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Exergy-Based Optimization of a CO 2 Polygeneration System: A Multi-Case Study

Author

Listed:
  • Bourhan Tashtoush

    (Mechanical Engineering Department, Jordan University of Science and Technology, P.O. Box 3030, Irbid 22110, Jordan)

  • Jing Luo

    (Institute for Energy Engineering, Technische Universität Berlin, Marchstr. 18, 10587 Berlin, Germany)

  • Tatiana Morosuk

    (Institute for Energy Engineering, Technische Universität Berlin, Marchstr. 18, 10587 Berlin, Germany)

Abstract

A polygeneration system for power, heat, and refrigeration has been evaluated and optimized using exergy-based methods. CO 2 is the working fluid. The study considered two environmental conditions for the potential implementation of the polygeneration system: cold (Case cold ) and hot (Case hot ). Aspen HYSYS ® was used to perform steady-state simulations, Python was used for the automation of the process, and the connection of Aspen HYSYS ® with Python was successfully applied for single-objective and multi-objective optimizations. A wide range of decision variables was implemented. The minimization of the average cost of a product per unit of exergy was the goal of single-objective optimization and was included in the multi-objective optimization in addition to the maximization of the overall exergy efficiency. Single-objective and multi-objective optimization were applied. Both optimization algorithms result in the necessity to increase the pinch temperature in the heat exchanger ( ΔT pinch,HE ), maintain the pinch temperature in the gas cooler ( ΔT pinch,GC ), and augment this value for the evaporator ( ΔT pinch,EVAP ). Notably, higher isentropic efficiency for turbomachinery correlates with improved optimization outcomes. These findings contribute to the applicability and performance of the polygeneration system, offering potential advancements in sustainable energy solutions.

Suggested Citation

  • Bourhan Tashtoush & Jing Luo & Tatiana Morosuk, 2024. "Exergy-Based Optimization of a CO 2 Polygeneration System: A Multi-Case Study," Energies, MDPI, vol. 17(2), pages 1-17, January.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:2:p:291-:d:1314354
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    References listed on IDEAS

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    2. Wang, Jiangjiang & Lu, Zherui & Li, Meng & Lior, Noam & Li, Weihua, 2019. "Energy, exergy, exergoeconomic and environmental (4E) analysis of a distributed generation solar-assisted CCHP (combined cooling, heating and power) gas turbine system," Energy, Elsevier, vol. 175(C), pages 1246-1258.
    3. Kasaeian, Alibakhsh & Bellos, Evangelos & Shamaeizadeh, Armin & Tzivanidis, Christos, 2020. "Solar-driven polygeneration systems: Recent progress and outlook," Applied Energy, Elsevier, vol. 264(C).
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