Core team:

Paul Hines

University of Vermont

School of Engineering, Associate Professor

Hines's work broadly focuses on finding ways to make electric energy more reliable, more affordable, with less environmental impact. Particular topics of interest include understanding the mechanisms by which small problems in the power grid become large blackouts, identifying and mitigating the stresses caused by large amounts of electric vehicle charging, and quantifying the impact of high penetrations of wind/solar on electricity systems.

Most recent papers:

Mitigating the Risk of Voltage Collapse using Statistical Measures from PMU Data.

Samuel Chevalier, Paul Hines. Preprint, 2018.
[pdf] [arXiv]

Systems and methods for randomized, packet-based power management of conditionally-controlled loads and bi-directional distributed energy storage systems.

Jeff Frolik, Paul Hines, Mads R. Almassalkhi. 2018.
[pdf] [journal page]

Can an influence graph driven by outage data determine transmission line upgrades that mitigate cascading blackouts?.

Kai Zhoa, Ian Dobson, Paul Hines, Zhaoyu Wang. IEEE International Conference Probabilistic Methods Applied to Power Systems (PMAPS), , , 2018.
[pdf] [journal page]

Crowdsourcing Predictors of Residential Electric Energy Usage.

Mark Wagy, Joshua Bongard, Jim Bagrow, Paul Hines. IEEE Systems Journal, , , 2017.
[pdf] [journal page] [arXiv]

(show all)

Most recent press: