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Multi-objective generation expansion planning considering uncertainty and modeling with the Pareto Uncertainty Index

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TitleInfo
Title
Multi-objective generation expansion planning considering uncertainty and modeling with the Pareto Uncertainty Index
Name (type = personal)
NamePart (type = family)
Selçuklu
NamePart (type = given)
Saltuk Buğra
NamePart (type = date)
1984-
DisplayForm
Saltuk Buğra
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Coit
NamePart (type = given)
David
DisplayForm
David Coit
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
chair
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
Graduate School - New Brunswick
Role
RoleTerm (authority = RULIB)
school
TypeOfResource
Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (encoding = w3cdtf); (qualifier = exact)
2015
DateOther (qualifier = exact); (type = degree)
2015-10
CopyrightDate (encoding = w3cdtf); (qualifier = exact)
2015
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
Many real life optimization problems are multi-objective problems where objectives under consideration usually conflict with each other and they are also stochastic due to inherent uncertainties. The electricity Generation Expansion Planning (GEP) problem is an example of such problems in which the goal is to expand the electric power network with new power plant investments including renewable resources. Decisions are made where and when to build new power plants and which technology to choose for new investments. Objectives can include but are not limited to minimization of the cost and pollutant emissions and maximization of reliability. There are inherent uncertainties in the GEP problem due to climate change, demand increase, fuel prices, technological progress and many other aspects that have to be considered. Some of these uncertainties directly affect the objective functions and some affect the constraint sets in the optimization model. In this study, a new uncertainty metric, the Pareto Uncertainty Index (PUI), is presented. The PUI includes uncertainty as part of the Pareto optimality concept so that the decision or policy maker can observe the uncertainty of Pareto optimal solutions. Using the PUI approach for objective function uncertainties and chance constrained programming or scenarios for constraint set uncertainties, a new multi-objective stochastic genetic algorithm, the Pareto Uncertain Genetic Algorithm (PUGA), is presented in this research, as well. In contrast with the other multi-objective genetic algorithms and classical methods, PUGA can incorporate both the multi-objective and stochastic aspects of problem solving without any transformation. A new post-Pareto pruning approach that reduces the number of Pareto optimal solutions to a smaller practical set is also included in PUGA with the help of the uncertainty information preserved in the PUI. Furthermore, this uncertainty information is used for risk assessments of solutions depending on the risk preferences of decision makers. The PUI and PUGA concepts are demonstrated and tested on several problems including the US Northeast region generation expansion planning (NEGEP) problem.
Subject (authority = RUETD)
Topic
Industrial and Systems Engineering
Subject (authority = ETD-LCSH)
Topic
Electric utilities--Mathematical models
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_6685
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (xx, 206 p. : ill.)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Note (type = statement of responsibility)
by Saltuk Buğra Selçuklu
RelatedItem (type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
Location
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NjNbRU
Identifier (type = doi)
doi:10.7282/T3WM1GCG
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Selçuklu
GivenName
Saltuk
MiddleName
Buğra
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2015-08-31 02:35:42
AssociatedEntity
Name
Saltuk Selcuklu
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
RightsEvent
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2015-10-31
DateTime (encoding = w3cdtf); (qualifier = exact); (point = end)
2016-10-30
Type
Embargo
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after October 30th, 2016.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical

RULTechMD (ID = TECHNICAL1)
ContentModel
ETD
OperatingSystem (VERSION = 5.1)
windows xp
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