Signal Processing in Smart Grids: From Data to Reliable Information

The recent proliferation of data is revolutionizing the practice of power system monitoring and control. With the Smart Grid initiative, more than two thousand multi-channel phasor measurement units (PMUs) [37] have now been installed in North America [35]. PMUs can directly measure GPS-synchronized bus voltage phasors, line current phasors, and the frequency, at a rate of 30 or 60 samples per second per channel. Compared to the conventional Supervisory Control and Data Acquisition (SCADA) systems that only provide measurements every 2–5 s, which are not accurately synchronized in time, PMUs can drastically improve the system visibility and enhance the situational awareness.

[1]  Frank Englert,et al.  Enhancing user privacy by preprocessing distributed smart meter data , 2013, 2013 Sustainable Internet and ICT for Sustainability (SustainIT).

[2]  Bruno Sinopoli,et al.  Integrity Data Attacks in Power Market Operations , 2011, IEEE Transactions on Smart Grid.

[3]  James S. Thorp,et al.  Synchronized Phasor Measurement Applications in Power Systems , 2010, IEEE Transactions on Smart Grid.

[4]  Jun Jason Zhang,et al.  Fault Detection, Identification, and Location in Smart Grid Based on Data-Driven Computational Methods , 2014, IEEE Transactions on Smart Grid.

[5]  Peng Ning,et al.  False data injection attacks against state estimation in electric power grids , 2009, CCS.

[6]  Karl Henrik Johansson,et al.  On Security Indices for State Estimators in Power Networks , 2010 .

[7]  Patrick D. McDaniel,et al.  Security and Privacy Challenges in the Smart Grid , 2009, IEEE Security & Privacy.

[8]  Scott G. Ghiocel,et al.  Missing Data Recovery by Exploiting Low-Dimensionality in Power System Synchrophasor Measurements , 2016, IEEE Transactions on Power Systems.

[9]  D.J. Trudnowski,et al.  A Perspective on WAMS Analysis Tools for Tracking of Oscillatory Dynamics , 2007, 2007 IEEE Power Engineering Society General Meeting.

[10]  A.G. Phadke,et al.  An Alternative for Including Phasor Measurements in State Estimators , 2006, IEEE Transactions on Power Systems.

[11]  Edmond Jonckheere,et al.  Statistical structure learning of smart grid for detection of false data injection , 2013, 2013 IEEE Power & Energy Society General Meeting.

[12]  Klara Nahrstedt,et al.  Detecting False Data Injection Attacks on DC State Estimation , 2010 .

[13]  Joe H. Chow,et al.  Low-rank matrix recovery from quantized and erroneous measurements: Accuracy-preserved data privatization in power grids , 2016, 2016 50th Asilomar Conference on Signals, Systems and Computers.

[14]  Joe H. Chow,et al.  Modeless reconstruction of missing synchrophasor measurements , 2014, 2014 IEEE PES General Meeting | Conference & Exposition.

[15]  Joe H. Chow,et al.  Identification of Successive “Unobservable” Cyber Data Attacks in Power Systems Through Matrix Decomposition , 2016, IEEE Transactions on Signal Processing.

[16]  Huiping Cao,et al.  Comprehensive Clustering of Disturbance Events Recorded by Phasor Measurement Units , 2014, IEEE Transactions on Power Delivery.

[17]  Jeff Dagle,et al.  Successes and Challenges for Synchrophasor Technology: An Update from the North American SynchroPhasor Initiative , 2012, 2012 45th Hawaii International Conference on System Sciences.

[18]  I. Kamwa,et al.  Dynamic State Estimation in Power System by Applying the Extended Kalman Filter With Unknown Inputs to Phasor Measurements , 2011, IEEE Transactions on Power Systems.

[19]  Xiaoqian Jiang,et al.  A Randomized Response Model for Privacy Preserving Smart Metering , 2012, IEEE Transactions on Smart Grid.

[20]  Zhu Han,et al.  Detecting False Data Injection Attacks on Power Grid by Sparse Optimization , 2014, IEEE Transactions on Smart Grid.

[21]  Wenting Li,et al.  Real-Time Event Identification Through Low-Dimensional Subspace Characterization of High-Dimensional Synchrophasor Data , 2018, IEEE Transactions on Power Systems.

[22]  Jian Ma,et al.  Use multi-dimensional ellipsoid to monitor dynamic behavior of power systems based on PMU measurement , 2008, 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century.

[23]  Gustavo Valverde,et al.  Unscented kalman filter for power system dynamic state estimation , 2011 .

[24]  Mohammad Shahidehpour,et al.  Synchrophasor Measurement Technology in Power Systems: Panorama and State-of-the-Art , 2014, IEEE Access.

[25]  Rakesh Bobba,et al.  Design Principles for Power Grid Cyber-Infrastructure Authentication Protocols , 2010, 2010 43rd Hawaii International Conference on System Sciences.

[26]  Joe H. Chow,et al.  A Low-Rank Matrix Approach for the Analysis of Large Amounts of Power System Synchrophasor Data , 2015, 2015 48th Hawaii International Conference on System Sciences.

[27]  H. Vincent Poor,et al.  Strategic Protection Against Data Injection Attacks on Power Grids , 2011, IEEE Transactions on Smart Grid.

[28]  T.J. Overbye,et al.  Line Outage Detection Using Phasor Angle Measurements , 2008, IEEE Transactions on Power Systems.

[29]  L. Tong,et al.  Malicious Data Attacks on Smart Grid State Estimation: Attack Strategies and Countermeasures , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[30]  Deniz Gündüz,et al.  Smart Meter Privacy for Multiple Users in the Presence of an Alternative Energy Source , 2013, IEEE Transactions on Information Forensics and Security.

[31]  Ruisheng Diao,et al.  Decision Tree-Based Online Voltage Security Assessment Using PMU Measurements , 2009, IEEE Transactions on Power Systems.

[32]  Wenting Li,et al.  Fast event identification through subspace characterization of PMU data in power systems , 2017, 2017 IEEE Power & Energy Society General Meeting.

[33]  Le Xie,et al.  Online Detection of Low-Quality Synchrophasor Measurements: A Data-Driven Approach , 2017, IEEE Transactions on Power Systems.

[34]  Jun Jason Zhang,et al.  Fault localization in Smart Grid using wavelet analysis and unsupervised learning , 2012, 2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR).

[35]  J. Quintero,et al.  Oscillation monitoring system based on wide area synchrophasors in power systems , 2007, 2007 iREP Symposium - Bulk Power System Dynamics and Control - VII. Revitalizing Operational Reliability.

[36]  Leon M. Tolbert,et al.  Multiple Event Detection and Recognition Through Sparse Unmixing for High-Resolution Situational Awareness in Power Grid , 2014, IEEE Transactions on Smart Grid.

[37]  A. K. Ghosh,et al.  The classification of power system disturbance waveforms using a neural network approach , 1994 .

[38]  Sebastien Guillon,et al.  Synchrophasor Data Baselining and Mining for Online Monitoring of Dynamic Security Limits , 2014, IEEE Transactions on Power Systems.

[39]  Joe H. Chow,et al.  Power system disturbance identification from recorded dynamic data at the Northfield substation , 2003 .

[40]  Hao Zhu,et al.  Sparse Overcomplete Representations for Efficient Identification of Power Line Outages , 2012, IEEE Transactions on Power Systems.

[41]  Ning Lu,et al.  Smart-grid security issues , 2010, IEEE Security & Privacy.

[42]  Heejo Lee,et al.  This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. INVITED PAPER Cyber–Physical Security of a Smart Grid Infrastructure , 2022 .

[43]  Joe H. Chow,et al.  Matrix completion with columns in union and sums of subspaces , 2015, 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

[44]  Ying-Hong Lin,et al.  A new PMU-based fault detection/location technique for transmission lines with consideration of arcing fault discrimination-part I: theory and algorithms , 2004 .

[45]  Yi Ma,et al.  Robust principal component analysis? , 2009, JACM.

[46]  Emmanuel J. Candès,et al.  Exact Matrix Completion via Convex Optimization , 2009, Found. Comput. Math..