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http://hdl.handle.net/11452/34692
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DC Field | Value | Language |
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dc.contributor.author | Ünver, Ümit | - |
dc.contributor.author | Keleşoğlu, Alper | - |
dc.date.accessioned | 2023-10-31T11:22:26Z | - |
dc.date.available | 2023-10-31T11:22:26Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | Ünver, Ü. vd. (2018). ''A novel method for prediction of gas turbine power production degree-day method''. Thermal Science, 22(Supplement 3), S809-S817. | en_US |
dc.identifier.issn | 0354-9836 | - |
dc.identifier.issn | 2334-7163 | - |
dc.identifier.uri | https://doi.org/10.2298/TSCI170915015U | - |
dc.identifier.uri | https://doiserbia.nb.rs/Article.aspx?ID=0354-98361800015U | - |
dc.identifier.uri | http://hdl.handle.net/11452/34692 | - |
dc.description.abstract | Gas turbines are widely used in the energy production. The quantity of the operating machines requires a special attention for prediction of power production in the energy marketing sector. Thus, the aim of this paper is to support the sector by making the prediction of power production more computable. By using the data from an operating power plant, correlation and regression analysis are performed and linear equation obtained for calculating useful power production vs atmospheric air temperature and a novel method, the gas turbine degree day method, was developed. The method has been addressed for calculating the isolation related issues for buildings so far. But in this paper, it is utilized to predict the theoretical maximum power production of the gas turbines in various climates for the first time. The results indicated that the difference of annual energy production capacity between the best and the last province options was calculated to be 7500 MWh approximately. | en_US |
dc.description.sponsorship | Yalova University Applied Science Center | en_US |
dc.language.iso | en | en_US |
dc.publisher | Vinca Institute of Nuclear Science | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.rights | Atıf Gayri Ticari Türetilemez 4.0 Uluslararası | tr_TR |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Thermodynamics | en_US |
dc.subject | Gas turbine | en_US |
dc.subject | Degree day | en_US |
dc.subject | Prediction of energy production | en_US |
dc.subject | Ambient temperature | en_US |
dc.subject | Energy prediction | en_US |
dc.subject | Environmental-temperature | en_US |
dc.subject | Ambient-temperature | en_US |
dc.subject | Plants | en_US |
dc.subject | Optimization | en_US |
dc.subject | Efficiency | en_US |
dc.subject | Performance | en_US |
dc.subject | Parameters | en_US |
dc.subject | Fuel | en_US |
dc.subject | Forecasting | en_US |
dc.subject | Gases | en_US |
dc.subject | Regression analysis | en_US |
dc.subject | Degree days | en_US |
dc.subject | Degree-day method | en_US |
dc.subject | Energy | en_US |
dc.subject | Energy productions | en_US |
dc.subject | Marketing sectors | en_US |
dc.subject | Novel methods | en_US |
dc.subject | Power production | en_US |
dc.subject | Turbine power | en_US |
dc.subject | Gas turbines | en_US |
dc.title | A novel method for prediction of gas turbine power production degree-day method | en_US |
dc.type | Article | en_US |
dc.identifier.wos | 000441484700004 | tr_TR |
dc.identifier.scopus | 2-s2.0-85052485611 | tr_TR |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi | tr_TR |
dc.contributor.department | Uludağ Üniversitesi/Mühendislik Fakültesi/Makina Mühendisliği Bölümü. | tr_TR |
dc.contributor.orcid | 0000-0003-2113-4510 | tr_TR |
dc.identifier.startpage | S809 | tr_TR |
dc.identifier.endpage | S817 | tr_TR |
dc.identifier.volume | 22 | tr_TR |
dc.identifier.issue | Supplement 3 | tr_TR |
dc.relation.journal | Thermal Science | tr_TR |
dc.contributor.buuauthor | Kılıç, Muhsin | - |
dc.contributor.researcherid | O-2253-2015 | tr_TR |
dc.relation.collaboration | Yurt içi | tr_TR |
dc.subject.wos | Thermodynamics | en_US |
dc.indexed.wos | SCIE | en_US |
dc.indexed.scopus | Scopus | en_US |
dc.wos.quartile | Q3 | en_US |
dc.contributor.scopusid | 57202677637 | tr_TR |
dc.subject.scopus | Gas Turbines; Gas; Air Cooling | en_US |
Appears in Collections: | Scopus Web of Science |
Files in This Item:
File | Description | Size | Format | |
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Kılıç_vd_2018.pdf | 1 MB | Adobe PDF | View/Open |
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