Energy, exergy, and economic (3E) analyses and multi-objective optimization of a cascade absorption refrigeration system for low-grade waste heat recovery. (15th March 2019)

• Record Type: Journal Article
• Authors: Cui, Peizhe; Yu, Mengxiao; Liu, Zhiqiang; Zhu, Zhaoyou; Yang, Sheng
• Is Part Of: Energy conversion and management. Volume 184(2019)
• Page Start: 249
• Page End: 261
• Publication Date: 2019-03-15
• Subjects: Cascade absorption refrigeration system -- Energy -- Exergy -- Economic -- Multi-objective optimization; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2019.01.047
• Languages: English
• ISSNs: 0196-8904

Abstract

Highlights: A cascade absorption refrigeration system is proposed. The proposed system is used to recover low-grade waste heat. Thermodynamic models of the proposed system have been built. Energy, exergy and economic analyses have been conducted. The multi-objective optimization scheme is optimized by NSGA-II. Abstract: In the present study, an innovative cascade absorption refrigeration (CAR) system for recovering low-grade waste heat is proposed. Based on the simulation results, the energy, exergy and economic (3E) analyses of the cascade refrigeration system have been conducted. The analysis results show that there is a contradiction between economic performance and thermodynamic performance. Then, the optimization scheme aiming at total exergy destruction ( E ̇ D t ), the optimization scheme aiming at total annual cost (Ct ) and multi-objective optimization scheme (Ct and E ̇ D t ) are optimized by non-dominated sort genetic algorithm-II (NSGA-II) technology. E ̇ D t is 11% more than its minimum result in the optimization scheme aiming at total annual cost, which shows that the thermal performance of the scheme is poor. Ct is 14.8% more than its minimum result in the optimization scheme aiming at total exergy destruction, which shows that the scheme is not economical. Ct and E ̇ D t are only 5.9% and 4.5% respectively higher than their minimum results in the multi-objective optimization scheme. Therefore, multi-objective optimization scheme is the most comprehensive and optimal scheme of the CAR system.