IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v265y2023ics0360544222031978.html
   My bibliography  Save this article

Nonlinear modeling and multi-scale influence characteristics analysis of organic Rankine cycle (ORC) system considering variable driving cycles

Author

Listed:
  • Ping, Xu
  • Yang, Fubin
  • Zhang, Hongguang
  • Xing, Chengda
  • Pan, Yachao
  • Zhang, Wujie
  • Wang, Yan

Abstract

The reasonable construction of the organic Rankine cycle (ORC) system model under road conditions is the key to analyze, evaluate, and optimize the performance of the ORC system. However, due to the variability of high-temperature waste heat source and the strong coupling correlation of operating parameters, the operation characteristics of the ORC system show evident time-varying characteristics. Based on the coupling correlation and redundancy characteristics of the ORC system in complex environment, this paper presents a nonlinear modeling framework for the multi-scale influence analysis of the ORC system under road conditions. The nonlinear modeling framework can improve the prediction accuracy of ORC model by at least 68.36% and reduce the time cost by 53.37%. Based on the nonlinear model, the synergistic effects of multiple variables on ORC system performance at different scales are studied. The frequent fluctuation of vehicle speed enhances the coupling correlation of operating parameters, resulting in nonlinear, hysteretic dynamic characteristics of ORC thermal efficiency. The maximum thermal efficiency of ORC is only 3.28%. The nonlinear modeling framework proposed in this paper can provide a practical solution for constructing the intelligent analysis, design, and optimization models of ORC systems under complex road conditions.

Suggested Citation

  • Ping, Xu & Yang, Fubin & Zhang, Hongguang & Xing, Chengda & Pan, Yachao & Zhang, Wujie & Wang, Yan, 2023. "Nonlinear modeling and multi-scale influence characteristics analysis of organic Rankine cycle (ORC) system considering variable driving cycles," Energy, Elsevier, vol. 265(C).
  • Handle: RePEc:eee:energy:v:265:y:2023:i:c:s0360544222031978
    DOI: 10.1016/j.energy.2022.126311
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222031978
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2022.126311?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ping, Xu & Yang, Fubin & Zhang, Hongguang & Xing, Chengda & Zhang, Wujie & Wang, Yan, 2022. "Evaluation of hybrid forecasting methods for organic Rankine cycle: Unsupervised learning-based outlier removal and partial mutual information-based feature selection," Applied Energy, Elsevier, vol. 311(C).
    2. Hoang, Anh Tuan, 2018. "Waste heat recovery from diesel engines based on Organic Rankine Cycle," Applied Energy, Elsevier, vol. 231(C), pages 138-166.
    3. Wang, Enhua & Zhang, Mengru & Meng, Fanxiao & Zhang, Hongguang, 2022. "Zeotropic working fluid selection for an organic Rankine cycle bottoming with a marine engine," Energy, Elsevier, vol. 243(C).
    4. Chatzopoulou, Maria Anna & Lecompte, Steven & Paepe, Michel De & Markides, Christos N., 2019. "Off-design optimisation of organic Rankine cycle (ORC) engines with different heat exchangers and volumetric expanders in waste heat recovery applications," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    5. Lu, Yiji & Roskilly, Anthony Paul & Yu, Xiaoli & Jiang, Long & Chen, Longfei, 2018. "Technical feasibility study of scroll-type rotary gasoline engine: A compact and efficient small-scale Humphrey cycle engine," Applied Energy, Elsevier, vol. 221(C), pages 67-74.
    6. Ziviani, Davide & James, Nelson A. & Accorsi, Felipe A. & Braun, James E. & Groll, Eckhard A., 2018. "Experimental and numerical analyses of a 5 kWe oil-free open-drive scroll expander for small-scale organic Rankine cycle (ORC) applications," Applied Energy, Elsevier, vol. 230(C), pages 1140-1156.
    7. Emadi, Mohammad Ali & Chitgar, Nazanin & Oyewunmi, Oyeniyi A. & Markides, Christos N., 2020. "Working-fluid selection and thermoeconomic optimisation of a combined cycle cogeneration dual-loop organic Rankine cycle (ORC) system for solid oxide fuel cell (SOFC) waste-heat recovery," Applied Energy, Elsevier, vol. 261(C).
    8. Fu, Hailun & He, Qing & Song, Jintao & Shi, Xinping & Hao, Yinping & Du, Dongmei & Liu, Wenyi, 2021. "Thermodynamic of a novel advanced adiabatic compressed air energy storage system with variable pressure ratio coupled organic rankine cycle," Energy, Elsevier, vol. 227(C).
    9. He, Yaoyao & Zheng, Yaya, 2018. "Short-term power load probability density forecasting based on Yeo-Johnson transformation quantile regression and Gaussian kernel function," Energy, Elsevier, vol. 154(C), pages 143-156.
    10. Loni, Reyhaneh & Mahian, Omid & Markides, Christos N. & Bellos, Evangelos & le Roux, Willem G. & Kasaeian, Ailbakhsh & Najafi, Gholamhassan & Rajaee, Fatemeh, 2021. "A review of solar-driven organic Rankine cycles: Recent challenges and future outlook," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    11. Ping, Xu & Yang, Fubin & Zhang, Hongguang & Zhang, Jian & Zhang, Wujie & Song, Gege, 2021. "Introducing machine learning and hybrid algorithm for prediction and optimization of multistage centrifugal pump in an ORC system," Energy, Elsevier, vol. 222(C).
    12. Ke, Ting & Lv, Hui & Sun, Mingjing & Zhang, Lidong, 2018. "A biased least squares support vector machine based on Mahalanobis distance for PU learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 422-438.
    13. Alirahmi, Seyed Mojtaba & Mousavi, Seyedeh Fateme & Ahmadi, Pouria & Arabkoohsar, Ahmad, 2021. "Soft computing analysis of a compressed air energy storage and SOFC system via different artificial neural network architecture and tri-objective grey wolf optimization," Energy, Elsevier, vol. 236(C).
    14. Ping, Xu & Yang, Fubin & Zhang, Hongguang & Xing, Chengda & Wang, Chongyao & Zhang, Wujie & Wang, Yan, 2022. "Energy, economic and environmental dynamic response characteristics of organic Rankine cycle (ORC) system under different driving cycles," Energy, Elsevier, vol. 246(C).
    15. Shu, Gequn & Zhao, Mingru & Tian, Hua & Wei, Haiqiao & Liang, Xingyu & Huo, Yongzhan & Zhu, Weijie, 2016. "Experimental investigation on thermal OS/ORC (Oil Storage/Organic Rankine Cycle) system for waste heat recovery from diesel engine," Energy, Elsevier, vol. 107(C), pages 693-706.
    16. Ping, Xu & Yao, Baofeng & Zhang, Hongguang & Yang, Fubin, 2021. "Thermodynamic analysis and high-dimensional evolutionary many-objective optimization of dual loop organic Rankine cycle (DORC) for CNG engine waste heat recovery," Energy, Elsevier, vol. 236(C).
    17. Xu, Bin & Li, Xiaoya, 2021. "A Q-learning based transient power optimization method for organic Rankine cycle waste heat recovery system in heavy duty diesel engine applications," Applied Energy, Elsevier, vol. 286(C).
    18. Ping, Xu & Yang, Fubin & Zhang, Hongguang & Wang, Yan & Lei, Biao & Wu, Yuting, 2022. "Performance limits of the single screw expander in organic Rankine cycle with ensemble learning and hyperdimensional evolutionary many-objective optimization algorithm intervention," Energy, Elsevier, vol. 245(C).
    19. Xie, Hui & Yang, Can, 2013. "Dynamic behavior of Rankine cycle system for waste heat recovery of heavy duty diesel engines under driving cycle," Applied Energy, Elsevier, vol. 112(C), pages 130-141.
    20. Ping, Xu & Yang, Fubin & Zhang, Hongguang & Xing, Chengda & Yu, Mingzhe & Wang, Yan, 2023. "Investigation and multi-objective optimization of vehicle engine-organic Rankine cycle (ORC) combined system in different driving conditions," Energy, Elsevier, vol. 263(PB).
    21. Ping, Xu & Yang, Fubin & Zhang, Hongguang & Xing, Chengda & Zhang, Wujie & Wang, Yan & Yao, Baofeng, 2023. "Dynamic response assessment and multi-objective optimization of organic Rankine cycle (ORC) under vehicle driving cycle conditions," Energy, Elsevier, vol. 263(PA).
    22. Huster, Wolfgang R. & Schweidtmann, Artur M. & Mitsos, Alexander, 2020. "Globally optimal working fluid mixture composition for geothermal power cycles," Energy, Elsevier, vol. 212(C).
    23. Palagi, Laura & Sciubba, Enrico & Tocci, Lorenzo, 2019. "A neural network approach to the combined multi-objective optimization of the thermodynamic cycle and the radial inflow turbine for Organic Rankine cycle applications," Applied Energy, Elsevier, vol. 237(C), pages 210-226.
    24. Huang, Junwei & Xiao, Qingtai & Liu, Jingjing & Wang, Hua, 2019. "Modeling heat transfer properties in an ORC direct contact evaporator using RBF neural network combined with EMD," Energy, Elsevier, vol. 173(C), pages 306-316.
    25. Yang, Fubin & Cho, Heejin & Zhang, Hongguang & Zhang, Jian, 2017. "Thermoeconomic multi-objective optimization of a dual loop organic Rankine cycle (ORC) for CNG engine waste heat recovery," Applied Energy, Elsevier, vol. 205(C), pages 1100-1118.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xia, Xiaoxia & Yang, Chengwu & Wang, Zhiqi & Sun, Tong & Zhang, Hualong & Wu, Jinhao, 2024. "Multi-objective optimization of the dual-pressure organic Rankine cycle system based on the orthogonal design method under different external conditions," Energy, Elsevier, vol. 296(C).
    2. Hailong Yang & Yonghong Xu & Xiaohui Zhong & Jiajun Zeng & Fubin Yang, 2024. "Experimental Investigation on the Performance of the Scroll Expander under Various Driving Cycles," Energies, MDPI, vol. 17(2), pages 1-24, January.
    3. Ping, Xu & Yang, Fubin & Zhang, Hongguang & Zhang, Jian & Xing, Chengda & Yan, Yinlian & Yang, Anren & Wang, Yan, 2023. "Information theory-based dynamic feature capture and global multi-objective optimization approach for organic Rankine cycle (ORC) considering road environment," Applied Energy, Elsevier, vol. 348(C).
    4. Yan, Yinlian & Yang, Fubin & Zhang, Hongguang & Pan, Yachao & Ping, Xu & Ge, Zhong, 2023. "Study on performance evaluation framework and design/ selection guidelines of working fluids for subcritical organic Rankine cycle from molecular structure perspective," Energy, Elsevier, vol. 282(C).
    5. Ping, Xu & Yang, Fubin & Zhang, Hongguang & Xing, Chengda & Yang, Anren & Yan, Yinlian & Pan, Yachao & Wang, Yan, 2023. "Ensemble of self-organizing adaptive maps and dynamic multi-objective optimization for organic Rankine cycle (ORC) under transportation and driving environment," Energy, Elsevier, vol. 275(C).
    6. Yu, Mingzhe & Yang, Fubin & Zhang, Hongguang & Yan, Yinlian & Ping, Xu & Pan, Yachao & Xing, Chengda & Yang, Anren, 2024. "Thermoeconomic performance of supercritical carbon dioxide Brayton cycle systems for CNG engine waste heat recovery," Energy, Elsevier, vol. 289(C).
    7. Wang, Chenfang & Liu, Shihao & Zhan, Shuming & Ou, Mengmeng & Wei, Jiangjun & Cheng, Xiaozhang & Zhuge, Weilin & Zhang, Yangjun, 2024. "Transcritical dual-loop Rankine cycle waste heat recovery system for China VI emission standards natural gas engine," Energy, Elsevier, vol. 292(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ping, Xu & Yang, Fubin & Zhang, Hongguang & Xing, Chengda & Yang, Anren & Yan, Yinlian & Pan, Yachao & Wang, Yan, 2023. "Ensemble of self-organizing adaptive maps and dynamic multi-objective optimization for organic Rankine cycle (ORC) under transportation and driving environment," Energy, Elsevier, vol. 275(C).
    2. Ping, Xu & Yang, Fubin & Zhang, Hongguang & Xing, Chengda & Zhang, Wujie & Wang, Yan & Yao, Baofeng, 2023. "Dynamic response assessment and multi-objective optimization of organic Rankine cycle (ORC) under vehicle driving cycle conditions," Energy, Elsevier, vol. 263(PA).
    3. Xu Ping & Baofeng Yao & Hongguang Zhang & Hongzhi Zhang & Jia Liang & Meng Yuan & Kai Niu & Yan Wang, 2022. "Comprehensive Performance Assessment of Dual Loop Organic Rankine Cycle (DORC) for CNG Engine: Energy, Thermoeconomic and Environment," Energies, MDPI, vol. 15(21), pages 1-28, October.
    4. Ping, Xu & Yang, Fubin & Zhang, Hongguang & Zhang, Jian & Xing, Chengda & Yan, Yinlian & Yang, Anren & Wang, Yan, 2023. "Information theory-based dynamic feature capture and global multi-objective optimization approach for organic Rankine cycle (ORC) considering road environment," Applied Energy, Elsevier, vol. 348(C).
    5. Ping, Xu & Yang, Fubin & Zhang, Hongguang & Xing, Chengda & Yu, Mingzhe & Wang, Yan, 2023. "Investigation and multi-objective optimization of vehicle engine-organic Rankine cycle (ORC) combined system in different driving conditions," Energy, Elsevier, vol. 263(PB).
    6. Ping, Xu & Yang, Fubin & Zhang, Hongguang & Xing, Chengda & Zhang, Wujie & Wang, Yan, 2022. "Evaluation of hybrid forecasting methods for organic Rankine cycle: Unsupervised learning-based outlier removal and partial mutual information-based feature selection," Applied Energy, Elsevier, vol. 311(C).
    7. 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).
    8. Ping, Xu & Yang, Fubin & Zhang, Hongguang & Xing, Chengda & Wang, Chongyao & Zhang, Wujie & Wang, Yan, 2022. "Energy, economic and environmental dynamic response characteristics of organic Rankine cycle (ORC) system under different driving cycles," Energy, Elsevier, vol. 246(C).
    9. Baofeng Yao & Xu Ping & Hongguang Zhang, 2021. "Dynamic Response Characteristics Analysis and Energy, Exergy, and Economic (3E) Evaluation of Dual Loop Organic Rankine Cycle (DORC) for CNG Engine Waste Heat Recovery," Energies, MDPI, vol. 14(19), pages 1-32, September.
    10. Miao, Zheng & Yan, Peiwei & Xiao, Meng & Zhang, Manzheng & Xu, Jinliang, 2023. "Comparative study on operating strategies of the organic Rankine cycle under transient heat source," Energy, Elsevier, vol. 285(C).
    11. Li, Xiaoya & Xu, Bin & Tian, Hua & Shu, Gequn, 2021. "Towards a novel holistic design of organic Rankine cycle (ORC) systems operating under heat source fluctuations and intermittency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    12. Long Lyu & Wu Chen & Ankang Kan & Yuan Zhang & Song Xue & Jingbin Zeng, 2022. "Investigation of a Dual-Loop ORC for the Waste Heat Recovery of a Marine Main Engine," Energies, MDPI, vol. 15(22), pages 1-22, November.
    13. Tian, Yaming & Zhang, Hongguang & Li, Jian & Hou, Xiaochen & Zhao, Tenglong & Yang, Fubin & Xu, Yonghong & Wang, Xin, 2018. "Development and validation of a single-piston free piston expander-linear generator for a small-scale organic Rankine cycle," Energy, Elsevier, vol. 161(C), pages 809-820.
    14. Zhuxian Liu & Zhong Wu & Yonghong Xu & Hongguang Zhang & Jian Zhang & Fubin Yang, 2022. "Performance Investigation of Single–Piston Free Piston Expander–Linear Generator with Multi–Parameter Based on Simulation Model," Energies, MDPI, vol. 15(23), pages 1-28, November.
    15. Lan, Song & Li, Qingshan & Guo, Xin & Wang, Shukun & Chen, Rui, 2023. "Fuel saving potential analysis of bifunctional vehicular waste heat recovery system using thermoelectric generator and organic Rankine cycle," Energy, Elsevier, vol. 263(PB).
    16. 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).
    17. Wang, Chenfang & Liu, Shihao & Zhan, Shuming & Ou, Mengmeng & Wei, Jiangjun & Cheng, Xiaozhang & Zhuge, Weilin & Zhang, Yangjun, 2024. "Transcritical dual-loop Rankine cycle waste heat recovery system for China VI emission standards natural gas engine," Energy, Elsevier, vol. 292(C).
    18. 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).
    19. Wu, Xialai & Lin, Ling & Xie, Lei & Chen, Junghui & Shan, Lu, 2024. "Fast robust optimization of ORC based on an artificial neural network for waste heat recovery," Energy, Elsevier, vol. 301(C).
    20. Li, Xiaoya & Tian, Hua & Shu, Gequn & Zhao, Mingru & Markides, Christos N. & Hu, Chen, 2019. "Potential of carbon dioxide transcritical power cycle waste-heat recovery systems for heavy-duty truck engines," Applied Energy, Elsevier, vol. 250(C), pages 1581-1599.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:265:y:2023:i:c:s0360544222031978. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.