In the recent years, several studies have been conducted about the possibilities of recovering heat from gas turbine (GT) exhaust gases using Organic Rankine Cycle (ORC) units. However, it is difficult to find out working fluids properly matching with GT exhaust gases. For this reason, the Authors have developed a computer tool able to perform fluid selection and plant layout optimization. The optimum fluid is selected among 81 pure working fluids and their mixtures. The optimization goal is the maximization of the net electric power while the optimized variables are the heat source outlet temperature, the evaporation pressure of the organic medium, the turbine inlet temperature, the fluid or mixture composition, the recuperator efficiency and the condensation pressure. Given that the plant components play a fundamental role in the prediction of the design performance, the efficiency charts of the axial and radial flow turbines are implemented into the tool. Exergetic and economic analyses are also performed. The plant model is built in Matlab environment and the optimization is performed using the genetic algorithm toolbox. The fluid thermodynamic properties have been retrieved from REFPROP and CoolProp database. Results show that hydrocarbon mixtures guarantee better performance than pure hydrocarbons.
Recovering gas turbine high-temperature exhaust heat using organic Rankine cycle with mixture as working fluid
PEZZUOLO, ALEX;BENATO, ALBERTO;STOPPATO, ANNA;MIRANDOLA, ALBERTO
2016
Abstract
In the recent years, several studies have been conducted about the possibilities of recovering heat from gas turbine (GT) exhaust gases using Organic Rankine Cycle (ORC) units. However, it is difficult to find out working fluids properly matching with GT exhaust gases. For this reason, the Authors have developed a computer tool able to perform fluid selection and plant layout optimization. The optimum fluid is selected among 81 pure working fluids and their mixtures. The optimization goal is the maximization of the net electric power while the optimized variables are the heat source outlet temperature, the evaporation pressure of the organic medium, the turbine inlet temperature, the fluid or mixture composition, the recuperator efficiency and the condensation pressure. Given that the plant components play a fundamental role in the prediction of the design performance, the efficiency charts of the axial and radial flow turbines are implemented into the tool. Exergetic and economic analyses are also performed. The plant model is built in Matlab environment and the optimization is performed using the genetic algorithm toolbox. The fluid thermodynamic properties have been retrieved from REFPROP and CoolProp database. Results show that hydrocarbon mixtures guarantee better performance than pure hydrocarbons.Pubblicazioni consigliate
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