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Three-step modification and optimization of Kalina power-cooling cogeneration based on energy, pinch, and economics analyses
被引:15
作者:
Dehghani, Mohammad Javad
[1
]
Yoo, ChangKyoo
[1
]
机构:
[1] Kyung Hee Univ, Coll Engn, Ctr Environm Studies, Dept Environm Sci & Engn, Seocheon Dong 1, Yongin 446701, Gyeonggi Do, South Korea
来源:
基金:
新加坡国家研究基金会;
关键词:
Kalina power-cooling plant;
Genetic algorithm multi-objective optimization;
Heat pinch analysis;
Nonlinear programming;
Geometry of heat exchanger;
Climate change adaption;
HEAT-EXCHANGER NETWORKS;
THERMODYNAMIC ANALYSIS;
THERMOECONOMIC ANALYSIS;
CYCLE SYSTEM;
EXERGY ANALYSIS;
WATER;
PERFORMANCE;
DRIVEN;
RECOVERY;
CONDENSATION;
D O I:
10.1016/j.energy.2020.118069
中图分类号:
O414.1 [热力学];
学科分类号:
摘要:
This study proposes a systematic approach for modification and optimization of Kalina power-cooling cogeneration (KPCC) under a three-step procedure. In the first of three steps, KPCC is modeled and optimized thermodynamically by a non-dominated sorting genetic algorithm II (NSGA-II). In the second step, heat pinch analysis (HEPA) modifies the performance of KPCC heat exchangers network (HEN). Finally, the geometries of the heat exchangers are optimized by nonlinear programming (NLP) to minimize the system's purchasing cost. The results showed that KPCC could achieve thermal and power-cooling efficiencies of 12.1% and 38.6%, respectively. Moreover, the HEN satisfied HEPA constraints with nine exchangers at a minimum temperature difference (DT) of 10 K. By employing NLP, investment costs of the heat exchangers were reduced significantly and the overall investment costs of KPCC decreased by approximately 31%, demonstrating that the three-step procedure can optimize KPCC efficiency while minimizing costs. (C) 2020 Elsevier Ltd. All rights reserved.
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页数:12
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