ETA 2021 Strategic Plan - Flipbook - Page 38
Risk-controlled Expansion Planning with
Distributed Resources (REPAIR). Power
system planning has become more challenging,
and it requires new methodologies and tools
to help utilities prioritize grid investments,
optimal power flow (both at distribution
and transmission levels), risk-constrained
optimization, game theory, and decision
support models. The REPAIR model is building
foundational capabilities to enable riskcontrolled decisions in utility grid planning, to
prevent and mitigate the impact of outages
caused by regular equipment failures or by
high-impact low-probability events such as
storms, earthquakes, or wildfires that may cause
longer-term interruptions of service from the
transmission system.
Control and Optimization. ETA is developing
novel control and optimization approaches to
manage DER, to provide power systems services
at minimal cost. ETA’s research employs spatiotemporal hierarchical controls, consistent with
wholesale market timelines, to utilize DER for
various power systems needs. Power-flowdriven optimization problems couple DER
operations with distribution voltage and power
management with wholesale market-based
energy and ancillary services to simultaneously
unlock value at multiple levels. ETA employs both
centralized and distributed real-time control
techniques. For power system applications,
ETA researchers have pioneered a real-time,
distributed, model-free control method, called
Extremum Seeking.
ETA’s Integrated Modeling Tool (IMT). IMT
captures the dynamic between consumers’
adoption of DERs, distribution grid planning,
and rate design, providing a unique modeling
framework to support utility and regulatory
decisions around electricity rate structures and
cost recovery.
Our evolving world continually offers new
demands and requires ever-more integrated
solutions. The challenge of decarbonizing
cross-sectoral infrastructure at scale and at
reasonable cost will require new platforms for
co-simulation that do not currently exist and
safe testbeds to study controls and validate
emerging technologies on those platforms. It
also will require new mathematical models that
can keep pace with rapidly evolving technologies
and their integration pathways, to address the
vulnerabilities between cyber-physical systems.
The IES initiative represents a newly focused
effort to achieve the breakthroughs needed
to meet the goals realizable only through the
real-time cooperation of integrated energy
systems that build upon the long-standing
core competencies of ETA’s domain expertise
— transportation, buildings, and the grid —
and their interactions with renewable energy
sources and energy storage and conversion
technologies. To this end, the initiative initially
targets three focus areas: (1) Breakthroughs in
Practical Platforms for Co-Simulation Software,
to enable these disparate systems to function
as an ensemble in real time; (2) a Testbed for
the Study of CoSimulation Controls and Testing
Component Technologies, which will function at
a scale suitable for scientific study of co-controls
and for the testing of component technologies/
hardware; and (3) Cybersecurity, to expand on
the role of security in IES cyber-physical systems
for detection of threats and system instabilities,
as well as computational methods that mitigate
them.
Under each topic, our initial efforts will use
a traditional scientific method to review the
integrated energy systems research domain, to
hypothesize potential roadblocks to realizing a
future energy system that is 100% renewably
powered and financially preferable to extant
systems. Hypotheses will cover the importance
of applications, the validity of methods, and
prioritization of the scientific breakthroughs
needed. To develop technologies that can lead
to commercial products, we will design thought
experiments to confirm these hypotheses and
meet with leading researchers to gather data
(information and opinion).
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Focus Areas
Breakthroughs in Practical Platforms for
Co-Simulation Software
As infrastructure co-simulation moves toward
increased complexity, a paradigm shift is needed
to create a simulation platform that enables
seamless integration of technologies and
systems across sectors. Policymakers, industry,
and scientists have identified a growing need
for better computational models for design and
operation that allow for one to consider a wide
variety of planning/feasibility opportunities and
threats in order to enable future operational
uses. Examples include: comparative analyses
of energy technologies (such as seasonal energy
storage) at national, sectoral, and technological
levels; development of energy use scenarios at
sub-hourly scales; unforeseen consequences
of one energy system imposing (nonlinear)
disruptions on another; common-cause threats
due to wide-ranging extreme weather; and
real-time, grid-aware building energy control
that minimizes cost and carbon emissions from
multiple energy sources and carriers. However,
a critical challenge with systems is how to
construct models at a suitable spatiotemporal
scale for their intended application that can be
still be performance tested (i.e., validated). On
this front, we aim to develop a roadmap and
solutions for how physics-based models can
supplement artificial intelligence (AI) models
to overcome the typical hurdles of using each
type — for example, by developing a reduced
order model to represent formal abstractions of
energy sectors suitable for applications.
Many questions remain unanswered: Is there
a new design paradigm for IES, given the
constraints of existing energy, building, and
transportation infrastructure? What would
be the underlying design principles? What
abstractions of real systems are needed? What
simulation and optimization tools are needed?
Which uncertainties or variability need to be
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