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Title: Fast Parallel Stochastic Subspace Algorithms for Large-Scale Ambient Oscillation Monitoring

Journal Article · · IEEE Transactions on Smart Grid
 [1]; ORCiD logo [1];  [2]
  1. Washington State Univ., Pullman, WA (United States)
  2. Purdue Univ., West Lafayette, IN (United States)
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With the installation of synchrophasors widely across the power grid, measurement-based oscillation monitoring algorithms are becoming increasingly useful in identifying the real-time oscillatory modal properties in power systems. When the number of phasor measurement unit (PMU) channels grows, the computational time of many PMU data based algorithms is dominated by the computational burden in processing large-scale dense matrices. In order to overcome this limitation, this paper presents new formulations and computational strategies for speeding up an ambient oscillation monitoring algorithm, namely, stochastic subspace identification (SSI). Based on previous work, two fast singular value decomposition (SVD) approaches are first applied to the SVD evaluation within the SSI algorithm. Next, block structures are exploited so that the large-scale dense matrix computations can be processed in parallel. This helps in memory savings as well as in overall computational time. Experimental results from three sets of archived data of the western interconnection demonstrate that the new approaches can provide significant speedups while retaining modal estimation accuracy. With proposed fast parallel algorithms, the real-time oscillation monitoring of the large-scale system using hundreds of PMU measurements becomes feasible.

Research Organization:
Purdue Univ., West Lafayette, IN (United States)
Sponsoring Organization:
National Science Foundation (NSF); USDOE
Grant/Contract Number:
SC0010205; 1552323
OSTI ID:
1418629
Journal Information:
IEEE Transactions on Smart Grid, Vol. 8, Issue 3; ISSN 1949-3053
Publisher:
IEEECopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 17 works
Citation information provided by
Web of Science

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