Recursive Dynamic Compressive Sensing in Smart Distribution Systems

Karimi, Hazhar Sufi; Natarajan, Balasubramaniam

doi:10.1109/isgt45199.2020.9087784

Title: Recursive Dynamic Compressive Sensing in Smart Distribution Systems

Conference · Sat Feb 01 00:00:00 EST 2020 · 2020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)

DOI:https://doi.org/10.1109/isgt45199.2020.9087784· OSTI ID:1907351

Karimi, Hazhar Sufi; Natarajan, Balasubramaniam

With a transition to a smarter grid, we are witnessing a significant growth in smart metering infrastructure and sensor deployment in the distribution system. The underlying communication infrastructure is stressed due to the large volume of data that is generated by the smart meters/sensors. Furthermore, real time operations such as state estimation and control are impaired due to the lack of reliable aggregation of the data. In this paper, we exploit the underlying sparsity in grid data to implement two recursive dynamic compressive sensing (CS) approaches-streaming modified weighted-`1 CS and Kalman filtered CS. These approaches aim to reconstruct the sparse signal using the current underdetermined measurements and the prior information about the sparse signal and its support set. Slow signal and support change is in distribution grid data is validated using Pecan Street data. Both the IEEE 34 node test feeder system and PecanStreet data are considered as two examples to validate the superior performance of the two recursive CS techniques relative to classic CS.

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Research Organization:: Kansas State Univ., Manhattan, KS (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office

DOE Contract Number:: EE0008767

OSTI ID:: 1907351

Report Number(s):: DOE-KSU-8767

Journal Information:: 2020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), Conference: 2020 IEEE PES Innovative Smart Grid Technologies (ISGT) Washington, DC, 17-20 February 2020

Country of Publication:: United States

Language:: English

References (14)

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