Risk-averse optimization of wind-based electricity generation with battery storage

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buir.advisorİyigün, Özlem Çavuş
dc.contributor.authorEser, Merve
dc.date.accessioned2023-03-01T08:53:30Z
dc.date.available2023-03-01T08:53:30Z
dc.date.copyright2022-12
dc.date.issued2022-12
dc.date.submitted2022-12-19
dc.departmentDepartment of Industrial Engineeringen_US
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (Master's): Bilkent University, Department of Industrial Engineering, İhsan Doğramacı Bilkent University, 2022.en_US
dc.descriptionIncludes bibliographical references (leaves 36-43).en_US
dc.description.abstractAs the global installed capacity of wind power increases, various solutions have been developed to accommodate the intermittent nature of wind. Investing in battery storage reduces power fluctuations, improves the reliability of delivering power on demand, and decreases wind curtailment. In the literature, power producers are generally modelled as risk-neutral decision makers, and the focus has been on expected profit maximization. For many privately-held small independent power producers, it is more important to capture their risk-aversion through specialized risk measurements driven by the owners’ specific risk preferences, even though the expected value-maximization objective is very desirable for large corporations with diversified investors. We consider a risk-averse, privately-held, small Independent Power Producer interested in investing in a battery storage system and jointly operating the wind farm and storage system with a trans-mission line connected to the market. We formulate the problem as a Markov decision process (MDP) to find optimal investment, generation, and operational storage decisions. Using dynamic coherent risk measures, we incorporate risk-aversion into our formulation. By choosing the risk measure as first-order mean semi-deviation, we obtain optimal threshold-based policy structure as well as optimal storage investment capacity. We perform a sensitivity analysis on optimal storage capacity with respect to the risk-aversion degree and transmission line limitations.en_US
dc.description.degreeM.S.en_US
dc.description.provenanceSubmitted by Betül Özen (ozen@bilkent.edu.tr) on 2023-03-01T08:53:30Z No. of bitstreams: 1 B161644.pdf: 1550616 bytes, checksum: 72d0402aa0448a8038230c0c8c74fe82 (MD5)en
dc.description.provenanceMade available in DSpace on 2023-03-01T08:53:30Z (GMT). No. of bitstreams: 1 B161644.pdf: 1550616 bytes, checksum: 72d0402aa0448a8038230c0c8c74fe82 (MD5) Previous issue date: 2022-12en
dc.description.statementofresponsibilityby Merve Eseren_US
dc.format.extentix, 45 leaves : charts ; 30 cm.en_US
dc.identifier.itemidB161644
dc.identifier.urihttp://hdl.handle.net/11693/111988
dc.language.isoEnglishen_US
dc.publisherBilkent Universityen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectWind energyen_US
dc.subjectBattery storageen_US
dc.subjectRisk-averse Markov decision processen_US
dc.subjectDynamic risk measuresen_US
dc.titleRisk-averse optimization of wind-based electricity generation with battery storageen_US
dc.title.alternativeBatarya depolaması ile rüzgar enerjisi bazlı elektrik üretiminin riskten kaçınan optimizasyonuen_US
dc.typeThesisen_US

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