Rigorous modelling and deterministic multi-objective optimization of a super-critical CO2 power system based on equation of state and non-linear programming

•A novel method is proposed for the PP locating and optimization of CO2 cycle.•A multi-objective NLP model incorporating rigorous equation of state is developed.•Case study is elaborated to demonstrate the effectiveness of the proposed methodology.•Sensitivity analysis of key parameters on PP and op...

Full description

Saved in:
Bibliographic Details
Published in:Energy conversion and management Vol. 198; p. 111798
Main Authors: Yang, Zhi, Kang, Ruili, Luo, Xianglong, Chen, Jianyong, Liang, Yingzong, Wang, Chao, Chen, Ying, Xu, Jinliang
Format: Journal Article
Language:English
Published: Oxford Elsevier Ltd 15.10.2019
Elsevier Science Ltd
Subjects:
Carbon dioxide
case studies
Clean technology
CO2 power cycle
Compressing
Computer simulation
Continuity (mathematics)
Efficiency
energy
Equation of state
equations
Equations of state
Fossil fuels
Heat exchange
Heat exchangers
Heat sinks
Heat transfer
Inlet temperature
Linear programming
Mathematical models
Mathematical programming
Multiple objective analysis
NLP
Nonlinear programming
Nuclear fuels
Optimization
Pareto optimization
Physical properties
Pinch point locating
Power efficiency
Sensitivity analysis
Solar energy
sustainable technology
system optimization
temperature
Thermodynamic efficiency
Waste heat
CO2 power cycle
NLP
Optimization
Equation of state
Pinch point locating
ISSN:0196-8904, 1879-2227
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:•A novel method is proposed for the PP locating and optimization of CO2 cycle.•A multi-objective NLP model incorporating rigorous equation of state is developed.•Case study is elaborated to demonstrate the effectiveness of the proposed methodology.•Sensitivity analysis of key parameters on PP and optimization results is conducted. CO2 power cycle is one of the promising sustainable technologies that generate power from fossil fuel, nuclear, solar, and various waste heat energy. The heat transfer process plays a key role in influencing the thermodynamic or thermo-economic performance of CO2 power cycle. The drastic variation of CO2 thermo-physical properties results in great difficulty in modeling and optimizing the heat exchangers and CO2 cycle configurations. In the present study, a mathematical programming method is proposed for the simulation and optimization of simple, regenerative, and recompression super-critical CO2 power systems. An accurate equation of state is applied to calculate CO2 properties, thereby enabling the performance indicator a continuous function of system parameters. A multi-objective non-linear programming model is formulated in GAMS for the automatic heat exchange pinch locating and system optimization. The simulation and optimization models are validated by comparison with REFPROP-based method. The maximum and average simulation errors are 0.064% and 0.015%. The thermal efficiency values achieved using the developed optimization method are improved by 6.14–10.85% compared with previous solutions. Then, a case study of a 573.15 K waste heat driven super-critical CO2 power system optimization is elaborated. Results show that pinch locating of all heat exchangers and system optimization can be simultaneously conducted within a short time. The solution optimality is validated by comparing the traditional pinch assignment concept and optimization method. Sensitivity analyses of heat source inlet temperature and heat sink temperature rise are also conducted. For both objectives of maximizing thermal efficiency and net power output, the recompression super-critical CO2 cycle features highest in thermal efficiency and the regenerative super-critical CO2 cycle features highest in net power output. Finally, a multi-objective optimization is conducted to achieve the Pareto Front for the studied three super-critical CO2 power systems.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:0196-8904
1879-2227
DOI:10.1016/j.enconman.2019.111798