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Performance analysis and multi-objective optimization of an organic Rankine cycle with binary zeotropic working fluid employing modified artificial bee colony algorithm

Sadeghi, S ; Sharif University of Technology | 2019

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  1. Type of Document: Article
  2. DOI: 10.1007/s10973-018-7801-y
  3. Publisher: Springer Netherlands , 2019
  4. Abstract:
  5. From a thermal point of view, zeotropic mixtures are likely to be more efficient than azeotropic fluids in low-temperature power cycles for reduction in exergy destruction occurring during heat absorption/rejection processes due to their suitable boiling characteristics. In this study, comprehensive energetic and exergetic analyses are mathematically performed for an organic Rankine cycle (ORC) system employing a potential binary zeotropic working fluid, namely R717/water. For this purpose, initially mass, energy, and exergy balance equations are derived. With regard to the similarity in molar mass of R717 (17.03 g mol −1 ) and water (18.01 g mol −1 ), there is no need to alter the size of the ORC components such as turbine and pump. In order to achieve the optimal thermal and exergy efficiencies of the ORC system, modified version a powerful and relatively new optimization algorithm called artificial bee colony (ABC) is used taking into account different effective constraints. The main motivation behind using ABC lies on its robustness, reliability, and convergence rate speed in dealing with complicated constrained multi-objective problems. Convergence rates of the algorithm for optimal calculation of the efficiencies are presented. Subsequently, due to the importance of exergy concept in ORC systems, exergy destructions occurring in the components are computed. Finally, the impacts of pressure, temperature, mass fraction, and mass flow rate on the ORC thermal and exergy efficiencies are discussed. © 2018, Akadémiai Kiadó, Budapest, Hungary
  6. Keywords:
  7. Artificial bee colony algorithm ; Binary zeotropic mixture ; Exergy efficiency ; Multi-objective optimization ; Organic Rankine cycle ; Evolutionary algorithms ; Exergy ; Fluids ; Mixtures ; Multiobjective optimization ; Temperature ; Artificial bee colony algorithms ; Exergy efficiencies ; Organic Rankine cycles ; Thermal efficiency ; Zeotropic mixture ; Rankine cycle
  8. Source: Journal of Thermal Analysis and Calorimetry ; Volume 136, Issue 4 , 2019 , Pages 1645-1665 ; 13886150 (ISSN)
  9. URL: https://link.springer.com/article/10.1007/s10973-018-7801-y