Grid Fault Detection Using Distributed Time-Correlated Measurements
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Solution Overview
Problem
Existing electric grids face challenges in accurately detecting and localizing faults due to various environmental factors, which can affect network performance and reliability.
Innovation Solution
A system comprising grid measuring devices equipped with current and voltage sensors, which measure and analyze electrical and physical parameters, and apply predefined rules to detect and characterize faults by correlating measurements across multiple devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple grid measuring devices are deployed to improve fault detection accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system divides the electric grid into multiple monitoring zones, each equipped with independent grid measuring devices. Each device independently measures local electrical parameters (voltage, current, power) and environmental conditions, then results are aggregated for comprehensive fault detection. This segmentation enables distributed measurement precision while managing system complexity through modular architecture.
Solution Approach 2:
The system combines measurements from multiple grid measuring devices with environmental data (temperature, humidity, wind speed) and applies rule-based analysis to detect faults. By merging diverse data sources and analysis rules into a unified fault detection framework, the system achieves high measurement precision without proportionally increasing operational complexity.
2Productivity
If real-time measurements are continuously monitored to improve fault detection speed, then productivity is improved, but energy consumption increases
Solution Approach 1:
The system implements periodic measurement cycles where grid measuring devices continuously monitor electrical parameters at defined intervals rather than constant real-time sampling. Measurements are taken at regular time periods, enabling fast fault detection while reducing overall energy consumption compared to continuous uninterrupted monitoring.
Solution Approach 2:
The fault detection system automatically analyzes measurements using predefined rules and detects faults without requiring constant external intervention or processing. The system self-manages measurement collection, analysis, and fault identification, improving detection speed while minimizing the energy required for external control and processing.
3Measurement precision
If environmental parameters are measured to improve fault characterization, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The grid measuring devices are designed with multi-functionality, incorporating both electrical parameter measurement (voltage, current, power) and environmental parameter sensing (temperature, humidity, wind speed) within single integrated units. This universality enables comprehensive fault characterization through multiple measurement types without proportionally increasing device complexity, as shared hardware and processing resources serve multiple measurement functions.
Data Source
AI summary
A system for detecting a fault in an electric grid, including a plurality of grid measuring devices distributed in the electric grid, being operative to measure current and/or voltage with their respective time of occurrence, enabling a user to define at least one fault type, and at least one rule for detecting the fault type, the rule associating the fault type with at least one of the measurements, executing the measurements, and analyzing the measurements according to the rule to detect a fault.