ETA 2021 Strategic Plan - Flipbook - Page 76
managed closely? What model fidelity is needed
given uncontrollable uncertainty? What temporal
and spatial domain can include electrical
grid interactions that can be calibrated and
tested with existing data? By answering these
questions, we hope to identify the scientific
breakthroughs needed to achieve the critical
societal and economic potential that could arise
from coupling transportation, buildings, and
industrial energy systems, and highlighting the
latest advances in the computational, economic,
and policy methods needed for them.
Testbed for the Study of Co-Simulation
Controls and Testing Component
Technologies
Testing the performance of co-simulation
platforms and controls at scale is essential for
the adoption of emerging and state-of-the-art
technologies (computation and hardware).
However, for practical reasons, few testbeds
exist. This is understandable given the
limitations of controlling a system that seeks
to integrate conveyance, transmission, and use
optimally, and that honors the complexities
arising from inherent uncertainties and
variability (e.g., user preference, meteorology,
model misspecification error). And yet,
testbeds at intermediate scale are essential for
development and future testing and validation of
simulation capabilities. In the years that follow,
ETA will explore these questions in several
ways. One area of work is to use Berkeley Lab’s
facilities as Living Lab testbeds. This effort builds
off current DOE funded research using model
predictive control at Wang Hall, demonstrating
the ability to reduce energy and provide flexible
loads in response to real-time electric price
and GHG signals. The research also will include
FLEXLAB/FLEXGRID, and other facilities within
the national laboratory complex that may be
suitable to provide real test data to calibrate and
validate the performance of future simulation
capabilities that will emerge. Many questions
must be answered: What type of hybrid physical
and virtual system could be suitable for testing
grid-level co-simulation? What computational
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abstractions could be allowed but still maintain
the tangible nature of a physical electrical
system with its accompanying complexities?
How would production and pricing be simulated
realistically? How can stakeholder concerns (e.g.,
system stability, cost, equity) be evaluated? In
the preliminary stages of this initiative we seek
not to supplant existing testbed construction,
but rather to provide enabling technologies that
help them represent their connection to real
synchronous electrical power grids.
Cybersecurity
The U.S. electric grid is a cyber-physical system,
interweaving an array of physics-based dynamic
processes with analog and digital sensing and
control systems. The future highly integrated
energy system will add the complexity of deeper
links throughout the energy production-touse chain. The stability of such a system will
be governed largely by actively monitoring the
interactions of the physical and cyber-based
components, and how operations or decisions
made on one sector present intended (and
unintended) consequences to other parts of
the network. IES cybersecurity means strictly
enforcing sustained control of a dynamic
system that includes countless entryways to
the grid for accidental errors and intentional
attacks. Unfortunately, as the number and
sophistication of these cyber-based systems
grow, the system relationships are increasingly
difficult to articulate mathematically. This focus
area, in part, seeks to develop the scientific
toolset needed to characterize the stability of
high-dimensional, nonlinear, uncertain dynamic
systems as a function of physical properties (e.g.,
mass) and cyber properties (e.g., gains in control
loops). To do so, it will develop techniques from
machine learning, for example, to collapse
multidimensional dynamics into scalar functions
characterizing the stability of the system. To
train and test these models will require use of
high-fidelity simulations of a microgrid with
high penetration of renewable energy with its
typical internal control loops of DC/AC inverter
power electronic devices. We will seek to identify
