Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/67183
DC Field | Value | Language |
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dc.contributor | Department of Building Services Engineering | - |
dc.creator | Campana, PE | en_US |
dc.creator | Quan, SJ | en_US |
dc.creator | Robbio, FI | en_US |
dc.creator | Lundblad, A | en_US |
dc.creator | Zhang, Y | en_US |
dc.creator | Ma, T | en_US |
dc.creator | Yan, J | en_US |
dc.date.accessioned | 2017-05-23T01:54:46Z | - |
dc.date.available | 2017-05-23T01:54:46Z | - |
dc.identifier.uri | http://hdl.handle.net/10397/67183 | - |
dc.description | Applied Energy Symposium and Summit on Low-Carbon Cities and Urban Energy Systems, CUE 2015, Fuzhou, China, 15-17 November 2015 | en_US |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.rights | © 2016 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). | en_US |
dc.rights | The following publication Campana, P. E., Quan, S. J., Robbio, F. I., Lundblad, A., Zhang, Y., Ma, T., & Yan, J. (2016). Spatial optimization of residential urban district - energy and water perspectives. Energy Procedia, 88, 38-43 is available athttps://dx.doi.org/10.1016/j.egypro.2016.06.011 | en_US |
dc.subject | Genetic algorithm | en_US |
dc.subject | Hybrid power systems | en_US |
dc.subject | Optimization | en_US |
dc.subject | Renewable energy | en_US |
dc.subject | Residential urban districts | en_US |
dc.subject | Water harvesting | en_US |
dc.title | Spatial optimization of residential urban district - energy and water perspectives | en_US |
dc.type | Conference Paper | en_US |
dc.identifier.spage | 38 | en_US |
dc.identifier.epage | 43 | en_US |
dc.identifier.volume | 88 | en_US |
dc.identifier.doi | 10.1016/j.egypro.2016.06.011 | en_US |
dcterms.abstract | 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. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Energy procedia, 2016, v. 88, p. 38-43 | en_US |
dcterms.isPartOf | Energy procedia | en_US |
dcterms.issued | 2016 | - |
dc.identifier.isi | WOS:000387975200006 | - |
dc.identifier.scopus | 2-s2.0-85007574574 | - |
dc.relation.conference | Applied Energy Symposium and Summit on Low-Carbon Cities and Urban Energy Systems [CUE] | - |
dc.identifier.eissn | 1876-6102 | en_US |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_IR/PIRA | en_US |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Conference Paper |
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File | Description | Size | Format | |
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Campana_Spatial_Residential_Urban.pdf | 700.5 kB | Adobe PDF | View/Open |
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