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Dynamic load-altering attack detection based on adaptive fading Kalman filter in power systems

2021-07-07

文章导读

随着智能电网技术的快速发展，现代电力系统已经发展成为一个典型的网络物理系统（CPS）。随着将电力系统与智能设备更紧密集成，电力系统正变得越来越复杂并存在诸多潜在网络攻击隐患。负载变化攻击（LAA）是其中一种对电力系统用户侧的网络物理攻击，本文提出了一种有效可行的电力系统动态负载变化（D-LAA）攻击检测方法。首先，建立了基于D-LAAs的智能电网离散系统模型。其次，设计了一种自适应衰落卡尔曼滤波器（AFKF）来估计智能电网的状态，AFKF能完全滤除电力系统的高斯噪声，得到更准确的状态变化曲线（包括攻击），又提出了一种基于AFKF的欧氏距离比检测算法。通过新的欧氏距离比放大不可感知的D-LAA，提高了D-LAA的检测灵敏度，特别是对于非常弱的D-LAA攻击。最后，通过仿真验证了欧氏距离比检测算法的可行性和有效性。

Dynamic load-altering attack detection based on adaptive fading Kalman filter in power systems

电力系统中基于自适应衰落卡尔曼滤波器的动态负载变化攻击检测

Qiang Ma¹, Zheng Xu¹, Wenting Wang², Lin Lin¹, Tiancheng Ren², Shuxian Yang³, Jian Li³

（1.State Grid Shandong Electric Power Company, Jinan 250000, P.R. China 2.State Grid Shandong Electric Power Company Electric Power Research Institute, Jinan 250003, P.R. China 3.School of Automation Engineering, Northeast Electric Power University, Jilin, Jilin 132012, P.R. China）

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Abstract

This paper presents an effective and feasible method for detecting dynamic load-altering attacks (D-LAAs) in a smart grid. First, a smart grid discrete system model is established in view of D-LAAs. Second, an adaptive fading Kalman filter (AFKF) is designed for estimating the state of the smart grid. The AFKF can completely filter out the Gaussian noise of the power system, and obtain a more accurate state change curve (including consideration of the attack). A Euclidean distance ratio detection algorithm based on the AFKF is proposed for detecting D-LAAs. Amplifying imperceptible D-LAAs through the new Euclidean distance ratio improves the D-LAA detection sensitivity, especially for very weak D-LAA attacks. Finally, the feasibility and effectiveness of the Euclidean distance ratio detection algorithm are verified based on simulations.

Keywords

Adaptive fading Kalman filter, Dynamic load, Attack detection.

Fig.1 Three examples of dynamic load-altering attacks:

a) open-loop dynamic load-altering attack (D-LAA), b) single- point closed-loop D-LAA, c) multi-point closed-loop D-LAAs

Fig.2 D-LAA detection scheme (AFKF: adaptive fading

Kalman filter)

Fig.3 Simulation result for smart grid under single-point closed-loop D-LAA

Fig.4Detection result for single-point closed-loop D-LAA

Fig.5 Simulation result for smart grid under multi-point closed-loop D-LAAs

Fig.6 Detection results for multi-point closed-loop D-LAAs

本文引文信息

Ma Q, Xu Z, Wang W, Lin L, Ren T, Yang S, Li J J (2021) Dynamic load-altering attack detection based on adaptive fading Kalman filter in power systems, 4(2): 184-192

马强，徐征，王文婷，林琳，任天成，杨淑仙，李健 (2021) 电力系统中基于自适应衰落卡尔曼滤波器的动态负载变化攻击检测. 全球能源互联网（英文），4(2): 184-192

Biographies

Qiang Ma

Qiang Ma received a master’s degree at Shandong University of Finance and Economic in 2008. He is working at the State Grid Shandong Electric Power Company. His research interests include transmission and distribution prices, price formation mechanisms of electricity markets, and power market settlement system.

Zheng Xu

Zheng Xu received a bachelor’s degree at North China Electric Power University, Beijing in 2005, and received a master’s degree at Shandong University of Finance and Economic in 2009. He is working at the State Grid Shandong Electric Power Company. His research interest is power system automation.

Wenting Wang

Wenting Wang received her B.S., and M.S. from the Department of Information Security Engineering, Northeast Electric Power University, China, in 2011, and 2015, respectively. In 2015, she joined the State Grid Shandong Electric Power Research Institute, where she is currently a senior engineer. Her research interests are electronic engineering, information security, network security, data security, and cryptography..

Lin Lin

Lin Lin graduated from Jinan University, Shandong, in 2009. She has a master’s degree in electrical engineering. She is working at the State Grid Shandong Electric Power Company, Shandong. Her research interests include dispatching automation and network security.

Tiancheng Ren

Tiancheng Ren received a bachelor’s degree at North China Electric Power University, Beijing, in 2001. He joined the State Grid Shandong Electric Power Research Institute, where he is currently a senior engineer. His research interests are electronic engineering, data security, and cryptography.

Shuxian Yang

Shuxian Yang received her B.Sc. degree in Measurement and Control Technology and Instruments in 2019 from North China Electric Power University, China. She is a master’s degree candidate at the School of North East Electric Power University, China. Her research interests include Kalman filter algorithms and attack detection in cyber-physical systems.

Jian Li

Jian Li received her B.Sc. and M.Sc. degrees in electrical automation and control theory and application from the Liaoning Technical University, China, in 2005 and 2008, respectively, and her Ph.D. degree in control theory and application from Northeast University, China in 2013. Currently, she is an Associate Professor at the School of Automation Engineering, Northeast Electric University, China. From July 2015 to August 2015, she was a visiting scholar at the Nonlinear Dynamics Group at Yeungnam University, South Korea. Her research interests include fault detection, robust control, and micro- grids.

编辑：王闻昊王彦博

审核：王伟

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