Power distribution risk visualization method and device, electronic equipment and storage medium

Abstract

The invention discloses a power distribution risk visualization method and device, electronic equipment and a storage medium. The method comprises the following steps: adaptively acquiring real-time operation data of the power distribution system through a sensor and monitoring equipment of the power distribution system, and processing the real-time operation data to obtain target operation data; evaluating the operation risk of the power distribution system according to the target operation data and a predetermined risk evaluation model to obtain a risk evaluation result; and realizing visual display of the real-time operation data and the risk assessment result through the user interface, and when an interaction event triggered by a user on the user interface is monitored, adjusting the visually displayed content. According to the technical scheme provided by the embodiment of the invention, the operation risk of the power distribution system can be accurately and comprehensively evaluated, so that a user can quickly and accurately obtain key information, and diversified requirements of the user on visual contents are met.

Description

Technical Field

[0001] The present application relates to the field of electric power technology, and in particular to a method, device, electronic device and storage medium for visualizing power distribution risks. Background Art

[0002] With the continuous expansion of the power grid and the growing demand for electricity, the complexity and operational risks of the power grid distribution system have also increased. The traditional power grid distribution management model often relies on manual inspections and regular maintenance, which is not only inefficient, but also difficult to detect and respond to potential risks in a timely manner. Especially in extreme weather, equipment aging, load mutations and other conditions, the power grid distribution system may face serious safety risks and even cause large-scale power outages, which will have a huge impact on the social economy and people's lives. At the same time, the information display method of the traditional power grid distribution system is often limited to text reports or simple charts, lacking intuitiveness and interactivity. Summary of the invention

[0003] The present application provides a distribution risk visualization method, device, electronic device and storage medium, which can accurately and comprehensively evaluate the operating risks of the distribution system, enable users to quickly and accurately obtain key information, and meet users' diverse needs for visualization content.

[0004] According to one aspect of the present application, a method for visualizing power distribution risks is provided, the method comprising:

[0005] Adaptively collecting real-time operating data of the power distribution system through sensors and monitoring equipment of the power distribution system, and processing the real-time operating data to obtain target operating data;

[0006] Assessing the operating risk of the power distribution system according to the target operating data and a predetermined risk assessment model to obtain a risk assessment result;

[0007] The real-time operation data and the risk assessment results are visualized through a user interface, and when an interactive event triggered by a user on the user interface is monitored, the content of the visualized display is adjusted.

[0008] According to another aspect of the present application, a power distribution risk visualization device is provided, the device comprising:

[0009] A target operation data determination module, used to adaptively collect real-time operation data of the power distribution system through sensors and monitoring equipment of the power distribution system, and process the real-time operation data to obtain target operation data;

[0010] A risk assessment result determination module, used to assess the operation risk of the power distribution system according to the target operation data and a predetermined risk assessment model to obtain a risk assessment result;

[0011] The power distribution risk visualization module is used to realize the visualization display of the real-time operation data and the risk assessment results through the user interface, and to adjust the content of the visualization display when monitoring the interaction events triggered by the user on the user interface.

[0012] According to another aspect of the present application, an electronic device is provided, the electronic device comprising:

[0013] at least one processor; and

[0014] a memory communicatively connected to the at least one processor; wherein,

[0015] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the power distribution risk visualization method described in any embodiment of the present invention.

[0016] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the power distribution risk visualization method described in any embodiment of the present invention when executed.

[0017] The technical solution of the embodiment of the present application is to adaptively collect the real-time operation data of the distribution system through the sensors and monitoring equipment of the distribution system, and process the real-time operation data to obtain the target operation data; evaluate the operation risk of the distribution system according to the target operation data and a predetermined risk assessment model to obtain a risk assessment result; realize the visualization of the real-time operation data and the risk assessment result through a user interface, and adjust the content of the visualization when monitoring the interactive event triggered by the user on the user interface. The technical solution of the embodiment of the present application is to evaluate the operation risk of the distribution system through a risk assessment model and real-time operation data, visualize the real-time operation data and the risk assessment result through a user interface, and provide interactive events for users to adjust the visualization content, so as to accurately and comprehensively evaluate the operation risk of the distribution system, enable users to quickly and accurately obtain key information, and meet the diverse needs of users for visualization content.

[0018] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 is a flow chart of a method for visualizing power distribution risks provided according to Embodiment 1 of the present application;

[0021] Figure 2 is a flow chart of a method for visualizing power distribution risks provided according to Embodiment 2 of the present application;

[0022] Figure 3 is a structural schematic diagram of a power distribution risk visualization device provided according to Embodiment 3 of the present application;

[0023] Figure 4 It is a structural schematic diagram of an electronic device for implementing the power distribution risk visualization method of an embodiment of the present application. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described 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, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0026] Embodiment 1

[0027] Figure 1A flow chart of a power distribution risk visualization method is provided for the first embodiment of the present application. This embodiment can be applied to the situation where the possible operation risks of the power distribution system of the power grid are visualized. The power distribution risk visualization method can be executed by a power distribution risk visualization device. The power distribution risk visualization device can be implemented in the form of hardware and / or software. The power distribution risk visualization device can be configured in an electronic device. Figure 1 As shown, the method includes:

[0028] S110, adaptively collecting real-time operation data of the power distribution system through sensors and monitoring equipment of the power distribution system, and processing the real-time operation data to obtain target operation data.

[0029] The power distribution system refers to the part of the power grid that distributes electric energy, including distribution rooms, distribution boxes, switch cabinets, transformers and other distribution equipment, as well as related control, protection and measurement devices. A sensor is a detection device that converts the detected information into electrical signals for output according to certain rules. Monitoring equipment refers to equipment that monitors and controls the equipment status of distribution equipment in the power distribution system.

[0030] Among them, real-time operation data includes key data and non-key data. Key data includes fault indication data and equipment status data, and non-key data includes current data, voltage data and temperature data. Target operation data refers to the data obtained after processing the real-time operation data, which is usually used to evaluate the operating status of the distribution system, predict potential faults of the distribution system, and optimize the resource allocation of the distribution system.

[0031] In the embodiment of the present application, current data, voltage data and temperature data can be obtained through the sensors of the power distribution system, and fault indication data and equipment status data can be obtained through the monitoring equipment of the power distribution system. Specifically, Python or C++ can be used to develop a data acquisition program, and the data sources such as various sensors, monitoring equipment and the like of the power distribution system can be communicated through the TCP / IP protocol to collect the real-time operation data of the power distribution equipment. It should be noted that, unlike the traditional fixed frequency sampling, the embodiment of the present application adopts intelligent adaptive sampling technology for adaptive acquisition when collecting the real-time operation data of the power distribution system. Specifically, the sampling frequency can be dynamically adjusted according to factors such as the load change and the equipment status of the power distribution system. For example, the sampling frequency is increased during the peak load period to capture more subtle changes, and the sampling frequency is reduced during the trough load period to save resources. By dynamically adjusting the sampling frequency, the validity of the real-time operation data can be guaranteed, and unnecessary data redundancy can be reduced. At the same time, considering the diversity of data sources in the power distribution system (such as analog signals, digital signals, video streams, etc.), the present application designs a multi-source heterogeneous data integration framework, which can automatically identify and adapt the data formats and communication protocols of different data sources to achieve unified access to real-time operation data. Afterwards, the real-time operation data is processed to obtain target operation data, and the target operation data is stored so as to facilitate the subsequent evaluation of the operation risk of the distribution system based on the target operation data.

[0032] S120: Evaluate the operating risk of the power distribution system according to the target operating data and a predetermined risk assessment model to obtain a risk assessment result.

[0033] The risk assessment model may be a machine learning model or a statistical model, such as a neural network model, a random forest model, etc. The risk assessment result may be a risk level of the operation risk of the distribution system, such as level one, level two, level three, or a calculated risk assessment score of the operation risk of the distribution system.

[0034] In an embodiment of the present application, the operating risk of the distribution system can be evaluated according to the target operating data and a predetermined risk assessment model. Specifically, an effective feature data set can be automatically generated according to the target operating data through automated feature engineering. The feature data set includes derivative feature data of the target operating data. These derivative feature data can better reflect the operating status and potential risks of the distribution system and provide strong support for subsequent risk assessment. Afterwards, in order to eliminate the influence of different dimensions and magnitudes on the risk assessment results, the feature data set can be standardized and normalized. Unlike simple linear transformations, the present application needs to select a suitable standardization or normalization method (such as Z-score standardization, Min-Max normalization, etc.) according to the data distribution characteristics in the feature data set to ensure the comparability and consistency of the data. Finally, the normalized feature data set can be input into a predetermined risk assessment model to evaluate the operating risk of the distribution system according to the risk assessment model to obtain a risk assessment result.

[0035] Optionally, the process of predetermining a risk assessment model includes: obtaining historical operating data of the distribution system from a database of the distribution system, and determining derived characteristic data corresponding to the historical operating data; wherein the derived characteristic data includes voltage fluctuation rate, current overload duration, equipment aging index, and ambient temperature change rate; and training a neural network model based on the historical operating data and the derived characteristic data to obtain a risk assessment model.

[0036] The voltage fluctuation rate refers to the ratio of the standard deviation of the voltage to the average value in each time window, and the current overload time refers to the duration of the current exceeding the set threshold. The equipment aging index is used to measure the degree to which the equipment gradually loses function or performance over time, and can be calculated based on the age of the equipment and the frequency of use. The ambient temperature change rate refers to the ratio of the ambient temperature difference between adjacent time points to the time interval.

[0037] The neural network model includes an input layer, multiple hidden layers, multiple attention layers, and an output layer. A certain number of neurons and RELU activation functions are set in the hidden layer. The attention layer is added after the hidden layer to enhance the neural network model's attention to key features. In the output layer, sigmoid, soft max, or linear activation functions can be selected according to task requirements.

[0038] In an embodiment of the present application, first, the historical operation data of the distribution system can be obtained from the database of the distribution system, and the derived feature data corresponding to the historical operation data can be determined through automated feature engineering to obtain a valid feature data set. Secondly, the feature data set is divided into a training set, a validation set, and a test set through the train-test-split function, and a random seed is set to ensure the repeatability of the results. After that, the neural network model is trained through the training set, and the parameter weights of the neural network model are updated using the small batch gradient descent method to obtain a risk assessment model. During the model training process, the Early Stopping callback can be used to monitor the loss of the neural network model on the validation set, and the training can be stopped in advance when the performance is no longer improved; the version of the neural network model can be called back using the Model Checkpoint to save the best version of the neural network model; the cross-Val-score function can be used for K-fold cross validation to evaluate the stability and generalization ability of the model on different data subsets. Finally, the performance of the risk assessment model can be evaluated through the test set, and detailed evaluation indicators can be recorded. Optionally, model explanatory tools (such as LIME, SHAP, etc.) can be introduced to improve the transparency of risk assessment model decisions.

[0039] Optionally, after training the neural network model according to the historical operating data and the derived characteristic data to obtain the risk assessment model, it also includes: performing a sensitivity analysis on the risk assessment model to determine an index value of the sensitivity of the risk assessment results to changes in various input parameters; setting targeted risk response measures according to the index value to reduce the probability of occurrence of operating risks of the distribution system.

[0040] Among them, sensitivity analysis is a method to evaluate the sensitivity of model output to changes in input parameters, which can help identify which parameters have a significant impact on risk assessment results and provide effective guidance for risk management and control. Indicators of sensitivity include sensitivity coefficient, elasticity coefficient, etc.

[0041] In an embodiment of the present application, before performing a sensitivity analysis on the risk assessment model, it is necessary to first collect and record the current risk assessment results, then adjust the input parameters, re-run the risk assessment model, collect new risk assessment results, and compare the new results with the original results to observe the impact of parameter adjustment on the risk assessment results. For example, for voltage fluctuation rate, the threshold of voltage fluctuation rate can be changed, such as adjusting the threshold from ±5% to ±10%, to observe whether the risk assessment results have changed significantly; for equipment aging index, the weights of equipment age, frequency of use, etc. in the process of calculating equipment aging index can be changed to observe whether the risk assessment results have changed significantly. In order to more accurately evaluate the sensitivity of input parameters to risk assessment results, the index value of the sensitivity of risk assessment results to changes in each input parameter can be determined to quantify the impact of input parameter changes on risk assessment results. Afterwards, the sensitive factors in the input parameters can be identified according to the indicator values, and the causes and mechanisms of the impact of these sensitive factors on the risk assessment results can be further analyzed to gain a deeper understanding of the operating laws and potential risks of the distribution system, and to set up targeted risk response measures, such as strengthening the monitoring and control of sensitive parameters to reduce the probability of operating risks of the distribution system.

[0042] S130: Visually display the real-time operation data and risk assessment results through the user interface, and adjust the content of the visual display when monitoring the interactive events triggered by the user on the user interface.

[0043] Among them, the user interface is an interface for users to obtain visual information and adjust the visual information through interactive events, and can be developed using Web front-end technology (such as HTML5, CSS3, JavaScript, etc.). Optionally, the process of developing a user interface using Web front-end technology is as follows: 1. Create a new folder locally or on a server as a workspace for the project. 2. In the project folder, create index.html as the main page file and write a basic HTML structure. 3. In the project folder, create a styles.css file and write a style to complete the page design. 4. In the project folder, create a script.js file and write JavaScript code to implement interactive events and chart drawing. Among them, interactive events include at least one of filtering, zooming, and drilling. Drilling usually refers to clicking on a part of the chart to view more detailed information or data.

[0044] In an embodiment of the present application, real-time operation data and risk assessment results can be displayed in a graphical manner through a user interface so that users can quickly and accurately obtain key information. Optionally, the change trend of the operation data can be obtained through historical operation data and real-time operation data, and the change trend can also be displayed in a graphical manner through the user interface. Optionally, the real-time voltage and current values ​​of each node of the distribution system can be displayed on the user interface, and the risk level can be marked with different colors (such as high-risk areas are highlighted in red). At the same time, the user interface also provides rich interactive functions through interactive events, such as filtering, zooming, and drilling, so that users can adjust the content of the visual display by triggering interactive events, and then have a deep understanding of specific content to meet the different needs of users.

[0045] The technical solution of the embodiment of the present application is to adaptively collect the real-time operation data of the distribution system through the sensors and monitoring equipment of the distribution system, and process the real-time operation data to obtain the target operation data; evaluate the operation risk of the distribution system according to the target operation data and a predetermined risk assessment model to obtain the risk assessment result; realize the visualization of the real-time operation data and the risk assessment result through the user interface, and adjust the content of the visualization when monitoring the interactive events triggered by the user on the user interface. The technical solution of the embodiment of the present application is to evaluate the operation risk of the distribution system through the risk assessment model and the real-time operation data, visualize the real-time operation data and the risk assessment result through the user interface, and provide interactive events for the user to adjust the visualization content, so as to accurately and comprehensively evaluate the operation risk of the distribution system, enable the user to quickly and accurately obtain key information, and meet the user's diverse needs for visualization content.

[0046] Embodiment 2

[0047] Figure 2 This is a flow chart of a method for visualizing power distribution risks provided in the second embodiment of the present application. The present embodiment is optimized based on the above embodiment. For solutions not described in detail in the present embodiment, please refer to the above embodiment. Figure 2 As shown, the method includes:

[0048] S210, adaptively collecting real-time operation data of the power distribution system through sensors and monitoring equipment of the power distribution system, and processing the real-time operation data to obtain target operation data.

[0049] Optionally, the real-time operation data includes critical data and non-critical data, the critical data includes fault indication data and equipment status data, and the non-critical data includes current data, voltage data and temperature data; the real-time operation data is processed to obtain target operation data, including: dynamically adjusting a preset threshold according to the real-time load changes of the power distribution system, and removing noise and outliers in the real-time operation data according to the preset threshold through a data cleaning algorithm; after removing the noise and outliers, losslessly compressing the critical data and lossily compressing the non-critical data to obtain the target operation data.

[0050] In the embodiment of the present application, considering that the operating status of the power distribution system is dynamically changing, therefore, before removing the noise and outliers in the real-time operation data according to the preset threshold, the preset threshold can be dynamically adjusted according to the real-time load change of the power distribution system to ensure the accuracy and adaptability of detecting outliers when removing outliers in the real-time operation data. After that, the noise and outliers in the real-time operation data can be removed according to the preset threshold by the data cleaning algorithm. Specifically, time series analysis techniques, such as seasonal decomposition (STL), isolation forest and other algorithms, can be used to perform anomaly detection on the collected real-time operation data. These algorithms can identify outliers that deviate significantly from normal values ​​and improve the accuracy and efficiency of data cleaning. After removing noise and outliers, key data (such as fault indication data, equipment status data, etc.) can be losslessly compressed to ensure the integrity of key data, and non-key data (such as current data, voltage data, and temperature data, etc.) can be losslessly compressed to reduce storage space occupancy, and the compressed real-time operation data can be used as target operation data.

[0051] S220: Evaluate the operating risk of the power distribution system according to the target operating data and a predetermined risk assessment model to obtain a risk assessment result.

[0052] S230. Draw display charts corresponding to the real-time operation data and risk assessment results through an integrated chart library, and display the display charts through a user interface.

[0053] In an embodiment of the present application, a display chart corresponding to the real-time operation data and the risk assessment results can be drawn through an integrated chart library. The display chart can be a pie chart, a line chart, a histogram, etc., and the display chart is displayed through a user interface. Optionally, the change trend of the operation data can be obtained through historical operation data and real-time operation data, and the change trend can also be displayed through the user interface in the form of a display chart. By drawing display charts corresponding to the real-time operation data and the risk assessment results and displaying them through the user interface, the user can have a more intuitive understanding of the real-time operation data and the risk assessment results, and it is convenient for the user to quickly and accurately obtain key information.

[0054] S240: When monitoring a user operating an interactive control on the user interface, adjust the visually displayed content according to an interactive event corresponding to the interactive control.

[0055] Among them, interactive controls include filter controls, zoom controls and drill controls. Filter controls include drop-down selection boxes, multiple-selection boxes and input boxes, etc. Zoom controls include sliders, zoom buttons, etc. Drill controls include clickable elements in display charts, such as columns in bar charts, data points in line charts, etc.

[0056] In an embodiment of the present application, a corresponding event listener can be bound to an interactive control on the user interface, and when the event listener detects that a user operates an interactive control on the user interface, the visually displayed content is adjusted according to the interactive event corresponding to the interactive control to meet the user's diverse needs for visual content.

[0057] Optionally, when it is detected that a user operates an interactive control on the user interface, the content of the visual display is adjusted according to the interactive event corresponding to the interactive control, including: when it is detected that a user changes the filter conditions in the filter box, determining the data that meets the conditions according to the changed filter conditions, and redrawing the display chart for display; when it is detected that a user clicks or slides a zoom control, determining the zoom parameters according to the user operation, and zooming the display chart according to the zoom parameters; when it is detected that a user clicks on a clickable element in the display chart, obtaining relevant information of the clicked element, and updating the display chart according to the relevant information.

[0058] In an embodiment of the present application, for the filter control, a corresponding event listener is bound to each input element of the filter box. When the user changes the filter condition, the event listener will immediately capture the event and trigger the corresponding processing function. The processing function will obtain the filter condition selected by the user and filter the corresponding data set according to the filter condition. The filter method of the array or more complex logic can be used here to ensure the accuracy and efficiency of the screening. After the screening is completed, the display chart is redrawn according to the filtered data through the integrated chart library. In some cases, it may be necessary to obtain the filtered data from the back end. At this time, AJAX or Fetch API can be used to send a request to the back end and receive the returned data. In order to improve performance, the browser's Local Storage or Session Storage can also be used to cache part of the data to reduce the number of requests to the back end.

[0059] For the zoom control, bind a slide or click event listener to the zoom control. When the user operates the zoom control, the event listener will immediately capture the event and determine the zoom parameters, such as the zoom ratio and zoom area, based on the user's operation, and call the zoom method of the chart library (such as the data Zoom component) to zoom the display chart. It should be noted that zooming may change the layout and display of elements such as the coordinate axis and data points of the display chart. During the zooming process, performance bottlenecks may be encountered. To solve this problem, you can use Canvas rendering, which has better performance when processing large amounts of data. At the same time, before performing the zooming operation, you can pre-process the relevant data, such as calculating the average, maximum, and minimum values ​​of the data, so that these data can be quickly obtained during the zooming process.

[0060] For drill controls, click event listeners are bound to clickable elements on the display chart (such as columns in a bar chart, data points in a line chart, etc.). When a user clicks on a clickable element on the display chart, the click event listener captures the event and obtains relevant information about the clicked element, such as data value, data category, etc. After that, a drill request can be sent to the backend using AJAX or Fetch API based on the relevant information of the clicked element. After receiving the request, the backend will query the database based on the parameters in the request and return more detailed data to the frontend. After receiving the data, the frontend will first process the data, such as parsing JSON, converting the format, etc., and then call the update method of the chart library to draw the new data on the display chart. It should be noted that in order to implement the drill function, a reasonable data model needs to be designed in the database to ensure that the relationship between the data is clear and easy to query, which usually involves foreign key associations between multiple tables, index optimization, etc. In order to ensure smooth communication between the front and back ends and the accuracy of the data, a clear communication protocol needs to be formulated, including request format, response format, error handling, etc.

[0061] S250. Set a warning threshold according to the risk assessment result, and when the real-time operation data exceeds the warning threshold, generate a warning message and send it to the corresponding operation and maintenance personnel, so that the operation and maintenance personnel can handle the operation risk according to the user authority; wherein the user authority is adjusted through the background management interface.

[0062] Among them, user authority information can be adjusted through the background management interface, such as adding, deleting and modifying the user authority information stored in the database through the background management interface to achieve role-based access control and ensure that different users can only access data within their authority. In addition, the system configuration stored in the database can also be adjusted through the background management interface to ensure the safe and stable operation of the distribution system.

[0063] In an embodiment of the present application, after obtaining the risk assessment results, an early warning threshold can be set according to the risk assessment results, and when the real-time operation data exceeds the early warning threshold, an early warning message is automatically generated, such as "Node XX has a high risk level, please check immediately", and the early warning message is sent to the corresponding operation and maintenance personnel through an integrated notification service in a variety of ways (such as email, SMS, Slack, etc.), so that the operation and maintenance personnel can handle the operation risk according to user permissions. By automatically generating early warning information when the real-time operation data exceeds the early warning threshold, and sending it to the corresponding operation and maintenance personnel through multiple channels, timely response and effective disposal of abnormal situations can be ensured to avoid the expansion of accidents and reduce accident losses.

[0064] The technical solution of the embodiment of the present application is to adaptively collect the real-time operation data of the distribution system through the sensors and monitoring equipment of the distribution system, and process the real-time operation data to obtain the target operation data; evaluate the operation risk of the distribution system according to the target operation data and the predetermined risk assessment model to obtain the risk assessment result; draw the display chart corresponding to the real-time operation data and the risk assessment result through the integrated chart library, and display the display chart through the user interface; when the user operates the interactive control on the user interface, adjust the content of the visual display according to the interactive event corresponding to the interactive control; set the warning threshold according to the risk assessment result, and when the real-time operation data exceeds the warning threshold, generate warning information and send it to the corresponding operation and maintenance personnel, so that the operation and maintenance personnel can handle the operation risk according to the user authority; wherein the user authority is adjusted through the background management interface. The technical solution of the embodiment of the present application is to evaluate the operation risk of the distribution system through the risk assessment model and the real-time operation data, visualize the real-time operation data and the risk assessment result in the form of a display chart through the user interface, and provide interactive events for users to adjust the visualization content, so as to accurately and comprehensively evaluate the operation risk of the distribution system, enable users to quickly and accurately obtain key information, and meet the diverse needs of users for visualization content. At the same time, when the real-time operating data exceeds the warning threshold, warning information is automatically generated and sent to the corresponding operation and maintenance personnel, which can ensure timely response and effective handling of abnormal situations, avoid the expansion of accidents, and reduce accident losses.

[0065] Embodiment 3

[0066] Figure 3 This is a schematic diagram of the structure of a power distribution risk visualization device provided in Example 3 of the present application. Figure 3 As shown, the device comprises:

[0067] The target operation data determination module 310 is used to adaptively collect the real-time operation data of the power distribution system through the sensors and monitoring equipment of the power distribution system, and process the real-time operation data to obtain the target operation data;

[0068] A risk assessment result determination module 320 is used to assess the operation risk of the power distribution system according to the target operation data and a predetermined risk assessment model to obtain a risk assessment result;

[0069] The power distribution risk visualization module 330 is used to realize the visualization of the real-time operation data and the risk assessment results through the user interface, and to adjust the content of the visualization when monitoring the interaction events triggered by the user on the user interface.

[0070] Optionally, the real-time operation data includes critical data and non-critical data, the critical data includes fault indication data and equipment status data, and the non-critical data includes current data, voltage data and temperature data; the target operation data determination module 310 includes:

[0071] A data cleaning unit, configured to dynamically adjust a preset threshold value according to a real-time load change of the power distribution system, and remove noise and abnormal values ​​in the real-time operation data according to the preset threshold value through a data cleaning algorithm;

[0072] The data compression unit is used to perform lossless compression on the key data and lossy compression on the non-key data after removing noise and outliers, so as to obtain target operation data.

[0073] Optionally, the risk assessment result determination module 320 includes:

[0074] A derived characteristic data determination unit, used to obtain historical operation data of the power distribution system from a database of the power distribution system, and determine derived characteristic data corresponding to the historical operation data; wherein the derived characteristic data includes voltage fluctuation rate, current overload duration, equipment aging index and ambient temperature change rate;

[0075] The risk assessment model determination unit is used to train the neural network model according to the historical operation data and the derived feature data to obtain a risk assessment model.

[0076] Optionally, the risk assessment result determination module 320 further includes:

[0077] A sensitivity analysis unit, used to perform sensitivity analysis on the risk assessment model to determine an index value of the sensitivity of the risk assessment result to changes in each input parameter;

[0078] The risk response measure setting unit is used to set targeted risk response measures according to the indicator value to reduce the probability of occurrence of operation risk of the power distribution system.

[0079] Optionally, the power distribution risk visualization module 330 includes:

[0080] A visualization display unit, used to draw display charts corresponding to the real-time operation data and the risk assessment results through an integrated chart library, and display the display charts through a user interface;

[0081] The visualization adjustment unit is used to adjust the visually displayed content according to the interactive event corresponding to the interactive control when monitoring the user operating the interactive control on the user interface.

[0082] Optionally, the interaction event includes at least one of filtering, zooming, and drilling; and the visualization adjustment unit includes:

[0083] The filter subunit is used to determine the data that meets the conditions according to the changed filter conditions when monitoring the user to change the filter conditions in the filter box, and redraw the display chart for display;

[0084] A zoom subunit, for determining a zoom parameter according to the user operation when monitoring a user clicking or sliding the zoom control, and performing zoom processing on the display chart according to the zoom parameter;

[0085] The drilling sub-unit is used to obtain relevant information of the clicked element when monitoring that the user clicks on the clickable element in the display chart, and update the display chart according to the relevant information.

[0086] Optionally, the device further comprises:

[0087] The risk warning module is used to set a warning threshold according to the risk assessment results, and when the real-time operation data exceeds the warning threshold, generate warning information and send it to the corresponding operation and maintenance personnel, so that the operation and maintenance personnel can handle the operation risk according to user permissions; wherein, the user permissions are adjusted through the background management interface.

[0088] The power distribution risk visualization device provided in the embodiment of the present application can execute the power distribution risk visualization method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0089] Embodiment 4

[0090] Figure 4 A schematic diagram of an electronic device 10 that can be used to implement an embodiment of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0091] like Figure 4As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0092] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0093] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the power distribution risk visualization method.

[0094] In some embodiments, the power distribution risk visualization method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the power distribution risk visualization method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the power distribution risk visualization method in any other appropriate manner (e.g., by means of firmware).

[0095] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0096] Computer programs for implementing the methods of the present application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0097] In the context of the present application, a computer readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device or equipment. A computer readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer readable storage medium may be a machine readable signal medium. A more specific example of a machine readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0098] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0099] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0100] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0101] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this application can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document is not limited here.

[0102] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of this application.

Claims

1. A method for visualizing power distribution risks, characterized in that: The method comprises: Adaptively collecting real-time operating data of the power distribution system through sensors and monitoring equipment of the power distribution system, and processing the real-time operating data to obtain target operating data; Assessing the operating risk of the power distribution system according to the target operating data and a predetermined risk assessment model to obtain a risk assessment result; The real-time operation data and the risk assessment results are visualized through a user interface, and when an interactive event triggered by a user on the user interface is monitored, the content of the visualized display is adjusted.

2. The method according to claim 1, characterized in that The real-time operation data includes critical data and non-critical data, the critical data includes fault indication data and equipment status data, and the non-critical data includes current data, voltage data and temperature data; Processing the real-time operation data to obtain target operation data includes: Dynamically adjusting a preset threshold value according to the real-time load change of the power distribution system, and removing noise and abnormal values ​​in the real-time operation data according to the preset threshold value through a data cleaning algorithm; After removing noise and outliers, the key data is losslessly compressed and the non-key data is losslessly compressed to obtain target operating data.

3. The method according to claim 1, characterized in that The process of pre-determining the risk assessment model includes: Acquire historical operation data of the power distribution system from a database of the power distribution system, and determine derived characteristic data corresponding to the historical operation data; wherein the derived characteristic data includes voltage fluctuation rate, current overload duration, equipment aging index, and ambient temperature change rate; The neural network model is trained according to the historical operation data and the derived feature data to obtain a risk assessment model.

4. The method according to claim 3, characterized in that After the neural network model is trained according to the historical operation data and the derived feature data to obtain the risk assessment model, the method further includes: Conducting a sensitivity analysis on the risk assessment model to determine the index value of the sensitivity of the risk assessment results to changes in various input parameters; Targeted risk response measures are set according to the indicator value to reduce the probability of occurrence of operation risks of the power distribution system.

5. The method according to claim 1, characterized in that Implementing a visual display of the real-time operation data and the risk assessment results through a user interface, and adjusting the content of the visual display when an interactive event triggered by a user on the user interface is monitored, including: Draw the display charts corresponding to the real-time operation data and the risk assessment results through an integrated chart library, and display the display charts through a user interface; When it is monitored that the user operates the interactive control on the user interface, the visually displayed content is adjusted according to the interactive event corresponding to the interactive control.

6. The method according to claim 5, characterized in that The interaction event includes at least one of filtering, zooming, and drilling; When monitoring a user operating an interactive control on the user interface, adjusting the visually displayed content according to the interactive event corresponding to the interactive control includes: When the user changes the filter conditions in the filter box, the data that meets the conditions is determined according to the changed filter conditions, and the display chart is redrawn for display; When monitoring that the user clicks or slides the zoom control, determining the zoom parameter according to the user operation, and performing zoom processing on the display chart according to the zoom parameter; When monitoring that a user clicks on a clickable element in the display chart, relevant information of the clicked element is obtained, and the display chart is updated according to the relevant information.

7. The method according to claim 1, characterized in that The method further comprises: A warning threshold is set according to the risk assessment result, and when the real-time operation data exceeds the warning threshold, a warning message is generated and sent to the corresponding operation and maintenance personnel, so that the operation and maintenance personnel can handle the operation risk according to the user authority; wherein the user authority is adjusted through the background management interface.

8. A power distribution risk visualization device, characterized in that: The device comprises: A target operation data determination module, used to adaptively collect real-time operation data of the power distribution system through sensors and monitoring equipment of the power distribution system, and process the real-time operation data to obtain target operation data; A risk assessment result determination module, used to assess the operation risk of the power distribution system according to the target operation data and a predetermined risk assessment model to obtain a risk assessment result; The power distribution risk visualization module is used to realize the visualization display of the real-time operation data and the risk assessment results through the user interface, and to adjust the content of the visualization display when monitoring the interaction events triggered by the user on the user interface.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the power distribution risk visualization method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the power distribution risk visualization method according to any one of claims 1 to 7 when executed.

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