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dc.contributor.authorNieto-Martin, Jen
dc.contributor.authorKipouros, Timoleonen
dc.contributor.authorSavill, Men
dc.contributor.authorWoodruff, Jen
dc.contributor.authorButans, Jen
dc.date.accessioned2018-11-23T00:32:40Z
dc.date.available2018-11-23T00:32:40Z
dc.date.issued2018-01-01en
dc.identifier.issn1076-2787
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/285828
dc.description.abstractThe transition to a secure low-carbon system is raising a set of uncertainties when planning the path to a reliable decarbonised supply. The electricity sector is committing large investments in the transmission and distribution sector upon 2050 in order to ensure grid resilience. The cost and limited flexibility of traditional approaches to 11 kV network reinforcement threaten to constrain the uptake of low-carbon technologies. This paper investigates the suitability and cost-effectiveness of smart grid techniques along with traditional reinforcements for the 11 kV electricity distribution network, in order to analyse expected investments up to 2050 under different DECC demand scenarios. The evaluation of asset planning is based on an area of study in Milton Keynes (East Midlands, United Kingdom), being composed of six 11 kV primaries. To undertake this, the analysis used a revolutionary new model tool for electricity distribution network planning, called scenario investment model (SIM). Comprehensive comparisons of short- and long-term evolutionary investment planning strategies are presented. The work helps electricity network operators to visualise and design operational planning investments providing bottom-up decision support.
dc.description.sponsorshipOFGEM and the Low Carbon Network Fund
dc.publisherWiley-Blackwell
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleTechnoeconomic distribution network planning using smart grid techniques with evolutionary self-healing network statesen
dc.typeArticle
prism.publicationDate2018en
prism.publicationNameComplexityen
prism.volume2018en
dc.identifier.doi10.17863/CAM.33172
dcterms.dateAccepted2018-10-10en
rioxxterms.versionofrecord10.1155/2018/1543179en
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2018-01-01en
dc.contributor.orcidKipouros, Timoleon [0000-0003-3392-283X]
dc.identifier.eissn1099-0526
rioxxterms.typeJournal Article/Reviewen


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International