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Exergy-Based Multi-Objective Optimization of an Organic Rankine Cycle with a Zeotropic Mixture.
Fergani, Zineb; Morosuk, Tatiana; Touil, Djamel.
Afiliação
  • Fergani Z; Laboratory of Biomaterials and Transport Phenomena, Department of Process and Environmental Engineering, University of Medea, Medea 26000, Algeria.
  • Morosuk T; Institute for Energy Engineering, Technische Universität Berlin, 10587 Berlin, Germany.
  • Touil D; Department of Process Engineering, Faculty of Technology, University of Blida, Blida 090000, Algeria.
Entropy (Basel) ; 23(8)2021 Jul 26.
Article em En | MEDLINE | ID: mdl-34441094
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Entropy (Basel) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Argélia País de publicação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Entropy (Basel) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Argélia País de publicação: Suíça