Sorry, you need to enable JavaScript to visit this website.

Emerging: Smart Grid & Energy Management

SPARSE ERROR CORRECTION FOR PMU DATA UNDER GPS SPOOFING ATTACKS


Time-synchronized phasor measurements from phasor measurement units (PMUs) are valuable for real time monitoring and control. However, their reliance on civilian GPS signals makes them vulnerable to GPS signal spoofing attacks which can be launched by an adversary to falsify PMU data entries.

Paper Details

Authors:
Shashini De Silva, Travis Hagen, Jinsub Kim, Eduardo Cotilla-Sanchez
Submitted On:
25 November 2018 - 9:43pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Presentation.pptx

(119)

Subscribe

[1] Shashini De Silva, Travis Hagen, Jinsub Kim, Eduardo Cotilla-Sanchez, "SPARSE ERROR CORRECTION FOR PMU DATA UNDER GPS SPOOFING ATTACKS", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3775. Accessed: May. 30, 2020.
@article{3775-18,
url = {http://sigport.org/3775},
author = {Shashini De Silva; Travis Hagen; Jinsub Kim; Eduardo Cotilla-Sanchez },
publisher = {IEEE SigPort},
title = {SPARSE ERROR CORRECTION FOR PMU DATA UNDER GPS SPOOFING ATTACKS},
year = {2018} }
TY - EJOUR
T1 - SPARSE ERROR CORRECTION FOR PMU DATA UNDER GPS SPOOFING ATTACKS
AU - Shashini De Silva; Travis Hagen; Jinsub Kim; Eduardo Cotilla-Sanchez
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3775
ER -
Shashini De Silva, Travis Hagen, Jinsub Kim, Eduardo Cotilla-Sanchez. (2018). SPARSE ERROR CORRECTION FOR PMU DATA UNDER GPS SPOOFING ATTACKS. IEEE SigPort. http://sigport.org/3775
Shashini De Silva, Travis Hagen, Jinsub Kim, Eduardo Cotilla-Sanchez, 2018. SPARSE ERROR CORRECTION FOR PMU DATA UNDER GPS SPOOFING ATTACKS. Available at: http://sigport.org/3775.
Shashini De Silva, Travis Hagen, Jinsub Kim, Eduardo Cotilla-Sanchez. (2018). "SPARSE ERROR CORRECTION FOR PMU DATA UNDER GPS SPOOFING ATTACKS." Web.
1. Shashini De Silva, Travis Hagen, Jinsub Kim, Eduardo Cotilla-Sanchez. SPARSE ERROR CORRECTION FOR PMU DATA UNDER GPS SPOOFING ATTACKS [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3775

Coincident Peak Prediction Using a Feed-Forward Neural Network


A significant portion of a business' annual electrical payments can be made up of coincident peak charges: a transmission surcharge for power consumed when the entire system is at peak demand. This charge occurs only a few times annually, but with per-MW prices orders of magnitudes higher than non-peak times. A business is incentivized to reduce its power consumption, but accurately predicting the timing of peak demand charges is nontrivial. In this paper we present a decision framework based on predicting the day-ahead likelihood of peak demand charges.

Paper Details

Authors:
Daniel Kirschen, Baosen Zhang
Submitted On:
28 November 2018 - 2:08pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Up-to-date slides.

(109)

Coincident_Peak_Prediction_Slides.pdf

(126)

Subscribe

[1] Daniel Kirschen, Baosen Zhang, "Coincident Peak Prediction Using a Feed-Forward Neural Network", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3773. Accessed: May. 30, 2020.
@article{3773-18,
url = {http://sigport.org/3773},
author = {Daniel Kirschen; Baosen Zhang },
publisher = {IEEE SigPort},
title = {Coincident Peak Prediction Using a Feed-Forward Neural Network},
year = {2018} }
TY - EJOUR
T1 - Coincident Peak Prediction Using a Feed-Forward Neural Network
AU - Daniel Kirschen; Baosen Zhang
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3773
ER -
Daniel Kirschen, Baosen Zhang. (2018). Coincident Peak Prediction Using a Feed-Forward Neural Network. IEEE SigPort. http://sigport.org/3773
Daniel Kirschen, Baosen Zhang, 2018. Coincident Peak Prediction Using a Feed-Forward Neural Network. Available at: http://sigport.org/3773.
Daniel Kirschen, Baosen Zhang. (2018). "Coincident Peak Prediction Using a Feed-Forward Neural Network." Web.
1. Daniel Kirschen, Baosen Zhang. Coincident Peak Prediction Using a Feed-Forward Neural Network [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3773

LARGE-SCALE ADAPTIVE ELECTRIC VEHICLE CHARGING


Large-scale charging infrastructure will play an important role in supporting the adoption of electric vehicles. In this presentation, we describe a unique physical testbed for large-scale, high-density EV charging research which we call the Adaptive Charging Network (ACN). We describe the architecture of the ACN including its hardware and software components. We also present a practical framework for online scheduling, which is based on model predictive control and convex optimization.

Paper Details

Authors:
Zachary J. Lee, Daniel Chang, Cheng Jin, George S. Lee, Rand Lee, Ted Lee, Steven H. Low
Submitted On:
24 November 2018 - 3:10am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Global SIP Presentation.pdf

(77)

Subscribe

[1] Zachary J. Lee, Daniel Chang, Cheng Jin, George S. Lee, Rand Lee, Ted Lee, Steven H. Low, "LARGE-SCALE ADAPTIVE ELECTRIC VEHICLE CHARGING", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3768. Accessed: May. 30, 2020.
@article{3768-18,
url = {http://sigport.org/3768},
author = {Zachary J. Lee; Daniel Chang; Cheng Jin; George S. Lee; Rand Lee; Ted Lee; Steven H. Low },
publisher = {IEEE SigPort},
title = {LARGE-SCALE ADAPTIVE ELECTRIC VEHICLE CHARGING},
year = {2018} }
TY - EJOUR
T1 - LARGE-SCALE ADAPTIVE ELECTRIC VEHICLE CHARGING
AU - Zachary J. Lee; Daniel Chang; Cheng Jin; George S. Lee; Rand Lee; Ted Lee; Steven H. Low
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3768
ER -
Zachary J. Lee, Daniel Chang, Cheng Jin, George S. Lee, Rand Lee, Ted Lee, Steven H. Low. (2018). LARGE-SCALE ADAPTIVE ELECTRIC VEHICLE CHARGING. IEEE SigPort. http://sigport.org/3768
Zachary J. Lee, Daniel Chang, Cheng Jin, George S. Lee, Rand Lee, Ted Lee, Steven H. Low, 2018. LARGE-SCALE ADAPTIVE ELECTRIC VEHICLE CHARGING. Available at: http://sigport.org/3768.
Zachary J. Lee, Daniel Chang, Cheng Jin, George S. Lee, Rand Lee, Ted Lee, Steven H. Low. (2018). "LARGE-SCALE ADAPTIVE ELECTRIC VEHICLE CHARGING." Web.
1. Zachary J. Lee, Daniel Chang, Cheng Jin, George S. Lee, Rand Lee, Ted Lee, Steven H. Low. LARGE-SCALE ADAPTIVE ELECTRIC VEHICLE CHARGING [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3768

Fast Nonconvex SDP Solver for Large-scale Power System State Estimation

Paper Details

Authors:
Submitted On:
24 November 2018 - 12:25am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Fast Nonconvex SDP Solver for Large-scale Power System State Estimation

(81)

Subscribe

[1] , "Fast Nonconvex SDP Solver for Large-scale Power System State Estimation", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3766. Accessed: May. 30, 2020.
@article{3766-18,
url = {http://sigport.org/3766},
author = { },
publisher = {IEEE SigPort},
title = {Fast Nonconvex SDP Solver for Large-scale Power System State Estimation},
year = {2018} }
TY - EJOUR
T1 - Fast Nonconvex SDP Solver for Large-scale Power System State Estimation
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3766
ER -
. (2018). Fast Nonconvex SDP Solver for Large-scale Power System State Estimation. IEEE SigPort. http://sigport.org/3766
, 2018. Fast Nonconvex SDP Solver for Large-scale Power System State Estimation. Available at: http://sigport.org/3766.
. (2018). "Fast Nonconvex SDP Solver for Large-scale Power System State Estimation." Web.
1. . Fast Nonconvex SDP Solver for Large-scale Power System State Estimation [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3766

Real-Time Power Outage Detection System using Social Sensing and Neural Networks

Paper Details

Authors:
Submitted On:
21 November 2018 - 7:49pm
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

Paper Presentation1.pdf

(84)

Subscribe

[1] , "Real-Time Power Outage Detection System using Social Sensing and Neural Networks ", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3707. Accessed: May. 30, 2020.
@article{3707-18,
url = {http://sigport.org/3707},
author = { },
publisher = {IEEE SigPort},
title = {Real-Time Power Outage Detection System using Social Sensing and Neural Networks },
year = {2018} }
TY - EJOUR
T1 - Real-Time Power Outage Detection System using Social Sensing and Neural Networks
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3707
ER -
. (2018). Real-Time Power Outage Detection System using Social Sensing and Neural Networks . IEEE SigPort. http://sigport.org/3707
, 2018. Real-Time Power Outage Detection System using Social Sensing and Neural Networks . Available at: http://sigport.org/3707.
. (2018). "Real-Time Power Outage Detection System using Social Sensing and Neural Networks ." Web.
1. . Real-Time Power Outage Detection System using Social Sensing and Neural Networks [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3707

OPTIMAL DATA TASK DISTRIBUTION FOR BALANCING ENERGY CONSUMPTION ON COOPERATIVE FOG NETWORKS


In this paper, the problem of how to balance the energy consumption during data processing in networks is investigated using a fog middleware. We first demonstrate that for a fog network with different kind of nodes, balancing the energy relies on a combinatorial optimization that is solved using graph theory. We propose a transformation of the transshipment graph problem to formulate an optimization problem that we solve with linear programming (LP).

Paper Details

Authors:
Jose Clemente, Fangyu Li, WenZhan Song
Submitted On:
18 November 2018 - 4:03pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

GlobalSIP_Jose.pdf

(105)

Subscribe

[1] Jose Clemente, Fangyu Li, WenZhan Song, "OPTIMAL DATA TASK DISTRIBUTION FOR BALANCING ENERGY CONSUMPTION ON COOPERATIVE FOG NETWORKS", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3679. Accessed: May. 30, 2020.
@article{3679-18,
url = {http://sigport.org/3679},
author = {Jose Clemente; Fangyu Li; WenZhan Song },
publisher = {IEEE SigPort},
title = {OPTIMAL DATA TASK DISTRIBUTION FOR BALANCING ENERGY CONSUMPTION ON COOPERATIVE FOG NETWORKS},
year = {2018} }
TY - EJOUR
T1 - OPTIMAL DATA TASK DISTRIBUTION FOR BALANCING ENERGY CONSUMPTION ON COOPERATIVE FOG NETWORKS
AU - Jose Clemente; Fangyu Li; WenZhan Song
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3679
ER -
Jose Clemente, Fangyu Li, WenZhan Song. (2018). OPTIMAL DATA TASK DISTRIBUTION FOR BALANCING ENERGY CONSUMPTION ON COOPERATIVE FOG NETWORKS. IEEE SigPort. http://sigport.org/3679
Jose Clemente, Fangyu Li, WenZhan Song, 2018. OPTIMAL DATA TASK DISTRIBUTION FOR BALANCING ENERGY CONSUMPTION ON COOPERATIVE FOG NETWORKS. Available at: http://sigport.org/3679.
Jose Clemente, Fangyu Li, WenZhan Song. (2018). "OPTIMAL DATA TASK DISTRIBUTION FOR BALANCING ENERGY CONSUMPTION ON COOPERATIVE FOG NETWORKS." Web.
1. Jose Clemente, Fangyu Li, WenZhan Song. OPTIMAL DATA TASK DISTRIBUTION FOR BALANCING ENERGY CONSUMPTION ON COOPERATIVE FOG NETWORKS [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3679

Dynamic power Allocation for Smart Grids via ADMM

Paper Details

Authors:
Joakim Jaldén
Submitted On:
20 June 2018 - 8:28am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

spawc2018.pdf

(160)

Subscribe

[1] Joakim Jaldén, "Dynamic power Allocation for Smart Grids via ADMM", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3236. Accessed: May. 30, 2020.
@article{3236-18,
url = {http://sigport.org/3236},
author = {Joakim Jaldén },
publisher = {IEEE SigPort},
title = {Dynamic power Allocation for Smart Grids via ADMM},
year = {2018} }
TY - EJOUR
T1 - Dynamic power Allocation for Smart Grids via ADMM
AU - Joakim Jaldén
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3236
ER -
Joakim Jaldén. (2018). Dynamic power Allocation for Smart Grids via ADMM. IEEE SigPort. http://sigport.org/3236
Joakim Jaldén, 2018. Dynamic power Allocation for Smart Grids via ADMM. Available at: http://sigport.org/3236.
Joakim Jaldén. (2018). "Dynamic power Allocation for Smart Grids via ADMM." Web.
1. Joakim Jaldén. Dynamic power Allocation for Smart Grids via ADMM [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3236

Trade-offs in Data-Driven False Data Injection Attacks Against the Power Grid


We address the problem of constructing false data injection (FDI) attacks that can bypass the bad data detector (BDD) of a power grid. The attacker is assumed to have access to only power flow measurement data traces (collected over a limited period of time) and no other prior knowledge about the grid. Existing related algorithms are formulated under the assumption that the attacker has access to measurements collected over a long (asymptotically infinite) time period, which may not be realistic.

Paper Details

Authors:
Fuxi Wen, David Yau
Submitted On:
19 April 2018 - 2:51pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Poster presentation

(196)

Subscribe

[1] Fuxi Wen, David Yau, " Trade-offs in Data-Driven False Data Injection Attacks Against the Power Grid", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3002. Accessed: May. 30, 2020.
@article{3002-18,
url = {http://sigport.org/3002},
author = {Fuxi Wen; David Yau },
publisher = {IEEE SigPort},
title = { Trade-offs in Data-Driven False Data Injection Attacks Against the Power Grid},
year = {2018} }
TY - EJOUR
T1 - Trade-offs in Data-Driven False Data Injection Attacks Against the Power Grid
AU - Fuxi Wen; David Yau
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3002
ER -
Fuxi Wen, David Yau. (2018). Trade-offs in Data-Driven False Data Injection Attacks Against the Power Grid. IEEE SigPort. http://sigport.org/3002
Fuxi Wen, David Yau, 2018. Trade-offs in Data-Driven False Data Injection Attacks Against the Power Grid. Available at: http://sigport.org/3002.
Fuxi Wen, David Yau. (2018). " Trade-offs in Data-Driven False Data Injection Attacks Against the Power Grid." Web.
1. Fuxi Wen, David Yau. Trade-offs in Data-Driven False Data Injection Attacks Against the Power Grid [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3002

Chance Constrained Optimization of Distributed Energy Resources via Affine Policies

Paper Details

Authors:
Krishna Sandeep Ayyagari, Nikolaos Gatsis, and Ahmad Taha
Submitted On:
21 November 2017 - 1:47pm
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

talk_GLOBALSIP_2017.pdf

(329)

Subscribe

[1] Krishna Sandeep Ayyagari, Nikolaos Gatsis, and Ahmad Taha, "Chance Constrained Optimization of Distributed Energy Resources via Affine Policies", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2367. Accessed: May. 30, 2020.
@article{2367-17,
url = {http://sigport.org/2367},
author = {Krishna Sandeep Ayyagari; Nikolaos Gatsis; and Ahmad Taha },
publisher = {IEEE SigPort},
title = {Chance Constrained Optimization of Distributed Energy Resources via Affine Policies},
year = {2017} }
TY - EJOUR
T1 - Chance Constrained Optimization of Distributed Energy Resources via Affine Policies
AU - Krishna Sandeep Ayyagari; Nikolaos Gatsis; and Ahmad Taha
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2367
ER -
Krishna Sandeep Ayyagari, Nikolaos Gatsis, and Ahmad Taha. (2017). Chance Constrained Optimization of Distributed Energy Resources via Affine Policies. IEEE SigPort. http://sigport.org/2367
Krishna Sandeep Ayyagari, Nikolaos Gatsis, and Ahmad Taha, 2017. Chance Constrained Optimization of Distributed Energy Resources via Affine Policies. Available at: http://sigport.org/2367.
Krishna Sandeep Ayyagari, Nikolaos Gatsis, and Ahmad Taha. (2017). "Chance Constrained Optimization of Distributed Energy Resources via Affine Policies." Web.
1. Krishna Sandeep Ayyagari, Nikolaos Gatsis, and Ahmad Taha. Chance Constrained Optimization of Distributed Energy Resources via Affine Policies [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2367

Using Smart Meter and PMU Data for Load Inference


Power distribution system operators require knowledge of power injections for accomplishing various grid dispatch tasks. Monitoring, collecting, and processing smart meter data across all grid nodes, however, may not be affordable given the communication and storage resources. In this context,

Paper Details

Authors:
Siddharth Bhela, Vassilis Kekatos, Sriharsha Veeramachaneni
Submitted On:
18 November 2017 - 2:34pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

GlobalSIP2017presentation.pdf

(436)

Subscribe

[1] Siddharth Bhela, Vassilis Kekatos, Sriharsha Veeramachaneni, "Using Smart Meter and PMU Data for Load Inference", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2363. Accessed: May. 30, 2020.
@article{2363-17,
url = {http://sigport.org/2363},
author = {Siddharth Bhela; Vassilis Kekatos; Sriharsha Veeramachaneni },
publisher = {IEEE SigPort},
title = {Using Smart Meter and PMU Data for Load Inference},
year = {2017} }
TY - EJOUR
T1 - Using Smart Meter and PMU Data for Load Inference
AU - Siddharth Bhela; Vassilis Kekatos; Sriharsha Veeramachaneni
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2363
ER -
Siddharth Bhela, Vassilis Kekatos, Sriharsha Veeramachaneni. (2017). Using Smart Meter and PMU Data for Load Inference. IEEE SigPort. http://sigport.org/2363
Siddharth Bhela, Vassilis Kekatos, Sriharsha Veeramachaneni, 2017. Using Smart Meter and PMU Data for Load Inference. Available at: http://sigport.org/2363.
Siddharth Bhela, Vassilis Kekatos, Sriharsha Veeramachaneni. (2017). "Using Smart Meter and PMU Data for Load Inference." Web.
1. Siddharth Bhela, Vassilis Kekatos, Sriharsha Veeramachaneni. Using Smart Meter and PMU Data for Load Inference [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2363

Pages