Performance assessment and multi objective optimization of an Organic Rankine Cycle driven cooling air conditioning system

Muhammad Tauseef Nasir, Muhammad Ansab Ali, Tariq S. Khan, Ebrahim Al-Hajri, Muhammad Bilal Kadri, Kyung Chun Kim

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

Present work aims to investigate the thermal performance assessment of different combinations of working fluids for an Organic Rankine Cycle powered Vapor Compression Cycle (ORC-VCC) for air-conditioning applications. Analysis of system performance is conducted for a fixed cooling load of a small conditioned space having a sensible heat factor of 0.7, at different ambient conditions. A preliminary evaluation of the system at the baseline conditions was conducted considering the second law efficiency, overall heat capacity of exchangers, overall internal exergy destruction, and overall Coefficient of Performance. Afterwards, parametric study was performed for the best performing candidates from the preliminary analysis using second law efficiency and overall heat capacity of heat exchangers. The system parameters considered for the study include saturated temperatures of heat exchangers, ORC boiler superheat, pinch points and the sub-cooling of both the ORC and VCC condensers. Then, multi objective optimization was performed using Genetic Algorithm followed by multi-criteria decision-making using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to select the best optimal solutions from the Pareto front. Sixteen combinations comprising of four working fluids, R245fa, R600, R600a, and R134a were analyzed. The optimization results showed R245fa ORC-R600a VCC to be the best candidate at ambient conditions of 30 °C, while at 35 °C and 40 °C, R600a ORC-R245fa VCC was found to be the most suitable candidate.

Original languageBritish English
Pages (from-to)13-30
Number of pages18
JournalEnergy and Buildings
Volume191
DOIs
StatePublished - 15 May 2019

Keywords

  • Air conditioning
  • Low grade heat
  • Multi-objective optimization
  • Organic Rankine Cycle
  • Vapor compression cycle

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