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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
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    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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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).
    7. 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.
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    Cited by:

    1. Song Wenjuan & Kai Zhao, 2023. "Balancing fiscal expenditure competition and long-term innovation investment: Exploring trade-offs and policy implications for local governments," PLOS ONE, Public Library of Science, vol. 18(11), pages 1-31, November.

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