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Optimization design of heat recovery systems on rotary kilns using genetic algorithms

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  • Yin, Qian
  • Du, Wen-Jing
  • Cheng, Lin

Abstract

Heat loss from rotary kilns accounts for certain amounts of the total energy consumption in chemical and metallurgical industries. To reduce the heat loss, a parallel and a series-parallel heat recovery systems with nine heat recovery exchangers are proposed to preheat the cold water in this paper. Experimental measurements are carried out to determine the heat transfer coefficient equations of each heat recovery exchanger. Then, the heat recovery systems are analyzed to deduce the mathematic relation between the design parameters and the system requirements, i.e. the temperatures and heat transfer rates of the nine heat recovery exchangers. The total heat transfer area, the total power consumption and the entropy generation due to heat transfer and fluid flow are set as the objective functions in four multi-objective optimization (MOO) cases. With the aid of the genetic algorithm in the Matlab 2015, the optimized operational and structural parameters are obtained. Finally, the MOO results are compared with that of the single objective optimization (SOO) method and the original values. The optimization results show that the MOO method are more suitable for the operational parameters design of the heat recovery systems compared with the SOO method. The required total heat transfer area and the total power consumption are decreased by at least 12.1% and 13.7%, respectively. Besides, as the entropy generation due to heat transfer and fluid flow decrease in the MOO cases, the corresponding heat transfer area and power consumption of the heat recovery system decrease, respectively.

Suggested Citation

  • Yin, Qian & Du, Wen-Jing & Cheng, Lin, 2017. "Optimization design of heat recovery systems on rotary kilns using genetic algorithms," Applied Energy, Elsevier, vol. 202(C), pages 153-168.
    • Handle: RePEc:eee:appene:v:202:y:2017:i:c:p:153-168
    DOI: 10.1016/j.apenergy.2017.05.072
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    References listed on IDEAS

    as
    1. Arora, Ranjana & Kaushik, S.C. & Arora, Rajesh, 2015. "Multi-objective and multi-parameter optimization of two-stage thermoelectric generator in electrically series and parallel configurations through NSGA-II," Energy, Elsevier, vol. 91(C), pages 242-254.
    2. Yuan, Xiaohui & Zhang, Binqiao & Wang, Pengtao & Liang, Ji & Yuan, Yanbin & Huang, Yuehua & Lei, Xiaohui, 2017. "Multi-objective optimal power flow based on improved strength Pareto evolutionary algorithm," Energy, Elsevier, vol. 122(C), pages 70-82.
    3. Sharafi, Masoud & ELMekkawy, Tarek Y., 2014. "Multi-objective optimal design of hybrid renewable energy systems using PSO-simulation based approach," Renewable Energy, Elsevier, vol. 68(C), pages 67-79.
    4. Cui, Yunfei & Geng, Zhiqiang & Zhu, Qunxiong & Han, Yongming, 2017. "Review: Multi-objective optimization methods and application in energy saving," Energy, Elsevier, vol. 125(C), pages 681-704.
    5. Antipova, Ekaterina & Boer, Dieter & Cabeza, Luisa F. & Guillén-Gosálbez, Gonzalo & Jiménez, Laureano, 2013. "Multi-objective design of reverse osmosis plants integrated with solar Rankine cycles and thermal energy storage," Applied Energy, Elsevier, vol. 102(C), pages 1137-1147.
    6. Manjunath, K. & Kaushik, S.C., 2014. "Second law thermodynamic study of heat exchangers: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 348-374.
    7. Hu, Yuan & Bie, Zhaohong & Ding, Tao & Lin, Yanling, 2016. "An NSGA-II based multi-objective optimization for combined gas and electricity network expansion planning," Applied Energy, Elsevier, vol. 167(C), pages 280-293.
    8. Chen, Qun & Wang, Yi-Fei & Xu, Yun-Chao, 2015. "A thermal resistance-based method for the optimal design of central variable water/air volume chiller systems," Applied Energy, Elsevier, vol. 139(C), pages 119-130.
    9. Yang, Fubin & Zhang, Hongguang & Song, Songsong & Bei, Chen & Wang, Hongjin & Wang, Enhua, 2015. "Thermoeconomic multi-objective optimization of an organic Rankine cycle for exhaust waste heat recovery of a diesel engine," Energy, Elsevier, vol. 93(P2), pages 2208-2228.
    10. Kabir, G. & Abubakar, A.I. & El-Nafaty, U.A., 2010. "Energy audit and conservation opportunities for pyroprocessing unit of a typical dry process cement plant," Energy, Elsevier, vol. 35(3), pages 1237-1243.
    11. Wang, Yi-Fei & Chen, Qun, 2015. "A direct optimal control strategy of variable speed pumps in heat exchanger networks and experimental validations," Energy, Elsevier, vol. 85(C), pages 609-619.
    12. Delgarm, N. & Sajadi, B. & Kowsary, F. & Delgarm, S., 2016. "Multi-objective optimization of the building energy performance: A simulation-based approach by means of particle swarm optimization (PSO)," Applied Energy, Elsevier, vol. 170(C), pages 293-303.
    13. Karellas, S. & Leontaritis, A.-D. & Panousis, G. & Bellos, E. & Kakaras, E., 2013. "Energetic and exergetic analysis of waste heat recovery systems in the cement industry," Energy, Elsevier, vol. 58(C), pages 147-156.
    14. Vaskan, Pavel & Guillén-Gosálbez, Gonzalo & Jiménez, Laureano, 2012. "Multi-objective design of heat-exchanger networks considering several life cycle impacts using a rigorous MILP-based dimensionality reduction technique," Applied Energy, Elsevier, vol. 98(C), pages 149-161.
    15. Yin, Qian & Du, Wen-Jing & Ji, Xing-Lin & Cheng, Lin, 2016. "Optimization design and economic analyses of heat recovery exchangers on rotary kilns," Applied Energy, Elsevier, vol. 180(C), pages 743-756.
    16. Atmaca, Adem & Kanoglu, Mehmet, 2012. "Reducing energy consumption of a raw mill in cement industry," Energy, Elsevier, vol. 42(1), pages 261-269.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Jaroslaw Krzywanski, 2019. "A General Approach in Optimization of Heat Exchangers by Bio-Inspired Artificial Intelligence Methods," Energies, MDPI, vol. 12(23), pages 1-32, November.
    2. Matelli, José Alexandre & Goebel, Kai, 2018. "Conceptual design of cogeneration plants under a resilient design perspective: Resilience metrics and case study," Applied Energy, Elsevier, vol. 215(C), pages 736-750.
    3. Chen, Xi & Chen, Qun & Chen, Hong & Xu, Ying-Gen & Zhao, Tian & Hu, Kang & He, Ke-Lun, 2019. "Heat current method for analysis and optimization of heat recovery-based power generation systems," Energy, Elsevier, vol. 189(C).

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