The Bridge - Issue 3, 2020 - 21

THE FUTURE OF RENEWABLE ENERGY CONSUMPTION: Grid-Interactive Efficient Buildings

[7] Bengea, S. C., Kelman, A. D., Borrelli, F., Taylor, R., and Narayanan,
S. 2014. Implementation of model predictive control for an
HVAC system in a mid-size commercial building. HVAC&R
Research, 20, no. 1: 121-135.
[8] Li, P., Li, D., Vrabie, D., Bengea, S., and Mijanovic, S. 2014.
"Experimental demonstration of model predictive control
in a medium-sized commercial building." Presented at the
International High Performance Buildings Conference, West
Lafayette, IN, July 14. https://docs.lib.purdue.edu/ihpbc/153/
[9] Jin, X., Baker, K., Christensen, D., and Isley, S. 2017. "Foresee:
A user-centric home energy management system for energy
efficiency and demand response." Applied Energy 205: 15831595.
[10] Ma, Y., Matuško, J., and Borrelli, F. 2014. "Stochastic model
predictive control for building HVAC systems: Complexity
and conservatism." IEEE Transactions on Control Systems
Technology 23, no.1: 101-116.
[11] Radhakrishnan, N., Srinivasan, S., Su, R., and Poolla, K. 2017.
"Learning-based hierarchical distributed HVAC scheduling with
operational constraints." IEEE Transactions on Control Systems
Technology 26, no.5: 1892-1900.
[12] Morosan, P. D., Bourdais, R., Dumur, D., and Buisson, J. 2010.
"Building temperature regulation using a distributed model
predictive control." Energy and Buildings 42, no. 9: 1445-1452.
[13] Wei, T., Wang, Y., and Zhu, Q. 2017. "Deep reinforcement
learning for building HVAC control." In Proceedings of the 54th
Annual Design Automation Conference 2017 (pp. 1-6).
[14] Amasyali, K., and El-Gohary, N. M. 2018. "A review of datadriven building energy consumption prediction studies."
Renewable and Sustainable Energy Reviews 81: 1192-1205.
[15] Drgoña, J., Picard, D., Kvasnica, M., and Helsen, L. 2018.
"Approximate model predictive building control via machine
learning." Applied Energy 218: 199-216.
[16] Reeve, H, Gourisetti, S., McKenzie, P., Mylrea, M., Ehrlich, P.,
Fink, G., and Vrabie, D. 2020. Challenges and Opportunities
to Secure Buildings from Cyber Threats. Richland, WA: Pacific
Northwest National Laboratory. No. PNNL-29813. https://www.
energy.gov/sites/prod/files/2020/05/f74/bto-pnnl-29813securing-buildings-cyber-threats-051420.pdf

Dr. Nikitha Radhakrishnan, is
a Research Engineer at the Pacific
Northwest National Laboratory
(PNNL) and Technical Advisor for the
U.S. Department of Energy Building
Technologies Office with the Emerging
Technologies program. Her work
focuses on optimization and control
methods for energy-efficient and
demand-flexible building systems.
Prior to joining PNNL in 2016, she was a graduate student
researcher at the Berkeley-Education Alliance for Research
in Singapore (BEARS) and received her Ph.D. from Nanyang
Technological University (NTU), Singapore. She is also a STEM
Ambassador with PNNL's Office of STEM education and is
actively involved in local STEM outreach events.

Feature

Erika Gupta is the Sensors and
Controls Technology Manager at
BTO with the Emerging Technologies
program. Her work leverages her
controls background, focusing on
building energy management controls
and projects supporting controls for
grid-integrated efficient buildings.
She first joined EERE as a technology
development manager in the Fuel
Cell Technologies Office, managing projects that could lower
the cost of hydrogen delivery. Under her management, the
subprogram achieved its cost goal a year ahead of schedule
through innovative control strategies, and several of her
portfolio projects were recognized through R&D 100 awards.
Prior to joining FCTO, she worked in the fuel cell industry as a
systems reliability engineer and then as a lead control systems
engineer on fuel cell battery hybrid systems for forklifts and
distributed steam methane reforming systems at Nuvera Fuel
Cells. She obtained her B.S. in mechanical engineering at
Boston University and M.S. in mechanical engineering, with a
focus on control systems, at Worcester Polytechnic Institute.
Dr. Karma Sawyer is the program
manager for the Emerging
Technologies (ET) program with BTO.
She oversees a diverse portfolio of
research and development program
areas, with the goal of developing
cost-effective, energy-efficient,
flexible building technologies. Her
team supports the development of
innovative solutions and technologies
with partners across academia, national labs, small businesses
and industry in HVAC, windows and envelope, sensors and
controls, solid-state lighting, transactive controls, and building
energy modeling. Prior to joining DOE, Dr. Sawyer worked
as a postdoctoral scholar in the Department of Mechanical
Engineering at the University of California, Berkeley. Dr. Sawyer
was named an AAAS Science and Technology Policy fellow
at ARPA-E (2010) and a fellow at the American Chemical
Society-Petroleum Research Fund Summer School (2006).
She received a B.S. with honors in chemistry from Syracuse
University and a Ph.D. in chemistry from the University of
California at Berkeley.
Monica Neukomm is the
Grid-Interactive Efficient Buildings
(GEB) Coordinator at BTO. She holds
a master's degree in Public Policy,
Energy, and Public Finance from
the University of Maryland and a
bachelor's in Business Administration
from the University of Oregon.

HKN.ORG

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https://docs.lib.purdue.edu/ihpbc/153/ https://www.eia.gov/outlooks/aeo/ https://www.energy.gov/sites/prod/files/2020/05/f74/bto-pnnl-29813-securing-buildings-cyber-threats-051420.pdf https://www.aceee.org/sites/default/files/publications/researchreports/u1704.pdf https://www.energy.gov/sites/prod/files/2020/05/f74/bto-pnnl-29813-securing-buildings-cyber-threats-051420.pdf https://www.aceee.org/sites/default/files/publications/researchreports/u1704.pdf https://www.energy.gov/sites/prod/files/2020/05/f74/bto-pnnl-29813-securing-buildings-cyber-threats-051420.pdf https://www.nrel.gov/docs/fy20osti/75470.pdf https://www.nrel.gov/docs/fy20osti/75470.pdf https://buildingretuning.pnnl.gov/publications/PNNL-25985.pdf https://buildingretuning.pnnl.gov/publications/PNNL-25985.pdf https://www1.eere.energy.gov/buildings/pdfs/75478.pdf https://www1.eere.energy.gov/buildings/pdfs/75478.pdf https://hkn.ieee.org/ https://hkn.ieee.org/

The Bridge - Issue 3, 2020

Table of Contents for the Digital Edition of The Bridge - Issue 3, 2020

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The Bridge - Issue 3, 2020 - Cover1
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