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Autonomous Energy Grids

Autonomous energy grids can self-organize and control themselves using advanced machine learning and simulation to create resilient, reliable, and affordable optimized energy systems.

Current frameworks to monitor, control, and optimize large-scale energy systems are becoming increasingly inadequate because of higher levels of distributed energy resources—including variable generation, energy storage, and controllable loads—being deployed into power systems; the data deluge from pervasive metering of energy grids; and the shaping of multi-level ancillary-service markets. NREL is therefore working to develop autonomous energy grids that are optimized for secure, resilient, and economic operations through advanced science in controls, optimization, big-data analytics, and complex systems.


Autonomous Energy Grids, 51st Hawaii International Conference on System Sciences (2018)
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 autonomous energy grid vision.


NREL hosted the Autonomous Energy Grids Workshop Sept. 13–14, 2017. The workshop brought together experts in the fields of nonlinear control theory, optimization theory, big data analytics, and complex systems simulation to discuss research needs in autonomous energy grids.


Ben Kroposki | 303-275-2979