Autonomous Energy Grids

Benjamin Kroposki, Emiliano Dall-Anese, Andrey Bernstein, Yingchen Zhang, Bri-Mathias Hodge

Research output: Contribution to conferencePaperpeer-review

6 Scopus Citations


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.

Original languageAmerican English
Number of pages10
StatePublished - 2018
Event51st Annual Hawaii International Conference on System Sciences, HICSS 2018 - Big Island, United States
Duration: 2 Jan 20186 Jan 2018


Conference51st Annual Hawaii International Conference on System Sciences, HICSS 2018
Country/TerritoryUnited States
CityBig Island

Bibliographical note

See NREL/CP-5D00-68712 for preprint

NREL Publication Number

  • NREL/CP-5D00-80521


  • autonomous energy grids
  • big data analytics
  • complex system theory
  • control theory
  • microgrid
  • optimization
  • renewable integration
  • smart grids


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