Gelişmiş Arama

Basit öğe kaydını göster

dc.contributor.authorUysal, Gökçen
dc.contributor.authorAkkol, Bulut
dc.contributor.authorTopçu, M. İrem
dc.contributor.authorŞensoy, Aynur
dc.contributor.authorSchwanenberg, Dirk
dc.contributor.editorKim, JH
dc.contributor.editorKim, HS
dc.contributor.editorYoo, DG
dc.date.accessioned2019-10-21T21:11:33Z
dc.date.available2019-10-21T21:11:33Z
dc.date.issued2016
dc.identifier.issn1877-7058
dc.identifier.urihttps://dx.doi.org/10.1016/j.proeng.2016.07.506
dc.identifier.urihttps://hdl.handle.net/11421/21036
dc.description12th International Conference on Hydroinformatics (HIC) - Smart Water for the Future -- AUG 21-26, 2016 -- SOUTH KOREAen_US
dc.descriptionWOS: 000385793200185en_US
dc.description.abstractShort-term operation of reservoir systems is challenging due to conflicting objectives and constraints as well as the need for taking robust decisions in real-time. This study compares simulation and optimization based decision support techniques in application to the mitigation of flood events. Two models are employed in the study to support the operators' decisions: (1) HEC-ResSim of USACE as a representative of a simulation-based approach, and (2) the RTC-Tools package of Deltares with an optimization approach. The methods are applied to a complex flood management problem at Yuvacik Dam, Turkey. A worst case scenario of an extreme flood event is used to evaluate the pros and cons of the models including a high initial water level exceeding the flood control pool. Objectives of the control are the maximization of water supply benefits, i.e. a full reservoir, at the end of the event as well as flood mitigation in the downstream river reach. In the first method, a script-based rule is defined in the GUI with user access to its parameters. The refinement of the reservoir operation is conducted manually by trial and error. Secondly, an optimization approach using Model Predictive Control (MPC) is used in combination with the IPOPT optimizer. The advantage of HEC-ResSim is the detailed representation of the gate management on the level of the individual gates. However, the implementation of the total release is partially up to user interaction and not necessarily optimal. RTC-Tools provides optimum releases on the project level, but not on the level of individual gates. Both approaches consider system constraints. Furthermore, an advantage of the optimization approach is its extension to probabilistic ensemble forecasts to consider forecast uncertainty in the decision by use stochastic optimization.en_US
dc.description.sponsorshipIncheon Metropolitan Govt, Korea Tourism Org, Smart Water Grid Res Grpen_US
dc.language.isoengen_US
dc.publisherElsevier Science BVen_US
dc.relation.ispartofseriesProcedia Engineering
dc.relation.isversionof10.1016/j.proeng.2016.07.506en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectForecastingen_US
dc.subjectShort-Term Reservoir Operationen_US
dc.subjectFlood Mitigationen_US
dc.titleComparison of Different Reservoir Models for Short Term Operation of Flood Managementen_US
dc.typeconferenceObjecten_US
dc.relation.journal12th International Conference On Hydroinformatics (Hic 2016) - Smart Water For the Futureen_US
dc.contributor.departmentAnadolu Üniversitesi, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümüen_US
dc.identifier.volume154en_US
dc.identifier.startpage1385en_US
dc.identifier.endpage1392en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.contributor.institutionauthorŞensoy, Aynur


Bu öğenin dosyaları:

Thumbnail

Bu öğe aşağıdaki koleksiyon(lar)da görünmektedir.

Basit öğe kaydını göster