scholarly journals Exergy-Based Multi-Objective Optimization of an Organic Rankine Cycle with a Zeotropic Mixture

Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 954
Author(s):  
Zineb Fergani ◽  
Tatiana Morosuk ◽  
Djamel Touil
Keyword(s):  
Organic Rankine Cycle ◽  
Optimal Solution ◽  
Rankine Cycle ◽  
Working Fluid ◽  
Particle Swarm Algorithm ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Benzene Toluene ◽  
Zeotropic Mixture

In this paper, the performance of an organic Rankine cycle with a zeotropic mixture as a working fluid was evaluated using exergy-based methods: exergy, exergoeconomic, and exergoenvironmental analyses. The effect of system operation parameters and mixtures on the organic Rankine cycle’s performance was evaluated as well. The considered performances were the following: exergy efficiency, specific cost, and specific environmental effect of the net power generation. A multi-objective optimization approach was applied for parametric optimization. The approach was based on the particle swarm algorithm to find a set of Pareto optimal solutions. One final optimal solution was selected using a decision-making method. The optimization results indicated that the zeotropic mixture of cyclohexane/toluene had a higher thermodynamic and economic performance, while the benzene/toluene zeotropic mixture had the highest environmental performance. Finally, a comparative analysis of zeotropic mixtures and pure fluids was conducted. The organic Rankine cycle with the mixtures as working fluids showed significant improvement in energetic, economic, and environmental performances.

scholarly journals Configuration Selection of the Multi-Loop Organic Rankine Cycle for Recovering Energy from a Single Source

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1435
Author(s):  
Youyi Li ◽  
Tianhao Tang
Keyword(s):  
Heat Source ◽  
Waste Heat ◽  
Organic Rankine Cycle ◽  
Optimal Solution ◽  
Rankine Cycle ◽  
Optimal Number ◽  
Exergy Efficiency ◽  
Working Fluid ◽  
Levelized Cost Of Electricity ◽  
Multi Objective

The Organic Rankine Cycle (ORC) is a well-established way to recover energy from a single waste heat source. This paper aims to select the suitable configuration, number of loops, and working fluids for the Multi-Loop ORC (MLORC) by using multi-objective optimization. The thermodynamic and economic performance of MLORC in three various configurations was analyzed. Multi-objective optimizations of the series and parallel MLORC using different working fluid groups were conducted to find the optimal configuration, number of loops, and working fluid combination. The analysis results show that the series–parallel MLORC performed the worst among the three configurations. The optimization results reveal that series MLORC has a higher exergy efficiency than the parallel MLORC. The exergy efficiency of the optimal solution in series dual-loop, triple-loop, and quadruple-loop ORC is 9.3%, 7.98%, and 6.23% higher than that of parallel ORC, respectively. Furthermore, dual-loop is the optimal number of cycles for recovering energy from a single heat source, according to the grey relational grade. Finally, the series dual-loop ORC using cyclohexane\cyclohexane was the suitable configuration for utilizing a single waste heat source. The exergy efficiency and levelized cost of electricity of the series dual-loop ORC with the optimal parameters are 62.18% and 0.1509 $/kWh, respectively.

scholarly journals Multi-objective optimization of CuO based organic Rankine cycle operated using R245ca

2019 ◽  
Vol 116 ◽  
pp. 00062 ◽  
Author(s):  
Parth Prajapati ◽  
Vivek Patel
Keyword(s):  
Heat Transfer ◽  
Thermal Efficiency ◽  
Heat Exchangers ◽  
Waste Heat ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Working Fluid ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Source Fluid

The present work deals with multi objective optimization of nanofluid based Organic Rankine Cycle (ORC) to utilise waste heat energy. Working fluid considered for the study is R245ca for its good thermodynamic properties and lower Global Warming Potential (GWP) compared to the conventional fluids used in the waste heat recovery system. Heat Transfer Search (HTS) algorithm is used to optimize the objective functions which tends to maximize thermal efficiency and minimize Levelised Energy Cost (LEC). To enhance heat transfer between the working fluid and source fluid, nanoparticles are added to the source fluid. Application of nanofluids in the heat transfer system helps in maximizing recovery of the waste heat in the heat exchangers. Based on the availability and cost, CuO nanoparticles are considered for the study. Effect of Pinch Point Temperature Difference (PPTD) and concentration of nanoparticles in heat exchangers is studied and discussed. Results showed that nanofluids based ORC gives maximum thermal efficiency of 18.50% at LEC of 2.59 $/kWh. Total reduction of 7.11% in LEC can be achieved using nanofluids.

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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