Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/50229

Autonomous Energy Grids

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Title:Autonomous Energy Grids
Authors:Kroposki, Benjamin
Dall'Anese, Emiliano
Bernstein, Andrey
Zhang, Yingchen
Hodge, Bri-Mathias
Keywords:Resilient Networks
Autonomous Grids, Optimization, Controls, Big Data, Complex Systems
Date Issued:03 Jan 2018
Abstract:Current frameworks to monitor, control, and optimize large-scale energy systems are becoming increasingly inadequate because of significantly high penetration levels of variable generation and distributed energy resources being integrated into electric power systems; the deluge of data from pervasive metering of energy grids; and a variety of new market mechanisms, including multilevel ancillary services. This paper outlines the concept of autonomous energy grids (AEGs). These systems are supported by a scalable, reconfigurable, and self-organizing information and control infrastructure, are extremely secure and resilient (self-healing), and can self-optimize in real time to ensure economic and reliable performance while systematically integrating energy in all forms. AEGs rely on cellular building blocks that can self-optimize when isolated from a larger grid and participate in optimal operation when interconnected to a larger grid. This paper describes the key concepts and research necessary in the broad domains of optimization theory, control theory, big data analytics, and complex system theory and modeling to realize the AEG vision.
Pages/Duration:10 pages
URI:http://hdl.handle.net/10125/50229
ISBN:978-0-9981331-1-9
DOI:10.24251/HICSS.2018.341
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Resilient Networks


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