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Eleven Nearly Zero New Building Life Cycle Cost and Dynamic Performance Optimization by Computer Modeling in Cold Climate

Zakis, Krisjanis ; Zakis, Valdis and Arfvidsson, Jesper LU (2016) In Procedia Computer Science 104. p.302-312
Abstract

The study aims to generate Building system performance design optimization for 11 nearly zero energy new building (nZEnB) types in the cold climate conditions for decision making. The coupling evolutionary algorithms with a building dynamic simulation engine has been applied to reach the "true" optimal solutions. Life cycle cost and performance modulation was carried out in the multi-objective computer model. The calculation of cost optimality was performed on predefined 11 reference building types by taking into account prices as they have been paid by the end consumer including taxes. 960 000 simulation variants were calculated for each building type. This paper proposes coupling of multivariate engine with the Pareto analysis for... (More)

The study aims to generate Building system performance design optimization for 11 nearly zero energy new building (nZEnB) types in the cold climate conditions for decision making. The coupling evolutionary algorithms with a building dynamic simulation engine has been applied to reach the "true" optimal solutions. Life cycle cost and performance modulation was carried out in the multi-objective computer model. The calculation of cost optimality was performed on predefined 11 reference building types by taking into account prices as they have been paid by the end consumer including taxes. 960 000 simulation variants were calculated for each building type. This paper proposes coupling of multivariate engine with the Pareto analysis for reduction of costs and energy use, while taking in consideration fiscal and resource economy long term trends as well as fossil energy replacement with the renewable ones from investment perspective.

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author
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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Life cycle cost optimality, Nearly zero energy new building, Pareto curve
in
Procedia Computer Science
volume
104
pages
11 pages
publisher
Elsevier
external identifiers
  • scopus:85016036010
  • wos:000399478800041
ISSN
1877-0509
DOI
10.1016/j.procs.2017.01.139
language
English
LU publication?
yes
id
f3742807-bfee-48b4-ae5e-501fd4c931e8
date added to LUP
2017-04-10 10:53:53
date last changed
2024-04-14 08:27:21
@article{f3742807-bfee-48b4-ae5e-501fd4c931e8,
  abstract     = {{<p>The study aims to generate Building system performance design optimization for 11 nearly zero energy new building (nZEnB) types in the cold climate conditions for decision making. The coupling evolutionary algorithms with a building dynamic simulation engine has been applied to reach the "true" optimal solutions. Life cycle cost and performance modulation was carried out in the multi-objective computer model. The calculation of cost optimality was performed on predefined 11 reference building types by taking into account prices as they have been paid by the end consumer including taxes. 960 000 simulation variants were calculated for each building type. This paper proposes coupling of multivariate engine with the Pareto analysis for reduction of costs and energy use, while taking in consideration fiscal and resource economy long term trends as well as fossil energy replacement with the renewable ones from investment perspective.</p>}},
  author       = {{Zakis, Krisjanis and Zakis, Valdis and Arfvidsson, Jesper}},
  issn         = {{1877-0509}},
  keywords     = {{Life cycle cost optimality; Nearly zero energy new building; Pareto curve}},
  language     = {{eng}},
  month        = {{12}},
  pages        = {{302--312}},
  publisher    = {{Elsevier}},
  series       = {{Procedia Computer Science}},
  title        = {{Eleven Nearly Zero New Building Life Cycle Cost and Dynamic Performance Optimization by Computer Modeling in Cold Climate}},
  url          = {{http://dx.doi.org/10.1016/j.procs.2017.01.139}},
  doi          = {{10.1016/j.procs.2017.01.139}},
  volume       = {{104}},
  year         = {{2016}},
}