Dynamic State Estimation of Smart Grid Based on CKF under False Data Injection Attacks

Xinghua Liu; Siwen Dong; Jingjing Huang; Lei Yang; Xiangqian Tong

doi:10.1109/ICIEA51954.2021.9516062

Dynamic State Estimation of Smart Grid Based on CKF under False Data Injection Attacks

Xinghua Liu
, Siwen Dong
, Jingjing Huang
, Lei Yang
, Xiangqian Tong

Faculty of Electronic and Information Engineering

Xi'an University of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The accurately estimated state is of great importance to a stable running condition of smart grid. The emergence of cyber attacks brings new challenges to the state estimation of smart grid. Especially, false data injection (FDI) attacks deteriorate the accuracy of state estimation by injecting the false data into the measurement device. To solve the problem, a cubature Kalman filter (CKF) is proposed, which can estimate the dynamic state of smart grid under FDI attacks. Firstly, due to the complexity of the state equation of smart grid, this paper adopts Holt's two-parameter exponential smoothing method to establish the state equation. Secondly, according to the principle that the measurement residuals before and after the FDI attack are equal, the expressions of the attack vectors are established. And they are applied to the measurement quantities to avoid the conventional bad data detection. Then, the cubature Kalman filter algorithm is utilized to estimate the dynamic state of the smart grid attacked by FDI. Finally, the simulated results verify effectiveness of the proposed method.

Original language	English
Title of host publication	Proceedings of the 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1883-1888
Number of pages	6
ISBN (Electronic)	9781665422482
DOIs	https://doi.org/10.1109/ICIEA51954.2021.9516062
State	Published - 1 Aug 2021
Event	16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021 - Chengdu, China Duration: 1 Aug 2021 → 4 Aug 2021

Publication series

Name	Proceedings of the 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021

Conference

Conference	16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021
Country/Territory	China
City	Chengdu
Period	1/08/21 → 4/08/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

CKF
FDI attacks
Smart grid
dynamic state estimation

Access to Document

10.1109/ICIEA51954.2021.9516062

Cite this

Liu, X., Dong, S., Huang, J., Yang, L., & Tong, X. (2021). Dynamic State Estimation of Smart Grid Based on CKF under False Data Injection Attacks. In Proceedings of the 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021 (pp. 1883-1888). (Proceedings of the 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIEA51954.2021.9516062

Liu, Xinghua ; Dong, Siwen ; Huang, Jingjing et al. / Dynamic State Estimation of Smart Grid Based on CKF under False Data Injection Attacks. Proceedings of the 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 1883-1888 (Proceedings of the 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021).

@inproceedings{7f0075df2c25469a8ddd1e3443657f42,

title = "Dynamic State Estimation of Smart Grid Based on CKF under False Data Injection Attacks",

abstract = "The accurately estimated state is of great importance to a stable running condition of smart grid. The emergence of cyber attacks brings new challenges to the state estimation of smart grid. Especially, false data injection (FDI) attacks deteriorate the accuracy of state estimation by injecting the false data into the measurement device. To solve the problem, a cubature Kalman filter (CKF) is proposed, which can estimate the dynamic state of smart grid under FDI attacks. Firstly, due to the complexity of the state equation of smart grid, this paper adopts Holt's two-parameter exponential smoothing method to establish the state equation. Secondly, according to the principle that the measurement residuals before and after the FDI attack are equal, the expressions of the attack vectors are established. And they are applied to the measurement quantities to avoid the conventional bad data detection. Then, the cubature Kalman filter algorithm is utilized to estimate the dynamic state of the smart grid attacked by FDI. Finally, the simulated results verify effectiveness of the proposed method.",

keywords = "CKF, FDI attacks, Smart grid, dynamic state estimation",

author = "Xinghua Liu and Siwen Dong and Jingjing Huang and Lei Yang and Xiangqian Tong",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021 ; Conference date: 01-08-2021 Through 04-08-2021",

year = "2021",

month = aug,

day = "1",

doi = "10.1109/ICIEA51954.2021.9516062",

language = "英语",

series = "Proceedings of the 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021",

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}

Liu, X, Dong, S, Huang, J, Yang, L & Tong, X 2021, Dynamic State Estimation of Smart Grid Based on CKF under False Data Injection Attacks. in Proceedings of the 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021. Proceedings of the 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021, Institute of Electrical and Electronics Engineers Inc., pp. 1883-1888, 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021, Chengdu, China, 1/08/21. https://doi.org/10.1109/ICIEA51954.2021.9516062

Dynamic State Estimation of Smart Grid Based on CKF under False Data Injection Attacks. / Liu, Xinghua; Dong, Siwen; Huang, Jingjing et al.
Proceedings of the 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 1883-1888 (Proceedings of the 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Dynamic State Estimation of Smart Grid Based on CKF under False Data Injection Attacks

AU - Liu, Xinghua

AU - Dong, Siwen

AU - Huang, Jingjing

AU - Yang, Lei

AU - Tong, Xiangqian

PY - 2021/8/1

Y1 - 2021/8/1

N2 - The accurately estimated state is of great importance to a stable running condition of smart grid. The emergence of cyber attacks brings new challenges to the state estimation of smart grid. Especially, false data injection (FDI) attacks deteriorate the accuracy of state estimation by injecting the false data into the measurement device. To solve the problem, a cubature Kalman filter (CKF) is proposed, which can estimate the dynamic state of smart grid under FDI attacks. Firstly, due to the complexity of the state equation of smart grid, this paper adopts Holt's two-parameter exponential smoothing method to establish the state equation. Secondly, according to the principle that the measurement residuals before and after the FDI attack are equal, the expressions of the attack vectors are established. And they are applied to the measurement quantities to avoid the conventional bad data detection. Then, the cubature Kalman filter algorithm is utilized to estimate the dynamic state of the smart grid attacked by FDI. Finally, the simulated results verify effectiveness of the proposed method.

AB - The accurately estimated state is of great importance to a stable running condition of smart grid. The emergence of cyber attacks brings new challenges to the state estimation of smart grid. Especially, false data injection (FDI) attacks deteriorate the accuracy of state estimation by injecting the false data into the measurement device. To solve the problem, a cubature Kalman filter (CKF) is proposed, which can estimate the dynamic state of smart grid under FDI attacks. Firstly, due to the complexity of the state equation of smart grid, this paper adopts Holt's two-parameter exponential smoothing method to establish the state equation. Secondly, according to the principle that the measurement residuals before and after the FDI attack are equal, the expressions of the attack vectors are established. And they are applied to the measurement quantities to avoid the conventional bad data detection. Then, the cubature Kalman filter algorithm is utilized to estimate the dynamic state of the smart grid attacked by FDI. Finally, the simulated results verify effectiveness of the proposed method.

KW - CKF

KW - FDI attacks

KW - Smart grid

KW - dynamic state estimation

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U2 - 10.1109/ICIEA51954.2021.9516062

DO - 10.1109/ICIEA51954.2021.9516062

M3 - 会议稿件

AN - SCOPUS:85115448688

T3 - Proceedings of the 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021

SP - 1883

EP - 1888

BT - Proceedings of the 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021

Y2 - 1 August 2021 through 4 August 2021

ER -

Liu X, Dong S, Huang J, Yang L, Tong X. Dynamic State Estimation of Smart Grid Based on CKF under False Data Injection Attacks. In Proceedings of the 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 1883-1888. (Proceedings of the 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021). doi: 10.1109/ICIEA51954.2021.9516062

Dynamic State Estimation of Smart Grid Based on CKF under False Data Injection Attacks

Abstract

Publication series

Conference

UN SDGs

Keywords

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