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PMU Missing Data Recovery Using Tensor Decomposition
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DOI：10.1109/TPWRS.2020.2991886.png)
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Abstract
En 中文
The paper proposes a new approach for the recovery of missing data from phasor measurement units (PMUs). The approach is based on the application of tensor decomposition to PMU data organized as three-dimensional tensors with respect to time, location and type of variables. The organization of the PMU data is in the form of a bus-oriented data structure and a branch-oriented data structure. Two versions of the approach are introduced. The first version uses polyadic tensor decomposition and the second version uses Tucker tensor decomposition. Several case studies are conducted validating the proposed approaches including measured PMU data in the New York transmission system. Comparison with existing approaches is performed to demonstrate the improvement in missing data recovery accuracy achieved by the new approach.
Keywords:
Tensors
Phasor measurement units
Data structures
Voltage measurement
Current measurement
Matrix decomposition
Power systems
Missing data recovery
phasor measurement unit
polyadic decomposition
tensor decomposition
Tucker decomposition
Journal
IF:
7.2
Papers:
1.1W
Citations:
5.0W