A Binary-Optimization-Based Coordinated Cyber-Physical Attack for Disrupting Electricity Market Operation

被引:10
作者
Jena, Prasanta Kumar [1 ]
Ghosh, Subhojit [1 ]
Koley, Ebha [1 ]
机构
[1] Natl Inst Technol Raipur, Dept Elect Engn, Raipur 492010, Madhya Pradesh, India
来源
IEEE SYSTEMS JOURNAL | 2021年 / 15卷 / 02期
关键词
Electricity supply industry; Real-time systems; Transmission line measurements; Smart grids; Cyberattack; State estimation; Day-ahead market (DAM); electricity market; locational marginal price (LMP); optimal power flow (OPF); real-time market (RTM); state estimation; SMART; SECURITY; THREATS; SYSTEM;
D O I
10.1109/JSYST.2020.3023859
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A reliable smart grid should possess the necessary security mechanism against any attack aiming at disrupting the electricity market operation. The operation is performed to allocate the final nodal price as per the states estimated in each node. The state estimator can be misdirected by changing the network configuration both at physical and/or information layer, leading to disruption in the market operation. As compared to the physical attack or cyber attack carried out independently, a coordinated cyber-physical attack has a larger impact on the market operation. This article proposes a coordinated cyber-physical attack to maximize the electricity market disruption in terms of deviation in the generation cost between the day-ahead market and real-time market operations. The identification of physical attack causing maximum unintended deviation in the electricity market operation has been formulated as a binary optimization problem. The second stage of the proposed attack involves injecting a state preserving attack vector into the communication channel. The false data injection hides the impact of the physical attack, thereby, refraining the control center from taking necessary actions. The impact of the attack has been quantified in terms of variation in the generation cost and nodal prices between the preattack and postattack scenarios for IEEE 9, 14, and 39-bus power systems.
引用
收藏
页码:2619 / 2629
页数:11
相关论文
共 30 条
[1]  
Abur A, 2004, Power System State Estimation: Theory and Implementation
[2]   OCPP Protocol: Security Threats and Challenges [J].
Alcaraz, Cristina ;
Lopez, Javier ;
Wolthusen, Stephen .
IEEE TRANSACTIONS ON SMART GRID, 2017, 8 (05) :2452-2459
[3]   Policy enforcement system for secure interoperable control in distributed Smart Grid systems [J].
Alcaraz, Cristina ;
Lopez, Javier ;
Wolthusen, Stephen .
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2016, 59 :301-314
[4]   Day-Ahead Deregulated Electricity Market Price Forecasting Using Recurrent Neural Network [J].
Anbazhagan, S. ;
Kumarappan, N. .
IEEE SYSTEMS JOURNAL, 2013, 7 (04) :866-872
[5]   Online Detection of Stealthy False Data Injection Attacks in Power System State Estimation [J].
Ashok, Aditya ;
Govindarasu, Manimaran ;
Ajjarapu, Venkataramana .
IEEE TRANSACTIONS ON SMART GRID, 2018, 9 (03) :1636-1646
[6]   Sensitivity Analysis of Real-Time Locational Marginal Price to SCADA Sensor Data Corruption [J].
Choi, Dae-Hyun ;
Xie, Le .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2014, 29 (03) :1110-1120
[7]  
Delavari A., 2018, 2018 IEEE Electrical Power and Energy Conference (EPEC), P1, DOI 10.1109/CCECE.2018.8447645
[8]   Cyber-physical attacks and defences in the smart grid: a surveyInspec keywordsOther keywords [J].
He, Haibo ;
Yan, Jun .
IET CYBER-PHYSICAL SYSTEMS: THEORY & APPLICATIONS, 2016, 1 (01) :13-27
[9]   Impact of Data Quality on Real-Time Locational Marginal Price [J].
Jia, Liyan ;
Kim, Jinsub ;
Thomas, Robert J. ;
Tong, Lang .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2014, 29 (02) :627-636
[10]  
Jingwen Liang, 2017, 2017 IEEE Power & Energy Society General Meeting, DOI 10.1109/PESGM.2017.8273736