Spark-Based Distribution Network Evaluation System
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for evaluating the operation of distribution networks lack real-time data authenticity and face performance bottlenecks in massive data processing, making it impossible to calculate key indicators in real time.
Innovation Solution
A method and system utilizing data capture and Spark technology, involving packet mirroring, Hadoop distributed file system storage, and Spark platform analysis to acquire and process 101/104 protocol packets, calculating key indicators such as feeder automation rates and tele-control usage rates for evaluating distribution network operations in real time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional data processing methods are used for distribution network evaluation, then system complexity is low, but real-time processing capability and data authenticity are insufficient
Solution Approach 1:
The system segments the data processing workflow into distinct modular components: packet capture module, protocol parsing module (101/104), data storage module (HDFS), and analysis module (Spark). Each module handles a specific function, enabling real-time processing while maintaining manageable system complexity through clear separation of concerns.
Solution Approach 2:
The patent introduces HDFS as an intermediary storage layer between packet capture and Spark analysis, and uses protocol parsing as an intermediary step to extract meaningful data from raw packets. These intermediary components buffer and structure data flow, enabling real-time processing without overwhelming the system.
2Quantity of substance
If massive data is processed using conventional methods, then data volume is handled, but performance bottlenecks occur and key indicators cannot be calculated in real time
Solution Approach 1:
The patent replaces conventional sequential data processing with Spark's distributed parallel processing framework. Instead of processing data through a single bottleneck, the system distributes data processing across multiple nodes simultaneously, enabling massive data volumes to be processed at high speed without performance bottlenecks.
Solution Approach 2:
The system transitions from single-node sequential processing to multi-node parallel processing by adding a spatial dimension to the processing architecture. HDFS distributes data across multiple storage nodes, and Spark processes data in parallel across compute nodes, fundamentally changing the processing dimension from linear to distributed.
3Reliability
If real-time evaluation indicators are implemented, then operational assessment capability is improved, but appropriate evaluation indicators were not previously available
Solution Approach 1:
The patent transforms raw protocol data into meaningful evaluation indicators by changing data parameters through protocol parsing (extracting 101/104 protocol fields) and statistical aggregation (calculating rates, averages, and key performance metrics). This parameter transformation enables reliable operational assessment from raw data.
Solution Approach 2:
The system automatically calculates evaluation indicators (such as automation rates, reliability metrics, and performance statistics) without manual intervention. The Spark platform self-services by reading from HDFS, processing data, and generating key indicators that directly assess distribution network operation quality.
Data Source
AI summary
The present application relates to a method for evaluating an operation of a distribution network based on data capture and Spark. The method includes: acquiring a packet from a terminal, and mirroring the packet through a mirroring port of a switch to acquire a mirror packet of the packet; analyzing the mirror packet, acquiring a 101/104 protocol packet, and storing the 101/104 protocol packet into an HDFS; acquiring the 101/104 protocol packet from the HDFS, parsing the 101/104 protocol packet on a Spark platform to acquire a parameter in the 101/104 protocol packet, and analyzing and processing the parameter to obtain a key indicator for evaluating the operation of the distribution network; and displaying the key indicator through a web page.