Security Enhancement of Network Constraint Grid-Edge Energy Management System

Hafiz, Faeza; Ishchenko, Dmitry

doi:10.1109/ias54023.2022.9940067

Security Enhancement of Network Constraint Grid-Edge Energy Management System

Conference · Sun Oct 09 04:00:00 EDT 2022 · 2022 IEEE Industry Applications Society Annual Meeting (IAS)

DOI:https://doi.org/10.1109/ias54023.2022.9940067· OSTI ID:2337873

Hafiz, Faeza ^[1]; Ishchenko, Dmitry ^[2]

Hitachi Energy Research Center,Raleigh,NC,USA; ABB USCRC
Hitachi Energy Research Center,Raleigh,NC,USA

Network constrained grid edge energy management system (EMS) provides economic solution for active and reactive power dispatch of distributed energy resources (DERs) at the grid edge level. Grid edge EMS ensures secure interconnection of a circuit segment to the distribution system by maintaining grid code requirements (e.g. IEEE 1547–2018). Grid edge EMS is dependent on communication to receive load measurement, which brings a risk of unobservable false data injection attacks (FDIAs). To mitigate the risk, this paper proposes a framework to enhance resilient operation of grid edge EMS by detecting the unobservable FDIAs on loads and replacing them with forecasted values. In this work, a two-step detection algorithm is proposed. In first step, conventional residual based algorithm is deployed. Autoencoder (AE) based data driven mechanism is included in second step to detect the presence of unobservable FDIAs. After ensuring the presence of FDIA, its specific location is detected by checking the maximum residue values till the predefined threshold value is reached. Detected false data injected loads are then replaced with forecasted load values following long-short term memory (LSTM) based forecast to ensure resilient performance of grid edge EMS in the presence of attacks. This proposed security enhancement framework for grid edge EMS is evaluated in IEEE 13 bus system with three integrated DERs. Numerical simulation shows the validation of the proposed framework by reducing voltage violation in real operation of grid edge EMS.

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Research Organization:: ABB Inc.

Sponsoring Organization:: USDOE Office of Electricity

DOE Contract Number:: OE0000896

OSTI ID:: 2337873

Conference Information:: Journal Name: 2022 IEEE Industry Applications Society Annual Meeting (IAS)

Country of Publication:: United States

Language:: English

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