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Dynamic performance comparison of different cascade waste heat recovery systems for internal combustion engine in combined cooling, heating and power

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  • Wang, Xuan
  • Shu, Gequn
  • Tian, Hua
  • Wang, Rui
  • Cai, Jinwen

Abstract

The internal combustion engine is an important prime mover in combined cooling, heating and power systems. However, approximately 30–40% of the input energy is discharged by exhaust; thus, it is significant to recover the exhaust waste heat. Cascade energy-utilisation systems have high efficiencies for exhaust recovery with a large temperature drop. However, waste heat-recovery systems usually work under different conditions and therefore, it is meaningful to study the dynamic performance of cascade systems. In this work, by developing a model library of common components in thermodynamic systems, dynamic simulation models of three cascade systems are established: an electric-cooling cogeneration system (ECCS), a double-effect absorption refrigeration system, and a double-stage organic Rankine cycle. The dynamic response speed and off-design performance of each system are analysed and compared. The results indicate that all the cascade systems respond considerably more slowly than any single-stage cycle, and the ECCS achieves the best off-design performance because both its upper and lower stages (high-temperature organic Rankine cycle and absorption refrigeration) exhibit perfect working condition adaptability, especially the lower stage. Furthermore, the structure of the ECCS is more beneficial for the lower stage to maintain satisfactory off-design performance.

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  • Wang, Xuan & Shu, Gequn & Tian, Hua & Wang, Rui & Cai, Jinwen, 2020. "Dynamic performance comparison of different cascade waste heat recovery systems for internal combustion engine in combined cooling, heating and power," Applied Energy, Elsevier, vol. 260(C).
    • Handle: RePEc:eee:appene:v:260:y:2020:i:c:s0306261919319324
    DOI: 10.1016/j.apenergy.2019.114245
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    Cited by:

    1. Wang, Xuan & Wang, Rui & Jin, Ming & Shu, Gequn & Tian, Hua & Pan, Jiaying, 2020. "Control of superheat of organic Rankine cycle under transient heat source based on deep reinforcement learning," Applied Energy, Elsevier, vol. 278(C).
    2. He, Jintao & Shi, Lingfeng & Tian, Hua & Wang, Xuan & Sun, Xiaocun & Zhang, Meiyan & Yao, Yu & Shu, Gequn, 2023. "Applying artificial neural network to approximate and predict the transient dynamic behavior of CO2 combined cooling and power cycle," Energy, Elsevier, vol. 285(C).
    3. Wang, Xuan & Shu, Gequn & Tian, Hua & Wang, Rui & Cai, Jinwen, 2020. "Operation performance comparison of CCHP systems with cascade waste heat recovery systems by simulation and operation optimisation," Energy, Elsevier, vol. 206(C).
    4. Yuan, Yu & Bai, Zhang & Liu, Qibin & Hu, Wenxin & Zheng, Bo, 2021. "Potential of applying the thermochemical recuperation in combined cooling, heating and power generation: Route of enhancing the operation flexibility," Applied Energy, Elsevier, vol. 301(C).
    5. Ouyang, Tiancheng & Su, Zixiang & Yang, Rui & Wang, Zhiping & Mo, Xiaoyu & Huang, Haozhong, 2021. "Advanced waste heat harvesting strategy for marine dual-fuel engine considering gas-liquid two-phase flow of turbine," Energy, Elsevier, vol. 224(C).
    6. Golmohamadi, Hessam & Larsen, Kim Guldstrand & Jensen, Peter Gjøl & Hasrat, Imran Riaz, 2022. "Integration of flexibility potentials of district heating systems into electricity markets: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    7. Chen, W.D. & Chua, K.J., 2021. "Energy performance analysis and optimization of a coupled adsorption and absorption cascade refrigeration system," Applied Energy, Elsevier, vol. 301(C).

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