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Simultaneous design and off-design operation optimization of a waste heat-driven organic Rankine cycle using a multi-period mathematical programming method

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  • Luo, Xianglong
  • Wei, Youxing
  • Qiu, Guanfu
  • Liang, Yingzong
  • Chen, Jianyong
  • Yang, Zhi
  • Wang, Chao
  • Chen, Ying

Abstract

The organic Rankine cycle (ORC) has been regarded as one of the most potential technologies for converting low-grade heat into power. In the past decades, the design and operation optimization of ORC has undergone investigation, and most approaches use a sequential or step-by-step approach by separating the off-design operation from the system design and typically lose solution optimality. The current study proposes a simultaneous optimization of the design and off-design operation for a waste heat-driven ORC. The detailed component configuration models for the heat exchangers are developed. A multi-period optimization model is developed to synchronously obtain the configurations of components and scheme of off-design operation that minimizes the annual average electricity production cost. A case study validates the superiority of the proposed multi-period optimization method over a two-step optimization. The ORC obtained using multi-period simultaneous optimization method features 5.7%–16.6% lower average electricity production cost than those achieved with the conventional two-step method.

Suggested Citation

  • Luo, Xianglong & Wei, Youxing & Qiu, Guanfu & Liang, Yingzong & Chen, Jianyong & Yang, Zhi & Wang, Chao & Chen, Ying, 2020. "Simultaneous design and off-design operation optimization of a waste heat-driven organic Rankine cycle using a multi-period mathematical programming method," Energy, Elsevier, vol. 213(C).
    • Handle: RePEc:eee:energy:v:213:y:2020:i:c:s0360544220319009
    DOI: 10.1016/j.energy.2020.118793
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    Cited by:

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    2. Dokl, Monika & Gomilšek, Rok & Čuček, Lidija & Abikoye, Ben & Kravanja, Zdravko, 2022. "Maximizing the power output and net present value of organic Rankine cycle: Application to aluminium industry," Energy, Elsevier, vol. 239(PE).
    3. Zhou, Jianzhao & Chu, Yin Ting & Ren, Jingzheng & Shen, Weifeng & He, Chang, 2023. "Integrating machine learning and mathematical programming for efficient optimization of operating conditions in organic Rankine cycle (ORC) based combined systems," Energy, Elsevier, vol. 281(C).
    4. Wei, Youxing & Luo, Xianglong & Liang, Yingzong & Chen, Jianyong & Yang, Zhi & He, Jiacheng & Wang, Chao & Chen, Ying, 2022. "Time series aggregation-based design and operation optimization of a solar-driven organic Rankine cycle incorporating variation of environmental temperature and solar radiation," Renewable Energy, Elsevier, vol. 192(C), pages 87-106.

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