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Multi-objective stochastic models for electricity generation expansion planning problems considering risk
Descriptive
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Text
TitleInfo
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Title
Multi-objective stochastic models for electricity generation expansion planning problems considering risk
Identifier
ETD_2536
Identifier
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http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000053282
Language
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eng
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theses
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Topic
Industrial and Systems Engineering
Subject
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(authority = ETD-LCSH)
Topic
Electric power production--Mathematical models
Subject
(ID = SBJ-3);
(authority = ETD-LCSH)
Topic
Stochastic models
Subject
(ID = SBJ-4);
(authority = ETD-LCSH)
Topic
Monte Carlo method
Abstract
(type = abstract)
This dissertation is focused on the development of mathematical models to solve electricity generation expansion planning problems where important problem objectives, such as cost, greenhouse gas and pollutant emissions and reliability are explicitly considered under an uncertain environment. Generation expansion planning problems are solved to determine what, when and where to built the new technologies. The main objective of the power grid is to provide an economic and reliable energy supply to consumers. Due to the increasing awareness for clean air and global warming, the power grid should also be designed to be environmental friendly. In this research, an approach is proposed to determine critical components for the grid with regard to reliability, cost and gas emissions, and an optimization approach is proposed to select a set of availability scenarios which represent the stochastic characteristics of the system and to determine the associated probabilities. The problem is formulated as a two stage multi-objective stochastic optimization problem considering the generated scenarios. There are also some other technological developments, called "Smart Grid Technologies" which can affect the grid. The impacts of "Smart Grid Technologies" on the grid are that (i) shift/reduce energy demand, (ii) increase the effective availability of the system components, and (iii) reduce the energy loss during transmission. This research is the first comprehensive attempt to include the Smart Grid technologies, affecting the availabilities and transmission loss, into the generation expansion planning problem. This research also leads to the contributions for developing models where risk aversion is incorporated into the model, improving solution efficiency by extending Benders decomposition and improving solution techniques for multi-objective optimization problems.
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electronic resource
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xvi, 235 p. : ill.
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Ph.D.
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Includes abstract
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Vita
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Includes bibliographical references
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by Hatice Tekiner
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Tekiner
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Hatice
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1981-
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author
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Hatice Tekiner
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Coit
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David W.
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chair
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David W. Coit
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Albin
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Susan L.
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Susan L. Albin
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Elsayed A.
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Elsayed A. Elsayed
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Luxhoj
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James T.
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James T. Luxhoj
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Felder
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Frank A.
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Frank A. Felder
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Rutgers University
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degree grantor
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Graduate School - New Brunswick
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school
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2010
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2010
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xx
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Rutgers University Electronic Theses and Dissertations
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ETD
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Graduate School - New Brunswick Electronic Theses and Dissertations
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rucore19991600001
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NjNbRU
Identifier
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doi:10.7282/T32R3RRD
Genre
(authority = ExL-Esploro)
ETD doctoral
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Rights
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The author owns the copyright to this work.
Copyright
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Copyright protected
Availability
Status
Open
Reason
Permission or license
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Tekiner
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Hatice
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DateTime
2010-04-06 11:59:11
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Hatice Tekiner
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Rutgers University. Graduate School - New Brunswick
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Author Agreement License
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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.
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