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Economic and Reliability Assessment of Hybrid PRO-RO Desalination Systems Using Brine for Salinity Gradient Energy Production

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  • Ewaoche John Okampo

    (Department of Electrical and Electronic Engineering Technology, University of Johannesburg, Johannesburg 2092, South Africa)

  • Nnamdi Nwulu

    (Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg 2092, South Africa)

  • Pitshou N. Bokoro

    (Department of Electrical and Electronic Engineering Technology, University of Johannesburg, Johannesburg 2092, South Africa)

Abstract

The energy requirements for desalination have made it an expensive process, however, it is still a viable and cost-effective means of water purification amidst freshwater scarcity. The management and disposal of brine is an external and extra desalination cost due to the effect of brine on the environment. The integration of Pressure Retarded Osmosis (PRO) with the Reverse Osmosis (RO) technique as modelled in this paper enhances brine management. The brine is fed back into the PRO unit to create a salinity gradient for water transfer via membrane and generate salinity gradient energy. The hybrid desalination model is designed to be powered by grid-tied offshore wind power. The use of wind power, a clean, renewable energy source devoid of carbon emission, as the main power source to drive the RO unit reduces the cost and effect of carbon emissions from the grid. The proposed model is assessed using Levelized cost of energy (LCOE), Annualized cost of the system (ACS), and cost of water (COW) as economic matrices. In contrast, loss of energy probability is used as a reliability matrix. Obtained results show a LCOE of 1.11 $/kW, ACW of $110,456, COW of 0.13 $/m 3 , loss of energy probability of 0.341, a low total carbon emissions of 193,323 kgCO 2-e , and zero brine production. Results show that the proposed model is economically viable, technically reliable, environmentally friendly, and generally sustainable.

Suggested Citation

  • Ewaoche John Okampo & Nnamdi Nwulu & Pitshou N. Bokoro, 2022. "Economic and Reliability Assessment of Hybrid PRO-RO Desalination Systems Using Brine for Salinity Gradient Energy Production," Sustainability, MDPI, vol. 14(6), pages 1-16, March.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:6:p:3328-:d:769582
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    References listed on IDEAS

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    1. Nwulu, Nnamdi I. & Xia, Xiaohua, 2017. "Optimal dispatch for a microgrid incorporating renewables and demand response," Renewable Energy, Elsevier, vol. 101(C), pages 16-28.
    2. Jia, Zhijun & Wang, Baoguo & Song, Shiqiang & Fan, Yongsheng, 2014. "Blue energy: Current technologies for sustainable power generation from water salinity gradient," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 91-100.
    3. Okampo, Ewaoche John & Nwulu, Nnamdi, 2021. "Optimisation of renewable energy powered reverse osmosis desalination systems: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
    4. Maleki, Akbar & Khajeh, Morteza Gholipour & Rosen, Marc A., 2016. "Weather forecasting for optimization of a hybrid solar-wind–powered reverse osmosis water desalination system using a novel optimizer approach," Energy, Elsevier, vol. 114(C), pages 1120-1134.
    5. Li, Zhenyu & Siddiqi, Afreen & Anadon, Laura Diaz & Narayanamurti, Venkatesh, 2018. "Towards sustainability in water-energy nexus: Ocean energy for seawater desalination," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3833-3847.
    6. Long, Rui & Lai, Xiaotian & Liu, Zhichun & Liu, Wei, 2019. "Pressure retarded osmosis: Operating in a compromise between power density and energy efficiency," Energy, Elsevier, vol. 172(C), pages 592-598.
    7. Saheed Lekan Gbadamosi & Nnamdi I. Nwulu, 2020. "Optimal Power Dispatch and Reliability Analysis of Hybrid CHP-PV-Wind Systems in Farming Applications," Sustainability, MDPI, vol. 12(19), pages 1-16, October.
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