Power Quality Indicator Using Worst-Event Selection
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Solution Overview
Problem
Existing power quality monitoring systems often miss deleterious events due to summation of measurements and weighting factors, which can allow anomalies to be masked, and may incorrectly consider undesirable conditions as normal over time.
Innovation Solution
A system that monitors power quality by selecting the worst observed event over both short and long intervals, with user-programmable weighting factors to emphasize or de-emphasize the impact of each electrical characteristic, using detectors, data selectors, and display components to provide a composite power quality indicator.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If summation of measurements and assigned quality values is used to determine overall power quality, then an aggregate indication of power quality is provided, but individual deleterious events may be masked and missed
Solution Approach 1:
The system segments the power quality assessment by maintaining separate tracked values for each electrical characteristic (voltage sags, swells, harmonics, etc.) rather than immediately aggregating them. Each characteristic is evaluated independently through its own detector and weighting factor application, allowing individual events to be identified and highlighted before being incorporated into the overall power quality indicator.
2Duration of action of stationary object
If statistical analysis over extended periods is used to determine normal power quality, then long-term trends are captured, but recent critical events may be averaged out and accepted as normal
Solution Approach 1:
The system dynamically adjusts the influence of historical data versus recent events through the decay factor mechanism. Recently detected power quality events are assigned higher weights and have greater impact on the current power quality indicator, while older events gradually decay in influence. This dynamic weighting ensures that recent critical events remain visible in the assessment rather than being completely averaged out by long-term statistical analysis.
3Adaptability or versatility
If multiple electrical characteristics are monitored simultaneously, then comprehensive power quality assessment is achieved, but complexity of monitoring and analysis increases
Solution Approach 1:
The system transforms multiple complex electrical characteristic measurements into a simplified standardized scale through the use of weighting factors and normalization. Each detected electrical characteristic (voltage sags, swells, harmonics, flicker, etc.) is converted into a comparable numerical value on a consistent scale, allowing diverse parameters to be aggregated into a single power quality indicator without requiring complex analysis of each individual parameter.
4Ease of operation
If weighting factors are applied to control relative importance of measurements, then prioritization of critical characteristics is achieved, but risk of masking anomalies through improper weighting increases
Solution Approach 1:
The system incorporates operator feedback through the graphical user interface that displays the power quality indicator and allows adjustment of weighting factors. When operators observe that certain events are being masked or that the indicator does not reflect actual system conditions, they can adjust the weighting factors to better prioritize critical characteristics. This feedback loop ensures that weighting factors remain appropriate and do not mask important anomalies.
Data Source
AI summary
A system and method of indicating power quality in an electric power system that generates an indication of power quality reflective of the worst observed power quality event over both a short and a long interval of time in which each component of the indicator is weighted by a user programmable factor to control its relative influence.