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Design methodology for flexible energy conversion systems accounting for dynamic performance

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  • Pierobon, Leonardo
  • Casati, Emiliano
  • Casella, Francesco
  • Haglind, Fredrik
  • Colonna, Piero

Abstract

This article presents a methodology to help in the definition of the optimal design of power generation systems. The innovative element is the integration of requirements on dynamic performance into the system design procedure. Operational flexibility is an increasingly important specification of power systems for base- and part-load operation. Thus, it is crucial to discard, in an early phase of the design process, plant configurations which feature unacceptable dynamic performance. The test case is the preliminary design of an off-grid power plant serving an off-shore platform where one of the three gas turbines is combined with an organic Rankine cycle turbogenerator to increase the overall energy efficiency. The core of the procedure is a stationary model, capable of performing the on-design thermodynamic cycle calculation, and the design of the components of the system. The results of these simulations are used within the framework of a multi-objective optimization procedure to identify a number of equally optimal system configurations. A dynamic model of each of these systems is automatically parameterized, by inheriting its parameters values from the design model. Dynamic simulations allow then to discriminate among the initial set of solutions, thus providing the designs that also comply with dynamic requirements.

Suggested Citation

  • Pierobon, Leonardo & Casati, Emiliano & Casella, Francesco & Haglind, Fredrik & Colonna, Piero, 2014. "Design methodology for flexible energy conversion systems accounting for dynamic performance," Energy, Elsevier, vol. 68(C), pages 667-679.
    • Handle: RePEc:eee:energy:v:68:y:2014:i:c:p:667-679
    DOI: 10.1016/j.energy.2014.03.010
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    Cited by:

    1. 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.
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    3. 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.
    4. Locatelli, Giorgio & Boarin, Sara & Pellegrino, Francesco & Ricotti, Marco E., 2015. "Load following with Small Modular Reactors (SMR): A real options analysis," Energy, Elsevier, vol. 80(C), pages 41-54.
    5. Hao, Zhaojun & Di Maio, Francesco & Zio, Enrico, 2023. "A sequential decision problem formulation and deep reinforcement learning solution of the optimization of O&M of cyber-physical energy systems (CPESs) for reliable and safe power production and supply," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    6. Pili, Roberto & Bojer Jørgensen, Søren & Haglind, Fredrik, 2022. "Multi-objective optimization of organic Rankine cycle systems considering their dynamic performance," Energy, Elsevier, vol. 246(C).
    7. Michael Chukwuemeka Ekwonu & Mirae Kim & Binqi Chen & Muhammad Tauseef Nasir & Kyung Chun Kim, 2023. "Dynamic Simulation of Partial Load Operation of an Organic Rankine Cycle with Two Parallel Expanders," Energies, MDPI, vol. 16(1), pages 1-18, January.
    8. Pierobon, L. & Benato, A. & Scolari, E. & Haglind, F. & Stoppato, A., 2014. "Waste heat recovery technologies for offshore platforms," Applied Energy, Elsevier, vol. 136(C), pages 228-241.
    9. 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.
    10. Martelli, Emanuele & Capra, Federico & Consonni, Stefano, 2015. "Numerical optimization of Combined Heat and Power Organic Rankine Cycles – Part A: Design optimization," Energy, Elsevier, vol. 90(P1), pages 310-328.
    11. Zhaojun Hao & Francesco Di Maio & Enrico Zio, 2021. "Multi-State Reliability Assessment Model of Base-Load Cyber-Physical Energy Systems (CPES) during Flexible Operation Considering the Aging of Cyber Components," Energies, MDPI, vol. 14(11), pages 1-18, June.
    12. Mondejar, M.E. & Andreasen, J.G. & Pierobon, L. & Larsen, U. & Thern, M. & Haglind, F., 2018. "A review of the use of organic Rankine cycle power systems for maritime applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 126-151.
    13. Luca Riboldi & Lars O. Nord, 2017. "Lifetime Assessment of Combined Cycles for Cogeneration of Power and Heat in Offshore Oil and Gas Installations," Energies, MDPI, vol. 10(6), pages 1-23, May.
    14. 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).
    15. Benato, A. & Kærn, M.R. & Pierobon, L. & Stoppato, A. & Haglind, F., 2015. "Analysis of hot spots in boilers of organic Rankine cycle units during transient operation," Applied Energy, Elsevier, vol. 151(C), pages 119-131.
    16. Imran, Muhammad & Haglind, Fredrik & Lemort, Vincent & Meroni, Andrea, 2019. "Optimization of organic rankine cycle power systems for waste heat recovery on heavy-duty vehicles considering the performance, cost, mass and volume of the system," Energy, Elsevier, vol. 180(C), pages 229-241.
    17. Serafino, Aldo & Obert, Benoit & Vergé, Léa & Cinnella, Paola, 2020. "Robust optimization of an organic Rankine cycle for geothermal application," Renewable Energy, Elsevier, vol. 161(C), pages 1120-1129.
    18. Najafi, Gholamhassan & Ghobadian, Barat & Yusaf, Talal & Safieddin Ardebili, Seyed Mohammad & Mamat, Rizalman, 2015. "Optimization of performance and exhaust emission parameters of a SI (spark ignition) engine with gasoline–ethanol blended fuels using response surface methodology," Energy, Elsevier, vol. 90(P2), pages 1815-1829.

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