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Modelling and optimization of modular system for power generation from a salinity gradient

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  • Altaee, Ali
  • Cipolina, Andrea

Abstract

Pressure retarded osmosis has been proposed for power generation from a salinity gradient resource. The process has been promoted as a promising technology for power generation from renewable resources, but most of the experimental work has been done on a laboratory size units. To date, pressure retarded osmosis optimization and operation is based on parametric studies performed on laboratory scale units, which leaves a gap in our understanding of the process behaviour in a full-scale modular system. A computer model has been developed to predict the process performance. Process modelling was performed on a full-scale membrane module and impact of key operating parameters such as hydraulic feed pressure and feed and draw solution rates were evaluated. Results showed that the optimum fraction of feed/draw solution in a mixture is less than what has been earlier proposed ratio of 50% and it is entirely dependent on the salinity gradient resource concentration. Furthermore, the optimized pressure retarded osmosis process requires a hydraulic pressure less than that in the normal (unoptimized) process. The results here demonstrate that the energy output from the optimized pressure regarded osmosis process is up to 54% higher than that in the normal (unoptimized) process.

Suggested Citation

  • Altaee, Ali & Cipolina, Andrea, 2019. "Modelling and optimization of modular system for power generation from a salinity gradient," Renewable Energy, Elsevier, vol. 141(C), pages 139-147.
    • Handle: RePEc:eee:renene:v:141:y:2019:i:c:p:139-147
    DOI: 10.1016/j.renene.2019.03.138
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    References listed on IDEAS

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    1. Altaee, Ali & Millar, Graeme J. & Zaragoza, Guillermo, 2016. "Integration and optimization of pressure retarded osmosis with reverse osmosis for power generation and high efficiency desalination," Energy, Elsevier, vol. 103(C), pages 110-118.
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    5. Altaee, Ali & Zhou, John & Alhathal Alanezi, Adnan & Zaragoza, Guillermo, 2017. "Pressure retarded osmosis process for power generation: Feasibility, energy balance and controlling parameters," Applied Energy, Elsevier, vol. 206(C), pages 303-311.
    6. Sharif, Arshian & Raza, Syed Ali & Ozturk, Ilhan & Afshan, Sahar, 2019. "The dynamic relationship of renewable and nonrenewable energy consumption with carbon emission: A global study with the application of heterogeneous panel estimations," Renewable Energy, Elsevier, vol. 133(C), pages 685-691.
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    5. Chunyan, Ling & Jingzhe, Lei & Way, Kuo, 2022. "Bayesian support vector machine for optimal reliability design of modular systems," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
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    7. Abdelkader, Bassel A. & Navas, Daniel Ruiz & Sharqawy, Mostafa H., 2023. "A novel spiral wound module design for harvesting salinity gradient energy using pressure retarded osmosis," Renewable Energy, Elsevier, vol. 203(C), pages 542-553.

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