changed data into the stored page.

[0048] It should be noted that this module discusses topological data preprocessing and real-time update from two aspects: topological data preprocessing is to process the sample data generated in the data simulator, converting the data from Oracle format to ison format. Topological data preprocessing runs through the entire process of system operation. Ajax requests incremental data from Oracle, and topological data preprocessing occurs when incremental data exists; topological data processing also occurs when users modify attributes;

[0049] Specifically, first get all the data tables from Oracle. Each data table belongs to an object in json, and the data in the data table corresponds to the data in the json object. The data in the Oracle data table corresponds one to one with the data in MongoDB. The json format is as follows:

[0050] ″global_protocol″:{

[0051] ″table_data″:[]

[0052] }

[0053] After the data conversion is completed, the converted json data is stored in MongoDB. If it is determined that there is incremental data in Oracle, all incremental data is obtained from Oracle, and then converted and stored in MongoDB;

[0054] The real-time update function is one of the key functions of the system, because when the system is running, it will obtain various data on the network in real time. If the system cannot update the data obtained by the back-end in real time, the user cannot make correct decisions on the attack information in time, which will cause serious losses. The real-time update is mainly achieved through Ajax. By setting Ajax to send data requests to the Torando server every 2 seconds, Torando will determine which data table the data request belongs to after receiving the request, and then request the data table from Oracle. Oracle returns the data table, and the back-end will compare the obtained data with the existing data. The flter function is used here. If the data is consistent, no operation is performed. Otherwise, the data is merged and the merged data is stored in MongoDB and the cache is updated. The front-end page is rendered through D3.js and OPTFR algorithm. Data inconsistency generally occurs in two situations. One is that there is new data in the acquired data. In this case, the front-end rendering will add new nodes, relationship lines, etc. The other is that the existing data is more than the acquired data, which means that there is redundant data in the current data table. In this case, there will also be corresponding redundant information in the cache. What the front-end rendering needs to do is to eliminate the redundant information, such as deleting the node and the relationship line connected to the node.

[0055] Preferably, the visualization layout module includes layout algorithm optimization, D3.js library optimization and D3.js drawing of topology map, and the topology map generated by the visualization layout module needs to provide interactive functions to users.

[0056] It should be noted that the algorithm is a force-guided layout algorithm. The core idea of ​​the force-guided layout algorithm is Hooke's law. When the distance between two nodes is far, they show a mutual attraction relationship. When the distance reaches a certain threshold, they show a mutual repulsion relationship.

[0057] Its principle is that each node will have repulsion and attraction, there is attraction between adjacent nodes, and there is repulsion between all nodes. Once the attraction between two nodes is greater than the repulsion, the positions of the two nodes will be adjusted very close; once the repulsion between two nodes is greater than the attraction, the positions of the two nodes will be adjusted very far. In other words, the closeness of the relationship between the nodes can be seen by the distance between the nodes. If the distance is too far, it means that the relationship between the two nodes is distant, and if the distance is close, it means that the relationship between the two nodes is close. Moreover, because of the repulsion, a certain distance will be generated between the nodes, and the overlap effect between the nodes will be reduced. The force-directed graph mainly includes: charge repulsion, gravity, and friction. The charges between nodes in the topological graph are manifested as mutual repulsion to ensure that the nodes do not overlap; gravity is manifested as the farther the node is from the center of gravity, the greater the gravity, completing the relative layout of the topological graph and ensuring that the nodes are relatively compact. Friction is manifested as the energy decay rate. The greater the friction, the faster the force-directed graph stops.

[0058] The essence of the force-guided algorithm is to continuously adjust the node position according to the mechanical formula to achieve a relatively balanced state. In the chaotic stage, the layout algorithm will traverse all nodes, calculate the gravitational force of the adjacent nodes and the repulsive force of the non-adjacent nodes, and convert them into the target node position of this iteration after the calculation is completed, and then displace them. After the displacement is completed, this iteration ends. The energy of each iteration force-guided graph decays to 98%, and the calculation stops when the energy is less than 5%.

[0059] The algorithm steps are as follows:

[0060] (1) Randomly assign longitude and latitude to each node, that is, the location of the node.

[0061] (2) Calculate the displacement difference caused by the repulsive force between each node in turn.

[0062] (3) Calculate the displacement difference caused by the gravity on each edge on its two end nodes in turn.

[0063] (4) Repulsion and attraction will affect the final layout of the graph. It is related to the spacing between nodes and the position of each node in the graph, so repulsion and attraction need to be subtly adjusted during the development process.

[0064] (5) Add all the displacement differences calculated in steps (2) and (3).

[0065] (6) Repeat (2), (3), (4), and (5) until the graph reaches relative equilibrium.

[0066] The visualization layout module is a bridging module, so drawing force-directed graphs is an important part of the network topology visualization system. How to quickly and efficiently layout the data returned by the background to the front-end page is what this section considers. This section starts with optimizing the force-directed layout algorithm, optimizing the D3.js library, and D3.js drawing topology. Figure 3 Each aspect is described in detail.

[0067] D3.js draws topology map

[0068] After optimizing the layout algorithm and D3.js, you can start drawing the topology map. D3.js has a ForceLayout module, and the following layout parameters need to be set:

[0069] size: used to control the topology graph, and is used as force.size([m, n]). This method has two functions: one is to set the center of gravity, i.e. (m / 2, n / 2); the other is to set the range of node activity, i.e. between [0, m] and [0, m]. If the user does not set it, size uses the default value [1, 1].

[0070] linkDistance: used to specify the distance between links between nodes. There are two types of parameters to choose from: function and constant. If a constant is selected as a parameter, the length of each link is fixed. Otherwise, the length of the link is determined by the result of the selected function. In this case, the longitude and latitude of the source and destination nodes are calculated to obtain the link length.

[0071] linkStrength: used to specify the hardness of the connection between nodes. Its value range is 0 to 1. The larger the value, the stronger the connection. When the value is 1, dragging a node M will cause the nodes connected to M to move at the distance specified by linkDistance. When the value is 0, dragging a node M will not cause the nodes connected to M to move, and the connection will become longer.

[0072] Fiction: specifies the function value of the friction coefficient. The default value is 0.9, and it can be a number between 0 and 1. In fact, this specified value is not the friction value at the physical level. It is more like the consumption caused by the movement over time, which exists for any node. When the value is 1, there is no movement consumption, and when the value is 0, the movement consumption is the largest.

[0073] charge: specifies the gravitational force, which is also repulsive force. The default value is -30. When the value is a positive number, it indicates that the two nodes have gravitational force. The larger the value, the greater the gravitational force. When the value is a negative number, it indicates that the two nodes have repulsive force. The smaller the value, the greater the repulsive force.

[0074] chargeDistance: Specifies the range of attraction. Once the range is exceeded, the attraction fails. The default value is positive infinity.

[0075] gravity: The center of gravity specified by size will generate gravity, and each node will move toward the center of gravity. The default value is 0.1.

[0076] When the value is 0, there is no gravity at the center of gravity.

[0077] theta: If there are too many nodes, it will take a lot of time to calculate and adjust the node positions. Theta is used to limit the amount of calculation. The default value is 0.8. The larger the value, the looser the calculation amount is.

[0078] alpha: specifies the time it takes to draw. Once this time is exceeded, the drawing action stops immediately. When drawing starts, the value of alpha is 0.1, and when drawing ends, the value of alpha is 0

[0079] Preferably, the interactive control module includes six parts: connection filtering, topology map expansion and contraction control, page synchronization, property modification, topology submap and traffic viewing.

[0080] Preferably, the UI layer is divided into a topology map and a property panel. The topology map is the main map for front-end visualization, which mainly draws nodes and node contact data obtained from the background. Nodes include routers, network segments, and hosts: business connections include E-Mail, SENT-MESSAGE, and Download-file. The protocol connection relationships are ICMP, DNS, FTP, and HTTP. The property panel contains detailed information on node attributes, the number of each node, and filter label flags.

[0081] Preferably, there are three types of nodes in the topology diagram, namely, routers, network segments and hosts. Routers distribute network segments, and there are multiple hosts in each network segment. There may be business connections and protocol connections between hosts. There are two types of connection relationships in the topology diagram, namely, business connection relationships (E-Mai1, SENT-MESSAGE, Download-file) and protocol connection relationships (ICMP, DNS, FTP, HTTP).

[0082] The technical options provided in this embodiment are:

[0083] In order to achieve a harmonious display effect, the Web front-end adopts the BootStrap framework to unify the interface style and increase the aesthetics of the system. In order to achieve data visualization, the Web front-end adopts the D3.is and echarts libraries, among which D3.js can beautifully display the back-end data in the geographic topology map, and echarts builds straight line graphs, bar graphs, etc. according to the background data. In terms of selecting the Web server, the Tornado server is selected because it can respond quickly to user needs. In order to achieve asynchronous updates of web pages, dynamic partial refresh of data, and avoid page jitter, Aiax is selected. In order to achieve page synchronization and complete synchronization, WebSocket is selected. MongoDB database is used to store data. Compared with MySQL database, it has faster user access and data acquisition speed, large storage capacity, rich third-party support, and better performance. Oracle is selected to store network data generated by the data simulator. In order to achieve fast development speed, simple development, and rapid implementation of background logic functions, the background is developed in Python.

[0084] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for automatically generating a system logic topology diagram for power grid business, characterized in that: Including data layer, business layer, UI layer, The first step: importing the power information data in the distribution network into the database to form a data layer; Step 2: The business layer includes a data simulation module, a data management module, a visualization layout module and an interactive control module, and the data simulation module extracts the desired data from the business layer; Step 3: The data management module processes the sample data generated by the data simulation module and provides data support to the visualization layout module and the interactive control module; Step 4: the visual layout module calculates the positions of the nodes in the data management module, determines the final positions of the nodes in the layout and draws a graph to provide to the interactive control module; Step 5: The UI layer displays the topology map generated by the mutual control module in the business layer. The UI layer provides an operation interface to the user and displays the network topology results to the user in a friendly, clear and interactive manner.

2. The method for automatically generating a system logic topology diagram for power grid services according to claim 1, characterized in that: The data layer includes an Oracle storage data simulator. The data generated by the Oracle storage data simulator is converted into ison format through middleware and stored in MongoDB. MongoDB stores all processed data and data relationships that meet the needs of the front-end display layer.

3. The method for automatically generating a system logic topology diagram for power grid services according to claim 1, characterized in that: The data simulation module includes a data simulator, which can generate sample data for simulating real-life scenarios required by the network topology visualization system. The simulated data will be stored in Oracle, which will convert the data into json format through a pattern and then store it in MongoDB. MongoDB provides an interface for adding, deleting, modifying and checking data to the server and front end.

4. The method for automatically generating a system logic topology diagram for power grid services according to claim 3, characterized in that: The data management module processes the data stored in the data simulator. The module includes topological data preprocessing, that is, converting the data mode and updating it in real time, and taking out data that meets the front-end request from MongoDB. However, the data format does not meet the requirements, so the data needs to be preprocessed. The system has the function of real-time update. When the system is running, the front-end requests data from the server every 2 seconds through Aiax. If the background data changes, the merged data will update the changed data into the stored page.

5. The method for automatically generating a system logic topology diagram for power grid services according to claim 1, characterized in that: The visualization layout module includes layout algorithm optimization, D3.js library optimization and D3.js drawing of topology map. The topology map generated by the visualization layout module needs to provide interactive functions to users.

6. The method for automatically generating a system logic topology diagram for power grid services according to claim 1, characterized in that: The interactive control module includes six parts: connection filtering, topology map expansion control, page synchronization, attribute modification, topology sub-map and traffic viewing.

7. The method for automatically generating a system logic topology diagram for power grid services according to claim 1, characterized in that: The UI layer is divided into a topology map and a property panel. The topology map is the main visual map of the front end, which mainly draws the nodes and node contact data obtained from the background. The nodes include routers, network segments, and hosts: business connections include E-Mail, SENT-MESSAGE, and Download-file. The protocol connection relationships are ICMP, DNS, FTP, and HTTP. The property panel contains detailed information on node attributes, the number of each node, and filter label marks.

8. The method for automatically generating a system logic topology diagram for power grid services according to claim 1, characterized in that: There are three types of nodes in the topology diagram, namely routers, network segments and hosts. Routers distribute network segments, and there are multiple hosts in each network segment. There may be business connections and protocol connections between hosts. There are two types of connection relationships in the topology diagram, namely business connection relationships (E-Mai1, SENT-MESSAGE, Download-file) and protocol connection relationships (ICMP, DNS, FTP, HTTP).

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