Automated Bellwether Smart Meter Selection via Anomaly Weighting
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The manual selection of bellwether smart grid meters is subjective and inefficient, often overlooking areas with developing power distribution problems and failing to adapt to changing load profiles and grid conditions.
Innovation Solution
A method and system for automatically selecting bellwether smart meters by monitoring anomalies, assigning weights to these anomalies, and continuously updating a subgroup of meters based on historical data and seasonal load profiles, using a network management system to prioritize and select meters that provide an overall health reading of the power grid.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual selection of bellwether meters is performed, then human judgment and flexibility are applied, but the selection becomes subjective and may overlook problematic areas
Solution Approach 1:
The patent replaces the manual mechanical selection process with an automated computer-based system that monitors smart meters and automatically identifies bellwether meters based on anomaly detection algorithms, eliminating human subjectivity while maintaining operational simplicity
Solution Approach 2:
The system enables smart meters to effectively select themselves as bellwether meters by automatically detecting their own anomalies and being identified by the monitoring system, reducing the need for manual intervention in the selection process
2Ease of manufacture
If random hand-selection of bellwether meters is performed, then implementation is simple, but the selection fails to adapt to changing load profiles and grid conditions
Solution Approach 1:
The patent implements a dynamic selection process where the system continuously monitors smart meters and automatically updates the bellwether meter list based on changing grid conditions, load profiles, and anomaly patterns, making the selection adaptive rather than static
Solution Approach 2:
The system incorporates continuous feedback loops where anomaly data from smart meters is constantly analyzed, and the bellwether meter selection is adjusted based on this feedback, enabling automatic adaptation to changing grid conditions without manual reconfiguration
3Loss of time
If manual updates of bellwether meter lists are performed at random times, then administrative effort is minimized, but the selection may overemphasize non-problematic areas and miss developing problems
Solution Approach 1:
The patent implements continuous monitoring and automatic updating of bellwether meter selections, eliminating the intermittent manual update process and ensuring that the bellwether meter list continuously reflects current grid conditions and emerging problems
Solution Approach 2:
The system performs preliminary anomaly detection and analysis on all smart meters continuously, preparing the data and identification of potential bellwether meters in advance, so that the selection is always based on current and accurate information rather than outdated manual assessments
Data Source
AI summary
A method for selection of bellwether smart meters from a plurality of smart meters in a power grid can include for at least each of a subset of the plurality of smart meters, monitoring a meter; determining at least one anomaly in the meter, in response to a determination of an anomaly in the meter, assigning a weight to the anomaly, determining a sum of weights of anomalies in the meter and selecting a sub group of the plurality of smart meters as bellwether meters.