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Dynamic simulation of solar-powered ORC using open-source tools: A case study combining SAM and coolprop via Python

Author

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  • Eddouibi, Jaouad
  • Abderafi, Souad
  • Vaudreuil, Sébastien
  • Bounahmidi, Tijani

Abstract

The lack of an open-source dynamic simulation framework integrated with well-established thermodynamic package represents a major constraint facing open-source software users in process industry. To overcome this limitation, many approaches can be adopted to create a unified dynamic co-simulation framework. The purpose of this work is to demonstrate one of them which aims at simulating a cyclopentane based ORC cycle powered by solar thermal energy using SAM, coolprop, and Python. All unit operations (UO) involved in the ORC cycle are coded in Python language, while thermodynamic properties are estimated using Coolprop Python wrapper. The required thermal power produced by the solar field (SF) has been simulated through PySAM wrapper and then transmitted to the power cycle. Once the co-simulation architecture is established, the overall system is dynamically simulated using 10 min time step weather data file measured in Benguerir city. Subsequently, the tool is validated against literature data for the aforementioned site. The estimated mean absolute error between the simulated and the literature results was found in the range 0.7%–10.0% in terms of the SF produced thermal power, Qsf, and less than 2.25% in terms of the ORC produced electrical power, W˙net. Thus, the proposed simulation approach allows properly simulating the entire system dynamics response to the solar irradiation evolution overtime with good accuracy. The simulation tool is also used to compare the dynamic performance of the ORC cycle using the weather data of seven sites in Morocco. The obtained dynamic profiles ofQsf, the working fluid (WF) temperatureTwf, and W˙net, for the studied sites are in good agreement with their respective DNI profiles. The most significant ORC time averaged efficiency have been achieved in Tata and Benguerir, its value found to be arround 18%.

Suggested Citation

  • Eddouibi, Jaouad & Abderafi, Souad & Vaudreuil, Sébastien & Bounahmidi, Tijani, 2022. "Dynamic simulation of solar-powered ORC using open-source tools: A case study combining SAM and coolprop via Python," Energy, Elsevier, vol. 239(PA).
    • Handle: RePEc:eee:energy:v:239:y:2022:i:pa:s0360544221021836
    DOI: 10.1016/j.energy.2021.121935
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    1. Jiménez-Arreola, Manuel & Wieland, Christoph & Romagnoli, Alessandro, 2019. "Direct vs indirect evaporation in Organic Rankine Cycle (ORC) systems: A comparison of the dynamic behavior for waste heat recovery of engine exhaust," Applied Energy, Elsevier, vol. 242(C), pages 439-452.
    2. Manenti, Flavio & Ravaghi-Ardebili, Zohreh, 2013. "Dynamic simulation of concentrating solar power plant and two-tanks direct thermal energy storage," Energy, Elsevier, vol. 55(C), pages 89-97.
    3. Kristianto, Yohanes & Zhu, Liandong, 2017. "Techno-economic optimization of ethanol synthesis from rice-straw supply chains," Energy, Elsevier, vol. 141(C), pages 2164-2176.
    4. Postawa, Karol & Szczygieł, Jerzy & Kułażyński, Marek, 2020. "A comprehensive comparison of ODE solvers for biochemical problems," Renewable Energy, Elsevier, vol. 156(C), pages 624-633.
    5. 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.
    6. Declaye, Sébastien & Quoilin, Sylvain & Guillaume, Ludovic & Lemort, Vincent, 2013. "Experimental study on an open-drive scroll expander integrated into an ORC (Organic Rankine Cycle) system with R245fa as working fluid," Energy, Elsevier, vol. 55(C), pages 173-183.
    7. Belgasim, Basim & Aldali, Yasser & Abdunnabi, Mohammad J.R. & Hashem, Gamal & Hossin, Khaled, 2018. "The potential of concentrating solar power (CSP) for electricity generation in Libya," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 1-15.
    8. Buzás, J. & Kicsiny, R., 2014. "Transfer functions of solar collectors for dynamical analysis and control design," Renewable Energy, Elsevier, vol. 68(C), pages 146-155.
    9. Dickes, Rémi & Dumont, Olivier & Daccord, Rémi & Quoilin, Sylvain & Lemort, Vincent, 2017. "Modelling of organic Rankine cycle power systems in off-design conditions: An experimentally-validated comparative study," Energy, Elsevier, vol. 123(C), pages 710-727.
    10. 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.
    11. Zhang, Qiang & Wang, Zhiming & Du, Xiaoze & Yu, Gang & Wu, Hongwei, 2019. "Dynamic simulation of steam generation system in solar tower power plant," Renewable Energy, Elsevier, vol. 135(C), pages 866-876.
    12. Rohde, Daniel & Knudsen, Brage Rugstad & Andresen, Trond & Nord, Natasa, 2020. "Dynamic optimization of control setpoints for an integrated heating and cooling system with thermal energy storages," Energy, Elsevier, vol. 193(C).
    13. Cox, Sam J. & Kim, Dongsu & Cho, Heejin & Mago, Pedro, 2019. "Real time optimal control of district cooling system with thermal energy storage using neural networks," Applied Energy, Elsevier, vol. 238(C), pages 466-480.
    14. Natalie Christine Nakaten & Thomas Kempka, 2017. "Techno-Economic Comparison of Onshore and Offshore Underground Coal Gasification End-Product Competitiveness," Energies, MDPI, vol. 10(10), pages 1-27, October.
    15. Lin, Shan & Zhao, Li & Deng, Shuai & Ni, Jiaxin & Zhang, Ying & Ma, Minglu, 2019. "Dynamic performance investigation for two types of ORC system driven by waste heat of automotive internal combustion engine," Energy, Elsevier, vol. 169(C), pages 958-971.
    Full references (including those not matched with items on IDEAS)

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    1. Zhang, Yuan & Wu, Xiaocheng & Tian, Zhen & Gao, Wenzhong & Peng, Hao & Yang, Ke, 2023. "Comparison of random forest, support vector regression, and long short term memory for performance prediction and optimization of a cryogenic organic rankine cycle (ORC)," Energy, Elsevier, vol. 280(C).
    2. José M. Cardemil & Ignacio Calderón-Vásquez & Alan Pino & Allan Starke & Ian Wolde & Carlos Felbol & Leonardo F. L. Lemos & Vinicius Bonini & Ignacio Arias & Javier Iñigo-Labairu & Jürgen Dersch & Rod, 2022. "Assessing the Uncertainties of Simulation Approaches for Solar Thermal Systems Coupled to Industrial Processes," Energies, MDPI, vol. 15(9), pages 1-29, May.

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