Optimization of multi-energy storage in urban building clusters
Created by W.Langdon from
gp-bibliography.bib Revision:1.8414
- @Article{Algburi:2025:rineng,
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author = "Sameer Algburi and Aymen Mohammed and
Hassan Falah Fakhruldeen and Ibrahim Abdullah and Israa Alhani and
Ali Khudhair and Qusay Hassan and Michael Ssebunya and
Feryal Ibrahim Jabbar",
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title = "Optimization of multi-energy storage in urban building
clusters",
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journal = "Results in Engineering",
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year = "2025",
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volume = "26",
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pages = "105427",
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keywords = "genetic algorithms, genetic programming, Energy
management, Storage systems, Optimization, Demand
response, Efficiency",
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ISSN = "2590-1230",
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URL = "
https://www.sciencedirect.com/science/article/pii/S2590123025014975",
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DOI = "
doi:10.1016/j.rineng.2025.105427",
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abstract = "A data-driven optimisation framework was developed to
enhance energy performance in building clusters through
multi-energy storage systems, combining electrical and
thermal solutions. The approach used surrogate
modelling, symbolic regression, and genetic programming
to simulate energy consumption, integrate weather and
tariff data, and refine storage strategies across
varied building types. Applied to a cluster in Bismayah
city, Iraq, the methodology evaluated HVAC
configurations, facade designs, and thermal mass levels
to tailor storage capacity recommendations. Results
revealed a 38 percent reduction in peak grid import and
a 24.6 percent drop in overall energy consumption when
hybrid energy storage was implemented. A thermal energy
storage tank capacity of 4651 kWh, coupled with a
battery storage unit of 342 kWh, demonstrated a 35
percent decrease in energy costs. Demand response
participation increased by 45 percent through strategic
use of pre-cooling routines and temperature reset
controls. TES-only configurations achieved energy usage
of 16.3 kWh/msquared, while hybrid configurations
further reduced to 8.7 kWh/msquared. Budget analyses
showed that investments ranging from $2.6 million to
$10.4 million proportionally enhanced system
performance without over-sizing. The integration of
Battery and Thermal Energy Storage with Phase Change
Materials further supported passive thermal control,
reducing HVAC reliance during peak hours",
- }
Genetic Programming entries for
Sameer Algburi
Aymen Mohammed
Hassan Falah Fakhruldeen
Ibrahim Abdullah
Israa Alhani
Ali Khudhair
Qusay Hassan
Michael Ssebunya
Feryal Ibrahim Jabbar
Citations