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Optimal design and control of cool thermal energy storage as a distributed energy resource
Heine, Karl W.
Heine, Karl W.
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2021
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2022-03-10
Abstract
The electric grid of the future is envisioned to be a smart grid, where electricity ismanaged in coordinated manner between suppliers and users. To achieve this, a high level of
electric demand flexibility must be integrated into our building infrastructure. In the U.S., 9% of
all electricity generated is used to cool buildings, making this end-use an ideal target for active
management through cool thermal energy storage (CTES) technologies. Historic uses for CTES
are designed around central chilled water plants, but these systems cool less than 25% of U.S.
commercial floorspace. Emerging technologies are under development to serve the many smaller
distributed cooling systems, such as rooftop units (RTUs), and have the potential to add CTES to
an additional 66% of cooled commercial floorspace. However, these unitary thermal storage
systems (UTSS) lack the modeling and analysis tools to evaluate them in the future interactive
grid context.
The purpose of this research is to develop the modeling and optimization tools necessary
to not only examine UTSS within specific building applications, but also within the multibuilding, connected community context. To do so, new simulation tools for the U.S. Department
of Energy’s OpenStudio energy modeling platform are developed, and a novel mixed-integer
linear program is devised to optimize the design and dispatch of multiple CTES technologies,
both UTSS and central systems. An integrated simulation-optimization workflow is created to
allow for rapid customized analysis. Several case studies are presented illustrating the benefits of
community-scale optimization and the impacts of storage costs and utility rate structure on CTES
design and dispatch. CTES modeling results, demonstrating the energy and flexibility tradeoffs
of various implementations are presented. Optimization results are described in terms of
minimum cost, optimal design, and optimal dispatch, with analysis on the CTES impacts on the
aggregated community electricity use. It is further demonstrated that community-scale
optimization yields greater cost savings potential than an individual-building approach and that
certain CTES technologies are more appropriate for different demand-response cost signals.
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