LAPSE:2023.19564
Published Article
LAPSE:2023.19564
Improved Air-Conditioning Demand Response of Connected Communities over Individually Optimized Buildings
Nicolas A. Campbell, Patrick E. Phelan, Miguel Peinado-Guerrero, Jesus R. Villalobos
March 9, 2023
Abstract
Connected communities potentially offer much greater demand response capabilities over singular building energy management systems (BEMS) through an increase of connectivity. The potential increase in benefits from this next step in connectivity is still under investigation, especially when applied to existing buildings. This work utilizes EnergyPlus simulation results on eight different commercial prototype buildings to estimate the potential savings on peak demand and energy costs using a mixed-integer linear programming model. This model is used in two cases: a fully connected community and eight separate buildings with BEMS. The connected community is optimized using all zones as variables, while the individual buildings are optimized separately and then aggregated. These optimization problems are run for a range of individual zone flexibility values. The results indicate that a connected community offered 60.0% and 24.8% more peak demand savings for low and high flexibility scenarios, relative to individually optimized buildings. Energy cost optimization results show only marginally better savings of 2.9% and 6.1% for low and high flexibility, respectively.
Keywords
air-conditioning, building energy management systems, coincidence factor, connected communities, demand response, electricity cost reduction, peak demand reduction
Suggested Citation
Campbell NA, Phelan PE, Peinado-Guerrero M, Villalobos JR. Improved Air-Conditioning Demand Response of Connected Communities over Individually Optimized Buildings. (2023). LAPSE:2023.19564
Author Affiliations
Campbell NA: School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ 85281, USA [ORCID]
Phelan PE: School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ 85281, USA [ORCID]
Peinado-Guerrero M: School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ 85281, USA
Villalobos JR: School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ 85281, USA
Journal Name
Energies
Volume
14
Issue
18
First Page
5926
Year
2021
Publication Date
2021-09-18
ISSN
1996-1073
Version Comments
Original Submission
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PII: en14185926, Publication Type: Journal Article
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LAPSE:2023.19564
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https://doi.org/10.3390/en14185926
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