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Research Papers: Energy Conversion/Systems

Optimization of Supercritical CO2 Brayton Cycle for Simple Cycle Gas Turbines Exhaust Heat Recovery Using Genetic Algorithm

[+] Author and Article Information
Akshay Khadse

Mechanical and Aerospace Engineering Department,
University of Central Florida,
Orlando, FL 32816
e-mail: akshaybkhadse@knights.ucf.edu

Lauren Blanchette

Mechanical and Aerospace Engineering Department,
University of Central Florida,
Orlando, FL 32816
e-mail: lblanchette@knights.ucf.edu

Jayanta Kapat

Mechanical and Aerospace Engineering Department,
University of Central Florida,
Orlando, FL 32816
e-mail: Jayanta.Kapat@ucf.edu

Subith Vasu

Mechanical and Aerospace Engineering Department,
University of Central Florida,
Orlando, FL 32816
e-mail: subith@ucf.edu

Jahed Hossain

Mechanical and Aerospace Engineering Department,
University of Central Florida,
Orlando, FL 32816
e-mail: jahed.hossain@knights.ucf.edu

Adrien Donazzolo

École nationale supérieure de physique,
électronique et Matériaux,
Grande école,
Grenoble, France
e-mail: adrien.donazzolo@phelma.grenoble-inp.fr

1Corresponding author.

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received September 15, 2017; final manuscript received February 6, 2018; published online March 15, 2018. Assoc. Editor: Esmail M. A. Mokheimer.

J. Energy Resour. Technol 140(7), 071601 (Mar 15, 2018) (8 pages) Paper No: JERT-17-1493; doi: 10.1115/1.4039446 History: Received September 15, 2017; Revised February 06, 2018

For the application of waste heat recovery (WHR), supercritical CO2 (S-CO2) Brayton power cycles offer significant suitable advantages such as compactness, low capital cost, and applicability to a broad range of heat source temperatures. The current study is focused on thermodynamic modeling and optimization of recuperated (RC) and recuperated recompression (RRC) configurations of S-CO2 Brayton cycles for exhaust heat recovery from a next generation heavy duty simple cycle gas turbine using genetic algorithm (GA). This nongradient based algorithm yields a simultaneous optimization of key S-CO2 Brayton cycle decision variables such as turbine inlet temperature, pinch point temperature difference, compressor pressure ratio, and mass flow rate of CO2. The main goal of the optimization is to maximize power out of the exhaust stream which makes it single objective optimization. The optimization is based on thermodynamic analysis with suitable practical assumptions which can be varied according to the need of user. The optimal cycle design points are presented for both RC and RRC configurations and comparison of net power output is established for WHR. For the chosen exhaust gas mass flow rate, RRC cycle yields more power output than RC cycle. The main conclusion drawn from the current study is that the choice of best cycle for WHR actually depends heavily on mass flow rate of the exhaust gas. Further, the economic analysis of the more power producing RRC cycle is performed and cost comparison between the optimized RRC cycle and steam Rankine bottoming cycle is presented.

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Figures

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Fig. 3

Stream path of the optimization process used

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Fig. 2

Recuperated recompression configuration of Brayton cycle

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Fig. 1

Recuperated configuration of Brayton cycle

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Fig. 4

Ts diagram for the optimized RC cycle describing state points and pressure in parenthesis

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Fig. 5

Ts diagram for the optimized RRC cycle describing state points and pressure in parenthesis

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Fig. 6

Variation in temperature along recuperator length for RC cycle

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Fig. 7

Variation of temperature along HTR length for RRC cycle

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Fig. 8

Variation of temperature along LTR length for RRC cycle

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Fig. 9

Open loop counter flow heat exchange between exhaust gas and CO2 for RC and RRC cycles

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Fig. 10

Population and optimum value (TTIT = 710 K) of turbine inlet temperature for RC cycle

Tables

Errata

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