Virtual Meter Power Quality Characterization With Dynamic Tolerance Curves
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Solution Overview
Problem
Power quality issues in electrical systems are costly and disruptive, with 80% of disturbances generated within facilities, causing significant economic losses and operational disruptions, and existing methods lack effective characterization and mitigation strategies.
Innovation Solution
The system characterizes power quality events by processing electrical measurement data from Intelligent Electronic Devices (IEDs) to generate dynamic tolerance curves, which quantify the impact of events on loads and systems, allowing for real-time monitoring and adjustment of alarm thresholds, and provides methods to reduce recovery time and economic losses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional fixed alarm thresholds are used for power quality monitoring, then the system is simple to operate, but it cannot accurately adapt to varying system conditions and load requirements, leading to false alarms or missed detections
Solution Approach 1:
The patent implements dynamic alarm thresholds that automatically adjust based on real-time system conditions, load characteristics, and historical power quality data. The thresholds transition from fixed static values to dynamic values that adapt to changing operational states, improving detection accuracy without requiring manual reconfiguration for different scenarios
Solution Approach 2:
The system incorporates feedback mechanisms that continuously monitor power quality events, system responses, and operational conditions. This feedback is used to refine and adjust alarm thresholds over time, creating a self-learning system that improves its detection accuracy while maintaining automated operation
Solution Approach 3:
The patent changes the fundamental parameter of alarm thresholds from fixed constant values to variable dynamic values that change based on system state. This parameter transformation allows the system to adapt to different operational conditions, load types, and power quality scenarios without increasing operational complexity
2Reliability
If comprehensive power quality monitoring is implemented across multiple metering points, then measurement coverage and reliability are improved, but system complexity and data processing requirements increase significantly
Solution Approach 1:
The patent divides the electrical system into multiple metering points and segments the monitoring function into distributed Intelligent Electronic Devices (IEDs). Each IED independently characterizes power quality events at its local metering point, processing data locally rather than requiring centralized processing of all system data, thus improving reliability through distributed monitoring while managing complexity through functional segmentation
Solution Approach 2:
The system introduces virtual meters as intermediary computational models that represent the electrical characteristics of metering points. These virtual meters process and correlate data from multiple physical IEDs, providing a simplified interface for system-wide power quality analysis without requiring direct complex interactions between all monitoring devices
3Measurement precision
If dynamic tolerance curves are generated and updated in real-time, then power quality event characterization precision is improved, but computational processing time and energy consumption increase
Solution Approach 1:
The system performs preliminary actions by pre-calculating baseline tolerance curves from historical power quality data and system characteristics before actual events occur. These pre-computed curves are stored and readily available for immediate comparison with real-time measurements, reducing the computational burden during actual event detection while maintaining high characterization precision
Solution Approach 2:
The patent implements partial updates to dynamic tolerance curves, updating only the portions of the curves that are affected by new data or changed conditions rather than performing complete recalculations. This selective updating approach maintains curve accuracy while significantly reducing computational energy consumption compared to full re-computation
Data Source
AI summary
A method for characterizing power quality events in an electrical system includes deriving electrical measurement data for at least one first virtual meter in an electrical system from (a) electrical measurement data from or derived from energy-related signals captured by at least one first IED in the electrical system, and (b) electrical measurement data from or derived from energy-related signals captured by at least one second IED in the electrical system. In embodiments, the at least one first IED is installed at a first metering point in the electrical system, the at least one second IED is installed at a second metering point in the electrical system, and the at least one first virtual meter is derived or located at a third metering point in the electrical system. The derived electrical measurement data may be used to generate or update a dynamic tolerance curve associated with the third metering point.