Energy production from fossil fuels has been regarded as the main source of the climate change. The reason for that is the oxidation of carbon in fossil fuels to carbon dioxide during combustion and the highest percentage of greenhouse gases in atmosphere belongs to carbon dioxide. Amongst the fossil fuels natural gas is preferred due to its low emission of greenhouse gases and having no particulate matter after combustion. While the other fossil fuels emit mainly carbon dioxide during the combustion process; natural gas emits mostly water together with carbon dioxide. Around 22 % of the world’s electricity is produced by natural gas and this share is expected to increase in near future. The power plants operating with natural gas as a gas cycle consisting of a compressor, a combustion chamber and gas turbine are combined with a vapor cycle in order to increase the efficiency. A heat recovery steam generator is used to reach this aim in recent years in generating steam by the heat received from the combustion gases leaving the gas turbine. It is very important to design and operate such energy conversion systems fired by natural gas in optimal conditions. If the efficiency can be increased, it can be said that the energetic, economic, and environmental aspects also improve. The modeling and optimization studies for a combined gas-vapor power plant are studied and the most important parameters which influence the efficiency are determined. The results indicate that the most effective parameters from the viewpoint of efficiency are air/fuel ratio, gas/steam ratio and the pressure ratios of the compressor and, thus, the gas turbine. The thermal efficiency increases by 18.25 % and, in the meantime, the exergy destroyed decreases by 9.84 % using optimum design parameters determined by the optimization algorithm proposed.
Primary Language | English |
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Journal Section | Research Article |
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Publication Date | December 28, 2017 |
Published in Issue | Year 2017 Volume: 4 Issue: 2 |
Hittite Journal of Science and Engineering is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY NC).