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Comparison of Mixed-Integer Programming and Genetic Algorithm Methods for Distributed Generation Planning

contributor authorFoster, J.D.
contributor authorBerry, Adam M.
contributor authorBoland, Natashia
contributor authorWaterer, Hamish
date accessioned2020-03-12T18:31:45Z
date available2020-03-12T18:31:45Z
date issued2014
identifier issn0885-8950
identifier other6654301.pdf
identifier urihttp://libsearch.um.ac.ir:80/fum/handle/fum/961517?show=full
formatgeneral
languageEnglish
publisherIEEE
titleComparison of Mixed-Integer Programming and Genetic Algorithm Methods for Distributed Generation Planning
typeJournal Paper
contenttypeMetadata Only
identifier padid7994325
subject keywordsdistributed power generation
subject keywordsdistribution networks
subject keywordselectric generators
subject keywordsgenetic algorithms
subject keywordsinteger programming
subject keywordsload flow
subject keywordspower generation planning
subject keywordsAC power flow approach
subject keywordsMIP methods
subject keywordsdistributed generation planning
subject keywordsdistribution network
subject keywordsgenetic algorithm
subject keywordsinteger generator placement variable
subject keywordslinear DC power flow approximation
subject keywordsmixed-integer programming
subject keywordsnonlinear DC power flow approximation
subject keywordsDistributed power generation
subject keywordsGenerators
subject keywordsGenetic algorithms
subject keywordsOptimization
subject keywordsPlanning
subject keywordsProgrammin
identifier doi10.1109/TPWRS.2013.2287880
journal titlePower Systems, IEEE Transactions on
journal volume29
journal issue2
filesize1818695
citations0


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