Forecasting Wind Power and Prices for Increased Revenue in the Texas Electricity Market

dc.contributor.advisorEnsor, Katherine B.en_US
dc.creatorBower, Bethen_US
dc.date.accessioned2012-07-03T22:49:14Zen_US
dc.date.available2012-07-03T22:49:14Zen_US
dc.date.created2010-07en_US
dc.date.issued2011en_US
dc.description.abstractThis research proposes an economic model for wind farm owners and operators to predict the amount of electricity to sell to the market to optimize revenue. The model takes as inputs predictions of imbalance prices as well as probabilistic predictions of wind generation at the farm. The proposed statistical methodology improves upon current forecasting by focusing on the accuracy of predictions at extreme events. We decompose the prediction of prices into a baseline and spike component. The mixture model of a seasonal autoregressive component for the daily baseline behavior and a autoregressive conditional duration model for the extreme events, achieves a higher level of accuracy in the prediction and therefore a higher revenue to the wind farm. Through the improved predictions of price as well as a probabilistic forecast of wind output, not only can wind farms maximize revenue, but the independent system operators (IS Os), who control operations of the grid, can also better account for wind generation in the dispatch process, thus allowing wind to become a reliable source of power generation.en_US
dc.format.extent97 ppen_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.callnoTHESIS STAT. 2011 BOWERen_US
dc.identifier.citationBower, Beth. "Forecasting Wind Power and Prices for Increased Revenue in the Texas Electricity Market." (2011) Diss., Rice University. <a href="https://hdl.handle.net/1911/64389">https://hdl.handle.net/1911/64389</a>.en_US
dc.identifier.digitalBowerBen_US
dc.identifier.urihttps://hdl.handle.net/1911/64389en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectStatisticsen_US
dc.titleForecasting Wind Power and Prices for Increased Revenue in the Texas Electricity Marketen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentStatisticsen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelDoctoralen_US
thesis.degree.nameDoctor of Philosophyen_US
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