Sensor fault and cyber attack resilient operation of DC microgrids

S Saha; T.K Roy; M.A Mahmud; M.E Haque; S.N Islam

doi:10.1016/j.ijepes.2018.01.007

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Sensor fault and cyber attack resilient operation of DC microgrids

Journal article

Peer reviewed

Sensor fault and cyber attack resilient operation of DC microgrids

S Saha, T.K Roy, M.A Mahmud, M.E Haque and S.N Islam

International Journal of Electrical Power & Energy Systems, Vol.99, pp.540-554

2018

DOI: https://doi.org/10.1016/j.ijepes.2018.01.007

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Abstract

Fault mitigation

Solar PV unit

Sensor fault

DC microgrids

Fault detection and estimation

Microturbine

Sliding mode observer

Wind generator

Cyber attack

This paper proposes a diagnosis and mitigation strategy for sensor faults and cyber attacks in a DC microgrid to ensure its fault and cyber attack resilient operation. Sliding mode observer-based fault diagnosis theory has been used in the proposed strategy to estimate the error in the sensor measurements due to any sensor fault or cyber attack in a DC microgrid. The estimated errors are used to initiate the proposed mitigation action, which rectifies the corrupted measurements to ensure fault and cyber attack resilient operation of the microgrid. The performance of the proposed strategy has been evaluated through rigorous simulation studies, carried out on a test DC microgrid under various fault and attack conditions. Simulation results clearly demonstrate that the proposed strategy is able to ensure the reliable and efficient operation of a DC microgrid under sensor faults or cyber attack conditions.

Details

Title: Sensor fault and cyber attack resilient operation of DC microgrids
Authors: S Saha (Author) - Deakin University
T.K Roy (Author) - Deakin University
M.A Mahmud (Author) - Deakin University
M.E Haque (Author) - Deakin University
S.N Islam (Author) - Deakin University
Publication details: International Journal of Electrical Power & Energy Systems, Vol.99, pp.540-554
Publisher: Elsevier Ltd
DOI: 10.1016/j.ijepes.2018.01.007
ISSN: 1879-3517
Organisation Unit: University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering
Language: English
Record Identifier: 99532306702621
Output Type: Journal article

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