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dc.contributor.authorHu, Zhouxing
dc.date.accessioned2013-11-14T22:42:09Z
dc.date.available2013-11-14T22:42:09Z
dc.date.issued2013-05
dc.identifier.otherd13008
dc.identifier.urihttp://hdl.handle.net/10057/6724
dc.descriptionThesis (Ph.D.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer Scienceen_US
dc.description.abstractWind and solar energy are clean, free of fuel cost and likely to have great potential in the future. However, besides the technical difficulties associated with integrating variable sources of generation with the electric grid, high capital cost and other indirect costs to power system operations, such as ancillary service requirements, delay more widespread investment in wind and solar power plants. Current energy policies, especially renewable incentives and CO2 emission regulations, remain controversial and uncertain. Pumped-hydroelectric energy storage has proven to be valuable as bulk energy storage for energy arbitrage coordinating with conventional thermal generators. In the future grid, there are uncertainties, in terms of modeling and optimization, of assessing the value of bulk energy storage coordinating less with thermal generators and more with wind and solar. Moreover, the price of natural gas is predicted to have large variations in the next several decades. It is therefore necessary to construct a generation planning model with comprehensive modeling of wind, solar and energy storage under multiple scenarios of energy policies and natural gas prices. This dissertation presents such an optimal planning model using a multi-period optimization formulation and its implementation in the MATPOWER's extensible optimal power flow structure. A 3-bus test system is constructed to test the sensitivity of the planning model. This model is further applied to the reduced 240-bus Western Electric Coordinating Council (WECC) system to study more practical planning results.en_US
dc.format.extentxv, 95.p
dc.language.isoen_USen_US
dc.publisherWichita State Universityen_US
dc.rightsCopyright Zhouxing Hu, 2013.
dc.subject.lcshElectronic dissertationsen
dc.titleOptimal generation expansion planning with integration of variable renewables and bulk energy storage systemsen_US
dc.typeDissertationen_US


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