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Title: Autonomous Energy Grids: Preprint

Conference ·
OSTI ID:1399662

With much higher levels of distributed energy resources - variable generation, energy storage, and controllable loads just to mention a few - being deployed into power systems, the data deluge from pervasive metering of energy grids, and the shaping of multi-level ancillary-service markets, current frameworks to monitoring, controlling, and optimizing large-scale energy systems are becoming increasingly inadequate. This position paper outlines the concept of 'Autonomous Energy Grids' (AEGs) - systems that are supported by a scalable, reconfigurable, and self-organizing information and control infrastructure, can be extremely secure and resilient (self-healing), and self-optimize themselves in real-time for economic and reliable performance while systematically integrating energy in all forms. AEGs rely on scalable, self-configuring cellular building blocks that ensure that each 'cell' can self-optimize when isolated from a larger grid as well as partaking in the optimal operation of a larger grid when interconnected. To realize this vision, this paper describes the concepts and key research directions in the broad domains of optimization theory, control theory, big-data analytics, and complex system modeling that will be necessary to realize the AEG vision.

Research Organization:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
DOE Contract Number:
AC36-08GO28308
OSTI ID:
1399662
Report Number(s):
NREL/CP-5D00-68712
Resource Relation:
Conference: To be presented at the Hawaii International Conference on System Sciences, 3-6 January 2018, Waikoloa, Hawaii
Country of Publication:
United States
Language:
English