IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v96y2016ipap98-119.html
   My bibliography  Save this article

Role of two different pretreatment methods in osmotic power (salinity gradient energy) generation

Author

Listed:
  • Abbasi-Garravand, Elham
  • Mulligan, Catherine N.
  • Laflamme, Claude B.
  • Clairet, Guillaume

Abstract

Pressure retarded osmosis is a membrane based technology that produces osmotic power as a sustainable energy by using salt and fresh waters. Pretreatment reduces membrane fouling as the main challenge in Pressure Retarded Osmosis (PRO). In this research, ultrafiltration and a sand filter were used for removing total organic carbon (TOC), turbidity, and hardness. In trials, efficiency and required power of the two methods were compared. Highest removal efficiency of turbidity occurred at 3.72 NTU and was 100% and 68.6% for ultrafiltration and the multimedia sand filter, respectively. Maximum TOC removal in ultrafiltration multimedia sand filter was 41% and 1.5% at 6.62 mg/L TOC initial concentration respectively. In all experiments, it was indicated that ultrafiltration had better removal efficiency and consequently more potential for osmotic power generation process improvement.

Suggested Citation

  • Abbasi-Garravand, Elham & Mulligan, Catherine N. & Laflamme, Claude B. & Clairet, Guillaume, 2016. "Role of two different pretreatment methods in osmotic power (salinity gradient energy) generation," Renewable Energy, Elsevier, vol. 96(PA), pages 98-119.
    • Handle: RePEc:eee:renene:v:96:y:2016:i:pa:p:98-119
    DOI: 10.1016/j.renene.2016.04.031
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148116303354
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2016.04.031?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. Kim, Juwan & Kim, Sung Jin & Kim, Dong-Kwon, 2013. "Energy harvesting from salinity gradient by reverse electrodialysis with anodic alumina nanopores," Energy, Elsevier, vol. 51(C), pages 413-421.
    2. Bruce E. Logan & Menachem Elimelech, 2012. "Membrane-based processes for sustainable power generation using water," Nature, Nature, vol. 488(7411), pages 313-319, August.
    3. Erdinc, O. & Uzunoglu, M., 2012. "Optimum design of hybrid renewable energy systems: Overview of different approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1412-1425.
    4. Li, Xue & Chung, Tai-Shung, 2014. "Thin-film composite P84 co-polyimide hollow fiber membranes for osmotic power generation," Applied Energy, Elsevier, vol. 114(C), pages 600-610.
    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. Cala, Anggie & Maturana-Córdoba, Aymer & Soto-Verjel, Joseph, 2023. "Exploring the pretreatments' influence on pressure reverse osmosis: PRISMA review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    2. Safder, Usman & Lim, Juin Yau & How, Bing Shen & Ifaei, Pouya & Heo, SungKy & Yoo, ChangKyoo, 2022. "Optimal configuration and economic analysis of PRO-retrofitted industrial networks for sustainable energy production and material recovery considering uncertainties: Bioethanol and sugar mill case stu," Renewable Energy, Elsevier, vol. 182(C), pages 797-816.
    3. Safder, Usman & Tariq, Shahzeb & Yoo, ChangKyoo, 2022. "Multilevel optimization framework to support self-sustainability of industrial processes for energy/material recovery using circular integration concept," Applied Energy, Elsevier, vol. 324(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. Tan, Guangcai & Xu, Nan & Gao, Dingxue & Zhu, Xiuping, 2022. "Superabsorbent graphene oxide/carbon nanotube hybrid Poly(acrylic acid-co-acrylamide) hydrogels for efficient salinity gradient energy harvest," Energy, Elsevier, vol. 258(C).
    2. Chanda, Sourayon & Tsai, Peichun Amy, 2019. "Numerical simulation of renewable power generation using reverse electrodialysis," Energy, Elsevier, vol. 176(C), pages 531-543.
    3. Tamburini, A. & Tedesco, M. & Cipollina, A. & Micale, G. & Ciofalo, M. & Papapetrou, M. & Van Baak, W. & Piacentino, A., 2017. "Reverse electrodialysis heat engine for sustainable power production," Applied Energy, Elsevier, vol. 206(C), pages 1334-1353.
    4. Maisonneuve, Jonathan & Chintalacheruvu, Sanjana, 2019. "Increasing osmotic power and energy with maximum power point tracking," Applied Energy, Elsevier, vol. 238(C), pages 683-695.
    5. Jihye Kim & Kwanho Jeong & Myoung Jun Park & Ho Kyong Shon & Joon Ha Kim, 2015. "Recent Advances in Osmotic Energy Generation via Pressure-Retarded Osmosis (PRO): A Review," Energies, MDPI, vol. 8(10), pages 1-25, October.
    6. Han, Gang & Ge, Qingchun & Chung, Tai-Shung, 2014. "Conceptual demonstration of novel closed-loop pressure retarded osmosis process for sustainable osmotic energy generation," Applied Energy, Elsevier, vol. 132(C), pages 383-393.
    7. Kang, Byeong Dong & Kim, Hyun Jung & Lee, Moon Gu & Kim, Dong-Kwon, 2015. "Numerical study on energy harvesting from concentration gradient by reverse electrodialysis in anodic alumina nanopores," Energy, Elsevier, vol. 86(C), pages 525-538.
    8. Maisonneuve, Jonathan & Laflamme, Claude B. & Pillay, Pragasen, 2016. "Experimental investigation of pressure retarded osmosis for renewable energy conversion: Towards increased net power," Applied Energy, Elsevier, vol. 164(C), pages 425-435.
    9. He, Wei & Wang, Yang & Shaheed, Mohammad Hasan, 2015. "Maximum power point tracking (MPPT) of a scale-up pressure retarded osmosis (PRO) osmotic power plant," Applied Energy, Elsevier, vol. 158(C), pages 584-596.
    10. Bevacqua, M. & Tamburini, A. & Papapetrou, M. & Cipollina, A. & Micale, G. & Piacentino, A., 2017. "Reverse electrodialysis with NH4HCO3-water systems for heat-to-power conversion," Energy, Elsevier, vol. 137(C), pages 1293-1307.
    11. Wan, Chun Feng & Chung, Tai-Shung, 2016. "Energy recovery by pressure retarded osmosis (PRO) in SWRO–PRO integrated processes," Applied Energy, Elsevier, vol. 162(C), pages 687-698.
    12. Al Busaidi, Ahmed Said & Kazem, Hussein A & Al-Badi, Abdullah H & Farooq Khan, Mohammad, 2016. "A review of optimum sizing of hybrid PV–Wind renewable energy systems in oman," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 185-193.
    13. He, Wei & Wang, Jihong, 2017. "Feasibility study of energy storage by concentrating/desalinating water: Concentrated Water Energy Storage," Applied Energy, Elsevier, vol. 185(P1), pages 872-884.
    14. Bernardos, Eva & López, Ignacio & Rodríguez, Javier & Abánades, Alberto, 2013. "Assessing the potential of hybrid fossil–solar thermal plants for energy policy making: Brayton cycles," Energy Policy, Elsevier, vol. 62(C), pages 99-106.
    15. García-Villoria, Alberto & Domenech, Bruno & Ferrer-Martí, Laia & Juanpera, Marc & Pastor, Rafael, 2020. "Ad-hoc heuristic for design of wind-photovoltaic electrification systems, including management constraints," Energy, Elsevier, vol. 212(C).
    16. M. Rambabu & G. V. Nagesh Kumar & S. Sivanagaraju, 2019. "Optimal Power Flow of Integrated Renewable Energy System using a Thyristor Controlled SeriesCompensator and a Grey-Wolf Algorithm," Energies, MDPI, vol. 12(11), pages 1-18, June.
    17. Liu, Zhengxuan & Zhou, Yuekuan & Yan, Jun & Tostado-Véliz, Marcos, 2023. "Frontier ocean thermal/power and solar PV systems for transformation towards net-zero communities," Energy, Elsevier, vol. 284(C).
    18. Nithya Saiprasad & Akhtar Kalam & Aladin Zayegh, 2019. "Triple Bottom Line Analysis and Optimum Sizing of Renewable Energy Using Improved Hybrid Optimization Employing the Genetic Algorithm: A Case Study from India," Energies, MDPI, vol. 12(3), pages 1-23, January.
    19. Mai, Van-Phung & Yang, Ruey-Jen, 2020. "Boosting power generation from salinity gradient on high-density nanoporous membrane using thermal effect," Applied Energy, Elsevier, vol. 274(C).
    20. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.

    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:renene:v:96:y:2016:i:pa:p:98-119. 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/renewable-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.