Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Multi-objective optimization and parametric analysis of energy system designs for the Albano university campus in Stockholm
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Building Service and Energy Systems.
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Building Technology.
Akademiska hus.
Akademiska hus.
Show others and affiliations
2017 (English)In: Procedia Engineering, Elsevier, 2017, 621-630 p.Conference paper, Published paper (Other academic)
Abstract [en]

In this study, a multi-objective optimization approach is applied to the energy system design of the Albano university campus in Stockholm. The greenhouse gas emissions, the life cycle cost and the net exergy deficit of the campus are minimized, while the nearly zero energy requirements are respected. Four optimal solutions are identified based on those under equal importance, environment-oriented, economy-oriented, and exergy-oriented scenarios. The energy components of the four scenarios are analyzed and compared. A parametric analysis is conducted to investigate the impact of the variations in a number of economic, environmental and technical parameters on the composition of the optimal solution.

Place, publisher, year, edition, pages
Elsevier, 2017. 621-630 p.
Series
Procedia Engineering, ISSN 1877-7058
National Category
Architecture
Research subject
Civil and Architectural Engineering
Identifiers
URN: urn:nbn:se:kth:diva-192952DOI: 10.1016/j.proeng.2017.04.221ISI: 000404873600063Scopus ID: 2-s2.0-85019337204OAI: oai:DiVA.org:kth-192952DiVA: diva2:974012
Conference
International High- Performance Built Environment Conference – A Sustainable Built Environment Conference 2016 Series (SBE16), iHBE 2016
Note

QC 20160923

Available from: 2016-09-23 Created: 2016-09-23 Last updated: 2017-08-09Bibliographically approved
In thesis
1. Optimal Design of District Energy Systems: a Multi-Objective Approach
Open this publication in new window or tab >>Optimal Design of District Energy Systems: a Multi-Objective Approach
2016 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The aim of this thesis is to develop a holistic approach to the optimal design of energy systems for building clusters or districts. The emerging Albano university campus, which is planned to be a vivid example of sustainable urban development, is used as a case study through collaboration with the property owners, Akademiska Hus and Svenska Bostäder. The design addresses aspects of energy performance, environmental performance, economic performance, and exergy performance of the energy system. A multi-objective optimization approach is applied to minimize objectives such as non-renewable primary energy consumptions, the greenhouse gas emissions, the life cycle cost, and the net exergy deficit. These objectives reflect both practical requirements and research interest. The optimization results are presented in the form of Pareto fronts, through which decision-makers can understand the options and limitations more clearly and ultimately make better and more informed decisions. Sensitivity analyses show that solutions could be sensitive to certain system parameters. To overcome this, a robust design optimization method is also developed and employed to find robust optimal solutions, which are less sensitive to the variation of system parameters. The influence of different preferences for objectives on the selection of optimal solutions is examined. Energy components of the selected solutions under different preference scenarios are analyzed, which illustrates the advantages and disadvantages of certain energy conversion technologies in the pursuit of various objectives. As optimal solutions depend on the system parameters, a parametric analysis is also conducted to investigate how the composition of optimal solutions varies to the changes of certain parameters. In virtue of the Rational Exergy Management Model (REMM), the planned buildings on the Albano campus are further compared to the existing buildings on KTH campus, based on energy and exergy analysis. Four proposed alternative energy supply scenarios as well as the present case are analyzed. REMM shows that the proposed scenarios have better levels of match between supply and demand of exergy and result in lower avoidable CO2 emissions, which promise cleaner energy structures.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2016. 43 p.
Series
TRITA-IES, 2016:05
Keyword
multi-objective optimization, robust design optimization, district energy
National Category
Architecture
Research subject
Civil and Architectural Engineering
Identifiers
urn:nbn:se:kth:diva-192948 (URN)978-91-7729-129-9 (ISBN)
Presentation
2016-10-14, Sal M108, Brinellvägen 23, Kungl Tekniska högskolan, Stockholm, 14:00 (English)
Opponent
Supervisors
Note

QC 20160923

Available from: 2016-09-23 Created: 2016-09-23 Last updated: 2016-09-23Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopushttp://www.sbe16sydney.be.unsw.edu.au/index.html

Search in DiVA

By author/editor
Wang, CongKilkis, SiirMartinac, Ivo
By organisation
Building Service and Energy SystemsBuilding Technology
Architecture

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 178 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf