Supercritical CO2 Brayton cycles (SCO2BC) including the SCO2 single-recuperated Brayton cycle (RBC) and recompression recuperated Brayton cycle (RRBC) are considered, and flexible thermodynamic and economic modeling methodologies are presented. The influences of the key cycle parameters on thermodynamic performance of SCO2BC are studied, and the comparative analyses on RBC and RRBC are conducted. Nondominated Sorting Genetic Algorithm II (NSGA-II) is selected for the Pareto-based multi-objective optimization of the RRBC, with the maximum exergy efficiency and the lowest cost per power (k$/kW) as its objectives. Artificial neural network (ANN) is chosen to accelerate the parameters query process. It is shown that the cycle parameters such as heat source temperature, turbine inlet temperature, cycle pressure ratio, and pinch temperature difference of heat exchangers have significant effects on the cycle exergy efficiency. The exergy destruction of heat exchanger is the main reason why the exergy efficiency of RRBC is higher than that of the RBC under the same cycle conditions. RBC has a cost advantage from economic perspective, while RRBC has a much better thermodynamic performance, and could rectify the temperature pinching problem that exists in RBC. It is also shown that there is a conflicting relationship between the cycle cost/cycle power (CWR) and the cycle exergy efficiency. The optimization results could provide an optimum tradeoff curve enabling cycle designers to choose their desired combination between the efficiency and cost. ANN could help the users to find the SCO2BC parameters fast and accurately.
Skip Nav Destination
Sign In or Register for Account
Article navigation
August 2016
Research-Article
Thermodynamic and Economic Analysis and Multi-objective Optimization of Supercritical CO2 Brayton Cycles
Hang Zhao
,
Hang Zhao
Institute of Turbomachinery,
School of Energy and Power Engineering,
Xi'an Jiaotong University,
Xi'an 710049, China
School of Energy and Power Engineering,
Xi'an Jiaotong University,
Xi'an 710049, China
Search for other works by this author on:
Qinghua Deng
,
Qinghua Deng
Institute of Turbomachinery,
School of Energy and Power Engineering,
Xi'an Jiaotong University,
Xi'an 710049, China
School of Energy and Power Engineering,
Xi'an Jiaotong University,
Xi'an 710049, China
Search for other works by this author on:
Wenting Huang
,
Wenting Huang
Institute of Turbomachinery,
School of Energy and Power Engineering,
Xi'an Jiaotong University,
Xi'an 710049, China
School of Energy and Power Engineering,
Xi'an Jiaotong University,
Xi'an 710049, China
Search for other works by this author on:
Dian Wang
,
Dian Wang
Institute of Turbomachinery,
School of Energy and Power Engineering,
Xi'an Jiaotong University,
Xi'an 710049, China
School of Energy and Power Engineering,
Xi'an Jiaotong University,
Xi'an 710049, China
Search for other works by this author on:
Zhenping Feng
Zhenping Feng
Institute of Turbomachinery,
School of Energy and Power Engineering,
Xi'an Jiaotong University,
Xi'an 710049, China
e-mail: zpfeng@mail.xjtu.edu.cn
School of Energy and Power Engineering,
Xi'an Jiaotong University,
Xi'an 710049, China
e-mail: zpfeng@mail.xjtu.edu.cn
Search for other works by this author on:
Hang Zhao
Institute of Turbomachinery,
School of Energy and Power Engineering,
Xi'an Jiaotong University,
Xi'an 710049, China
School of Energy and Power Engineering,
Xi'an Jiaotong University,
Xi'an 710049, China
Qinghua Deng
Institute of Turbomachinery,
School of Energy and Power Engineering,
Xi'an Jiaotong University,
Xi'an 710049, China
School of Energy and Power Engineering,
Xi'an Jiaotong University,
Xi'an 710049, China
Wenting Huang
Institute of Turbomachinery,
School of Energy and Power Engineering,
Xi'an Jiaotong University,
Xi'an 710049, China
School of Energy and Power Engineering,
Xi'an Jiaotong University,
Xi'an 710049, China
Dian Wang
Institute of Turbomachinery,
School of Energy and Power Engineering,
Xi'an Jiaotong University,
Xi'an 710049, China
School of Energy and Power Engineering,
Xi'an Jiaotong University,
Xi'an 710049, China
Zhenping Feng
Institute of Turbomachinery,
School of Energy and Power Engineering,
Xi'an Jiaotong University,
Xi'an 710049, China
e-mail: zpfeng@mail.xjtu.edu.cn
School of Energy and Power Engineering,
Xi'an Jiaotong University,
Xi'an 710049, China
e-mail: zpfeng@mail.xjtu.edu.cn
1Corresponding author.
Contributed by the Controls, Diagnostics and Instrumentation Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received December 30, 2015; final manuscript received January 7, 2016; published online March 15, 2016. Editor: David Wisler.
J. Eng. Gas Turbines Power. Aug 2016, 138(8): 081602 (9 pages)
Published Online: March 15, 2016
Article history
Received:
December 30, 2015
Revised:
January 7, 2016
Citation
Zhao, H., Deng, Q., Huang, W., Wang, D., and Feng, Z. (March 15, 2016). "Thermodynamic and Economic Analysis and Multi-objective Optimization of Supercritical CO2 Brayton Cycles." ASME. J. Eng. Gas Turbines Power. August 2016; 138(8): 081602. https://doi.org/10.1115/1.4032666
Download citation file:
Sign In
Get Email Alerts
Cited By
Design of a Compact Magnetically Levitated Blower for Space Applications
J. Eng. Gas Turbines Power
Wall-Modeled Large Eddy Simulations of Axial Turbine Rim Sealing
J. Eng. Gas Turbines Power (June 2021)
A Theoretical Investigation on the Performance and Combustion Parameters in an Spark Ignition Engine Fueled With Different Shale Gas Mixtures
J. Eng. Gas Turbines Power (June 2021)
A Quasi-Dimensional Fuel Distribution Model for a Radially Stratified Engine
J. Eng. Gas Turbines Power (August 2021)
Related Articles
Close supercritical versus inverse Brayton cycles for power supply, using waste of a biogas-driven open Brayton cycle
J. Energy Resour. Technol (January,0001)
Mass Optimization of a Supercritical CO 2 Brayton Cycle Power Conversion System for a Mars Surface Fission Power Reactor
ASME J of Nuclear Rad Sci (July,2017)
Optimization of Supercritical CO 2 Brayton Cycle for Simple Cycle Gas Turbines Exhaust Heat Recovery Using Genetic Algorithm
J. Energy Resour. Technol (July,2018)
MULTI-OBJECTIVE OPTIMIZATION OF THERMO-ECOLOGICAL CRITERIA BASED PERFORMANCE PARAMETERS OF REHEAT AND REGENERATIVE BRAYSSON CYCLE
J. Energy Resour. Technol (January,0001)
Related Proceedings Papers
Related Chapters
A Novel Approach for LFC and AVR of an Autonomous Power Generating System
International Conference on Mechanical Engineering and Technology (ICMET-London 2011)
The Impact of Plant Economics on the Design of Industrial Energy Systems
Industrial Energy Systems
The Importance of Process Heat Exchangers in Industrial Energy Systems
Industrial Energy Systems