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dc.contributor.authorLaasasenaho, K.
dc.contributor.authorLensu, Anssi
dc.contributor.authorLauhanen, R.
dc.contributor.authorRintala, J.
dc.date.accessioned2019-05-24T11:58:25Z
dc.date.available2021-05-19T21:35:08Z
dc.date.issued2019fi
dc.identifier.citationLaasasenaho, K., Lensu, A., Lauhanen, R., & Rintala, J. (2019). GIS-data related route optimization, hierarchical clustering, location optimization, and kernel density methods are useful for promoting distributed bioenergy plant planning in rural areas. <em>Sustainable Energy Technologies and Assessments</em>, 32, 47-57. <a href="https://doi.org/10.1016/j.seta.2019.01.006">doi:10.1016/j.seta.2019.01.006</a>fi
dc.identifier.otherTUTKAID_80621
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/64192
dc.description.abstractCurrently, geographic information system (GIS) models are popular for studying location-allocation-related questions concerning bioenergy plants. The aim of this study was to develop a model to investigate optimal locations for two different types of bioenergy plants, for farm and centralized biogas plants, and for wood terminals in rural areas based on minimizing transportation distances. The optimal locations of biogas plants were determined using location optimization tools in R software, and the optimal locations of wood terminals were determined using kernel density tools in ArcGIS. The present case study showed that the utilized GIS tools are useful for bioenergy-related decision-making to identify potential bioenergy areas and to optimize biomass transportation, and help to plan power plant sizing when candidate bioenergy plant locations have not been defined in advance. In the study area, it was possible to find logistically viable locations for 13 farm biogas plants (>100 kW) and for 8 centralized biogas plants (>300 kW) using a 10-km threshold for feedstock supply. In the case of wood terminals, the results identified the most intensive wood reserves near the highest road classes, and two potential locations were determined.fi
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherElsevier BV
dc.relation.ispartofseriesSustainable Energy Technologies and Assessments
dc.rightsCC BY-NC-ND 4.0
dc.subject.otherkiertotalousfi
dc.subject.otherbiokaasufi
dc.subject.otherbiomassafi
dc.subject.othertuotantoketjutfi
dc.subject.otheroptimointifi
dc.subject.otherpaikkatietojärjestelmätfi
dc.subject.otherbiogasfi
dc.subject.othercircular economyfi
dc.subject.otherlocation-allocationfi
dc.subject.othernetwork analysisfi
dc.subject.otherwood terminalfi
dc.titleGIS-data related route optimization, hierarchical clustering, location optimization, and kernel density methods are useful for promoting distributed bioenergy plant planning in rural areasfi
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-201905242791
dc.contributor.laitosBio- ja ympäristötieteiden laitosfi
dc.contributor.laitosThe Department of Biological and Environmental Scienceen
dc.contributor.oppiaineYmpäristötiede ja -teknologia
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.date.updated2019-05-24T09:15:04Z
dc.description.reviewstatuspeerReviewed
dc.format.pagerange47-57
dc.relation.issn2213-1388
dc.relation.numberinseries0
dc.relation.volume32
dc.type.versionacceptedVersion
dc.rights.copyright© 2019 Elsevier Ltd. All rights reserved.
dc.rights.accesslevelopenAccessfi
dc.format.contentfulltext
dc.rights.urlhttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.relation.doi10.1016/j.seta.2019.01.006


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CC BY-NC-ND 4.0
Except where otherwise noted, this item's license is described as CC BY-NC-ND 4.0