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Optimal operating policies for organic Rankine cycles for waste heat recovery under transient conditions

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  • Vaupel, Yannic
  • Huster, Wolfgang R.
  • Mhamdi, Adel
  • Mitsos, Alexander

Abstract

Waste heat recovery for trucks via organic Rankine cycle is a promising technology to reduce fuel consumption and emissions. As the vehicles are operated in street traffic, the heat source is subject to strong fluctuations. Consequently, such disturbances have to be considered to enable safe and efficient operation. Herein, we find optimal operating policies for several representative scenarios by means of dynamic optimization and discuss the implications on control strategy design. First, we optimize operation of a typical driving cycle with data from a test rig. Results indicate that operating the cycle at minimal superheat is an appropriate operating policy. Second, we consider a scenario where the permissible expander power is temporarily limited, which is realistic in street traffic. In this case, an operating policy with flexible superheat can reduce the losses associated with operation at minimal superheat by up to 53% in the considered scenario. As the duration of power limitation increases, other constraints might become active which results in part of the exhaust gas being bypassed, hence reduced savings.

Suggested Citation

  • Vaupel, Yannic & Huster, Wolfgang R. & Mhamdi, Adel & Mitsos, Alexander, 2021. "Optimal operating policies for organic Rankine cycles for waste heat recovery under transient conditions," Energy, Elsevier, vol. 224(C).
  • Handle: RePEc:eee:energy:v:224:y:2021:i:c:s0360544221003753
    DOI: 10.1016/j.energy.2021.120126
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    3. Huang, Bin & Shen, Zu-Guo, 2022. "Performance assessment of annular thermoelectric generators for automobile exhaust waste heat recovery," Energy, Elsevier, vol. 246(C).
    4. Ping, Xu & Yang, Fubin & Zhang, Hongguang & Xing, Chengda & Yao, Baofeng & Wang, Yan, 2022. "An outlier removal and feature dimensionality reduction framework with unsupervised learning and information theory intervention for organic Rankine cycle (ORC)," Energy, Elsevier, vol. 254(PB).
    5. Gu, Zhengzhao & Feng, Kewen & Ge, Lei & Quan, Long, 2023. "Dynamic modeling and optimization of organic Rankine cycle in the waste heat recovery of the hydraulic system," Energy, Elsevier, vol. 263(PB).

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