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Title: | A novel method for prediction of gas turbine power production degree-day method |
Authors: | Ünver, Ümit Keleşoğlu, Alper Uludağ Üniversitesi/Mühendislik Fakültesi/Makina Mühendisliği Bölümü. 0000-0003-2113-4510 Kılıç, Muhsin O-2253-2015 57202677637 |
Keywords: | Thermodynamics Gas turbine Degree day Prediction of energy production Ambient temperature Energy prediction Environmental-temperature Ambient-temperature Plants Optimization Efficiency Performance Parameters Fuel Forecasting Gases Regression analysis Degree days Degree-day method Energy Energy productions Marketing sectors Novel methods Power production Turbine power Gas turbines |
Issue Date: | 2018 |
Publisher: | Vinca Institute of Nuclear Science |
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. |
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. |
URI: | https://doi.org/10.2298/TSCI170915015U https://doiserbia.nb.rs/Article.aspx?ID=0354-98361800015U http://hdl.handle.net/11452/34692 |
ISSN: | 0354-9836 2334-7163 |
Appears in Collections: | Scopus Web of Science |
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Kılıç_vd_2018.pdf | 1 MB | Adobe PDF | View/Open |
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