Phasor Measurement Units Optimal Placement and Performance Limits for Fault Localization

Journal Article · Wed Nov 06 00:00:00 EST 2019 · IEEE Journal on Selected Areas in Communications

DOI:https://doi.org/10.1109/JSAC.2019.2951971· OSTI ID:1637305

Jamei, Mahdi ^[1]; Ramakrishna, Raksha ^[2]; Tesfay, Teklemariam ^[3]; Gentz, Reinhard ^[4]; Roberts, Ciaran ^[4]; Scaglione, Anna ^[2]; Peisert, Sean ^[4]

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1. Invenia Labs., Cambridge (UK)
2. Arizona State Univ., Tempe, AZ (United States). School of Electrical Computer and Energy Engineering
3. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Sloan School of Management
4. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

Here, the performance limits of faults localization are investigated using synchrophasor data. The focus is on a non-trivial operating regime where the number of Phasor Measurement Unit (PMU) sensors available is insufficient to have full observability of the grid state. Proposed analysis uses the Kullback Leibler (KL) divergence between the distributions corresponding to different fault location hypotheses associated with the observation model. This analysis shows that the most likely locations are concentrated in clusters of buses more tightly connected to the actual fault site akin to graph communities. Consequently, a PMU placement strategy is derived that achieves a near-optimal resolution for localizing faults for a given number of sensors. The problem is also analyzed from the perspective of sampling a graph signal, and how the placement of the PMUs i.e. the spatial sampling pattern and the topological characteristic of the grid affect the ability to successfully localize faults. To highlight the superior performance of presented fault localization and placement algorithms, the proposed strategy is applied to a modified IEEE 34, IEEE-123 bus test cases and to data from a real distribution grid. Additionally, the detection of cyber-physical attacks is also examined where PMU data and relevant Supervisory Control and Data Acquisition (SCADA) network traffic information are compared to determine if a network breach has affected the integrity of the system information and/or operations.

• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: USDOE Office of Cybersecurity, Energy Security, and Emergency Response (CESER); USDOE Office of Science (SC)
• Grant/Contract Number: AC02-05CH11231; OE0000780
• OSTI ID: 1637305
• Journal Information: IEEE Journal on Selected Areas in Communications, Journal Name: IEEE Journal on Selected Areas in Communications Journal Issue: 1 Vol. 38; ISSN 0733-8716
• Publisher: IEEE
• Country of Publication: United States
• Language: English

Related Subjects

42 ENGINEERING
Cluster detection
KL divergence
Kullback Leibler divergence
PMU placement strategy
SCADA network traffic information
circuit faults
current measurement
cyber-physical security
data acquisition network traffic information
distribution grid state
fault localization
fault location
graph signal sampling
identification
intrusion detection
modified IEEE 34 bus test cases
modified IEEE-123 bus test cases
observability
optimal PMU placement
phase measurement
phasor measurement
phasor measurement unit sensors
phasor measurement units
power distribution faults
power grids
sensors
signal sampling
spatial sampling pattern
supervisory control and data acquisition network traffic information
synchrophasor data
voltage measurement