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Multi-objective exergy-based optimization of a polygeneration energy system using an evolutionary algorithm

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  • Ahmadi, Pouria
  • Rosen, Marc A.
  • Dincer, Ibrahim

Abstract

A comprehensive thermodynamic modeling and optimization is reported of a polygeneration energy system for the simultaneous production of heating, cooling, electricity and hot water from a common energy source. This polygeneration system is composed of four major parts: gas turbine (GT) cycle, Rankine cycle, absorption cooling cycle and domestic hot water heater. A multi-objective optimization method based on an evolutionary algorithm is applied to determine the best design parameters for the system. The two objective functions utilized in the analysis are the total cost rate of the system, which is the cost associated with fuel, component purchasing and environmental impact, and the system exergy efficiency. The total cost rate of the system is minimized while the cycle exergy efficiency is maximized by using an evolutionary algorithm. To provide a deeper insight, the Pareto frontier is shown for multi-objective optimization. In addition, a closed form equation for the relationship between exergy efficiency and total cost rate is derived. Finally, a sensitivity analysis is performed to assess the effects of several design parameters on the system total exergy destruction rate, CO2 emission and exergy efficiency.

Suggested Citation

  • Ahmadi, Pouria & Rosen, Marc A. & Dincer, Ibrahim, 2012. "Multi-objective exergy-based optimization of a polygeneration energy system using an evolutionary algorithm," Energy, Elsevier, vol. 46(1), pages 21-31.
    • Handle: RePEc:eee:energy:v:46:y:2012:i:1:p:21-31
    DOI: 10.1016/j.energy.2012.02.005
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    References listed on IDEAS

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    1. Rosen, Marc A. & Dincer, Ibrahim & Kanoglu, Mehmet, 2008. "Role of exergy in increasing efficiency and sustainability and reducing environmental impact," Energy Policy, Elsevier, vol. 36(1), pages 128-137, January.
    2. Ahmadi, Pouria & Dincer, Ibrahim, 2010. "Exergoenvironmental analysis and optimization of a cogeneration plant system using Multimodal Genetic Algorithm (MGA)," Energy, Elsevier, vol. 35(12), pages 5161-5172.
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