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Optimization of a residential district with special consideration on energy and water reliability
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0002-1351-9245
Georgia Institute of Technology, US.
ABB AB, Västerås, Sweden.
Mälardalen University, School of Business, Society and Engineering, Future Energy Center. KTH Royal Institute of Technology, Sweden.
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2017 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 194, 751-764 p.Article in journal (Refereed) Published
Abstract [en]

Many cities around the world have reached a critical situation when it comes to energy and water supply, threatening the urban sustainable development. From an engineering and architecture perspective it is mandatory to design cities taking into account energy and water issues to achieve high living and sustainability standards. The aim of this paper is to develop an optimization model for the planning of residential urban districts with special consideration of renewables and water harvesting integration. The optimization model is multi-objective which uses a genetic algorithm to minimize the system life cycle costs, and maximize renewables and water harvesting reliability through dynamic simulations. The developed model can be used for spatial optimization design of new urban districts. It can also be employed for analyzing the performances of existing urban districts under an energy-water-economic viewpoint.

The optimization results show that the reliability of the hybrid renewables based power system can vary between 40 and 95% depending on the scenarios considered regarding the built environment area and on the cases concerning the overall electric load. The levelized cost of electricity vary between 0.096 and 0.212 $/kW h. The maximum water harvesting system reliability vary between 30% and 100% depending on the built environment area distribution. For reliabilities below 20% the levelized cost of water is kept below 1 $/m3 making competitive with the network water tariff.

Place, publisher, year, edition, pages
2017. Vol. 194, 751-764 p.
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-34033DOI: 10.1016/j.apenergy.2016.10.005ISI: 000399623600069OAI: oai:DiVA.org:mdh-34033DiVA: diva2:1052508
Available from: 2016-12-06 Created: 2016-12-06 Last updated: 2017-05-19Bibliographically approved

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Campana, PietroLundblad, AndersKarlsson, BjörnYan, Jinyue
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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
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