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Thermodynamic and exergoeconomic assessment of a trigeneration system driven by a biomass energy source for power, cooling, and heating generation

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  • Shang, Mengya
  • Zhu, Yiping

Abstract

Environmental concerns and the limitations of conventional energy drive the exploration of reliable renewable sources. Herein, a biomass-assisted trigeneration system in conjunction with a methane-fed gas turbine cycle for generating power, cooling, and heating, and an attempt has been made to maximize the energy extraction from the energy source. The proposed system includes a steam Rankine cycle, a gas turbine unit, and a Kalina subsystem, and is investigated from energetic, exergetic, and economic viewpoints. A comprehensive parametric evaluation is carried out, and a multi-objective grey wolf optimization algorithm integrated with the LINMAP decision-maker method is employed to detect the most optimum point through two different scenarios. By conducting a base study, a net output power of 5926 kW, cooling load of 36.56 kW, heating load of 843.4 kW, and an energetic efficiency of 47.41 % can be achieved. The exergetic and economic standpoints bring out an exergy destruction rate of 7697.07 kW, cycle exergetic efficiency of 41.44 %, and a net present value of 12.420 $M that sequels to a payback period of 5.56 years. Biomass proves reliable in multigeneration systems, emphasizing the pivotal role of studies in maximizing energy extraction for diverse product outputs.

Suggested Citation

  • Shang, Mengya & Zhu, Yiping, 2024. "Thermodynamic and exergoeconomic assessment of a trigeneration system driven by a biomass energy source for power, cooling, and heating generation," Energy, Elsevier, vol. 290(C).
    • Handle: RePEc:eee:energy:v:290:y:2024:i:c:s0360544223034795
    DOI: 10.1016/j.energy.2023.130085
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    References listed on IDEAS

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    5. Feng, Jieru & Huang, Yiqing & Li, Juqiang & Li, Xuetao, 2024. "Design and multi-criteria optimization and financial assessment of an innovative combined power plant and desalination process," Energy, Elsevier, vol. 300(C).
    6. Balali, Adel & Raji Asadabadi, Mohammad Javad & Lotfollahi, Amirhosein & Moghimi, Mahdi, 2025. "Machine learning-based optimization of a waste-to-energy power plant with CAES for peak load management: Feasibility and a case study in Tehran," Energy, Elsevier, vol. 335(C).

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