Smart Meter Assignment via Activity Pattern Correlation
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Solution Overview
Problem
Manual assignment of intelligent meters in low-voltage networks is economically infeasible and prone to errors, especially when processing large volumes of sensor data, and is susceptible to communication channel and protocol changes.
Innovation Solution
An automated method that assigns measuring nodes to low-voltage networks by analyzing the activity patterns of intelligent meters over time, correlating them with reference meters, and using transformer data to determine network affiliation, allowing for dynamic integration and identification of sensor malfunctions or critical states without requiring sent data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual assignment of intelligent meters is performed, then accuracy of assignment can be maintained, but time consumption and cost increase significantly
Solution Approach 1:
The patent replaces the manual mechanical assignment process with an automated information processing system. The middleware automatically determines network affiliation by analyzing activity patterns from smart meters and comparing them with reference meters, eliminating manual intervention while maintaining assignment accuracy through correlation-based algorithms.
Solution Approach 2:
The system enables self-service assignment where the middleware autonomously performs the assignment task without external human assistance. The automatic determination process uses available measurement data and activity patterns to independently identify network affiliations, making the system self-sufficient for assignment operations.
2Reliability
If manual assignment of intelligent meters is performed, then assignment can be controlled, but susceptibility to errors and cost increase
Solution Approach 1:
The patent replaces manual assignment operations with an automated information processing system that eliminates human error sources. The systematic analysis of activity patterns and correlation calculations provide consistent, reproducible results without the variability and errors inherent in manual processes.
Solution Approach 2:
The system incorporates feedback mechanisms by continuously monitoring activity patterns and using correlation results to validate assignments. The automatic determination process can detect inconsistencies and adjust assignments based on pattern matching, providing built-in error detection and correction capabilities.
3Measurement precision
If data from sensors or transformers is required for assignment, then assignment accuracy may improve, but system complexity and data requirements increase
Solution Approach 1:
The patent extracts only the necessary activity pattern information from smart meter data, ignoring unnecessary detailed measurements. By focusing solely on activity patterns (presence/absence of measurements) rather than full measurement data, the system achieves assignment precision while minimizing data requirements and system complexity.
Solution Approach 2:
The system creates simplified representations (copies) of the complex measurement data in the form of activity patterns. These binary activity indicators serve as adequate substitutes for detailed measurement data, enabling assignment determination without processing the full complexity of原始 measurement information.
Data Source
Figure 1
AI summary
Method for assigning measuring nodes such as smart meters to low-voltage networks, wherein the measurement data of the smart meters to be assigned is detected over a predetermined period of time, wherein activity patterns of the meters are further determined from the detected data and wherein the activity patterns are compared with one another and an extent of the agreement is determined, and an assigning of the smart meter is specified from the extent of the agreement of the activity pattern. In this way, a simple and robust assigning of the meters is enabled.