The Bridge - Issue 3, 2020 - 16

Feature

THE FUTURE OF RENEWABLE ENERGY TRANSMISSION: An Autonomous Energy Grid

steps of demonstrating these algorithms in real time for
real-world devices in the laboratory and now in smart
homes. Additional work will be needed in controls,
optimization, data analytics, complex systems, and
cybersecurity to implement the AEG across the entire
U.S. grid.

Acknowledgments
This work was authored in part by the National
Renewable Energy Laboratory, operated by Alliance
for Sustainable Energy, LLC, for the U.S. Department
of Energy (DOE) under Contract No. DE-AC3608GO28308. This work was supported in part by
the Laboratory Directed Research and Development
(LDRD) program at NREL. The views expressed in the
article do not necessarily represent the views of the
DOE or the U.S. Government. The U.S. Government
retains and the publisher, by accepting the article for
publication, acknowledges that the U.S. Government
retains a nonexclusive, paid-up, irrevocable, worldwide
license to publish or reproduce the published form
of this work, or allow others to do so, for U.S.
Government purposes.
References
[1] Kroposki, B., E. Dall'Anese, A. Bernstein, Y. Zhang, and B.
Hodge. "Autonomous Energy Grids." Proceedings of the
51st Hawaii International Conference on System Sciences.
January 2018. https://scholarspace.manoa.hawaii.edu/
bitstream/10125/50229/1/paper0342.pdf
[2] "Autonomous Energy Grids: Controlling the Future Grid
with Large Amounts of Distributed Energy Resources" by B.
Kroposki et al. IEEE Power and Energy Magazine, November/
December 2020.
[3] Bernstein, A., E. Dall'Anese, and A. Simonetto. "Online primaldual methods with measurement feedback for time-varying
convex optimization." IEEE Transactions on Signal Processing
67 (8), 1978-1991, 2019 https://ieeexplore.ieee.org/
document/8631190
[4] Colombino, M., E. Dall'Anese, and A. Bernstein. "Online
optimization as a feedback controller: Stability and Tracking."
IEEE Transactions on Control of Network Systems (March
2019). https://ieeexplore.ieee.org/document/8673636
[5] Zhou, X., Z. Liu, C. Zhao, and L. Chen. "Accelerated voltage
regulation in multi-phase distribution networks based on
hierarchical distributed algorithm." IEEE Transactions on Power
Systems (October 2019).
[6] Bernstein, A., and E. Dall'Anese. "Real-Time Feedback-Based
Optimization of Distribution Grids: A Unified Approach."
IEEE Transactions on Control of Network Systems 6, no. 3
(September 2019).

THE BRIDGE

Dr. Benjamin Kroposki is the
Director of the Power Systems
Engineering Center at the National
Renewable Energy Laboratory (NREL)
where he leads NREL's strategic
research in the design, planning
and operations of electrical power
systems. He has over 25 years of
experience in the design, testing,
and integration of renewable and
distributed power systems and has
more than 140 publications in these areas. Dr. Kroposki
received his BSEE and MSEE from Virginia Tech and Ph.D.
from the Colorado School of Mines. As an IEEE Fellow, Dr.
Kroposki was recognized for his leadership in renewable
and distributed energy systems integration. Dr. Kroposki
is the recipient of the IEEE Power & Energy Society (PES)
Ramakumar Family Renewable Energy Excellence Award.
Dr. Andrey Bernstein is the
manager of the Energy Systems
Optimization and Control Group
at the National Renewable Energy
Laboratory. He received the B.Sc. and
M.Sc. degrees (summa cum laude)
in electrical engineering and the
Ph.D. degree in electrical engineering
from the Technion-Israel Institute
of Technology. Prior to working at
NREL he was a Visiting Researcher
with Columbia University, a Visiting Assistant Professor with
Stony Brook University, and a Post-Doctoral Researcher
with the Laboratory for Communications and Applications,
École Polytechnique Fédérale de Lausanne, Switzerland. His
research interests are in decision and control problems in
complex environments and related optimization and machine
learning methods, with particular application to intelligent
power and energy systems. His current research focuses on
real-time optimization of power distribution systems with
a high penetration of renewables and machine learning
methods for grid data analytics.
Dr. Jennifer King is a Research
Engineer at the National Renewable
Energy Laboratory working at the
National Wind Technology Center
on hybrid system modeling and
control. This includes developing
model and real-time distributed
optimization capabilities for wind
farm control, optimally designing and
operating utility-scale hybrid power
plants as well as developing a control
frameworks for large-scale autonomous energy systems. Jen
obtained her PhD in Aerospace Engineering and Mechanics
from the University of Minnesota where her primary focus
was on reduced-order modeling for wind farm control. Her
current research focus areas are in reduced-order modeling,
distributed control/optimization, and co-design.

https://scholarspace.manoa.hawaii.edu/bitstream/10125/50229/1/paper0342.pdf https://scholarspace.manoa.hawaii.edu/bitstream/10125/50229/1/paper0342.pdf https://ieeexplore.ieee.org/document/8631190 https://ieeexplore.ieee.org/document/8631190 https://ieeexplore.ieee.org/document/8673636 https://hkn.ieee.org/ https://hkn.ieee.org/

The Bridge - Issue 3, 2020

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