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Multi-objective optimization and performance analysis of CCHP system for working fluid selecting mechanism modeling

Author

Listed:
  • Wang, Yi
  • Yang, Jiawen
  • Hou, Yan
  • Song, Yanlei
  • Xia, Li
  • Sun, Xiaoyan
  • Wang, Lili
  • Teng, Junfeng
  • Xiang, Shuguang

Abstract

Low-temperature waste heat from industrial devices is a valuable heat resource that can be effectively utilized. Therefore, a novel Combined Cooling, Heating, and Power (CCHP) system is proposed to recover waste heat. A mechanistic model for the selection of working fluid is established, based on multidimensional parameters including thermal efficiency, safety, and environmental impact. Subsequently, the proposed system is optimized by a multi-objective approach utilizing the genetic algorithm NSGA-III, focusing on exergy efficiency, CO2 emission reduction (CER), and return on investment (ROI). The solutions are then evaluated using the TOPSIS method, and the performance of the optimized system is assessed. The results showed that R1233zd(E) exhibited superior performance in the organic Rankine cycle (ORC) system across various heat source temperatures. The exergy efficiency of the CCHP system improved from 0.78 to 0.80. The operating cost experienced a marginal increase to $29,470.82, while the equipment cost was substantially reduced to $467,039.89. Additionally, the ROI increased from 0.49 to 0.54 prior to optimization, marking a 7.80 % rise. The CER of the system improved to 1958.31 tons/year, an increase of 6.42 %. The refined design enhanced the system's economic benefits and promoted its environmental sustainability through judicious equipment selection and process optimization.

Suggested Citation

  • Wang, Yi & Yang, Jiawen & Hou, Yan & Song, Yanlei & Xia, Li & Sun, Xiaoyan & Wang, Lili & Teng, Junfeng & Xiang, Shuguang, 2025. "Multi-objective optimization and performance analysis of CCHP system for working fluid selecting mechanism modeling," Energy, Elsevier, vol. 332(C).
    • Handle: RePEc:eee:energy:v:332:y:2025:i:c:s0360544225027203
    DOI: 10.1016/j.energy.2025.137078
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    References listed on IDEAS

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    2. Xie, Yue & Ji, Pengcheng & Zhang, Yin & Si, Pengfei, 2025. "Inverse problem method for two-stage co-optimization of solar hybrid combined cooling, heating and power systems with energy storage through improved particle swarm algorithm," Energy, Elsevier, vol. 335(C).

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