An Accurate False Data Injection Attack (FDIA) Detection in Renewable-Rich Power Grids

Mostafa Mohammadpourfard, Yang Weng, Istemihan Genc, Taesic Kim

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Citations (Scopus)

Abstract

An accurate state estimation (SE) considering increased uncertainty by the high penetration of renewable energy systems (RESs) is more and more important to enhance situational awareness, and the optimal and resilient operation of the renewable-rich power grids. However, it is anticipated that adversaries who plan to manipulate the target power grid will generate attacks that inject inaccurate data to the SE using the vulnerabilities of the devices and networks. Among potential attack types, false data injection attack (FDIA) is gaining popularity since this can bypass bad data detection (BDD) methods implemented in the SE systems. Although numerous FDIA detection methods have been recently proposed, the uncertainty of system configuration that arises by the continuously increasing penetration of RESs has been been given less consideration in the FDIA algorithms. To address this issue, this paper proposes a new FDIA detection scheme that is applicable to renewable energy-rich power grids. A deep learning framework is developed in particular by synergistically constructing a Bidirectional Long Short-Term Memory (Bi-LSTM) with modern smart grid characteristics. The developed framework is evaluated on the IEEE 14-bus system integrating several RESs by using several attack scenarios. A comparison of the numerical results shows that the proposed FDIA detection mechanism outperforms the existing deep learning-based approaches in a renewable energy-rich grid environment.

Original languageEnglish
Title of host publication2022 10th Workshop on Modelling and Simulation of Cyber-Physical Energy Systems, MSCPES 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665468657
DOIs
Publication statusPublished - 2022
Event10th Workshop on Modelling and Simulation of Cyber-Physical Energy Systems, MSCPES 2022 - Milan, Italy
Duration: 3 May 2022 → …

Publication series

Name2022 10th Workshop on Modelling and Simulation of Cyber-Physical Energy Systems, MSCPES 2022

Conference

Conference10th Workshop on Modelling and Simulation of Cyber-Physical Energy Systems, MSCPES 2022
Country/TerritoryItaly
CityMilan
Period3/05/22 → …

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Funding

This work was supported by TUBITAK and European Commission Horizon 2020 Marie Sklodowska-Curie Actions Cofund program (Project Number: 120C080) This work was supported by TÜB˙TAK and European Commission Horizon 2020 Marie Skłodowska-Curie Actions Cofund program (Project Number: 120C080). 978-1-6654-6865-7/22/$31.00 © 2022 IEEE

FundersFunder number
European Commission Horizon 2020
European Commission Horizon 2020 Marie Skłodowska-Curie Actions120C080, 978-1-6654-6865-7/22
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu

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