Elements of Networked Protection Systems for Distribution Networks and Microgrids: A Cyber-Security Perspective

Networked protection systems use information, communication and computation technologies to collect and process sensor data from spatially distributed sensors, and launch protective and control actions by sending commands to local devices. Such protection systems are also capable of supporting specialized tasks including asset control and backup protection in case of traditional relaying failures. This paper explains the structure and the fundamental elements of the networked protection systems in distribution systems and microgrids. The overall system is divided into three subsystems which are interconnected by communication systems. Different types of cyber-attacks on the subsystems and their impacts are discussed from the vantage point of protection. False and delayed tripping, non-detection, cascading failures, and unstable operation of distributed energy resources (DERs) are discussed as the critical issues that can be related to cyber-attacks.

[1]  Mourad Debbabi,et al.  Optimal Tree Construction Model for Cyber-Attacks to Wide Area Measurement Systems , 2018, IEEE Transactions on Smart Grid.

[2]  M. M. Eissa,et al.  Challenges and novel solution for wide‐area protection due to renewable sources integration into smart grid: an extensive review , 2018, IET Renewable Power Generation.

[3]  Richard Brooks,et al.  A survey of electric power synchrophasor network cyber security , 2014, IEEE PES Innovative Smart Grid Technologies, Europe.

[4]  Xi He,et al.  Cyber-Attacks in PMU-Based Power Network and Countermeasures , 2018, IEEE Access.

[5]  Younes Seyedi,et al.  Design of networked protection systems for smart distribution grids: A data-driven approach , 2017, 2017 IEEE Power & Energy Society General Meeting.

[6]  Kang B. Lee,et al.  Smart Sensors and Standard-Based Interoperability in Smart Grids , 2017, IEEE Sensors Journal.

[7]  Raheem A. Beyah,et al.  Cyber Security and Operational Reliability , 2015, 2015 48th Hawaii International Conference on System Sciences.

[8]  Zhihan Lv,et al.  PMU Placement in Electric Transmission Networks for Reliable State Estimation Against False Data Injection Attacks , 2017, IEEE Internet of Things Journal.

[9]  T. H. Morris,et al.  Cyber security recommendations for wide area monitoring, protection, and control systems , 2012, 2012 IEEE Power and Energy Society General Meeting.

[10]  Joe H. Chow,et al.  An Online Mechanism for Detection of Gray-Hole Attacks on PMU Data , 2018, IEEE Transactions on Smart Grid.

[11]  Haris M. Khalid,et al.  A Bayesian Algorithm to Enhance the Resilience of WAMS Applications Against Cyber Attacks , 2016, IEEE Transactions on Smart Grid.

[12]  Jinfu Chen,et al.  Distributed Framework for Detecting PMU Data Manipulation Attacks With Deep Autoencoders , 2019, IEEE Transactions on Smart Grid.

[13]  Eklas Hossain,et al.  Application of Big Data and Machine Learning in Smart Grid, and Associated Security Concerns: A Review , 2019, IEEE Access.

[14]  Walid G. Morsi,et al.  Fault Detection and Classification Based on Co-training of Semisupervised Machine Learning , 2018, IEEE Transactions on Industrial Electronics.

[15]  Zoran Obradovic,et al.  Spatially Aware Ensemble-Based Learning to Predict Weather-Related Outages in Transmission , 2019, HICSS.

[16]  Jaime Lloret,et al.  An Integrated IoT Architecture for Smart Metering , 2016, IEEE Communications Magazine.

[17]  Ravishankar K. Iyer,et al.  Self-Healing Attack-Resilient PMU Network for Power System Operation , 2018, IEEE Transactions on Smart Grid.

[18]  Ed Cortez,et al.  Distribution Synchrophasors: Pairing Big Data with Analytics to Create Actionable Information , 2018, IEEE Power and Energy Magazine.

[19]  M. M. Eissa,et al.  A Novel Centralized Wide Area Protection “CWAP” in Phase Portrait Based on Pilot Wire Including Phase Comparison , 2019, IEEE Transactions on Smart Grid.

[20]  Ahmed Al-Durra,et al.  A Prediction Algorithm to Enhance Grid Resilience Toward Cyber Attacks in WAMCS Applications , 2019, IEEE Systems Journal.

[21]  Younes Seyedi,et al.  Coordinated Protection and Control Based on Synchrophasor Data Processing in Smart Distribution Networks , 2018, IEEE Transactions on Power Systems.

[22]  Sandeep K. Shukla,et al.  Cyber security impacts on all-PMU state estimator - a case study on co-simulation platform GECO , 2012, 2012 IEEE Third International Conference on Smart Grid Communications (SmartGridComm).

[23]  Joe H. Chow,et al.  Classification and Detection of PMU Data Manipulation Attacks Using Transmission Line Parameters , 2018, IEEE Transactions on Smart Grid.

[24]  Josep M. Guerrero,et al.  Centralized Disturbance Detection in Smart Microgrids With Noisy and Intermittent Synchrophasor Data , 2017, IEEE Transactions on Smart Grid.

[25]  Konstantinos N. Plataniotis,et al.  Noncircular Attacks on Phasor Measurement Units for State Estimation in Smart Grid , 2018, IEEE Journal of Selected Topics in Signal Processing.