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dc.contributor.advisorJewell, Ward T.en_US
dc.contributor.authorPoonpun, Piyasaken_US
dc.descriptionThesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical and Computer Engineeringen_US
dc.description.abstractThe electric power industry produces substantial amounts of carbon dioxide (CO2) as well as other greenhouse gas (GHG) emissions. Recent GHG regulations along with renewable portfolio standards encourage the integration of low carbon emission generation into the electric power system and, as a result, drastically affect operations, design, and planning of the electric power system. Extensive studies on this issue, therefore, are important. This dissertation first discusses renewable standards and policies in the United States (U.S.), which include renewable portfolio standards. Current U.S. electricity markets for renewable generators such as wind generation resources and solar power plants are investigated. This research analyzes several factors that affect an electric power system due to the integration of these low carbon generators. The dissertation then develops system operating cost models for renewable generation and energy storage. With consideration of CO2 emission costs, the system operating cost model for a fossil-fired generating unit is presented and discussed. By using optimal power flow, security-constrained optimal power flow, time step series input, and the CO2 emissions incorporated objective function, this dissertation develops a new methodology to study the effects of low carbon emission generation and energy storage on GHG emissions in electric power systems. A number of relevant study cases are presented. The cost models and methodology are applied to the study cases. The IEEE 24 bus Reliability Test System (IEEE RTS) is used as the sample test system. This system has been modified to include additional generation fuels to study the amount of various CO2 emissions. vii Simulation results, including system operating costs, total emissions, economic dispatch, and locational marginal prices, are presented and discussed. This dissertation addresses two major issues: system operating cost and system reliability. Finally, conclusions are drawn and discussed, and future work is recommended. Conclusions include: • The integration of renewable generation reduces CO2 but emissions of reserve units must be considered. • The integration of low carbon emission generation tends to reduce system operating cost. The system operator still must consider the operating cost of renewable generators and reserve fossil-fired generators. • The change of emissions and system operating cost are not proportional to the additional capacity of renewable generation installed due to complexities of an electric power system. • The system operating cost model for renewable generation is able to properly represent the special characteristics of these low carbon emission generators. The proposed operating cost model for energy storage can also be used to verify its effects on overall system cost and emissions. • The developed methodology can be used to investigate an electric power system with integrated renewable generation and energy storage. It has the ability to consider several factors and unique characteristics of renewable generation, energy storage, and the transmission system. • Generation output profiles of low carbon emission generation significantly affect total CO2 emissions of an electric power system.en_US
dc.format.extentxvi, 140 p.en_US
dc.format.extent1590542 bytes
dc.publisherWichita State Universityen_US
dc.subject.lcshElectronic dissertations
dc.titleEffects of low carbon emission generation and energy storage on greenhouse gas emissions in electric power systemsen_US

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  • CE Theses and Dissertations
    Doctoral and Master's theses authored by the College of Engineering graduate students
  • Dissertations
    This collection includes Ph.D. dissertations completed at the Wichita State University Graduate School (Fall 2005 --)
  • EECS Theses and Dissertations
    Collection of Master's theses and Ph.D. dissertations completed at the Dept. of Electrical Engineering and Computer Science

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