kth.sePublications
Change search
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
  • rtf
Spatial optimization of residential urban district - Energy and water perspectives
Show others and affiliations
2016 (English)In: CUE 2015 - APPLIED ENERGY SYMPOSIUM AND SUMMIT 2015: LOW CARBON CITIES AND URBAN ENERGY SYSTEMS, Elsevier, 2016, p. 38-43Conference paper, Published paper (Refereed)
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. The aim of this paper is to develop a spatial optimization model for the planning of residential urban districts with special consideration of renewables and water harvesting integration. In particular, the paper analyses the optimal configuration of built environment area, PV area, wind turbines number and relative occupation area, battery and water harvester storage capacities, as a function of electricity and water prices. 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. 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. Assuming a built environment area equal to 75% of the total available area, the results show that the reliability of the renewables and water harvesting system cannot exceed the 6475 and 2500 hours/year, respectively. The life cycle costs of integrating renewables and water harvesting into residential districts are mainly sensitive to the battery system specific costs since most of the highest renewables reliabilities are guaranteed through the energy storage system.

Place, publisher, year, edition, pages
Elsevier, 2016. p. 38-43
Series
Energy Procedia, ISSN 1876-6102 ; 88
Keywords [en]
Optimization, genetic algorithm, renewable energy, hybrid power systems, water harvesting, residential urban districts
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:kth:diva-197822DOI: 10.1016/j.egypro.2016.06.011ISI: 000387975200006Scopus ID: 2-s2.0-85007574574OAI: oai:DiVA.org:kth-197822DiVA, id: diva2:1060015
Conference
Applied Energy Symposium and Summit - Low Carbon Cities and Urban Energy Systems (CUE), NOV 15-17, 2015, Fuzhou, PEOPLES R CHINA
Note

QC 20161227

Available from: 2016-12-27 Created: 2016-12-08 Last updated: 2022-06-27Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Yan, Jinyue

Search in DiVA

By author/editor
Yan, Jinyue
By organisation
Energy Processes
Energy Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 286 hits
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
  • rtf