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Emerging: Smart Grid & Energy Management

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.

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Authors:
Fuxi Wen, David Yau
Submitted On:
19 April 2018 - 2:51pm
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Poster presentation

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[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. 27, 2018.
@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

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Authors:
Krishna Sandeep Ayyagari, Nikolaos Gatsis, and Ahmad Taha
Submitted On:
21 November 2017 - 1:47pm
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talk_GLOBALSIP_2017.pdf

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[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. 27, 2018.
@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,

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Authors:
Siddharth Bhela, Vassilis Kekatos, Sriharsha Veeramachaneni
Submitted On:
18 November 2017 - 2:34pm
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GlobalSIP2017presentation.pdf

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[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. 27, 2018.
@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

DELAY AWARE MEASUREMENTS GATHERING IN WAMS COMMUNICATION NETWORK


The rapid deployment of phasor measurements units (PMUs) supporting Wide Area Measurement System (WAMS) in smart grid has opened opportunities to enhance the grid operations through the introduction of WAMS applications. However, the increased deployment of synchrophasor technologies increases the effective attack surface available to attackers and exposesWAMS applications. Such applications have strict and stringent delay requirements, e.g., end to end delay as well as delay variation between measurements from different PMUs.

WAMS_2.pdf

PDF icon WAMS_2.pdf (123 downloads)

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Authors:
Parisa Akaber, Mosaddek H. K. Tushar, Mourad Debbabi, Chadi Assi
Submitted On:
13 November 2017 - 11:10am
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[1] Parisa Akaber, Mosaddek H. K. Tushar, Mourad Debbabi, Chadi Assi, "DELAY AWARE MEASUREMENTS GATHERING IN WAMS COMMUNICATION NETWORK", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2334. Accessed: May. 27, 2018.
@article{2334-17,
url = {http://sigport.org/2334},
author = {Parisa Akaber; Mosaddek H. K. Tushar; Mourad Debbabi; Chadi Assi },
publisher = {IEEE SigPort},
title = {DELAY AWARE MEASUREMENTS GATHERING IN WAMS COMMUNICATION NETWORK},
year = {2017} }
TY - EJOUR
T1 - DELAY AWARE MEASUREMENTS GATHERING IN WAMS COMMUNICATION NETWORK
AU - Parisa Akaber; Mosaddek H. K. Tushar; Mourad Debbabi; Chadi Assi
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2334
ER -
Parisa Akaber, Mosaddek H. K. Tushar, Mourad Debbabi, Chadi Assi. (2017). DELAY AWARE MEASUREMENTS GATHERING IN WAMS COMMUNICATION NETWORK. IEEE SigPort. http://sigport.org/2334
Parisa Akaber, Mosaddek H. K. Tushar, Mourad Debbabi, Chadi Assi, 2017. DELAY AWARE MEASUREMENTS GATHERING IN WAMS COMMUNICATION NETWORK. Available at: http://sigport.org/2334.
Parisa Akaber, Mosaddek H. K. Tushar, Mourad Debbabi, Chadi Assi. (2017). "DELAY AWARE MEASUREMENTS GATHERING IN WAMS COMMUNICATION NETWORK." Web.
1. Parisa Akaber, Mosaddek H. K. Tushar, Mourad Debbabi, Chadi Assi. DELAY AWARE MEASUREMENTS GATHERING IN WAMS COMMUNICATION NETWORK [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2334

A Game-Theoretic Approach for Communication-Free Voltage-VAR Optimization

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Authors:
Kaiqing Zhang; Hao Zhu
Submitted On:
13 November 2017 - 12:01am
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GlobalSIP2017.pdf

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[1] Kaiqing Zhang; Hao Zhu, "A Game-Theoretic Approach for Communication-Free Voltage-VAR Optimization", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2329. Accessed: May. 27, 2018.
@article{2329-17,
url = {http://sigport.org/2329},
author = {Kaiqing Zhang; Hao Zhu },
publisher = {IEEE SigPort},
title = {A Game-Theoretic Approach for Communication-Free Voltage-VAR Optimization},
year = {2017} }
TY - EJOUR
T1 - A Game-Theoretic Approach for Communication-Free Voltage-VAR Optimization
AU - Kaiqing Zhang; Hao Zhu
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2329
ER -
Kaiqing Zhang; Hao Zhu. (2017). A Game-Theoretic Approach for Communication-Free Voltage-VAR Optimization. IEEE SigPort. http://sigport.org/2329
Kaiqing Zhang; Hao Zhu, 2017. A Game-Theoretic Approach for Communication-Free Voltage-VAR Optimization. Available at: http://sigport.org/2329.
Kaiqing Zhang; Hao Zhu. (2017). "A Game-Theoretic Approach for Communication-Free Voltage-VAR Optimization." Web.
1. Kaiqing Zhang; Hao Zhu. A Game-Theoretic Approach for Communication-Free Voltage-VAR Optimization [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2329

Dynamic ADMM For Real-Time Optimal Power Flow


This paper considers distribution networks featuring distributed energy resources (DERs), and develops a dynamic optimization method to maximize given operational objectives in real time while adhering to relevant network constraints. The design of the dynamic algorithm is based on suitable linearization of the AC power flow equations, and it leverages the

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Authors:
Emiliano Dall'Anese, Mingyi Hong
Submitted On:
12 November 2017 - 11:33am
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globalsip_poster.pdf

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[1] Emiliano Dall'Anese, Mingyi Hong, "Dynamic ADMM For Real-Time Optimal Power Flow", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2316. Accessed: May. 27, 2018.
@article{2316-17,
url = {http://sigport.org/2316},
author = {Emiliano Dall'Anese; Mingyi Hong },
publisher = {IEEE SigPort},
title = {Dynamic ADMM For Real-Time Optimal Power Flow},
year = {2017} }
TY - EJOUR
T1 - Dynamic ADMM For Real-Time Optimal Power Flow
AU - Emiliano Dall'Anese; Mingyi Hong
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2316
ER -
Emiliano Dall'Anese, Mingyi Hong. (2017). Dynamic ADMM For Real-Time Optimal Power Flow. IEEE SigPort. http://sigport.org/2316
Emiliano Dall'Anese, Mingyi Hong, 2017. Dynamic ADMM For Real-Time Optimal Power Flow. Available at: http://sigport.org/2316.
Emiliano Dall'Anese, Mingyi Hong. (2017). "Dynamic ADMM For Real-Time Optimal Power Flow." Web.
1. Emiliano Dall'Anese, Mingyi Hong. Dynamic ADMM For Real-Time Optimal Power Flow [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2316

INCORPORATING TIME-OF-DAY USAGE PATTERNS INTO NON-INTRUSIVE LOAD MONITORING


Load monitoring techniques determine the appliances that are turned ON within a given period of time in a household or workplace. They can help occupants optimize their
power consumption behavior. Load monitoring is broadly classified as intrusive or nonintrusive. Intrusive load monitoring requires the attachment of individual sensors to each

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Authors:
Chinthaka Dinesh, Stephen Makanin, Ivan V. Bajic
Submitted On:
11 November 2017 - 12:08am
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INCORPORATING TIME-OF-DAY USAGE PATTERNS INTO NON-INTRUSIVE LOAD MONITORING.pdf

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[1] Chinthaka Dinesh, Stephen Makanin, Ivan V. Bajic, "INCORPORATING TIME-OF-DAY USAGE PATTERNS INTO NON-INTRUSIVE LOAD MONITORING", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2303. Accessed: May. 27, 2018.
@article{2303-17,
url = {http://sigport.org/2303},
author = {Chinthaka Dinesh; Stephen Makanin; Ivan V. Bajic },
publisher = {IEEE SigPort},
title = {INCORPORATING TIME-OF-DAY USAGE PATTERNS INTO NON-INTRUSIVE LOAD MONITORING},
year = {2017} }
TY - EJOUR
T1 - INCORPORATING TIME-OF-DAY USAGE PATTERNS INTO NON-INTRUSIVE LOAD MONITORING
AU - Chinthaka Dinesh; Stephen Makanin; Ivan V. Bajic
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2303
ER -
Chinthaka Dinesh, Stephen Makanin, Ivan V. Bajic. (2017). INCORPORATING TIME-OF-DAY USAGE PATTERNS INTO NON-INTRUSIVE LOAD MONITORING. IEEE SigPort. http://sigport.org/2303
Chinthaka Dinesh, Stephen Makanin, Ivan V. Bajic, 2017. INCORPORATING TIME-OF-DAY USAGE PATTERNS INTO NON-INTRUSIVE LOAD MONITORING. Available at: http://sigport.org/2303.
Chinthaka Dinesh, Stephen Makanin, Ivan V. Bajic. (2017). "INCORPORATING TIME-OF-DAY USAGE PATTERNS INTO NON-INTRUSIVE LOAD MONITORING." Web.
1. Chinthaka Dinesh, Stephen Makanin, Ivan V. Bajic. INCORPORATING TIME-OF-DAY USAGE PATTERNS INTO NON-INTRUSIVE LOAD MONITORING [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2303

Autonomous Navigation of UAV in Large-scale Unknown Complex Environment with Deep Reinforcement Learning

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Authors:
Chao Wang, Jian Wang, Xudong Zhang, Xiao Zhang
Submitted On:
10 November 2017 - 6:54am
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oral_presentation_1159.pdf

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[1] Chao Wang, Jian Wang, Xudong Zhang, Xiao Zhang, "Autonomous Navigation of UAV in Large-scale Unknown Complex Environment with Deep Reinforcement Learning", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2289. Accessed: May. 27, 2018.
@article{2289-17,
url = {http://sigport.org/2289},
author = {Chao Wang; Jian Wang; Xudong Zhang; Xiao Zhang },
publisher = {IEEE SigPort},
title = {Autonomous Navigation of UAV in Large-scale Unknown Complex Environment with Deep Reinforcement Learning},
year = {2017} }
TY - EJOUR
T1 - Autonomous Navigation of UAV in Large-scale Unknown Complex Environment with Deep Reinforcement Learning
AU - Chao Wang; Jian Wang; Xudong Zhang; Xiao Zhang
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2289
ER -
Chao Wang, Jian Wang, Xudong Zhang, Xiao Zhang. (2017). Autonomous Navigation of UAV in Large-scale Unknown Complex Environment with Deep Reinforcement Learning. IEEE SigPort. http://sigport.org/2289
Chao Wang, Jian Wang, Xudong Zhang, Xiao Zhang, 2017. Autonomous Navigation of UAV in Large-scale Unknown Complex Environment with Deep Reinforcement Learning. Available at: http://sigport.org/2289.
Chao Wang, Jian Wang, Xudong Zhang, Xiao Zhang. (2017). "Autonomous Navigation of UAV in Large-scale Unknown Complex Environment with Deep Reinforcement Learning." Web.
1. Chao Wang, Jian Wang, Xudong Zhang, Xiao Zhang. Autonomous Navigation of UAV in Large-scale Unknown Complex Environment with Deep Reinforcement Learning [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2289

Autonomous Navigation of UAV in Large-scale Unknown Complex Environment with Deep Reinforcement Learning

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Authors:
Chao Wang, Jian Wang, Xudong Zhang, Xiao Zhang
Submitted On:
10 November 2017 - 6:54am
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oral_presentation_1159.pdf

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[1] Chao Wang, Jian Wang, Xudong Zhang, Xiao Zhang, "Autonomous Navigation of UAV in Large-scale Unknown Complex Environment with Deep Reinforcement Learning", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2288. Accessed: May. 27, 2018.
@article{2288-17,
url = {http://sigport.org/2288},
author = {Chao Wang; Jian Wang; Xudong Zhang; Xiao Zhang },
publisher = {IEEE SigPort},
title = {Autonomous Navigation of UAV in Large-scale Unknown Complex Environment with Deep Reinforcement Learning},
year = {2017} }
TY - EJOUR
T1 - Autonomous Navigation of UAV in Large-scale Unknown Complex Environment with Deep Reinforcement Learning
AU - Chao Wang; Jian Wang; Xudong Zhang; Xiao Zhang
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2288
ER -
Chao Wang, Jian Wang, Xudong Zhang, Xiao Zhang. (2017). Autonomous Navigation of UAV in Large-scale Unknown Complex Environment with Deep Reinforcement Learning. IEEE SigPort. http://sigport.org/2288
Chao Wang, Jian Wang, Xudong Zhang, Xiao Zhang, 2017. Autonomous Navigation of UAV in Large-scale Unknown Complex Environment with Deep Reinforcement Learning. Available at: http://sigport.org/2288.
Chao Wang, Jian Wang, Xudong Zhang, Xiao Zhang. (2017). "Autonomous Navigation of UAV in Large-scale Unknown Complex Environment with Deep Reinforcement Learning." Web.
1. Chao Wang, Jian Wang, Xudong Zhang, Xiao Zhang. Autonomous Navigation of UAV in Large-scale Unknown Complex Environment with Deep Reinforcement Learning [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2288

Enhancing Observability in Power Distribution Grids


Power distribution grids are currently challenged by observability issues due to limited metering infrastructure. On the other hand, smart meter data, including local voltage magnitudes and power injections, are collected at grid nodes with renewable generation and demand response programs. A power flow-based approach using these data is put forth here to infer the unknown power injections at non-metered grid nodes.

ICASSP1.pdf

PDF icon ICASSP1.pdf (200 downloads)

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Authors:
Siddharth Bhela, Vassilis Kekatos, Liang Zhang, Sriharsha Veeramachaneni
Submitted On:
18 November 2017 - 2:40pm
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ICASSP1.pdf

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[1] Siddharth Bhela, Vassilis Kekatos, Liang Zhang, Sriharsha Veeramachaneni , "Enhancing Observability in Power Distribution Grids", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1758. Accessed: May. 27, 2018.
@article{1758-17,
url = {http://sigport.org/1758},
author = {Siddharth Bhela; Vassilis Kekatos; Liang Zhang; Sriharsha Veeramachaneni },
publisher = {IEEE SigPort},
title = {Enhancing Observability in Power Distribution Grids},
year = {2017} }
TY - EJOUR
T1 - Enhancing Observability in Power Distribution Grids
AU - Siddharth Bhela; Vassilis Kekatos; Liang Zhang; Sriharsha Veeramachaneni
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1758
ER -
Siddharth Bhela, Vassilis Kekatos, Liang Zhang, Sriharsha Veeramachaneni . (2017). Enhancing Observability in Power Distribution Grids. IEEE SigPort. http://sigport.org/1758
Siddharth Bhela, Vassilis Kekatos, Liang Zhang, Sriharsha Veeramachaneni , 2017. Enhancing Observability in Power Distribution Grids. Available at: http://sigport.org/1758.
Siddharth Bhela, Vassilis Kekatos, Liang Zhang, Sriharsha Veeramachaneni . (2017). "Enhancing Observability in Power Distribution Grids." Web.
1. Siddharth Bhela, Vassilis Kekatos, Liang Zhang, Sriharsha Veeramachaneni . Enhancing Observability in Power Distribution Grids [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1758

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