Phase-to-Ground Fault Admittance Detection in Microgrids
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Solution Overview
Problem
Existing methods for detecting electrical faults in power grids, particularly in microgrids with low spinning inertia, are inadequate as they fail to accurately sense faulted phases due to small electrical fault currents from distributed energy sources.
Innovation Solution
The implementation of a ground fault apparent (PGFA) admittance system that measures PGFA admittance magnitudes to differentiate between faulted and non-faulted phases, using phase/ground boundaries defined by total admittance and zero-sequence admittance values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If overcurrent relays are used to detect faulted phases, then fault detection is possible in microgrids with high spinning inertia, but faulted phases cannot be sensed in microgrids with low spinning inertia due to small electrical fault currents
Solution Approach 1:
The patent changes the detection parameter from current magnitude to voltage magnitude. By measuring the magnitude of voltage at each phase, the system can detect faulted phases even when fault currents are small, as voltage magnitude changes occur during phase-to-ground faults regardless of the microgrid's spinning inertia level.
Solution Approach 2:
The patent replaces the overcurrent relay mechanism with a voltage-based detection mechanism. Instead of relying on current transformers and overcurrent protection logic, the system uses voltage magnitude measurement and comparison to identify faulted phases, making it effective across different microgrid configurations.
2Measurement precision
If phase voltage and current magnitudes are measured to identify electrical faults, then fault types can be detected, but the identification process takes significant time as relays operate in latching mode with delayed activation
Solution Approach 1:
The patent implements preliminary action by continuously monitoring voltage magnitudes during normal operation and establishing baseline values. When a fault occurs, the system immediately compares the new voltage magnitudes against the pre-established baselines and boundaries, enabling rapid fault identification without waiting for relay latching delays.
Solution Approach 2:
The patent creates a simplified representation of the fault condition by measuring only voltage magnitudes rather than full waveform data. This copied information (voltage magnitude values) is sufficient for fault type identification and can be processed much faster than complete waveform analysis, reducing identification time while maintaining accuracy.
3Measurement precision
If conventional impedance measurement methods are used for fault detection, then fault location can be determined, but the methods are not accurate enough to distinguish between different fault types in microgrids with distributed energy sources
Solution Approach 1:
The patent applies local quality by focusing measurement on specific characteristics (voltage magnitude at each phase) rather than attempting to measure all possible fault parameters. By concentrating on the local property of voltage magnitude change at faulted phases, the system achieves accurate fault type discrimination with simpler measurements compared to comprehensive impedance analysis.
Data Source
AI summary
A phase to ground fault apparent (PGFA) admittance system and method with phase/ground boundaries for detecting electrical power line faults. The PGFA admittance method with phase/ground boundaries is based on measuring the A, B and C phase admittance magnitudes for faulted and non-faulted phases, resulting in greater than zero and near zero, respectively, and using the phase/ground boundaries to distinguish between the LL and LLG electrical faults. The PGFA admittance method with phase/ground boundaries is based on a pre-setting of values by using the zero, positive and negative sequences of power line sections, to determine phase and ground boundaries. The PGFA admittance algorithm with phase/ground boundaries was built with MATLAB/Simulink software and tested and evaluated with a confusion matrix. The measured and predicted values matched in more than 90% of the tests, and the PGFA admittance method presented an accuracy of 94.3% and a precision of 100%.