Performance evaluation and working fluid selection of combined heat pump and power generation system (HP-PGs) using multi-objective optimization

2020 ◽  
Vol 221 ◽  
pp. 113164 ◽  
Author(s):  
Zhangxiang Wu ◽  
Li Sha ◽  
Xiaochen Yang ◽  
Yufeng Zhang
Keyword(s):  
Power Generation ◽  
Performance Evaluation ◽  
Heat Pump ◽  
Working Fluid ◽  
Multi Objective Optimization ◽  
Generation System ◽  
Multi Objective ◽  
Working Fluid Selection ◽  
Power Generation System ◽  
Selection Of

scholarly journals Multi-objective optimization of solar thermal photovoltaic hybrid power generation system based on NSGA-II algorithm

2021 ◽  
Vol 336 ◽  
pp. 02022
Author(s):  
Liang Meng ◽  
Wen Zhou ◽  
Yang Li ◽  
Zhibin Liu ◽  
Yajing Liu
Keyword(s):  
Power Generation ◽  
Optimization Problems ◽  
Optimal Solution ◽  
Solar Thermal ◽  
Multi Objective Optimization ◽  
Generation System ◽  
Nsga Ii ◽  
Multi Objective ◽  
Hybrid Power ◽  
Power Generation System

In this paper, NSGA-Ⅱ is used to realize the dual-objective optimization and three-objective optimization of the solar-thermal photovoltaic hybrid power generation system; Compared with the optimal solution set of three-objective optimization, optimization based on technical and economic evaluation indicators belongs to the category of multi-objective optimization. It can be considered that NSGA-Ⅱ is very suitable for multi-objective optimization of solar-thermal photovoltaic hybrid power generation system and other similar multi-objective optimization problems.

scholarly journals Multi‐objective optimization of solar‐aided coal‐fired power generation system under off‐design work conditions

2019 ◽  
Vol 7 (2) ◽  
pp. 379-398 ◽  
Author(s):  
Jianxing Wang ◽  
Liqiang Duan ◽  
Yongping Yang ◽  
Liping Pang ◽  
Laishun Yang
Keyword(s):  
Power Generation ◽  
Work Conditions ◽  
Multi Objective Optimization ◽  
Generation System ◽  
Design Work ◽  
Multi Objective ◽  
Power Generation System

Analysis and Operation Optimization of Recompression Supercritical Carbon Dioxide Power Generation System Based on the Power Flow Method

2018 ◽  
Author(s):  
Xia Li ◽  
Qun Chen ◽  
Xi Chen
Keyword(s):  
Heat Transfer ◽  
Carbon Dioxide ◽  
Power Generation ◽  
Mass Flow ◽  
Power Flow ◽  
Heat Transfer Process ◽  
Working Fluid ◽  
Generation System ◽  
Fluid Properties ◽  
Power Generation System

Due to the peculiar physical properties, supercritical carbon dioxide (sCO2) is considered as a promising working fluid in power generation cycles with high reliability, simple structure and great efficiency. Compared with the general thermal systems, the variable properties of sCO2 make the system models obtained by the traditional modelling method more complex. Besides, the pressure distribution in the system will affect the distribution of the fluid properties, the fluid properties influencing the heat transfer process will produce an impact on the temperature distribution which will in turn affect the pressure distribution through the mass flow characteristics of all components. This contribution introduces the entransy-based power flow method to analyze and optimize a recompression sCO2 power generation system under specific boundary conditions. About the heat exchanger, by subdividing the heat transfer area into several segment, the fluid properties in each segment are considered constant. Combining the entransy dissipation thermal resistance of each segment and the energy conservation of each fluid in each segment offers the governing equations for the whole heat transfer process without any intermediate segment temperatures, based on which the power flow diagram of the overall heat transfer process is constructed. Meanwhile, the pressure drops are constrained by the mass flow characteristics of each component, and the inlet and outlet temperatures of compressors and turbines are constrained by the isentropic process constraints and the isentropic efficiencies. Combining the governing equations for the heat exchangers and the constraints for turbine and the compressors, the whole system is modeled by sequential modular method. Based on this newly developed model, applying the genetic algorithm offers the maximum thermal efficiency of the system and the corresponding optimal operating variables, such as the mass flow rate of the working fluid in the cycle, the heat capacity rate of the cold source and the recompression mass fraction under the given heat source. Furthermore, the optimization of the system under different boundary conditions is conducted to study its influence on the optimal mass flow rate of the working fluid, the heat capacity of the cold source and the maximum system thermal efficiency. The results proposes some useful design suggestions to get better performance of the recompression supercritical carbon dioxide power generation system.

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