Repository logo
 
Publication

Optimization techniques for power distribution planning with uncertainties: a comparative study

2009Conference object Restricted access
Simple item page
dc.contributor.authorKhodr, H. M.
dc.contributor.authorVale, Zita
dc.contributor.authorRamos, Carlos
dc.contributor.authorFaria, Pedro
dc.date.accessioned2013-05-16T10:40:50Z
dc.date.available2013-05-16T10:40:50Z
dc.date.issued2009
dc.date.updated2013-04-15T14:35:42Z
dc.description.abstractImportant research effort has been devoted to the topic of optimal planning of distribution systems. The non linear nature of the system, the need to consider a large number of scenarios and the increasing necessity to deal with uncertainties make optimal planning in distribution systems a difficult task. Heuristic techniques approaches have been proposed to deal with these issues, overcoming some of the inherent difficulties of classic methodologies. This paper considers several methodologies used to address planning problems of electrical power distribution networks, namely mixedinteger linear programming (MILP), ant colony algorithms (AC), genetic algorithms (GA), tabu search (TS), branch exchange (BE), simulated annealing (SA) and the Bender´s decomposition deterministic non-linear optimization technique (BD). Adequacy of theses techniques to deal with uncertainties is discussed. The behaviour of each optimization technique is compared from the point of view of the obtained solution and of the methodology performance. The paper presents results of the application of these optimization techniques to a real case of a 10-kV electrical distribution system with 201 nodes that feeds an urban area.por
dc.identifierDOI 10.1109/PES.2009.5275569
dc.identifier.isbn978-1-4244-4241-6
dc.identifier.urihttp://hdl.handle.net/10400.22/1599
dc.language.isoengpor
dc.publisherIEEEpor
dc.relation.publisherversionhttp://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5275569por
dc.subjectFuzzy power flowpor
dc.subjectHeuristic optimizationpor
dc.subjectOptimization methodspor
dc.subjectPower distribution planningpor
dc.subjectUncertaintiespor
dc.titleOptimization techniques for power distribution planning with uncertainties: a comparative studypor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceCalgary, Canada, 2009por
oaire.citation.titleIEEE Power & Energy Society General Meeting (PES)por
person.familyNameVale
person.familyNameRamos
person.familyNameFaria
person.givenNameZita
person.givenNameCarlos
person.givenNamePedro
person.identifier632184
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.ciencia-id1011-FAFC-AEBA
person.identifier.ciencia-idB212-2309-F9C3
person.identifier.orcid0000-0002-4560-9544
person.identifier.orcid0000-0002-5143-1711
person.identifier.orcid0000-0002-5982-8342
person.identifier.ridA-5824-2012
person.identifier.ridK-7403-2014
person.identifier.scopus-author-id7004115775
person.identifier.scopus-author-id7201559105
rcaap.rightsclosedAccesspor
rcaap.typeconferenceObjectpor
relation.isAuthorOfPublicationff1df02d-0c0f-4db1-bf7d-78863a99420b
relation.isAuthorOfPublication43ef055e-80e6-4b31-8400-2d3592927e03
relation.isAuthorOfPublication35e6a4ab-f644-4bc5-b6fc-9fd89c23d6c6
relation.isAuthorOfPublication.latestForDiscovery43ef055e-80e6-4b31-8400-2d3592927e03

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
COM_HKhodr_2009_GECAD.pdf
Size:
1.4 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

ISEP – GECAD – Comunicações em eventos científicos