Electric power data analysis and display method and device and storage medium
By encapsulating analysis using the strategy pattern, collecting and integrating power data, and generating and displaying analysis results, the problem of poor scalability in the power system is solved, enabling rapid response to business needs and in-depth insights, and improving the system's flexibility and maintainability.
Patent Information
- Application Number
- CN202511750507.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-26
- Publication Date
- 2026-03-03
AI Technical Summary
In existing power system data display and management, the system has poor scalability, requires frequent modification of core code, has a single analytical perspective, and is difficult to support comprehensive decision-making needs that are cross-domain, correlated, and traceable, thus restricting the intelligent operation and maintenance and management of new power systems.
The analysis is encapsulated using the Strategy Pattern. By collecting multimodal power data, fusing it into target data and writing it into a distributed data lake, the analysis results are generated using the Strategy Pattern analysis engine cluster and uniformly displayed to the client, thus decoupling the data analysis logic from the core of the business system.
It enables rapid response to changes in business needs, shortens the iteration cycle of analysis functions to the hour/minute level, improves system scalability and maintainability, and provides in-depth insights and intelligent decision support.
Smart Images
Figure CN121597865A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of electric power technology, and in particular relates to a method, device and storage medium for analyzing and displaying electric power data. Background Technology
[0002] In current power system data integration and analysis scenarios, data display and management mostly adopt traditional Web (web page) architecture and business reporting tools.
[0003] A typical framework is based on the MVC (Model-View-Controller) framework. The backend implements data ETL (extraction, transformation, and loading) and aggregation calculations through customized coding, while the frontend relies on basic chart libraries (such as ECharts and D3.js) for static visualization rendering.
[0004] At the data management level, various indicators, tasks, and demonstration zone data are usually stored in independent relational databases, and data services are provided to the front end through predefined fixed APIs (Application Programming Interfaces).
[0005] When various indicators, tasks, and demonstration zone business are iterated, developers have to frequently modify the core code, resulting in poor system scalability. Summary of the Invention
[0006] In view of this, the present invention provides a method, device and storage medium for analyzing and displaying power data, so as to improve the scalability of power analysis and display systems.
[0007] The first aspect of the present invention provides a method for analyzing and displaying power data, comprising:
[0008] Collect raw power data from multiple modes and fuse the raw power data into target power data;
[0009] Write the target power data into a distributed data lake;
[0010] The strategy component in the strategy pattern analysis engine cluster is invoked to generate analysis results using the target power data in the distributed data lake based on the analysis strategy in the strategy configuration database. The analysis results are then written into the unified analysis result database.
[0011] The analysis results from the unified analysis results database are sent to the client for display.
[0012] Optionally, the step of collecting raw power data from multiple modalities and fusing the raw power data into target power data includes:
[0013] The raw power data is periodically retrieved from the task management database by calling the interface through the data acquisition agent.
[0014] Raw power data can be collected from the demonstration zone management database by subscribing to channels in the message queue through streaming data services, calling interfaces or parsing logs, and collecting raw power data from the indicator management database through change data capture.
[0015] The raw power data is preprocessed;
[0016] If preprocessing is completed, the original power data is aligned in time and space to obtain the target power data.
[0017] Optionally, the strategy component in the strategy pattern analysis engine cluster generates analysis results using the target power data in the distributed data lake based on the analysis strategy in the strategy configuration database, including:
[0018] The calculation instructions are triggered by the timer scheduler and distributed to the indicator calculation service in the strategy pattern analysis engine set.
[0019] The indicator calculation service extracts the target power data from the distributed data lake according to the indicator calculation strategy in the strategy configuration database, and uses the target power data to calculate key power indicators.
[0020] Optionally, the strategy component in the strategy pattern analysis engine cluster generates analysis results using the target power data in the distributed data lake based on the analysis strategy in the strategy configuration database, including:
[0021] The task evaluation service in the analysis engine listens to the target power data in the distributed data lake. When a change in the target power data in the distributed data lake is detected, the actual progress of the task is calculated using the target power data. The actual progress is compared with the planned progress of the task to obtain progress comparison information. Based on the progress comparison information and other indicators of the task, a task evaluation result is generated.
[0022] Optionally, the strategy component in the strategy pattern analysis engine cluster generates analysis results using the target power data in the distributed data lake based on the analysis strategy in the strategy configuration database, including:
[0023] The calculation instructions are triggered by a timer and distributed to the demonstration area scoring service in the strategy pattern analysis engine set.
[0024] The demonstration zone scoring service aggregates target power data within a preset time period from the distributed data lake according to the demonstration zone evaluation strategy in the strategy configuration database, and uses the aggregated target power data to generate a comprehensive score and technology application report for the demonstration zone within the time period.
[0025] Optionally, sending the analysis results from the unified analysis results database to the client for display includes:
[0026] The analysis results from the unified analysis results database are pushed to the client via a real-time push service to update the view components based on the type field in the analysis results.
[0027] Optionally, if the type field is indicator update, it means that the view component of a chart updates the indicator panel corresponding to the analysis result;
[0028] If the type field is a task health alarm, it means that the view component of task monitoring will issue an alarm for the task corresponding to the analysis result in the task list and update the health status icon.
[0029] If the type field is a demonstration area score, it means that the view component of the demonstration area monitoring displays a summary of the comprehensive score and technology application report in the analysis results.
[0030] Optionally, it also includes:
[0031] Receive the query request generated by the client when it receives the analysis results;
[0032] The analysis results adapted to the query request from the unified analysis results database are sent to the client for display.
[0033] The query request is written into the user interaction log through the behavior analysis platform;
[0034] The strategy optimization service updates the analysis strategy in the strategy configuration database based on the user interaction logs.
[0035] A second aspect of the present invention provides an apparatus for analyzing and displaying power data, comprising:
[0036] The power data generation module is used to collect raw power data from multiple modes and fuse the raw power data into target power data.
[0037] The power data storage module is used to write the target power data into a distributed data lake;
[0038] The power data analysis module is used to call the strategy component in the strategy pattern analysis engine cluster to generate analysis results using the target power data in the distributed data lake according to the analysis strategy in the strategy configuration database, and write the analysis results into the unified analysis result database.
[0039] The analysis result sending module is used to send the analysis results from the unified analysis result database to the client for display.
[0040] Optionally, the power data generation module is further configured to:
[0041] The raw power data is periodically retrieved from the task management database by calling the interface through the data acquisition agent.
[0042] Raw power data can be collected from the demonstration zone management database by subscribing to channels in the message queue through streaming data services, calling interfaces or parsing logs, and collecting raw power data from the indicator management database through change data capture.
[0043] The raw power data is preprocessed;
[0044] If preprocessing is completed, the original power data is aligned in time and space to obtain the target power data.
[0045] Optionally, the power data analysis module is further used for:
[0046] The calculation instructions are triggered by the timer scheduler and distributed to the indicator calculation service in the strategy pattern analysis engine set.
[0047] The indicator calculation service extracts the target power data from the distributed data lake according to the indicator calculation strategy in the strategy configuration database, and uses the target power data to calculate key power indicators.
[0048] Optionally, the power data analysis module is further used for:
[0049] The task evaluation service in the analysis engine listens to the target power data in the distributed data lake. When a change in the target power data in the distributed data lake is detected, the actual progress of the task is calculated using the target power data. The actual progress is compared with the planned progress of the task to obtain progress comparison information. Based on the progress comparison information and other indicators of the task, a task evaluation result is generated.
[0050] Optionally, the power data analysis module is further used for:
[0051] The calculation instructions are triggered by a timer and distributed to the demonstration area scoring service in the strategy pattern analysis engine set.
[0052] The demonstration zone scoring service aggregates target power data within a preset time period from the distributed data lake according to the demonstration zone evaluation strategy in the strategy configuration database, and uses the aggregated target power data to generate a comprehensive score and technology application report for the demonstration zone within the time period.
[0053] Optionally, the analysis result sending module is further configured to:
[0054] The analysis results from the unified analysis results database are pushed to the client via a real-time push service to update the view components based on the type field in the analysis results.
[0055] Optionally, if the type field is indicator update, it means that the view component of a chart updates the indicator panel corresponding to the analysis result;
[0056] If the type field is a task health alarm, it means that the view component of task monitoring will issue an alarm for the task corresponding to the analysis result in the task list and update the health status icon.
[0057] If the type field is a demonstration area score, it means that the view component of the demonstration area monitoring displays a summary of the comprehensive score and technology application report in the analysis results.
[0058] Optionally, it also includes:
[0059] A query request receiving module is used to receive a query request generated by the client when it receives the analysis results.
[0060] The query result sending module is used to send the analysis results adapted to the query request from the unified analysis result database to the client for display.
[0061] The user interaction log generation module is used to write the query request into the user interaction log through the behavior analysis platform;
[0062] The analysis strategy update module is used to update the analysis strategy in the strategy configuration database based on the user interaction logs through the strategy optimization service.
[0063] A third aspect of the present invention provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for analyzing and displaying power data as described in the first aspect above.
[0064] A fourth aspect of the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method for analyzing and displaying power data as described in the first aspect above.
[0065] The fifth aspect of the present invention provides a computer program product that, when run on a computer, causes the computer to perform the method for analyzing and displaying power data as described in the first aspect above.
[0066] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:
[0067] In this embodiment, raw power data from multiple modalities is collected and fused into target power data. This target power data is then written into a distributed data lake. The strategy component in the strategy pattern analysis engine cluster is invoked to generate analysis results using the target power data from the distributed data lake, based on the analysis strategies in the strategy configuration database. These results are then written into a unified analysis result database and sent to the client for display. This embodiment uses the strategy pattern to encapsulate analysis, decoupling data analysis logic from the core business system. When adding a new indicator calculation rule or adjusting the demonstration area evaluation model, only the strategy component in the strategy pattern analysis engine cluster and the analysis strategies in the strategy configuration database need to be configured, avoiding modification of the core code of the business system. This allows for rapid response to changes in business requirements, shortening the development cycle of analysis function iterations from weeks / days to hours / minutes, offering high flexibility and effectively improving scalability and maintainability. Attached Figure Description
[0068] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0069] Figure 1 This is a schematic diagram of a method for analyzing and displaying power data provided in an embodiment of the present invention;
[0070] Figure 2 This is a schematic diagram of the structure of a power data analysis and display system provided in an embodiment of the present invention;
[0071] Figure 3 This is a schematic diagram of another method for analyzing and displaying power data provided in an embodiment of the present invention;
[0072] Figure 4 This is a schematic diagram of an electrical data analysis and display device provided in an embodiment of the present invention;
[0073] Figure 5 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation
[0074] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of the present invention. However, those skilled in the art will recognize that the present application may be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted to avoid unnecessary detail that could obscure the description of the present application.
[0075] The technical solution of the present invention will be illustrated below through specific embodiments.
[0076] Current data visualization platforms for new power systems suffer from core flaws such as data silos, superficial analysis, and static presentation. Frequent modifications to the core code are required for iterative updates to various indicators, tasks, and demonstration zone operations, resulting in poor system scalability. The presentation layers are mostly composed of separate tables and charts, lacking deep data linkage and interactive responses between views. This leads to a singular analytical perspective, making it difficult to support comprehensive decision-making needs involving cross-domain, correlation, and traceability. This has become a key technical bottleneck restricting the intelligent operation and maintenance management of new power systems.
[0077] The technical solution in this invention is an automated data processing and intelligent analysis pipeline executed collaboratively by multiple machines and services. It is applicable to the fields of macro-level situational awareness of new power systems, full-process monitoring of tasks, evaluation of demonstration zone construction achievements, and refined management of core indicator systems. This system, as a core decision support platform, is deployed on cloud infrastructure to automatically process and integrate multi-dimensional heterogeneous data from power grid management platforms, project management platforms, demonstration zone construction indicators, and various business databases. Its core objective is to address the technical deficiencies caused by isolated data sources, single analytical dimensions, and static and rigid displays, which prevent dynamic understanding of the overall construction status of new power systems from macro to micro levels, intelligent assessment and early warning of key tasks and demonstration zone progress, and the inability to perform linked source-tracing analysis of multi-dimensional indicators.
[0078] Reference Figure 1 The diagram illustrates a method for analyzing and displaying power data according to an embodiment of the present invention, which may specifically include the following steps:
[0079] Step 101: Collect raw power data from multiple modes and fuse the raw power data into target power data.
[0080] In this embodiment, raw power data of multiple modes can be collected from multiple channels and fused into unified target power data.
[0081] like Figure 2 As shown, in one channel, the data acquisition agent can automatically call the API interface at a preset frequency (such as every 5 minutes) to periodically pull the task list from the task management database, and pull the raw power data of the latest progress according to the list of personnel.
[0082] For example, the original power data is {"task_id": "T-007", "name": "Virtual power plant construction", "progress": 85, "milestone": "Second phase acceptance completed"}.
[0083] In another channel, raw power data can be obtained by subscribing to channels (such as Kafka) in a message queue via streaming data services, calling interfaces, or parsing logs (CDC) to collect real-time data streams from the demonstration zone management database. Additionally, raw power data can be obtained by collecting batch update messages from the indicator management database through change data capture.
[0084] For example, the raw current data collected from the demonstration zone management database is {"zone_id": "Demo-Z01", "solar_power_kw": 1250.7, "grid_frequency_hz": 50.01}.
[0085] Raw power data from different sources and in different formats are input into the data fusion processing engine, which performs various preprocessing steps on the raw power data to standardize it.
[0086] If preprocessing is completed, the original power data will be aligned in time and space (e.g., all original power data will be labeled with region ID: Demo-Z01 and timestamp: 1736789123456) to make the original power data correlated and form a unified fused data model to obtain the target power data.
[0087] Step 102: Write the target power data into the distributed data lake.
[0088] like Figure 2 As shown, the raw power data will be written into the distributed data lake to output the target power data, awaiting further analysis.
[0089] Step 103: Invoke the strategy component in the strategy pattern analysis engine cluster to generate analysis results using the target power data in the distributed data lake based on the analysis strategy in the strategy configuration database, and write the analysis results into the unified analysis results database.
[0090] In this embodiment, the strategy pattern analysis engine cluster has one or more strategy components and a strategy configuration database. The strategy configuration database stores one or more analysis strategies, and the strategy components can be associated with one or more analysis strategies. Both can be added, modified, and deleted according to business needs.
[0091] The strategy component in the strategy pattern analysis engine cluster can pull the required target power data from the distributed data lake according to the analysis strategy in the strategy configuration database, analyze the target power data according to the same analysis strategy, generate analysis results, and write the analysis results into an external unified analysis result database.
[0092] In one example, such as Figure 2 As shown, the strategy component includes a graph-based indicator calculation service, and the analysis strategy includes an indicator calculation strategy.
[0093] In this example, a timer schedules calculation instructions to be triggered periodically (e.g., every 15 minutes) and distributed to the metric calculation service in the strategy pattern analysis engine set.
[0094] The indicator calculation service extracts the required target power data from the distributed data lake according to the indicator calculation strategy in the strategy configuration database. The target power data is used to calculate key power indicators (such as the penetration rate of new energy and the self-sufficiency rate of clean energy in demonstration areas), and the key power indicators are written into the unified analysis results database.
[0095] For example, the execution index calculation strategy Calc_CleanEnergySelfSufficiency queries the data lake for the current total power generation and total power consumption of the Demo-Z01 demonstration area, and calculates the self-sufficiency rate (1250.7 kW / 980.2 kW)·100%=127.6%.
[0096] In another example, such as Figure 2 As shown, the strategy component includes a task evaluation service, and the analysis strategy includes a task evaluation strategy. Since the task evaluation service is used to assess the health of tasks, it can also be called a task health assessment service.
[0097] In this example, a computation command is triggered by a timer and distributed to the task evaluation service in the policy pattern analysis engine set.
[0098] The task evaluation service, centralized through the strategy pattern analysis engine, monitors the target power data required in the distributed data lake according to the task evaluation strategy in the strategy configuration database. When a change in the target power data required in the distributed data lake is detected, the actual progress of the task is calculated using the target power data. The actual progress is compared with the planned progress of the task to obtain progress comparison information. Based on the progress comparison information and other indicators of the task, a task evaluation result is generated to characterize the health of the task. The task evaluation result is then written into the unified analysis result database.
[0099] For example, when an update to the progress field (target power data) of task T-007 is detected, the task evaluation policy Eval_TaskHealth is automatically triggered. According to the task evaluation policy Eval_TaskHealth, the rule engine is called to compare the task's planned progress (e.g., 90%) with the task's actual progress (85%), and combine other related indicators of the task (e.g., whether the related demonstration area indicators have been met) to generate the task evaluation result {"status": "warning", "message": "Progress is slightly delayed"}.
[0100] In yet another example, such as Figure 2 As shown, the strategy components include a demonstration zone scoring service, and the analysis strategy includes a demonstration zone evaluation strategy.
[0101] The calculation instructions are triggered periodically by the timer (e.g., at 00:00 on the 1st of each month), and then distributed to the demonstration area scoring service in the strategy pattern analysis engine.
[0102] The demonstration zone scoring service aggregates target power data for a preset time period (such as the previous month) from the distributed data lake according to the demonstration zone evaluation strategy configured in the strategy database. Using the aggregated target power data, a multi-dimensional scoring algorithm (such as the weighted comprehensive scoring method) is used to generate a comprehensive score and technology application report for the demonstration zone within the time period. The comprehensive score and technology application report of the demonstration zone are then written into the unified analysis results database.
[0103] Of course, the above-described strategy components and their analysis strategies are merely examples. When implementing this embodiment, other strategy components and their analysis strategies can be set according to actual circumstances, and this embodiment does not impose any limitations on this. Furthermore, in addition to the above-described strategy components and their analysis strategies, those skilled in the art can also employ other strategy components and their analysis strategies as needed, and this embodiment does not impose any limitations on this either.
[0104] The strategy pattern analysis engine cluster in this embodiment, with its unified multidimensional data model and integrated OLAP (Online Analytical Processing) engine for BI (Business Intelligence) tools, places previously isolated power data such as indicators, tasks, and demonstration areas under a unified analysis framework. It can automatically perform cross-domain data correlation, drill-down, and slicing analysis, enabling root cause localization and impact analysis of complex business problems (such as abnormal indicators caused by task delays) from a technical perspective. It upgrades data analysis from passive, static descriptive statistics to proactive, dynamic diagnostic analysis, providing unprecedented depth of insight for operation and maintenance decisions, thereby realizing data-driven deep correlation analysis and intelligent decision support.
[0105] Step 104: Send the analysis results from the unified analysis results database to the client for display.
[0106] In this embodiment, as Figure 2 As shown, the real-time push service (WebSocket Server Cluster) establishes WebSocket connections with online clients (such as web browsers and large-screen terminals).
[0107] When the real-time push service (WebSocket Server Cluster) detects changes in the data (i.e., analysis results) in the unified analysis results database, it encapsulates the changed data (i.e., analysis results) into a new data packet (e.g., {"type": "indicator_update", "data": {"id": "self_sufficiency", "value": 127.6, "zone":"Demo-Z01"}}). This data packet is then actively and in real-time pushed to the corresponding client (machine) on the front end (e.g., a machine with the necessary permissions and that has subscribed to the data) via an established WebSocket connection. The client parses the data packet and renders the changed data (i.e., analysis results) onto the user interface (UI) for display to the user.
[0108] In the specific implementation, the analysis results in the unified analysis results database are pushed to the client through the real-time push service (WebSocket Server Cluster) to update the view components on the user interface (UI) according to the type field in the analysis results. The view components include "One Chart" view, "Task Monitoring" view, "Demonstration Zone Monitoring" view, "Indicator Control" view, etc.
[0109] Furthermore, when the client receives the pushed data packet (i.e., message), its internal rendering engine automatically drives the corresponding view components on the user interface (UI) to update based on the type field in the data packet, thus achieving automatic refresh.
[0110] In one example, if the type field is indicator_update, it means that the view component of a chart updates the indicator panel corresponding to the analysis results. The updated objects include the indicator panel's values, status colors, etc.
[0111] If the type field is task_health_alert, it means that the view component of task monitoring will issue an alert (such as highlighting or flashing) for the task corresponding to the analysis results in the task list and update the corresponding health status icon.
[0112] If the type field is "demo_zone_score", it means that the view component (also known as the display card) for demonstration zone monitoring displays the comprehensive score and summary of the technology application report of the demonstration zone in the analysis results, thereby filling the comprehensive score and summary of the technology application report of the demonstration zone into the view component representing demonstration zone monitoring.
[0113] Of course, the above-described method of displaying analysis results is merely an example. When implementing this embodiment, other methods of displaying analysis results can be set according to actual circumstances, and this embodiment does not impose any limitations on this. Furthermore, in addition to the above-described method of displaying analysis results, those skilled in the art can also adopt other methods of displaying analysis results according to actual needs, and this embodiment does not impose any limitations on this either.
[0114] This embodiment ensures the high performance and reliability of the system in processing massive amounts of data. By adopting a microservice architecture and a unified stream and batch data processing pipeline, components such as data ingestion, real-time processing, batch computing, and analysis services are decoupled into independently deployed and elastically scalable services. This enables the system to efficiently and stably handle massive, high-concurrency, and multimodal data streams in new power system scenarios. From an architectural perspective, it guarantees the real-time nature of data analysis, the high reliability of computing tasks, and the overall fault tolerance of the system, avoiding system unavailability due to single points of failure or resource bottlenecks.
[0115] In this embodiment, raw power data from multiple modalities is collected and fused into target power data. This target power data is then written into a distributed data lake. The strategy component in the strategy pattern analysis engine cluster is invoked to generate analysis results using the target power data from the distributed data lake, based on the analysis strategies in the strategy configuration database. These results are then written into a unified analysis result database and sent to the client for display. This embodiment uses the strategy pattern to encapsulate analysis, decoupling data analysis logic from the core business system. When adding a new indicator calculation rule or adjusting the demonstration area evaluation model, only the strategy component in the strategy pattern analysis engine cluster and the analysis strategies in the strategy configuration database need to be configured, avoiding modification of the core code of the business system. This allows for rapid response to changes in business requirements, shortening the development cycle of analysis function iterations from weeks / days to hours / minutes, offering high flexibility and effectively improving scalability and maintainability.
[0116] Reference Figure 3 The diagram illustrates another method for analyzing and displaying power data provided by an embodiment of the present invention, which may specifically include the following steps:
[0117] Step 301: Collect raw power data from multiple modes and fuse the raw power data into target power data.
[0118] Step 302: Write the target power data into the distributed data lake.
[0119] Step 303: Invoke the strategy component in the strategy pattern analysis engine cluster to generate analysis results using the target power data in the distributed data lake according to the analysis strategy in the strategy configuration database, and write the analysis results into the unified analysis results database.
[0120] Step 304: Send the analysis results from the unified analysis results database to the client for display.
[0121] Step 305: Receive the query request generated by the client when it receives the analysis results.
[0122] Step 306: Send the analysis results adapted to the query request from the unified analysis results database to the client for display.
[0123] In this embodiment, when a user performs an operation on the client's user interface (such as clicking on a demonstration area in "A Picture" to filter), the operation is captured and a machine-readable query request (such as GET / api / demo-zones / Z01 / details) is generated. This request is sent to the server through the API gateway, thereby triggering a new round of data acquisition and analysis. The analysis results adapted to the query request in the unified analysis result database are sent to the client for display, realizing interactive-driven deep drilling.
[0124] Step 307: Write the query request into the user interaction log through the behavior analysis platform.
[0125] Step 308: Update the analysis strategies in the strategy configuration database based on user interaction logs using the strategy optimization service.
[0126] like Figure 2 As shown, user actions (i.e. query requests) are written into user interaction logs through the behavior analysis platform. The accumulated user interaction logs are used for data mining. The strategy optimization service updates the analysis strategies in the strategy configuration database based on the user interaction logs, thereby continuously improving the accuracy of the analysis strategies in the strategy configuration database.
[0127] This embodiment provides an efficient and immersive interactive data insight experience. Through multi-view collaboration and linkage technology based on a unified data model, it achieves real-time data synchronization and rendering updates for multiple views, including a single overview, indicator dashboards, and 3D digital twins. It ensures that user interactions (such as clicking or filtering) in any view instantly trigger the recalculation and visualization update of global data, achieving "what you point to is what you get" real-time interactive analysis. This reduces the operational complexity and time cost of multi-dimensional data exploration for users, and improves the efficiency and immersiveness of information acquisition.
[0128] It should be noted that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
[0129] Reference Figure 4 The diagram illustrates a power data analysis and display device according to an embodiment of the present invention, which may specifically include the following modules:
[0130] The power data generation module 401 is used to collect raw power data from multiple modes and fuse the raw power data into target power data.
[0131] The power data storage module 402 is used to write the target power data into a distributed data lake;
[0132] The power data analysis module 403 is used to call the strategy component in the strategy pattern analysis engine cluster to generate analysis results using the target power data in the distributed data lake according to the analysis strategy in the strategy configuration database, and write the analysis results into the unified analysis result database.
[0133] The analysis result sending module 404 is used to send the analysis results from the unified analysis result database to the client for display.
[0134] In one embodiment of the present invention, the power data generation module 401 is further configured to:
[0135] The raw power data is periodically retrieved from the task management database by calling the interface through the data acquisition agent.
[0136] Raw power data can be collected from the demonstration zone management database by subscribing to channels in the message queue through streaming data services, calling interfaces or parsing logs, and collecting raw power data from the indicator management database through change data capture.
[0137] The raw power data is preprocessed;
[0138] If preprocessing is completed, the original power data is aligned in time and space to obtain the target power data.
[0139] In one embodiment of the present invention, the power data analysis module 403 is further configured to:
[0140] The calculation instructions are triggered by the timer scheduler and distributed to the indicator calculation service in the strategy pattern analysis engine set.
[0141] The indicator calculation service extracts the target power data from the distributed data lake according to the indicator calculation strategy in the strategy configuration database, and uses the target power data to calculate key power indicators.
[0142] In another embodiment of the present invention, the power data analysis module 403 is further configured to:
[0143] The task evaluation service in the analysis engine listens to the target power data in the distributed data lake. When a change in the target power data in the distributed data lake is detected, the actual progress of the task is calculated using the target power data. The actual progress is compared with the planned progress of the task to obtain progress comparison information. Based on the progress comparison information and other indicators of the task, a task evaluation result is generated.
[0144] In yet another embodiment of the present invention, the power data analysis module 403 is further configured to:
[0145] The calculation instructions are triggered by a timer and distributed to the demonstration area scoring service in the strategy pattern analysis engine set.
[0146] The demonstration zone scoring service aggregates target power data within a preset time period from the distributed data lake according to the demonstration zone evaluation strategy in the strategy configuration database, and uses the aggregated target power data to generate a comprehensive score and technology application report for the demonstration zone within the time period.
[0147] In one embodiment of the present invention, the analysis result sending module 404 is further configured to:
[0148] The analysis results from the unified analysis results database are pushed to the client via a real-time push service to update the view components based on the type field in the analysis results.
[0149] In one embodiment of the present invention, if the type field is indicator update, it means that the view component of a graph updates the indicator panel corresponding to the analysis result;
[0150] If the type field is a task health alarm, it means that the view component of task monitoring will issue an alarm for the task corresponding to the analysis result in the task list and update the health status icon.
[0151] If the type field is a demonstration area score, it means that the view component of the demonstration area monitoring displays a summary of the comprehensive score and technology application report in the analysis results.
[0152] In one embodiment of the present invention, it further includes:
[0153] A query request receiving module is used to receive a query request generated by the client when it receives the analysis results.
[0154] The query result sending module is used to send the analysis results adapted to the query request from the unified analysis result database to the client for display.
[0155] The user interaction log generation module is used to write the query request into the user interaction log through the behavior analysis platform;
[0156] The analysis strategy update module is used to update the analysis strategy in the strategy configuration database based on the user interaction logs through the strategy optimization service.
[0157] The present invention provides a power data analysis and display device, which can realize the steps in the aforementioned power data analysis and display method embodiments.
[0158] It should be noted that the module division in the various power data analysis and display devices provided in the above embodiments is illustrative and only represents a logical functional division. In actual implementation, other division methods may also be used. Furthermore, the functional modules in the various embodiments of this invention can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.
[0159] If the integrated module is implemented as a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the technical solution of the embodiments of the present invention can be embodied in the form of a computer program product, which is stored in a computer storage medium and includes several instructions to cause an electronic device or processor to execute all or part of the steps of the methods in the various embodiments of the present invention. The aforementioned computer storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0160] Furthermore, the power data analysis and display device and the power data analysis and display method provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.
[0161] Reference Figure 5 The diagram illustrates an electronic device according to an embodiment of the present invention. Figure 5 As shown, the electronic device in this embodiment of the invention includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps in the above-described embodiment of the power data analysis and display method. Alternatively, when the processor executes the computer program, it implements the functions of each module in the above-described embodiment of the power data analysis and display device.
[0162] For example, the computer program may be divided into one or more modules, which are stored in the memory and executed by the processor to complete this application. The one or more modules may be a series of computer program instruction segments capable of performing a specific function, which can be used to describe the execution process of the computer program in the electronic device.
[0163] The electronic device may be a desktop computer, a cloud server, or other computing device. The electronic device may include, but is not limited to, a processor and memory. Those skilled in the art will understand that... Figure 5 This is merely one example of an electronic device and does not constitute a limitation on the electronic device. It may include more or fewer components than illustrated, or combine certain components, or different components. For example, the electronic device may also include input / output devices, network access devices, buses, etc.
[0164] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.
[0165] The memory can be an internal storage unit of the electronic device, such as a hard drive or RAM. Alternatively, it can be an external storage device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, etc. Furthermore, the memory can include both internal and external storage units. The memory is used to store the computer program and other programs and data required by the electronic device. The memory can also be used to temporarily store data that has been output or will be output.
[0166] This invention also discloses an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the power data analysis and display method as described in the foregoing embodiments.
[0167] This invention also discloses a computer-readable storage medium storing a computer program that, when executed by a processor, implements the power data analysis and display method as described in the foregoing embodiments.
[0168] This invention also discloses a computer program product that, when run on a computer, causes the computer to execute the power data analysis and display methods described in the foregoing embodiments.
[0169] The embodiments described above are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.
Claims
1. A method for analyzing and displaying power data, characterized in that, include: Collect raw power data from multiple modes and fuse the raw power data into target power data; Write the target power data into a distributed data lake; The strategy component in the strategy pattern analysis engine cluster is invoked to generate analysis results using the target power data in the distributed data lake based on the analysis strategy in the strategy configuration database. The analysis results are then written into the unified analysis result database. The analysis results from the unified analysis results database are sent to the client for display.
2. The method according to claim 1, characterized in that, The process of collecting raw power data from multiple modalities and fusing the raw power data into target power data includes: The raw power data is periodically retrieved from the task management database by calling the interface through the data acquisition agent. Raw power data can be collected from the demonstration zone management database by subscribing to channels in the message queue through streaming data services, calling interfaces or parsing logs, and collecting raw power data from the indicator management database through change data capture. The raw power data is preprocessed; If preprocessing is completed, the original power data is aligned in time and space to obtain the target power data.
3. The method according to claim 1, characterized in that, The strategy component in the call strategy pattern analysis engine cluster generates analysis results using the target power data in the distributed data lake based on the analysis strategy in the strategy configuration database, including: The calculation instructions are triggered by the timer scheduler and distributed to the indicator calculation service in the strategy pattern analysis engine set. The indicator calculation service extracts the target power data from the distributed data lake according to the indicator calculation strategy in the strategy configuration database, and uses the target power data to calculate key power indicators.
4. The method according to claim 1, characterized in that, The strategy component in the call strategy pattern analysis engine cluster generates analysis results using the target power data in the distributed data lake based on the analysis strategy in the strategy configuration database, including: The task evaluation service in the analysis engine listens to the target power data in the distributed data lake. When a change in the target power data in the distributed data lake is detected, the actual progress of the task is calculated using the target power data. The actual progress is compared with the planned progress of the task to obtain progress comparison information. Based on the progress comparison information and other indicators of the task, a task evaluation result is generated.
5. The method according to claim 1, characterized in that, The strategy component in the call strategy pattern analysis engine cluster generates analysis results using the target power data in the distributed data lake based on the analysis strategy in the strategy configuration database, including: The calculation instructions are triggered by a timer and distributed to the demonstration area scoring service in the strategy pattern analysis engine set. The demonstration zone scoring service aggregates target power data within a preset time period from the distributed data lake according to the demonstration zone evaluation strategy in the strategy configuration database, and uses the aggregated target power data to generate a comprehensive score and technology application report for the demonstration zone within the time period.
6. The method according to claim 1, characterized in that, The step of sending the analysis results from the unified analysis result database to the client for display includes: The analysis results from the unified analysis results database are pushed to the client via a real-time push service to update the view components based on the type field in the analysis results.
7. The method according to claim 6, characterized in that, If the type field is indicator update, it means that the view component of a chart updates the indicator panel corresponding to the analysis result; If the type field is a task health alarm, it means that the view component of task monitoring will issue an alarm for the task corresponding to the analysis result in the task list and update the health status icon. If the type field is a demonstration area score, it means that the view component of the demonstration area monitoring displays a summary of the comprehensive score and technology application report in the analysis results.
8. The method according to any one of claims 1-7, characterized in that, Also includes: Receive the query request generated by the client when it receives the analysis results; The analysis results adapted to the query request from the unified analysis results database are sent to the client for display. The query request is written into the user interaction log through the behavior analysis platform; The strategy optimization service updates the analysis strategy in the strategy configuration database based on the user interaction logs.
9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method for analyzing and displaying power data as described in any one of claims 1-8.
10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for analyzing and displaying power data as described in any one of claims 1-8.