Economic efficiencies of the energy flows from the primary resource suppliers to the electric load centers

dc.contributor.advisor James D. McCalley
dc.contributor.author Quelhas Alves de Freitas, Ana
dc.contributor.department Electrical and Computer Engineering
dc.date 2018-08-24T18:43:06.000
dc.date.accessioned 2020-06-30T07:45:23Z
dc.date.available 2020-06-30T07:45:23Z
dc.date.copyright Sun Jan 01 00:00:00 UTC 2006
dc.date.issued 2006-01-01
dc.description.abstract <p>The economic efficiency of the electric energy system depends not only on the performance of the electric generation and transmission subsystems, but also on the ability to produce and transport the various forms of primary energy, particularly coal and natural gas. However, electric power systems have traditionally been developed and operated without a conscious awareness of the energy system-wide implications, namely the consideration of the integrated dynamics with the fuel markets and infrastructures. This has been partly due to the difficulty of formulating models capable of analyzing the large-scale, complex, time-dependent, and highly interconnected behavior of the integrated energy system. In this dissertation, a novel approach for studying the movements of coal, natural gas, and electricity in an integrated fashion is presented. Conceptually, the model developed is a simplified representation of the national infrastructures, structured as a generalized, multiperiod network composed of nodes and arcs. Under this formulation, fuel supply and electricity demand nodes are connected via a transportation network and the model is solved for the most efficient allocation of quantities and corresponding prices for the mutual benefits of all. The synergistic action of economic, physical, and environmental constraints produces the optimal pattern of energy flows. Key data elements are derived from various publicly available sources, including publications from the Energy Information Administration, survey forms administered by the Federal Energy Regulatory Commission, and databases maintained by the Environmental Protection Agency. The results of different test cases are analyzed to demonstrate that the decentralized level of decision-making combined with imperfect competition may be preventing the realization of potential cost savings. An overall optimization at the national level shows that there are opportunities to better utilize low cost generators, curtailing usage of higher cost units and increasing electric power trade, which would ultimately allow customers to benefit from lower electricity prices. In summary, the model developed is a simulation tool that helps build a better understanding of the complex dynamics and interdependencies of the coal, natural gas, and electricity networks. It enables public and private decision makers to carry out comprehensive analyses of a wide range of issues related to the energy sector, such as strategic planning, economic impact assessment, and the effects of different regulatory regimes.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/rtd/1555/
dc.identifier.articleid 2554
dc.identifier.contextkey 6094995
dc.identifier.doi https://doi.org/10.31274/rtd-180813-12059
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath rtd/1555
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/69194
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/rtd/1555/r_3229117.pdf|||Fri Jan 14 20:42:52 UTC 2022
dc.subject.disciplines Electrical and Electronics
dc.subject.disciplines Operational Research
dc.subject.disciplines Other Economics
dc.subject.disciplines Power and Energy
dc.subject.keywords Economics
dc.subject.keywords Electronics and Electrical Engineering
dc.subject.keywords Operations Research
dc.subject.keywords Electrical and computer engineering
dc.subject.keywords Electrical engineering
dc.title Economic efficiencies of the energy flows from the primary resource suppliers to the electric load centers
dc.type article
dc.type.genre dissertation
dspace.entity.type Publication
relation.isOrgUnitOfPublication a75a044c-d11e-44cd-af4f-dab1d83339ff
thesis.degree.level dissertation
thesis.degree.name Doctor of Philosophy
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