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Real-Time Optimization of Organic Rankine Cycle Systems by Extremum-Seeking Control

Author

Listed:
  • Andres Hernandez

    (Department of Electrical Energy, Systems and Automation, Ghent University, 9000 Ghent, Belgium
    Thermodynamics Laboratory, University of Liege, Campus du Sart Tilman B49, 4000 Liege, Belgium)

  • Adriano Desideri

    (Thermodynamics Laboratory, University of Liege, Campus du Sart Tilman B49, 4000 Liege, Belgium)

  • Clara Ionescu

    (Department of Electrical Energy, Systems and Automation, Ghent University, 9000 Ghent, Belgium)

  • Robin De Keyser

    (Department of Electrical Energy, Systems and Automation, Ghent University, 9000 Ghent, Belgium)

  • Vincent Lemort

    (Thermodynamics Laboratory, University of Liege, Campus du Sart Tilman B49, 4000 Liege, Belgium)

  • Sylvain Quoilin

    (Thermodynamics Laboratory, University of Liege, Campus du Sart Tilman B49, 4000 Liege, Belgium)

Abstract

In this paper, the optimal operation of a stationary sub-critical 11 kW el organic Rankine cycle (ORC) unit for waste heat recovery (WHR) applications is investigated, both in terms of energy production and safety conditions. Simulation results of a validated dynamic model of the ORC power unit are used to derive a correlation for the evaporating temperature, which maximizes the power generation for a range of operating conditions. This idea is further extended using a perturbation-based extremum seeking (ES) algorithm to identify online the optimal evaporating temperature. Regarding safety conditions, we propose the use of the extended prediction self-adaptive control (EPSAC) approach to constrained model predictive control (MPC). Since it uses input/output models for prediction, it avoids the need for state estimators, making it a suitable tool for industrial applications. The performance of the proposed control strategy is compared to PID-like schemes. Results show that EPSAC-MPC is a more effective control strategy, as it allows a safer and more efficient operation of the ORC unit, as it can handle constraints in a natural way, operating close to the boundary conditions where power generation is maximized.

Suggested Citation

  • Andres Hernandez & Adriano Desideri & Clara Ionescu & Robin De Keyser & Vincent Lemort & Sylvain Quoilin, 2016. "Real-Time Optimization of Organic Rankine Cycle Systems by Extremum-Seeking Control," Energies, MDPI, vol. 9(5), pages 1-18, May.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:5:p:334-:d:69379
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    References listed on IDEAS

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    Cited by:

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    2. 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.
    3. 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).
    4. Desideri, Adriano & Hernandez, Andres & Gusev, Sergei & van den Broek, Martijn & Lemort, Vincent & Quoilin, Sylvain, 2016. "Steady-state and dynamic validation of a small-scale waste heat recovery system using the ThermoCycle Modelica library," Energy, Elsevier, vol. 115(P1), pages 684-696.
    5. Marchionni, Matteo & Bianchi, Giuseppe & Karvountzis-Kontakiotis, Apostolos & Pesyridis, Apostolos & Tassou, Savvas A., 2018. "An appraisal of proportional integral control strategies for small scale waste heat to power conversion units based on Organic Rankine Cycles," Energy, Elsevier, vol. 163(C), pages 1062-1076.
    6. Hernandez, Andres & Desideri, Adriano & Gusev, Sergei & Ionescu, Clara M. & Den Broek, Martijn Van & Quoilin, Sylvain & Lemort, Vincent & De Keyser, Robin, 2017. "Design and experimental validation of an adaptive control law to maximize the power generation of a small-scale waste heat recovery system," Applied Energy, Elsevier, vol. 203(C), pages 549-559.
    7. 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.
    8. Wu, Xialai & Chen, Junghui & Xie, Lei, 2018. "Integrated operation design and control of Organic Rankine Cycle systems with disturbances," Energy, Elsevier, vol. 163(C), pages 115-129.
    9. Pallis, Platon & Varvagiannis, Efstratios & Braimakis, Konstantinos & Roumpedakis, Tryfonas & Leontaritis, Aris - Dimitrios & Karellas, Sotirios, 2021. "Development, experimental testing and techno-economic assessment of a fully automated marine organic rankine cycle prototype for jacket cooling water heat recovery," Energy, Elsevier, vol. 228(C).
    10. 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).
    11. Xu, Bin & Rathod, Dhruvang & Yebi, Adamu & Filipi, Zoran & Onori, Simona & Hoffman, Mark, 2019. "A comprehensive review of organic rankine cycle waste heat recovery systems in heavy-duty diesel engine applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 107(C), pages 145-170.

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