Multi-objective optimization and sensitivity analysis of an organic Rankine cycle coupled with a one-dimensional radial-inflow turbine efficiency prediction model

2018 ◽  
Vol 166 ◽  
pp. 37-47 ◽  
Author(s):  
Zhonghe Han ◽  
Zhongkai Mei ◽  
Peng Li
Keyword(s):  
Sensitivity Analysis ◽  
Prediction Model ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Multi Objective Optimization ◽  
One Dimensional ◽  
Multi Objective ◽  
Turbine Efficiency ◽  
Radial Inflow Turbine

Integrated Modelling and Multi-Objective Optimization of Organic Rankine Cycle Based on Radial Inflow Turbine

2015 ◽  
Author(s):  
K. Rahbar ◽  
S. Mahmoud ◽  
R. K. Al-Dadah ◽  
N. Moazami
Keyword(s):  
Thermal Efficiency ◽  
Organic Rankine Cycle ◽  
Operating Conditions ◽  
Cycle Performance ◽  
Integrated Modelling ◽  
Working Fluid ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Turbine Efficiency ◽  
Radial Inflow Turbine

This paper presents the integrated modelling and multi-objective optimization of ORC based on radial inflow turbine. With this approach it is possible to replace the constant turbine efficiency with a dynamic efficiency that is unique for each set of cycle operating conditions and working fluid properties. This allows overcoming any arbitrary assumption of the turbine efficiency, unlike the previous literature, and providing a more realistic estimation of the cycle performance. Parametric studies were conducted utilizing the developed model to identify the key input variables that have significant effects on the critical turbine-ORC performance indicators. These variables were then included in the optimization process using DIRECT algorithm to optimize two objective functions as the cycle thermal efficiency and the turbine overall size for five organic fluids. Optimization results predicted that isobutane exhibited the best performance with the maximum cycle thermal efficiency of 13.21% and turbine overall size of 0.1434m while having relatively high turbine isentropic efficiency of 77.03%.

scholarly journals Multi-objective optimization of ORC geothermal conversion system integrated with life cycle assessment

2018 ◽  
Vol 70 ◽  
pp. 01012
Author(s):  
Dominika Matuszewska ◽  
Marta Kuta ◽  
Jan Górski
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Geothermal System ◽  
Geothermal Systems ◽  
Multi Objective Optimization ◽  
Geothermal Resources ◽  
Multi Objective ◽  
Conversion Technology

This paper details the development of a systematic methodology to integrated life cycle assessment (LCA) with thermo-economic models and to thereby identify the optimal exploitation schemes of geothermal resources. Overall geothermal systems consist of a superstructure of geothermal exploitable resources, a superstructure of conversion technology and multiple demand profiles for Swiss city. In this paper, an enhanced geothermal system has been chosen as exploitable resources. The energy conversion technology used in modelling is an organic Rankine cycle, which can be used to supply heat and electricity. In the Swiss case four demand profiles periods are considered: summer, interseason, winter and extreme winter, the city Nyon serving for the example case study. The multi-objective optimization system, that uses an evolutionary algorithm, is employed to determine the optimal scheme for some of the prepared models, with exergy efficiency and environmental impact as objectives.

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