IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v261y2022ipas0360544222019624.html
   My bibliography  Save this article

Modified hierarchical strategy for transient performance improvement of the ORC based waste heat recovery system

Author

Listed:
  • Shi, Yao
  • Zhang, Zhiming
  • Xie, Lei
  • Wu, Xialai
  • Liu, Xueqin Amy
  • Lu, Shan
  • Su, Hongye

Abstract

Organic Rankine Cycle (ORC) system outperforms in the low-grade waste heat recovery and has found its wide application in engineering practice. Due to the strong coupling multivariable nature of the ORC power unit, the traditional hierarchical control scheme, which is composed of real-time optimization (RTO) in the upper layer and model predictive control (MPC) in the lower one, is usually utilized in the control of the ORC system for good economic performance. The upper RTO solves an economic objective function in real time and obtains the optimal steady-state setpoints which are sent to the lower MPC layer for tracking. However, the disadvantage of the traditional hierarchical control scheme lies in its neglection to the transient characteristics with the evolution of the ORC system, which will finally lead to poor overall control performance. To address this problem, in this article, a modified hierarchical control strategy which is denoted as RTO-PFFDMC grounded on pseudo feedforward dynamic matrix control (PFFDMC) algorithm is proposed. The novel PFFDMC presented in this article is applied to replace the traditional dynamic matrix control (DMC) in the lower layer and thus achieve the closed-loop reference trajectory of ORC system expected by field engineers as closely as possible without cumbersome adjustment of tuning parameters. Simulations are performed to verify the effectiveness of the proposed strategy on transient performance in comparison with the traditional one.

Suggested Citation

  • Shi, Yao & Zhang, Zhiming & Xie, Lei & Wu, Xialai & Liu, Xueqin Amy & Lu, Shan & Su, Hongye, 2022. "Modified hierarchical strategy for transient performance improvement of the ORC based waste heat recovery system," Energy, Elsevier, vol. 261(PA).
  • Handle: RePEc:eee:energy:v:261:y:2022:i:pa:s0360544222019624
    DOI: 10.1016/j.energy.2022.125067
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222019624
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2022.125067?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. Baccioli, Andrea & Ferrari, Lorenzo & Vizza, Francesco & Desideri, Umberto, 2019. "Potential energy recovery by integrating an ORC in a biogas plant," Applied Energy, Elsevier, vol. 256(C).
    2. Zhang, Jianhua & Zhou, Yeli & Wang, Rui & Xu, Jinliang & Fang, Fang, 2014. "Modeling and constrained multivariable predictive control for ORC (Organic Rankine Cycle) based waste heat energy conversion systems," Energy, Elsevier, vol. 66(C), pages 128-138.
    3. 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).
    4. Jiménez-Arreola, Manuel & Pili, Roberto & Wieland, Christoph & Romagnoli, Alessandro, 2018. "Analysis and comparison of dynamic behavior of heat exchangers for direct evaporation in ORC waste heat recovery applications from fluctuating sources," Applied Energy, Elsevier, vol. 216(C), pages 724-740.
    5. 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).
    6. Quoilin, Sylvain & Aumann, Richard & Grill, Andreas & Schuster, Andreas & Lemort, Vincent & Spliethoff, Hartmut, 2011. "Dynamic modeling and optimal control strategy of waste heat recovery Organic Rankine Cycles," Applied Energy, Elsevier, vol. 88(6), pages 2183-2190, June.
    7. Wang, Jiangfeng & Dai, Yiping & Gao, Lin, 2009. "Exergy analyses and parametric optimizations for different cogeneration power plants in cement industry," Applied Energy, Elsevier, vol. 86(6), pages 941-948, June.
    8. Fiaschi, Daniele & Manfrida, Giampaolo & Maraschiello, Francesco, 2012. "Thermo-fluid dynamics preliminary design of turbo-expanders for ORC cycles," Applied Energy, Elsevier, vol. 97(C), pages 601-608.
    9. 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).
    10. Rathod, Dhruvang & Xu, Bin & Filipi, Zoran & Hoffman, Mark, 2019. "An experimentally validated, energy focused, optimal control strategy for an Organic Rankine Cycle waste heat recovery system," Applied Energy, Elsevier, vol. 256(C).
    11. Mateu-Royo, Carlos & Navarro-Esbrí, Joaquín & Mota-Babiloni, Adrián & Molés, Francisco & Amat-Albuixech, Marta, 2019. "Experimental exergy and energy analysis of a novel high-temperature heat pump with scroll compressor for waste heat recovery," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    12. Li, C.Y. & Deethayat, T. & Wu, J.Y. & Kiatsiriroat, T. & Wang, R.Z., 2018. "Simulation and evaluation of a biomass gasification-based combined cooling, heating, and power system integrated with an organic Rankine cycle," Energy, Elsevier, vol. 158(C), pages 238-255.
    13. Gou, Xiaolong & Yang, Suwen & Xiao, Heng & Ou, Qiang, 2013. "A dynamic model for thermoelectric generator applied in waste heat recovery," Energy, Elsevier, vol. 52(C), pages 201-209.
    14. Shi, Rongqi & He, Tianqi & Peng, Jie & Zhang, Yangjun & Zhuge, Weilin, 2016. "System design and control for waste heat recovery of automotive engines based on Organic Rankine Cycle," Energy, Elsevier, vol. 102(C), pages 276-286.
    15. Hung, T.C. & Shai, T.Y. & Wang, S.K., 1997. "A review of organic rankine cycles (ORCs) for the recovery of low-grade waste heat," Energy, Elsevier, vol. 22(7), pages 661-667.
    16. Liu, Changwei & Gao, Tieyu, 2019. "Off-design performance analysis of basic ORC, ORC using zeotropic mixtures and composition-adjustable ORC under optimal control strategy," Energy, Elsevier, vol. 171(C), pages 95-108.
    17. Xu, Yonghong & Tong, Liang & Zhang, Hongguang & Hou, Xiaochen & Yang, Fubin & Yu, Fei & Yang, Yuxin & Liu, Rong & Tian, Yaming & Zhao, Tenglong, 2018. "Experimental and simulation study of a free piston expander–linear generator for small-scale organic Rankine cycle," Energy, Elsevier, vol. 161(C), pages 776-791.
    18. Wang, Dexin & Bao, Ainan & Kunc, Walter & Liss, William, 2012. "Coal power plant flue gas waste heat and water recovery," Applied Energy, Elsevier, vol. 91(1), pages 341-348.
    19. Freeman, James & Hellgardt, Klaus & Markides, Christos N., 2017. "Working fluid selection and electrical performance optimisation of a domestic solar-ORC combined heat and power system for year-round operation in the UK," Applied Energy, Elsevier, vol. 186(P3), pages 291-303.
    20. Eyerer, Sebastian & Dawo, Fabian & Kaindl, Johannes & Wieland, Christoph & Spliethoff, Hartmut, 2019. "Experimental investigation of modern ORC working fluids R1224yd(Z) and R1233zd(E) as replacements for R245fa," Applied Energy, Elsevier, vol. 240(C), pages 946-963.
    21. Zhang, Jianhua & Zhou, Yeli & Li, Ying & Hou, Guolian & Fang, Fang, 2013. "Generalized predictive control applied in waste heat recovery power plants," Applied Energy, Elsevier, vol. 102(C), pages 320-326.
    22. Wu, Xialai & Chen, Junghui & Xie, Lei, 2019. "Fast economic nonlinear model predictive control strategy of Organic Rankine Cycle for waste heat recovery: Simulation-based studies," Energy, Elsevier, vol. 180(C), pages 520-534.
    23. Lion, Simone & Taccani, Rodolfo & Vlaskos, Ioannis & Scrocco, Pietro & Vouvakos, Xenakis & Kaiktsis, Lambros, 2019. "Thermodynamic analysis of waste heat recovery using Organic Rankine Cycle (ORC) for a two-stroke low speed marine Diesel engine in IMO Tier II and Tier III operation," Energy, Elsevier, vol. 183(C), pages 48-60.
    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. Shi, Yao & Zhang, Zhiming & Chen, Xiaoqiang & Xie, Lei & Liu, Xueqin & Su, Hongye, 2023. "Data-Driven model identification and efficient MPC via quasi-linear parameter varying representation for ORC waste heat recovery system," Energy, Elsevier, vol. 271(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. Shi, Yao & Zhang, Zhiming & Chen, Xiaoqiang & Xie, Lei & Liu, Xueqin & Su, Hongye, 2023. "Data-Driven model identification and efficient MPC via quasi-linear parameter varying representation for ORC waste heat recovery system," Energy, Elsevier, vol. 271(C).
    2. Shi, Yao & Lin, Runze & Wu, Xialai & Zhang, Zhiming & Sun, Pei & Xie, Lei & Su, Hongye, 2022. "Dual-mode fast DMC algorithm for the control of ORC based waste heat recovery system," Energy, Elsevier, vol. 244(PA).
    3. Imran, Muhammad & Pili, Roberto & Usman, Muhammad & Haglind, Fredrik, 2020. "Dynamic modeling and control strategies of organic Rankine cycle systems: Methods and challenges," Applied Energy, Elsevier, vol. 276(C).
    4. 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).
    5. Tailu Li & Zeyu Wang & Jingyi Wang & Xiang Gao, 2023. "Dynamic Performance of Organic Rankine Cycle Driven by Fluctuant Industrial Waste Heat for Building Power Supply," Energies, MDPI, vol. 16(2), pages 1-24, January.
    6. Wu, Xialai & Chen, Junghui & Xie, Lei, 2019. "Fast economic nonlinear model predictive control strategy of Organic Rankine Cycle for waste heat recovery: Simulation-based studies," Energy, Elsevier, vol. 180(C), pages 520-534.
    7. Pili, R. & Eyerer, S. & Dawo, F. & Wieland, C. & Spliethoff, H., 2020. "Development of a non-linear state estimator for advanced control of an ORC test rig for geothermal application," Renewable Energy, Elsevier, vol. 161(C), pages 676-690.
    8. Zhang, Jianhua & Lin, Mingming & Fang, Fang & Xu, Jinliang & Li, Kang, 2016. "Gain scheduling control of waste heat energy conversion systems based on an LPV (linear parameter varying) model," Energy, Elsevier, vol. 107(C), pages 773-783.
    9. Jolevski, Danijel & Bego, Ozren & Sarajcev, Petar, 2017. "Control structure design and dynamics modelling of the organic Rankine cycle system," Energy, Elsevier, vol. 121(C), pages 193-204.
    10. Jin, Yunli & Gao, Naiping & Wang, Tiantian, 2020. "Influence of heat exchanger pinch point on the control strategy of Organic Rankine cycle (ORC)," Energy, Elsevier, vol. 207(C).
    11. Cavazzini, G. & Bari, S. & Pavesi, G. & Ardizzon, G., 2017. "A multi-fluid PSO-based algorithm for the search of the best performance of sub-critical Organic Rankine Cycles," Energy, Elsevier, vol. 129(C), pages 42-58.
    12. Lisheng Pan & Huaixin Wang, 2019. "Experimental Investigation on Performance of an Organic Rankine Cycle System Integrated with a Radial Flow Turbine," Energies, MDPI, vol. 12(4), pages 1-20, February.
    13. Ni, Jiaxin & Zhao, Li & Zhang, Zhengtao & Zhang, Ying & Zhang, Jianyuan & Deng, Shuai & Ma, Minglu, 2018. "Dynamic performance investigation of organic Rankine cycle driven by solar energy under cloudy condition," Energy, Elsevier, vol. 147(C), pages 122-141.
    14. Fabio Fatigati & Diego Vittorini & Yaxiong Wang & Jian Song & Christos N. Markides & Roberto Cipollone, 2020. "Design and Operational Control Strategy for Optimum Off-Design Performance of an ORC Plant for Low-Grade Waste Heat Recovery," Energies, MDPI, vol. 13(21), pages 1-23, November.
    15. 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).
    16. Ying Zhang & Li Zhao & Shuai Deng & Ming Li & Yali Liu & Qiongfen Yu & Mengxing Li, 2022. "Novel Off-Design Operation Maps Showing Functionality Limitations of Organic Rankine Cycle Validated by Experiments," Energies, MDPI, vol. 15(21), pages 1-19, November.
    17. Ibarra, Mercedes & Rovira, Antonio & Alarcón-Padilla, Diego-César & Blanco, Julián, 2014. "Performance of a 5kWe Organic Rankine Cycle at part-load operation," Applied Energy, Elsevier, vol. 120(C), pages 147-158.
    18. Cao, Shuang & Xu, Jinliang & Miao, Zheng & Liu, Xiulong & Zhang, Ming & Xie, Xuewang & Li, Zhi & Zhao, Xiaoli & Tang, Guihua, 2019. "Steady and transient operation of an organic Rankine cycle power system," Renewable Energy, Elsevier, vol. 133(C), pages 284-294.
    19. 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).
    20. Zhang, Jianhua & Lin, Mingming & Chen, Junghui & Xu, Jinliang & Li, Kang, 2017. "PLS-based multi-loop robust H2 control for improvement of operating efficiency of waste heat energy conversion systems with organic Rankine cycle," Energy, Elsevier, vol. 123(C), pages 460-472.

    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:261:y:2022:i:pa:s0360544222019624. 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.