Multi-objective optimization of ORC parameters and selection of working fluid using preliminary radial inflow turbine design

2019 ◽  
Vol 183 ◽  
pp. 833-847 ◽  
Author(s):  
Hasan Eren Bekiloğlu ◽  
Hasan Bedir ◽  
Günay Anlaş
Author(s):  
K. Rahbar ◽  
S. Mahmoud ◽  
R. K. Al-Dadah ◽  
N. Moazami

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%.


2022 ◽  
Vol 252 ◽  
pp. 115136
Author(s):  
Nikolaos Georgousis ◽  
Panagiotis Lykas ◽  
Evangelos Bellos ◽  
Christos Tzivanidis

Author(s):  
Cristina Johansson ◽  
Johan Ölvander ◽  
Micael Derelöv

In early design phases, it is vital to be able to screen the design space for a set of promising design alternatives for further study. This article presents a method able to balance several objectives of different mathematical natures, with high impact on the design choices. The method (MOSART) handles multi-objective optimization for safety and reliability trade-offs. The article focuses on optimization problem approach and processing of results as a base for decision-making. The output of the optimization step is the selection of specific system elements obtaining the best balance between the targets. However, what is a good base for decision can easily transform into too much information and overloading of the decision-maker. To solve this potential issue, from a set of Pareto optimal solutions, a smaller sub-set of selected solutions are visualized and filtered out using preference levels of the objectives, yielding a solid base for decision-making and valuable information on potential solutions. Trends were observed regarding each system element and discussed while processing the results of the analysis, supporting the decision of one final best solution.


Author(s):  
Jiangfeng Guo ◽  
Mengxun Li ◽  
Mingtian Xu ◽  
Lin Cheng

The heat conduction and fluid friction are two main detrimental irreversibilities in heat exchanger. According to the entransy dissipation theory, the entransy dissipation can be employed to quantify these two irreversibilities. In the present work, the optimization of heat exchanger design is investigated by applying the entransy dissipation theory and genetic algorithm. Firstly, by taking the total dimensionless entransy dissipation caused by heat conduction and fluid friction as objective function, a single-objective optimization approach to heat exchanger design is developed. However, it is found that the role played by the fluid friction is not fully taken into account in this approach when the working fluid of heat exchanger is liquid. In order to circumvent this problem, the non-dimensional entransy dissipations associated with heat conduction and fluid friction are taken as two separate objective functions and a multi-objective optimization approach to heat exchanger design is established. In comparison with the single-objective optimization approach, the multi-objective optimization approach demonstrates more advantages and flexibilities for heat exchanger design.


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