Meter-to-Transformer Mapping Using Distance and Correlation
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Solution Overview
Problem
Utility providers face inaccuracies in mapping electrical meters to transformers, leading to issues during power outages and maintenance, as current methods rely on incomplete and unreliable human-recorded data.
Innovation Solution
A system utilizing a central utility controller to receive and adjust meter-to-transformer mappings by analyzing data from electrical meters, applying similarity measures and distance-based assignments to iteratively refine connections, ensuring compliance with predefined constraints and maximizing correlations between meter statistics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If field personnel manually map meters to transformers, then the process is simple and quick to implement, but the mapping accuracy deteriorates to only 80%-90%
Solution Approach 1:
The system enables self-service by allowing meters to automatically determine their own transformer connections through data analysis and correlation algorithms, eliminating the need for manual field personnel mapping while achieving near-100% accuracy
Solution Approach 2:
The patent replaces the mechanical/manual process of field personnel physically mapping meters to transformers with an automated electronic system that uses data correlation, statistical analysis, and algorithmic determination to establish connections with superior accuracy
2Measurement precision
If automated data analysis is used to determine meter-transformer connections, then mapping accuracy is improved to near 100%, but the computational complexity and processing time increase
Solution Approach 1:
The system performs preliminary actions by continuously collecting and pre-processing operational data from meters and transformers, so that when mapping determination is needed, the analysis can be performed quickly using already-prepared data sets and correlation metrics
Solution Approach 2:
The patent employs parameter changes by adjusting correlation thresholds, data sampling rates, and analysis depth dynamically based on system conditions, allowing the system to achieve high accuracy while optimizing processing time through adaptive parameter tuning
3Measurement precision
If iterative random analysis is performed on all meters, then connection accuracy is enhanced, but the computational load and processing duration increase significantly
Solution Approach 1:
The system applies partial action by performing iterative random analysis selectively on subsets of meters rather than all meters simultaneously, using statistical sampling and progressive refinement to achieve high overall accuracy while maintaining processing efficiency through controlled partial analysis
Solution Approach 2:
The patent implements periodic action by conducting iterative analysis in cycles or batches rather than continuously, allowing the system to process meters in structured intervals with intermediate results being validated and refined over multiple periodic passes, balancing accuracy with processing efficiency
Data Source
AI summary
A utility distribution including a number of electrical meters, a number of transformers, and a central utility controller. The central utility controller is configured to receive an initial map of the number of electrical meters to their respective transformers, receive data from the number of electrical meters, and execute an initial adjustment to the initial map by verifying that each electrical meter and transformer complies with a predefined constraint. The central utility controller is further configured to randomly analyze a first meter of the number of electrical meters to determine a first likely connection to a first transformer of the number of transformers and update a connection of the first meter to the first transformer in the initial map based on the determined first likely connection.