Distributed Intelligence for Online Situational Awareness in Power Grids
- Resource Type
- Periodical
- Authors
- Wang, S.; Li, L.; Dehghanian, P.
- Source
- IEEE Transactions on Power Systems IEEE Trans. Power Syst. Power Systems, IEEE Transactions on. 37(4):2499-2515 Jul, 2022
- Subject
- Power, Energy and Industry Applications
Components, Circuits, Devices and Systems
Phasor measurement units
Sea measurements
Power grids
Power measurement
Event detection
Intelligent sensors
Phase measurement
Feature extraction
event detection
machine learning
situational awareness
signal processing
smart sensor
synchrophasor estimation
waveform classification
- Language
- ISSN
- 0885-8950
1558-0679
This paper presents a suite of analytics that are proposed to be embedded in next-generation smart sensors in electric power grids. The proposed analytics take the electrical signals as the input and unlock the full potential in signal processing and machine learning for real-time event detection and classification. Meanwhile, a robust synchrophasor estimation mechanism is housed within the proposed sensor technology that will be triggered following a detected event and guides on the adaptive selection of the best-fit (most accurate) synchrophasor estimation algorithms at all times. Embedding such analytics within the sensor and closer to where the waveforms are captured, the proposed distributed intelligence solution technology mitigates the potential risks to communication failures and latencies as well as malicious cyber threats. Our experiments demonstrate that the introduced scheme achieves improved quality of measurements with a promising event detection and classification accuracy, collectively resulting in enhanced online situational awareness in modern power grids.