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Climate resilient interconnected infrastructure : Co-optimization of energy systems and urban morphology

Perera, A. T.D. ; Javanroodi, Kavan LU and Nik, Vahid M. LU orcid (2021) In Applied Energy 285.
Abstract

Co-optimization of urban morphology and distributed energy systems is key to curb energy consumption and optimally exploit renewable energy in cities. Currently available optimization techniques focus on either buildings or energy systems, mostly neglecting the impact of their interactions, which limits the renewable energy integration and robustness of the energy infrastructure; particularly in extreme weather conditions. To move beyond the current state-of-the-art, this study proposes a novel methodology to optimize urban energy systems as interconnected urban infrastructures affected by urban morphology. A set of urban morphologies representing twenty distinct neighborhoods is generated based on fifteen influencing parameters. The... (More)

Co-optimization of urban morphology and distributed energy systems is key to curb energy consumption and optimally exploit renewable energy in cities. Currently available optimization techniques focus on either buildings or energy systems, mostly neglecting the impact of their interactions, which limits the renewable energy integration and robustness of the energy infrastructure; particularly in extreme weather conditions. To move beyond the current state-of-the-art, this study proposes a novel methodology to optimize urban energy systems as interconnected urban infrastructures affected by urban morphology. A set of urban morphologies representing twenty distinct neighborhoods is generated based on fifteen influencing parameters. The energy performance of each urban morphology is assessed and optimized for typical and extreme warm and cold weather datasets in three time periods from 2010 to 2039, 2040 to 2069, and 2070 to 2099 for Athens, Greece. Pareto optimization is conducted to generate an optimal energy system and urban morphology. The results show that a thus optimized urban morphology can reduce the levelized cost for energy infrastructure by up to 30%. The study reveals further that the current building form and urban density of the modelled neighborhoods will lead to an increase in the energy demand by 10% and 27% respectively. Furthermore, extreme climate conditions will increase energy demand by 20%, which will lead to an increment in the levelized cost of energy infrastructure by 40%. Finally, it is shown that co-optimization of both urban morphology and energy system will guarantee climate resilience of urban energy systems with a minimum investment.

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author
; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Energy systems, Interconnected infrastructure, Sustainable cities, Urban form, Urban planning
in
Applied Energy
volume
285
article number
116430
publisher
Elsevier
external identifiers
  • scopus:85099266991
ISSN
0306-2619
DOI
10.1016/j.apenergy.2020.116430
project
Flexible energy system integration using concept development, demonstration and replication
language
English
LU publication?
yes
id
3d5e634e-a17a-4e22-bb16-a80f6214c3ba
date added to LUP
2021-01-25 07:48:41
date last changed
2023-02-01 23:37:38
@article{3d5e634e-a17a-4e22-bb16-a80f6214c3ba,
  abstract     = {{<p>Co-optimization of urban morphology and distributed energy systems is key to curb energy consumption and optimally exploit renewable energy in cities. Currently available optimization techniques focus on either buildings or energy systems, mostly neglecting the impact of their interactions, which limits the renewable energy integration and robustness of the energy infrastructure; particularly in extreme weather conditions. To move beyond the current state-of-the-art, this study proposes a novel methodology to optimize urban energy systems as interconnected urban infrastructures affected by urban morphology. A set of urban morphologies representing twenty distinct neighborhoods is generated based on fifteen influencing parameters. The energy performance of each urban morphology is assessed and optimized for typical and extreme warm and cold weather datasets in three time periods from 2010 to 2039, 2040 to 2069, and 2070 to 2099 for Athens, Greece. Pareto optimization is conducted to generate an optimal energy system and urban morphology. The results show that a thus optimized urban morphology can reduce the levelized cost for energy infrastructure by up to 30%. The study reveals further that the current building form and urban density of the modelled neighborhoods will lead to an increase in the energy demand by 10% and 27% respectively. Furthermore, extreme climate conditions will increase energy demand by 20%, which will lead to an increment in the levelized cost of energy infrastructure by 40%. Finally, it is shown that co-optimization of both urban morphology and energy system will guarantee climate resilience of urban energy systems with a minimum investment.</p>}},
  author       = {{Perera, A. T.D. and Javanroodi, Kavan and Nik, Vahid M.}},
  issn         = {{0306-2619}},
  keywords     = {{Energy systems; Interconnected infrastructure; Sustainable cities; Urban form; Urban planning}},
  language     = {{eng}},
  publisher    = {{Elsevier}},
  series       = {{Applied Energy}},
  title        = {{Climate resilient interconnected infrastructure : Co-optimization of energy systems and urban morphology}},
  url          = {{http://dx.doi.org/10.1016/j.apenergy.2020.116430}},
  doi          = {{10.1016/j.apenergy.2020.116430}},
  volume       = {{285}},
  year         = {{2021}},
}