Utility Meter Floating Neutral Detection Algorithm
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Solution Overview
Problem
Traditional electrical meters cannot effectively detect a 'floating neutral' condition, which can lead to imbalances in line-to-neutral voltages, equipment damage, and potential fire hazards, due to insufficient data and inability to measure line-to-neutral voltages.
Innovation Solution
An electric utility meter with a controller having an electronic processor and memory, configured to measure characteristics of input electricity, determine fault parameter values, calculate a confidence score, and compare it to a threshold to detect a floating neutral condition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional electrical meters are used to collect data, then the device complexity is low, but the measurement precision is insufficient to detect floating neutral conditions
Solution Approach 1:
The patent segments the floating neutral detection function into separate analytical components: measuring line-to-line voltage, measuring first and second line currents, calculating neutral impedance using specific formulas, and comparing against threshold values. This allows traditional meters to gain advanced detection capability through software algorithms rather than hardware complexity.
Solution Approach 2:
The patent replaces the need for additional physical measurement hardware (mechanical/electrical components) with computational methods. By substituting mathematical calculations and signal processing algorithms, the system achieves floating neutral detection without adding physical measurement devices, thus maintaining low device complexity while improving measurement precision.
2Reliability
If insufficient data is used for fault detection, then the ease of operation is high, but the reliability of fault detection is low
Solution Approach 1:
The patent implements feedback by continuously monitoring electrical parameters (line-to-line voltage, line currents) and using this feedback to calculate neutral impedance in real-time. The system compares the calculated impedance against predetermined threshold values and provides continuous feedback on the floating neutral status, improving detection reliability while maintaining operational simplicity through automated decision-making.
Solution Approach 2:
The patent performs preliminary actions by establishing predetermined threshold values for neutral impedance before operation. These pre-calculated thresholds enable the system to make reliable fault detection decisions based on simple comparisons during operation, combining thorough analysis with ease of operation during actual use.
3Measurement precision
If artificial faulted conditions are created to establish a baseline, then the measurement precision improves, but the loss of time increases due to impracticality
Solution Approach 1:
The patent creates a virtual model (copy) of the electrical system's normal operating conditions through mathematical calculations. By copying the relationships between voltage, current, and neutral impedance using formulated equations, the system establishes a baseline for fault detection without requiring physical creation of fault conditions, thus avoiding time loss while maintaining measurement precision.
Solution Approach 2:
The patent uses parameter changes by monitoring variations in electrical parameters (voltage, current) under normal operating conditions and comparing these changes against expected patterns. This allows the system to establish baselines through natural parameter variations during normal operation rather than requiring time-consuming artificial fault creation, achieving both precision and efficiency.
Data Source
AI summary
An electric utility meter includes a housing, an input configured on the housing that receives input electricity from an electricity source, and a controller having an electronic processor and a memory. The electronic processor is configured to measure a first characteristic and a second characteristic of the input electricity, determine a fault parameter value, calculate a confidence score corresponding to the fault parameter value, compare the confidence score to a threshold value, and determine that a fault is occurring based on the confidence score exceeding the threshold value.