Multiobjective optimization of a cogeneration system based on gas turbine, organic rankine cycle and double-effect absorbtion chiller

Hai T 1 , Alsubai S 2 , Yahya RO 3 , Gemeay E 4 , Sharma K 5 , Alqahtani A 6 Show all authors , Alanazi A 2

Affiliations 

  • 1 School of Computer and Information, Qiannan Normal University for Nationalities, Duyun, Guizhou, 558000, China; School of Electronics and Information Engineering, Ankang University, Ankang, China; Institute for Big Data Analytics and Artifcial Intelligence (IBDAAI), Universiti Teknologi MARA, Shah Alam, Selangor, 40450, Malaysia. Electronic address: [email protected]
  • 2 Department of Computer Science, College of Computer Engineering and Sciences in Al-Kharj, Prince Sattam Bin Abdulaziz University, P.O. Box 151, Al-Kharj 11942, Saudi Arabia
  • 3 Department of Computer Science, College of Science, Cihan University-Erbil, Erbil, Iraq
  • 4 Department of Computer Engineering, Computer and Information Technology College, Taif University, Taif, Saudi Arabia; Department of Electronics and Communication Engineering, College of Engineering, Tanta University, Tanta, Egypt
  • 5 Institute of Engineering and Technology, GLA University, Mathura, UP 281406, India
  • 6 Software Engineering Department, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, P.O. Box 151, Al-Kharj 11942, Saudi Arabia
Chemosphere, 2023 Oct;338:139371.
PMID: 37442387 DOI: 10.1016/j.chemosphere.2023.139371

Abstract

Combined cooling, heating and power (CCHP) is one of methods for enhancing the efficiency of the energy conversion systems. In this study a CCHP system consisting of a gas turbin (GT) as the topping cycle, and an organic Rankine cycle (ORC) associated with double-effect absorbtion chiller (DEACH) is decisioned as the bottoming cycle to recover the waste heat from GT exhaust gas. The considered CCHP system is investigated to maintain electricity, heating and cooling demand of a town. A parametric study is investigated and the effect decision variables on the performance indicators including exergy efficiency, total cost rate (TCR), cooling capacity, and ORC power generation is examined. Decision variables of the ORC system consist of HRVG pressure, and condenser pressure and the DEACH including evaporator pressure, condseser pressure, concentration of the concentrated solution, concentration of the weak solution, and solution mass flow rate. Finally a multi-objective optimization performed using Genetic Algorithm (GA) and the optimal design point is selected. It is observed at the optimum point the exergy efficiency, TCR, and sustainability index are 17.56%, 74.49 $/h, and 1.21, respectively.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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