Energy Meter Mapping Using Transformer Signal Correlation
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Solution Overview
Problem
Current methods for monitoring and controlling grid topology in power distribution networks are manual, unreliable, and fail to adapt to changes over time, such as households switching feeders or lines being connected to different transformers, leading to cumbersome and inaccurate mapping.
Innovation Solution
An autonomous method and device for mapping energy meters by correlating signals from power transformers and energy meters, using active power series data to determine connections to specific branches, allowing for automated identification and reliable tracking of transformer and feeder connections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual mapping by operators is used, then mapping can be performed with basic equipment, but the process is cumbersome, unreliable, and cannot keep up with network changes
Solution Approach 1:
The system enables autonomous mapping where the energy meter itself performs the mapping operation by detecting transformer signals and automatically determining its connection topology, eliminating the need for operator intervention and physical device consultation
Solution Approach 2:
The patent replaces manual mechanical mapping operations with automated signal processing and correlation algorithms that analyze electrical signals to determine topology, substituting human operators with computational methods
2Extent of automation
If automatic solutions using only smart meter data are used, then automation is improved, but the solutions are prone to errors and limitations due to restricted parameters
Solution Approach 1:
The patent introduces transformer signals as an intermediary element that bridges the smart meter and the grid topology, allowing the meter to indirectly detect its connection point through signal correlation without direct physical inspection
Solution Approach 2:
The system adds a new dimension of analysis by incorporating transformer-side signal measurements into the correlation process, moving beyond traditional single-point meter data to a multi-point signal comparison approach
3Loss of information
If GPS information is used for mapping, then location data is obtained, but the information is sensitive, error-prone, and requires additional assumptions about topology
Solution Approach 1:
The patent extracts location and topology information directly from electrical signal characteristics and correlation patterns, removing the dependency on external GPS data and eliminating the need for separate location tracking systems
4Reliability
If periodic assertion of topology changes is implemented, then up-to-date mapping is maintained, but continuous monitoring increases energy consumption and processing requirements
Solution Approach 1:
The system performs correlation and topology determination periodically or event-driven rather than continuously, allowing the energy meter to enter low-power states between measurements while still maintaining current topology information
Solution Approach 2:
The autonomous mapping system uses feedback from signal correlation results to determine when re-mapping is necessary, only performing full topology determination when changes are detected rather than continuously
Data Source
Figure 1~2
AI summary
The present invention is enclosed in the area of intelligent monitoring and control of the grid topology of a power distribution network. It is an object of the present invention method for the autonomous mapping of an energy meter which comprises the following steps: i) obtaining at least one signal from a power transformer, ii) obtaining at least one signal from an energy meter, iii) correlating the at least one signal from the power transformer with the at least one signal from an energy meter, thereby obtaining a correlation value, and iv) based on the correlation value, determining if said energy meter is connected to a branch fed by said power transformer. The method of the present invention thereby provides the autonomous mapping of energy meters and, as a consequence, also of the household or other kind of installation which such energy meter monitors.