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Three Essays on the Economics of Renewable Electricity Generation Technologies

dc.contributor.advisor Patiño-Echeverri, Dalia
dc.contributor.author ALQAHTANI, BANDAR
dc.date.accessioned 2018-05-31T21:14:57Z
dc.date.available 2019-05-02T08:17:08Z
dc.date.issued 2018
dc.identifier.uri https://hdl.handle.net/10161/16922
dc.description.abstract <p>This PhD dissertation presents three studies that individually aim to increase understanding of various aspects of solar and wind energy and the challenge of integrating them in the electricity power system. The first study explores the opportunity to improve the technical and economic performance of concentrated solar thermal power plants (CSPs) through joint installation and operation with fossil-fuel combined cycle power plants (CCPPs). The second study presents an analysis of the feasibility and technical, environmental, and economic effects of integrating large levels of distributed solar Photovoltaic (PV) into a rather inflexible (nuclear-heavy generating base) power system. The last study evaluates the potential of off-grid distributed generation (DG) technologies including solar PV and wind systems to provide a cost-effective solution to supply electricity to isolated loads in Saudi Arabia. </p><p> Several tools and models have been developed to accomplish these studies including a thermodynamic model developed in MATLAB environment to simulate ISCC plant operations, a PV production model that estimates hourly PV power output, a unit commitment and real-time economic dispatch (UC−ED) model that simulates hourly system operations and a mixed integer linear programing that determines the optimal off-grid energy mix and capacity. </p><p>Although two of three main studies presented do not focus specifically on Saudi Arabia, they provide valuable insights for a transition of its electricity sector towards less dependence on fossil fuels and increased use of renewables.</p><p>Saudi Arabia, the world’s largest oil producer, relies on fossil fuels as the primary energy source to meet its electricity needs. Its existing electricity generation fleet consists of a large number of old and inefficient gas combustion and steam turbines, several gas and oil-fired combined cycle power plants, and many diesel combustion engines located in non-interconnected areas. The recently launched governmental plan Saudi Arabia Vision 2030 intends to enhance the resiliency of the Saudi economy by diversifying the electricity generation portfolio through the inclusion of renewable and nuclear energy. </p><p>Pertinent to the Kingdom of Saudi Arabia (KSA), the first study shows that Integrated Solar Combined Cycle Power Plants (ISCCs) offer an opportunity to reduce fossil-fuel consumption while reducing the levelized cost of solar thermal energy (LCOE) by 35-40%. The third study shows that the in three non-interconnected regions of KSA, off-grid distributed generation including more than 300 MW of solar PV and wind energy is a cost-effective alternative assuming plausible scenarios for fuel prices and electricity demand. In addition, the results reveal that the local excellent solar resources and the high efficiency of the wind turbine technologies that could be installed make the LCOE of solar PV and wind lower than the LCOE of highly efficient oil-fired combined cycle power plants (CCPP) under moderate and high oil price scenarios. </p><p>Finally, the second study illustrates a potential barrier to the integration of a high share of distributed intermittent energy sources into a power network that operates large base-load thermal generation units and rather inflexible nuclear power plants.</p>
dc.subject Energy
dc.subject Alternative energy
dc.subject Engineering
dc.subject Distributed Generation
dc.subject Energy Efficiency
dc.subject Integrated Solar Combined Cycle Power Plant
dc.subject Microgrid
dc.subject Solar Photovoltaic (PV)
dc.subject Wind Energy
dc.title Three Essays on the Economics of Renewable Electricity Generation Technologies
dc.type Dissertation
dc.department Environment
duke.embargo.months 11


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