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Modelling and optimization of possible bottoming units for general single flash geothermal power plants

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Titill: Modelling and optimization of possible bottoming units for general single flash geothermal power plantsModelling and optimization of possible bottoming units for general single flash geothermal power plants
Höfundur: Bandoro Swandaru, Roy ; Swandaru, Roy Bandoro ; Jarðhitaskóli Háskóla Sameinuðu þjóðanna
URI: http://hdl.handle.net/10802/6742
Útgefandi: United Nations University; Orkustofnun
Útgáfa: 12.2009
Ritröð: United Nations University., UNU Geothermal Training Programme, Iceland. Report ; 2009:2
Efnisorð: Meistaraprófsritgerðir; Jarðhiti; Orkuver
ISSN: 1670-7427
ISBN: 9789979682677 (ób.)
Tungumál: Enska
Tengd vefsíðuslóð: http://www.os.is/gogn/unu-gtp-report/UNU-GTP-2009-02.pdf
Tegund: Bók
Gegnir ID: 991009059109706886
Athugasemdir: Myndefni: myndir, línurit, töflur
Útdráttur: When utilizing geothermal fields for power production, a single flash power plant is often the initial plant to be built. In most cases, a considerable amount of hot brine is wasted when using single flash plants, but the energy from this brine could be utilized for additional power generation. This study was performed to find for a fast and easy way to determine the optimum power output, based on a given enthalpy of a geothermal fluid. Five energy conversion systems were considered: double flash, single and second flash, organic Rankine cycle (ORC), advanced ORC and a Kalina cycle. These were assumed to be installed as a bottoming unit of a single flash plant. The optimum specific power output of the combined single flash and the bottoming units was determined, based on an enthalpy range of the geothermal fluid from 500 to 2000 kJ/kg. Furthermore, a comparison of the optimum specific power outputs of the combined plants was performed. The study was based on the fundamental thermodynamic principles of energy and mass conservation, where a new methodology for modelling and optimization was used. Modelling was performed by using material data from the REFPROP7 database along with a Fortran to MATLAB interface. Optimization was performed by using robust state of the art techniques, based on evolutionary search. A cost analysis was also performed to obtain the specific levelized annual costs of the combined plants.


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