Distribution Network Risk Identification via Multi-Source Data Analysis
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Solution Overview
Problem
Conventional power grid risk assessment methods lack diversity in data sources, relevance between models and data, and fail to provide actionable insights for risk cause and source identification, limiting effective risk prevention and control measures.
Innovation Solution
A distribution network risk identification system that acquires multi-source information data, processes it using methods like evidence theory and neural networks, calculates risk indices, and performs analogue simulations to determine risk severity and location, providing comprehensive early warning information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional probability-statistics-based risk assessment methods are used, then overall risk level can be reflected, but risk cause and source identification capability is limited
Solution Approach 1:
The patent segments the risk assessment process into multiple independent modules: data acquisition module, data processing module, risk identification module, and risk source location module. Each module handles specific aspects of risk analysis, allowing detailed tracking of risk characteristics through temporal and spatial dimensions while maintaining overall system reliability.
Solution Approach 2:
The patent introduces temporal and spatial dimensions to traditional risk assessment by analyzing the temporal variation rules and spatial distribution characteristics of risk characteristics. This multi-dimensional approach enables identification of risk causes and sources while maintaining accurate risk level assessment.
2Measurement precision
If multi-source information data is acquired and processed, then risk identification accuracy is improved, but system complexity increases
Solution Approach 1:
The system divides complex data processing into distinct modules: data acquisition from multiple sources, data processing with specific algorithms, risk identification through calculated indices, and risk source location through temporal-spatial analysis. This segmentation manages complexity while improving accuracy.
Solution Approach 2:
The patent creates a universal risk identification system that can process multiple types of data sources (monitoring systems, PMS, external environmental data) through a unified processing framework, reducing overall system complexity despite handling diverse inputs.
3Reliability
If conventional risk assessment systems are implemented, then macro-level risk evaluation is achieved, but micro-level risk source identification is difficult
Solution Approach 1:
The patent adds temporal and spatial dimensions to risk analysis, examining how risk characteristics vary over time and space. This enables the system to trace risks back to specific sources and locations while maintaining macro-level risk evaluation capabilities.
Solution Approach 2:
The system separates macro-level risk evaluation functions from micro-level risk source identification functions into distinct processing stages, allowing each to optimize for its specific purpose while working together within the unified system.
Data Source
AI summary
A distribution network risk identification system and method and a computer storage medium include: multi-source information data for risk identification is acquired; the multi-source information data is analyzed and processed to obtain a risk characteristic; a risk identification index is calculated on the basis of the risk characteristic, and a state of a power grid is determined according to the risk identification index; a temporal and spatial variation rule and variation trend of the risk characteristic are analyzed; a location and cause of occurrence of a risk are determined according to the temporal and spatial variation rule and variation trend of the risk characteristic; a severity of the risk is analyzed by adopting an analogue simulation manner; and the severity of the risk is assessed, and risk early warning information is issued on the basis of an assessment result.