NDLI: PMU placement for dynamic state tracking of power systems

Content Provider	IEEE Xplore Digital Library
Author	Yannan Sun Pengwei Du Zhenyu Huang Kalsi, K. Ruisheng Diao Anderson, K.K. Yulan Li Lee, B.
Copyright Year	2011
Description	Author affiliation: Pacific Northwest National Laboratory, Richland, WA 99352 USA (Yannan Sun; Pengwei Du; Zhenyu Huang; Kalsi, K.; Ruisheng Diao; Anderson, K.K.; Yulan Li; Lee, B.)
Abstract	The complexity of power systems continue to increase as load demands grow and new energy technologies emerge. Efficient methodologies and instrumentation are needed for real-time monitoring and control of power systems. Accurately tracking the state variables (rotor angle and speed) is necessary for monitoring system stability conditions and assessing the risks of large-scale system collapse. Previous work proposed an extended Kalman filter (EKF) method, which makes use of data from phasor measurement units (PMU) and corrects the estimation predicted by the system model, for real-time tracking of system dynamics. This paper will explore how the number and locations of PMUs installed in the system should be determined to ensure satisfactory performance of the EKF-based tracking. Finding the optimal PMU placement, i.e., attaining whole system observability with the fewest PMUs, is very difficult to solve. In this paper, a novel search algorithm is presented for determining PMU placement (location and quantity). The algorithm determines a placement that gives small tracking error in polynomial time, while the optimal placement would be determined in exponential time. A modified, scalable algorithm is also presented. Observability of grid dynamics is considered in the sense that all the state variables can be tracked dynamically. Furthermore, observability in the presence of faults is considered. Simulation results for a 16-machine system and a 50-machine system are provided.
Starting Page	1
Ending Page	7
File Size	700671
Page Count	7
File Format	PDF
ISBN	9781457704178
e-ISBN	9781457704192
e-ISBN	9781457704185
DOI	10.1109/NAPS.2011.6024865
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Phasor measurement units Heuristic algorithms Power system dynamics Generators Mathematical model State estimation Noise dynamic state estimation PMU placement extended Kalman filter multi-machine power system
Content Type	Text
Resource Type	Article

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