A risk-averse approach for the planning of a hybrid renewable energy system

Simple item page
buir.advisorİyigün, Özlem Çavuş
dc.contributor.authorYılmaz, Özlem
dc.date.accessioned2017-09-06T12:43:31Z
dc.date.available2017-09-06T12:43:31Z
dc.date.copyright2017-08
dc.date.issued2017-08
dc.date.submitted2017-09-05
dc.departmentDepartment of Industrial Engineeringen_US
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (M.S.): Bilkent University, Department of Industrial Engineering, İhsan Doğramacı Bilkent University, 2017.en_US
dc.descriptionIncludes bibliographical references (leaves 45-48).en_US
dc.description.abstractWe propose a risk-averse two-stage stochastic programming for a hybrid renewable energy system planning problem, where we model the risk-aversion using Conditional Value at Risk (CVaR). The aim of this study is to find the optimal capacities of the system components in a cost e ective way while considering the risk-aversion of the decision maker. Renewable energy sources that are utilized in our hybrid system are solar and hydro, while the diesel fuel is used as a backup source. We assume that the water in ow to the reservoirs is uncertain, therefore, based on historical stream ow data for Mediterranean Region of Turkey, we generate scenarios for stream ow by using a modified k-nearest neighbor (k-NN) algorithm. We solve our model for di erent levels of risk-aversion and compare the optimal solutions. For models with large number of scenarios, we propose a multi-cut scenario-wise decomposition algorithm as an exact solution method. In order to evaluate the performance of our algorithm, we compare it with CPLEX. We conclude that, for a large number of scenarios, our algorithm is more efficient than CPLEX.en_US
dc.description.degreeM.S.en_US
dc.description.statementofresponsibilityby Özlem Yılmaz.en_US
dc.embargo.release2019-08-28
dc.format.extentxii, 73 leaves : charts (some color) ; 30 cmen_US
dc.identifier.itemidB156126
dc.identifier.urihttp://hdl.handle.net/11693/33574
dc.language.isoEnglishen_US
dc.publisherBilkent Universityen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectTwo-stage stochastic optimizationen_US
dc.subjectConditional Value at Risk (CVaR)en_US
dc.subjectScenario-wise decompositionen_US
dc.subjectScenario generationen_US
dc.titleA risk-averse approach for the planning of a hybrid renewable energy systemen_US
dc.title.alternativeYenilenebilir hibrit enerji sistemi planlamasına riskten kaçınan bir yaklaşımen_US
dc.typeThesisen_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
MS_Thesis_Ozlem_Yilmaz_Bilkent_IE.pdf
Size:
2.72 MB
Format:
Adobe Portable Document Format
Description:
Full printable version
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Dept. of Industrial Engineering - Master's degree