IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i8p6545-d1121910.html
   My bibliography  Save this article

A New Multi-Heuristic Method to Optimize the Ammonia–Water Power/Cooling Cycle Combined with an HCCI Engine

Author

Listed:
  • Keyvan Bahlouli

    (Energy System Engineering Program, Mechanical Engineering Department, Cyprus International University, 99258 Nicosia, TRNC, Turkey)

  • Nasser Lotfi

    (Computer Engineering Department, Cyprus International University, 99258 Nicosia, TRNC, Turkey)

  • Mazyar Ghadiri Nejad

    (Industrial Engineering Department, Cyprus International University, 99258 Nicosia, TRNC, Turkey)

Abstract

Nowadays, sustainability is one of the key elements which should be considered in energy systems. Such systems are essential in any manufacturing system to supply the energy requirements of those systems. To optimize the energy consumption of any manufacturing system, various applications have been developed in the literature, with a number of pros and cons. In addition, in the majority of such applications, multi-objective optimization (MOO) plays an outstanding role. In related studies, the MOO strategy has been mainly used to maximize the performance and minimize the total cost of a trigeneration system with an HCCI (homogeneous charge compression ignition) engine as a prime mover based on the NSGA-II (non-dominated sorting genetic algorithm-II) algorithm. The current study introduces a novel multi-heuristic system (MHS) that serves as a metaheuristics cooperation platform for selecting the best design parameters. The MHS operates on a proposed strategy and prefers short runs of various metaheuristics to a single long run of a metaheuristic. The proposed MHS consists of four multi-objective metaheuristics collaborating to work on a common population of solutions. The optimization aims to maximize the exergy efficiency and minimize the total system cost. By utilizing four local archives and one global archive, the system optimizes these two objective functions. The idea behind the proposed MHS is that metaheuristics will be able to compensate for each other’s shortcomings in terms of extracting the most promising regions of the search space. Comparing the findings of the developed MHS shows that implementing the suggested strategy decreases the total unit costs of the system products to 25.85 USD/GJ, where the total unit cost of the base system was 28.89 USD/GJ, and the exergy efficiency of the system is increased up to 39.37%, while this efficiency was 22.81% in the base system. The finding illustrates significant improvements in system results and proves the high performance of the proposed method.

Suggested Citation

  • Keyvan Bahlouli & Nasser Lotfi & Mazyar Ghadiri Nejad, 2023. "A New Multi-Heuristic Method to Optimize the Ammonia–Water Power/Cooling Cycle Combined with an HCCI Engine," Sustainability, MDPI, vol. 15(8), pages 1-14, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6545-:d:1121910
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/8/6545/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/8/6545/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bahlouli, K. & Khoshbakhti Saray, R. & Sarabchi, N., 2015. "Parametric investigation and thermo-economic multi-objective optimization of an ammonia–water power/cooling cycle coupled with an HCCI (homogeneous charge compression ignition) engine," Energy, Elsevier, vol. 86(C), pages 672-684.
    2. Hajabdollahi, Zahra & Hajabdollahi, Farzaneh & Tehrani, Mahdi & Hajabdollahi, Hassan, 2013. "Thermo-economic environmental optimization of Organic Rankine Cycle for diesel waste heat recovery," Energy, Elsevier, vol. 63(C), pages 142-151.
    3. Tichi, S.G. & Ardehali, M.M. & Nazari, M.E., 2010. "Examination of energy price policies in Iran for optimal configuration of CHP and CCHP systems based on particle swarm optimization algorithm," Energy Policy, Elsevier, vol. 38(10), pages 6240-6250, October.
    4. Sarabchi, N. & Khoshbakhti Saray, R. & Mahmoudi, S.M.S., 2013. "Utilization of waste heat from a HCCI (homogeneous charge compression ignition) engine in a tri-generation system," Energy, Elsevier, vol. 55(C), pages 965-976.
    5. Wang, Jiangjiang & Zhai, Zhiqiang (John) & Jing, Youyin & Zhang, Chunfa, 2010. "Particle swarm optimization for redundant building cooling heating and power system," Applied Energy, Elsevier, vol. 87(12), pages 3668-3679, December.
    6. Khaljani, M. & Saray, R. Khoshbakhti & Bahlouli, K., 2016. "Evaluation of a combined cycle based on an HCCI (Homogenous Charge Compression Ignition) engine heat recovery employing two organic Rankine cycles," Energy, Elsevier, vol. 107(C), pages 748-760.
    7. Zinsalo, Joël M. & Lamarche, Louis & Raymond, Jasmin, 2022. "Performance analysis and working fluid selection of an Organic Rankine Cycle Power Plant coupled to an Enhanced Geothermal System," Energy, Elsevier, vol. 245(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jradi, M. & Riffat, S., 2014. "Tri-generation systems: Energy policies, prime movers, cooling technologies, configurations and operation strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 396-415.
    2. Khaljani, M. & Saray, R. Khoshbakhti & Bahlouli, K., 2016. "Evaluation of a combined cycle based on an HCCI (Homogenous Charge Compression Ignition) engine heat recovery employing two organic Rankine cycles," Energy, Elsevier, vol. 107(C), pages 748-760.
    3. Sara Ghaem Sigarchian & Anders Malmquist & Viktoria Martin, 2018. "Design Optimization of a Small-Scale Polygeneration Energy System in Different Climate Zones in Iran," Energies, MDPI, vol. 11(5), pages 1-19, May.
    4. Bahlouli, Keyvan & Khoshbakhti Saray, Rahim, 2016. "Energetic and exergetic analyses of a new energy system for heating and power production purposes," Energy, Elsevier, vol. 106(C), pages 390-399.
    5. Wei, Dajun & Chen, Alian & Sun, Bo & Zhang, Chenghui, 2016. "Multi-objective optimal operation and energy coupling analysis of combined cooling and heating system," Energy, Elsevier, vol. 98(C), pages 296-307.
    6. Zare, A. Darabadi & Saray, R. Khoshbakhti & Mirmasoumi, S. & Bahlouli, K., 2019. "Optimization strategies for mixing ratio of biogas and natural gas co-firing in a cogeneration of heat and power cycle," Energy, Elsevier, vol. 181(C), pages 635-644.
    7. Zhang, Guoqing & Wang, Jiangjiang & Ren, Fukang & Liu, Yi & Dong, Fuxiang, 2021. "Collaborative optimization for multiple energy stations in distributed energy network based on electricity and heat interchanges," Energy, Elsevier, vol. 222(C).
    8. Hu, Mengqi & Cho, Heejin, 2014. "A probability constrained multi-objective optimization model for CCHP system operation decision support," Applied Energy, Elsevier, vol. 116(C), pages 230-242.
    9. Jayasekara, Saliya & Halgamuge, Saman K. & Attalage, Rahula A. & Rajarathne, Rohitha, 2014. "Optimum sizing and tracking of combined cooling heating and power systems for bulk energy consumers," Applied Energy, Elsevier, vol. 118(C), pages 124-134.
    10. Bahri, Bahram & Shahbakhti, Mahdi & Aziz, Azhar Abdul, 2017. "Real-time modeling of ringing in HCCI engines using artificial neural networks," Energy, Elsevier, vol. 125(C), pages 509-518.
    11. He, Zhaoyu & Guo, Weimin & Zhang, Peng, 2022. "Performance prediction, optimal design and operational control of thermal energy storage using artificial intelligence methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    12. Ibrahim, Amin & Rahnamayan, Shahryar & Vargas Martin, Miguel & Yilbas, Bekir, 2014. "Multi-objective thermal analysis of a thermoelectric device: Influence of geometric features on device characteristics," Energy, Elsevier, vol. 77(C), pages 305-317.
    13. Khaljani, M. & Khoshbakhti Saray, R. & Bahlouli, K., 2015. "Thermodynamic and thermoeconomic optimization of an integrated gas turbine and organic Rankine cycle," Energy, Elsevier, vol. 93(P2), pages 2136-2145.
    14. Kai Yang & Hongguang Zhang & Songsong Song & Jian Zhang & Yuting Wu & Yeqiang Zhang & Hongjin Wang & Ying Chang & Chen Bei, 2014. "Performance Analysis of the Vehicle Diesel Engine-ORC Combined System Based on a Screw Expander," Energies, MDPI, vol. 7(5), pages 1-20, May.
    15. Yeqiang Zhang & Biao Lei & Zubair Masaud & Muhammad Imran & Yuting Wu & Jinping Liu & Xiaoding Qin & Hafiz Ali Muhammad, 2020. "Waste Heat Recovery from Diesel Engine Exhaust Using a Single-Screw Expander Organic Rankine Cycle System: Experimental Investigation of Exergy Destruction," Energies, MDPI, vol. 13(22), pages 1-15, November.
    16. Alklaibi, A.M. & Lior, N., 2021. "Waste heat utilization from internal combustion engines for power augmentation and refrigeration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    17. Piacentino, Antonio & Barbaro, Chiara & Cardona, Fabio & Gallea, Roberto & Cardona, Ennio, 2013. "A comprehensive tool for efficient design and operation of polygeneration-based energy μgrids serving a cluster of buildings. Part I: Description of the method," Applied Energy, Elsevier, vol. 111(C), pages 1204-1221.
    18. Jie, Pengfei & Yan, Fuchun & Li, Jing & Zhang, Yumei & Wen, Zhimei, 2019. "Optimizing the insulation thickness of walls of existing buildings with CHP-based district heating systems," Energy, Elsevier, vol. 189(C).
    19. Ren, Fukang & Wei, Ziqing & Zhai, Xiaoqiang, 2021. "Multi-objective optimization and evaluation of hybrid CCHP systems for different building types," Energy, Elsevier, vol. 215(PA).
    20. Bostan, Alireza & Nazar, Mehrdad Setayesh & Shafie-khah, Miadreza & Catalão, João P.S., 2020. "Optimal scheduling of distribution systems considering multiple downward energy hubs and demand response programs," Energy, Elsevier, vol. 190(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6545-:d:1121910. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.