Grid Location Analysis Using Correlation Signals
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Solution Overview
Problem
Current technologies face challenges in accurately determining the topology and operational state of electrical distribution grids due to noise, cross-talk, and limitations in data-bearing capacity, making it difficult to efficiently communicate and manage grid operations.
Innovation Solution
A system that uses a specially engineered characterizing signal, known as the GLA signal, to correlate and identify the feeder and phase of signal transmission by analyzing signals across the distribution grid, allowing for precise determination of signal origin and grid topology, while mitigating noise and interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If signal correlation analysis is performed across all feeders and phases to identify signal origin, then measurement precision of grid topology is improved, but device complexity increases due to need for analyzing multiple signal paths
Solution Approach 1:
The system segments the grid analysis by processing each feeder and phase independently through separate correlation operations, then combines results to identify the signal origin. This division into manageable segments allows precise measurement without overwhelming system complexity.
Solution Approach 2:
The patent introduces an intermediary correlation process that acts as a mediator between the received signal and the reference signal database. This intermediary correlation analysis simplifies the overall system by providing a standardized method to compare signals across multiple feeders and phases without requiring direct complex interactions between all components.
2Measurement precision
If multiple copies of transmitted signal are received due to cross-talk and reflections, then loss of information increases, but measurement precision can be improved by comparing correlation results across topology
Solution Approach 1:
The system converts the harmful effect of multiple signal copies caused by cross-talk and reflections into a beneficial measurement tool. By comparing correlation results across different feeders and phases, the system uses these multiple copies to accurately identify the original signal path and discriminate the feeder phase, transforming information loss into a precision measurement opportunity.
Solution Approach 2:
The correlation comparison process provides feedback about signal quality and origin across different feeders and phases. This feedback mechanism allows the system to identify and select the most reliable signal path while discarding degraded copies, thereby maintaining measurement precision despite the presence of multiple signal reflections.
3Measurement precision
If correlation analysis is performed in time domain with sharp correlation, then measurement precision of transmission time is improved, but difficulty of detecting and measuring increases due to noise and interference
Solution Approach 1:
The system performs preliminary correlation analysis to establish a reference pattern before attempting to detect the actual transmitted signal. This preliminary action creates a template that makes subsequent detection more robust against noise and interference, allowing sharp time-domain correlation to achieve high precision without being overwhelmed by environmental factors.
Data Source
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AI summary
A computer system at a substation of an electrical grid examines on-grid communication channels and for very channel, the system compares and correlates a GLA signal provided by a downstream transmitter on that channel to a reference GLA signal. The channel that provided the signal with the best correlation is mostly likely the channel with the transmitter. Thus, the feeder and phase of the signal can be determined from the correlation of signals.