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Award Abstract #1254549

CAREER: Harnessing Smart Grid Data to Enable Resilient and Efficient Electricity

NSF Org: ECCS
Div Of Electrical, Commun & Cyber Sys
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Initial Amendment Date: January 3, 2013
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Latest Amendment Date: July 8, 2015
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Award Number: 1254549
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Award Instrument: Standard Grant
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Program Manager: Radhakisan S. Baheti
ECCS Div Of Electrical, Commun & Cyber Sys
ENG Directorate For Engineering
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Start Date: September 1, 2013
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End Date: August 31, 2018 (Estimated)
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Awarded Amount to Date: $408,000.00
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Investigator(s): Paul Hines paul.hines@uvm.edu (Principal Investigator)
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Sponsor: University of Vermont & State Agricultural College
85 SO. PROSPECT ST.
BURLINGTON, VT 05405-0160 (802)656-3660
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NSF Program(s): ENERGY,POWER,ADAPTIVE SYS
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Program Reference Code(s): 1045, 155E, 1653, 9150, 9251
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Program Element Code(s): 7607

ABSTRACT

The objective of this research is to harness Smart Grid data (Big Data) to enable more resilient and efficient electricity. Three research sub-projects contribute to this goal. Project 1 combines a new ?Random Chemistry? computational algorithm with complex networks methods to find patterns of vulnerability in power systems, and uses the results to reduce cascading failure blackout risk. Project 2 transforms smart grid data into actionable information about the health of a power grid by looking at statistical properties (structured noise) in data from grid sensors. Projects 1 and 2 seeks to make power grids more resilient to fluctuations from renewable generation or weather events. Project 3 uses crowdsourcing to identify trends affecting residential energy consumption through a web-based energy efficiency social network.

Intellectual Merit

This project integrates research ideas from diverse scientific disciplines, including complex systems, graph theory, data science, computational intelligence and crowdsourcing. Projects 1 and 2 use abstract complex systems approaches, while retaining critical information about the physics of power systems. By using data from real power systems the project will contribute to the emerging field of data science. The third project combines computational intelligence with crowdsourcing in a way that could open new ways to improve energy efficiency.

Broader Impacts

This project tests new educational approaches, including a unique LEGO-based grid simulator, and integrates smart grid data into new courses. New curriculum and a hands on ?smart grid road show? will be leveraged to attract students from diverse educational and demographic backgrounds to study electric energy.


PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 13)
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Alexander D. Hilshey and Paul D. H. Hines and Jonathan R. Dowds. "Estimating the Effect of Electric Vehicle Smart Charging on Distribution Transformer Aging," IEEE Transactions on Smart Grid, v.4, 2013. 

Bevelander, Kirsten E and Kaipainen, Kirsikka and Swain, Robert and Dohle, Simone and Bongard, Josh C and Hines, Paul DH and Wansink, Brian. "Crowdsourcing Novel Childhood Predictors of Adult Obesity," PloS one, v.9, 2014, p. e87756. 

Brummitt, Charles D and Hines, Paul DH and Dobson, Ian and Moore, Cristopher and D'Souza, Raissa M. "Transdisciplinary electric power grid science," Proceedings of the National Academy of Sciences, v.110, 2013, p. 12159--12. 

Eduardo Cotilla-Sanchez and Paul D. H. Hines and Clayton Barrows and Seth Blumsack and Mahendra Patel. "Multi-attribute Partitioning of Power Networks Based on Electrical Distance," IEEE Trans. on Power Systems, v.28, 2013, p. 4979-4987. 

Goodarz Ghanavati and Paul D. H. Hines and Taras I. Lakoba and Eduardo Cotilla-Sanchez. "Understanding early indicators of critical transitions in power systems from autocorrelation functions," IEEE Transactions on Circuits and Systems I: Regular Papers, v.61, 2014. 

Hilshey, A. and Hines, P. and Rezaei, P. and Dowds, J. "Estimating the Impact of Electric Vehicle Smart Charging on Distribution Transformer Aging," Smart Grid, IEEE Transactions on, v.4, 2013, p. 905 - 913. 

Jon Dowds and Paul Hines and Seth Blumsack. "Estimating the impact of fuel-switching between liquid fuels and electricity under electricity-sector carbon-pricing schemes," Socio-Economic Planning Sciences, v.47, 2013, p. 76 -- 88. 

Josh C. Bongard and Paul D. H. Hines and Dylan Conger and Peter Hurd and Zhenyu Lu. "Crowdsourcing Predictors of Behavioral Outcomes," IEEE Transactions on Systems, Man, and Cybernetics--Part A: Systems and Humans, v.43, 2013. 

Pooya Rezaei and Jeff Frolik and Paul Hines. "Packetized Plug-in Electric Vehicle Charge Management," IEEE Trans. Smart Grid, v.5, 2014, p. 642-650. 

Goodarz Ghanavati and Paul D. H. Hines and Taras I. Lakoba. "Identifying Useful Statistical Indicators of Proximity to Instability in Stochastic Power Systems," IEEE Transactions on Power Systems, v.(in pre, 2015. 


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