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Robust optimization of electric power generation expansion planning considering uncertainty of climate change
Descriptive
TitleInfo
Title
Robust optimization of electric power generation expansion planning considering uncertainty of climate change
Name
(type = personal)
NamePart
(type = family)
Li
NamePart
(type = given)
Shuya
NamePart
(type = date)
1990-
DisplayForm
Shuya Li
Role
RoleTerm
(authority = RULIB)
author
Name
(type = personal)
NamePart
(type = family)
Coit
NamePart
(type = given)
David W.
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David W. Coit
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
chair
Name
(type = personal)
NamePart
(type = family)
Felder
NamePart
(type = given)
Frank A.
DisplayForm
Frank A. Felder
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Baykal-Gursoy
NamePart
(type = given)
Melike
DisplayForm
Melike Baykal-Gursoy
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Wang
NamePart
(type = given)
Honggang
DisplayForm
Honggang Wang
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
internal member
Name
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NamePart
Rutgers University
Role
RoleTerm
(authority = RULIB)
degree grantor
Name
(type = corporate)
NamePart
Graduate School - New Brunswick
Role
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(authority = RULIB)
school
TypeOfResource
Text
Genre
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theses
OriginInfo
DateCreated
(qualifier = exact)
2014
DateOther
(qualifier = exact);
(type = degree)
2014-05
Place
PlaceTerm
(type = code)
xx
Language
LanguageTerm
(authority = ISO639-2b);
(type = code)
eng
Abstract
(type = abstract)
This research is dedicated to the study of electric power system generation expansion planning considering uncertainty of climate change. Policymakers across the world are increasingly concerned about the effects of climate change and its impact on human systems when making decisions. Electric power Generation Expansion Planning (GEP) problems that determine the optimal expansion capacity and technology under particular technical constraints, given cost and policy assumptions are undoubtedly among those decisions. Now and in the future, climate change is and will be affecting new power plant investment decisions and the electricity generation system in more uncertain ways. The power system needs to be more reliable, cost-effective and environmentally friendly when exposed to higher temperature, less precipitation and more intense and frequent extreme events. However, incorporating the climate change effects into a GEP model has rarely been attempted before in the literature. The best approach to comprehensively model those uncertainties into electricity generation, and to optimize the generation planning under uncertainty needs be studied in a more specific way. In this research, a preliminary GEP model is proposed with available input data from various resources. Discrete scenarios and robust optimization are adopted to specifically model uncertainty. Relationships between climate change and GEP parameters are defined and considered in each scenario. The preliminary GEP model is then solved under each scenario to identify the climate change impact on the generation expansion planning decision. Two robust optimization models are presented and solved to find the optimal results under uncertainty: Model 1 is expected total cost minimization and Model 2 is maximum regret minimization. Both models find a compromise solution that is good for all scenarios, which avoids the possible risk associated with a poor decision that is only optimal for one particular scenario. The results suggest recommendations for further power system uncertainty modeling and risk management.
Subject
(authority = RUETD)
Topic
Industrial and Systems Engineering
RelatedItem
(type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier
(type = RULIB)
ETD
Identifier
ETD_5535
PhysicalDescription
Form
(authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
xiii, 111 p. : ill.
Note
(type = degree)
M.S.
Note
(type = bibliography)
Includes bibliographical references
Note
(type = statement of responsibility)
by Shuya Li
Subject
(authority = ETD-LCSH)
Topic
Electric power systems--Management
Subject
(authority = ETD-LCSH)
Topic
Climatic changes
RelatedItem
(type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier
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rucore19991600001
Location
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(displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier
(type = doi)
doi:10.7282/T3G73C0J
Genre
(authority = ExL-Esploro)
ETD graduate
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Rights
RightsDeclaration
(ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder
(type = personal)
Name
FamilyName
Li
GivenName
Shuya
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime
(encoding = w3cdtf);
(qualifier = exact);
(point = start)
2014-04-16 12:59:46
AssociatedEntity
Name
Shuya Li
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
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(qualifier = exact);
(point = start)
2014-05-31
DateTime
(encoding = w3cdtf);
(qualifier = exact);
(point = end)
2016-05-30
Type
Embargo
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after May 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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