TY - GEN
T1 - Online Thevenin parameter tracking using synchrophasor data
AU - Jamei, Mahdi
AU - Scaglione, Anna
AU - Roberts, Ciaran
AU - McEachern, Alex
AU - Stewart, Emma
AU - Peisert, Sean
AU - McParland, Chuck
N1 - Funding Information:
This research was supported in part by the Director, Office of Electricity Delivery and Energy Reliability, Cybersecurity for Energy Delivery Systems program, of the U.S. Department of Energy, under contracts DE-AC02-05CH11231 and DEOE0000780. Any opinions, and findings expressed in this material are those of the authors and do not necessarily reflect those of the sponsors.). M. Jamei and A. Scaglione are with the School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ, USA. Emails: {mjamei, ascaglio}@asu.edu. C. Roberts, E. Stewart, S. Peisert, and C. McParland are with the Lawrence Berkeley National Laboratory, Berkeley, CA, USA. Emails: {cmroberts, estewart, sppeisert, cpmcparland}@lbl.gov. A. McEachern is the CEO of the Power Standards Lab, Alameda, CA, USA. Email: Alex@McEachern.com.
Publisher Copyright:
© 2017 IEEE.
PY - 2018/1/29
Y1 - 2018/1/29
N2 - There is significant interest in smart grid analytics based on phasor measurement data. One application is estimation of the Thevenin equivalent model of the grid from local measurements. In this paper, we propose methods using phasor measurement data to track Thevenin parameters at substations delivering power to both an unbalanced and balanced feeder. We show that for an unbalanced grid, it is possible to estimate the Thevenin parameters at each instant of time using only instantaneous phasor measurements. For balanced grids, we propose a method that is well-suited for online applications when the data is highly temporally-correlated over a short window of time. The effectiveness of the two methods is tested via simulation for two use-cases, one for monitoring voltage stability and the other for identifying cyber attackers performing 'reconnaissance' in a distribution substation.
AB - There is significant interest in smart grid analytics based on phasor measurement data. One application is estimation of the Thevenin equivalent model of the grid from local measurements. In this paper, we propose methods using phasor measurement data to track Thevenin parameters at substations delivering power to both an unbalanced and balanced feeder. We show that for an unbalanced grid, it is possible to estimate the Thevenin parameters at each instant of time using only instantaneous phasor measurements. For balanced grids, we propose a method that is well-suited for online applications when the data is highly temporally-correlated over a short window of time. The effectiveness of the two methods is tested via simulation for two use-cases, one for monitoring voltage stability and the other for identifying cyber attackers performing 'reconnaissance' in a distribution substation.
KW - Anomaly Detection
KW - Cybersecurity
KW - Phasor Measurement Unit (PMU)
KW - Thevenin Parameters
UR - http://www.scopus.com/inward/record.url?scp=85046366720&partnerID=8YFLogxK
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U2 - 10.1109/PESGM.2017.8273818
DO - 10.1109/PESGM.2017.8273818
M3 - Conference contribution
AN - SCOPUS:85046366720
T3 - IEEE Power and Energy Society General Meeting
SP - 1
EP - 5
BT - 2017 IEEE Power and Energy Society General Meeting, PESGM 2017
PB - IEEE Computer Society
T2 - 2017 IEEE Power and Energy Society General Meeting, PESGM 2017
Y2 - 16 July 2017 through 20 July 2017
ER -