Abstract
The traditional implementation of cool thermal energy storage (CTES) must be reimagined within the context of a dynamic grid and smart buildings operating as connected communities. As most buildings do not operate central chillers or connect to district cooling loops, this necessitates a broader use of packaged CTES. Our objective is to begin answering the question of how such packaged CTES should be implemented within a connected community. We do so by presenting a simulation–optimization workflow employing building energy modeling software and a mixed-integer linear program to design and dispatch a packaged CTES technology to achieve minimum total annual cost. We demonstrate this methodology on a seven-building case study using current utility rates and find that total annual cooling energy costs can be reduced by 17.8% compared to baseline, after accounting for the cost of storage. We perform three parametric sensitivity studies to evaluate modeling assumptions and obtain the prioritization of storage procurement as a function of annualized life-cycle cost of storage. We find that a community optimization approach provides significantly different results than individual building optimizations and provides greater savings compared to baseline.
Original language | American English |
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Article number | 117147 |
Number of pages | 14 |
Journal | Applied Energy |
Volume | 298 |
DOIs | |
State | Published - 2021 |
Bibliographical note
Publisher Copyright:© 2021 Elsevier Ltd
NREL Publication Number
- NREL/JA-5500-78717
Keywords
- Connected community optimization
- Cool thermal energy storage
- Energy storage
- EnergyPlus
- Mixed-integer linear programming
- Packaged ice storage
- Unitary thermal storage systems