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Centralized volt-var optimization strategy considering malicious attack on distributed energy resources control

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journal contribution
posted on 15.09.2017 by Ankur Majumdar, Yashodhan Agalgaonkar, Bikash C. Pal, Ralph Gottschalg
The adoption of information and communication technology (ICT) based centralized volt-var control (VVC) leads to an optimal operation of a distribution feeder. However, it also poses a challenge that an adversary can tamper with the metered data and thus can render the VVC action ineffective. Distribution system state estimation (DSSE) acts as a backbone of centralized VVC. Distributed energy resources (DER) injection measurements constitute leverage measurements from a DSSE point of view. This paper proposes two solutions as a volt var optimization-distribution system state estimation (VVO-DSSE) malicious attack mitigating strategy when the DER injection measurements are compromised. The first solution is based on local voltage regulation controller set-points. The other solution effectively employs historical data or forecast information. The concept is based on a cumulant based probabilistic optimal power flow with the objective of minimizing the expectation of total power losses. The effectiveness of the approach is performed on the 95-bus UK generic distribution system (UKGDS) and validated against Monte Carlo simulations.

Funding

This work has been supported by the Engineering and Physical Sciences Research Council (EPSRC) UK through the PV2025-Potential Costs and Benefits of Photovoltaics for UK-Infrastructure and Society (EP/K02227X/1).

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

IEEE Transactions on Sustainable Energy

Citation

MAJUMDAR, A. ... et al, 2018. Centralized volt-var optimization strategy considering malicious attack on distributed energy resources control. IEEE Transactions on Sustainable Energy, 9(1), pp. 148-156.

Publisher

IEEE

Version

VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 3.0 Unported (CC BY 3.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/by/3.0/

Acceptance date

17/06/2017

Publication date

2018

Notes

This is an Open Access Article. It is published by IEEE under the Creative Commons Attribution 3.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/3.0/

ISSN

1949-3029

Language

en

Licence

Exports