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Reverse electrodialysis: Modelling and performance analysis based on multi-objective optimization

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Listed:
  • Long, Rui
  • Li, Baode
  • Liu, Zhichun
  • Liu, Wei

Abstract

In this paper, we proposed a refined model to describe the RED process by considering the variation of flow rates along the flow direction, and the concentration depended density and viscosity. The model was verified by good accordance between the calculated and experimental measured data. For evaluating the performance of a RED stack for some special applications, the net power density and the energy efficiency are two main criteria. However, they could not achieve their maximum values simultaneously. To achieve such a compromise, an optimization based on Non-dominated Sorting Genetic Algorithm II (NSGA-II) was conducted. Besides, the net power output and energy efficiency under single-objective optimization methods were calculated and compared. Results revealed that compared to the results under the maximum net power density, the net power density under the multi-objective optimization is slightly less than the maximum one, meanwhile the energy efficiency was much greater. The performance under the multi-objective optimization exhibited no obvious disadvantage against that under the maximum energy efficiency, considering the significant increase of the net power density.

Suggested Citation

  • Long, Rui & Li, Baode & Liu, Zhichun & Liu, Wei, 2018. "Reverse electrodialysis: Modelling and performance analysis based on multi-objective optimization," Energy, Elsevier, vol. 151(C), pages 1-10.
    • Handle: RePEc:eee:energy:v:151:y:2018:i:c:p:1-10
    DOI: 10.1016/j.energy.2018.03.003
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    References listed on IDEAS

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    1. Long, Rui & Li, Baode & Liu, Zhichun & Liu, Wei, 2015. "A hybrid system using a regenerative electrochemical cycle to harvest waste heat from the proton exchange membrane fuel cell," Energy, Elsevier, vol. 93(P2), pages 2079-2086.
    2. Long, R. & Bao, Y.J. & Huang, X.M. & Liu, W., 2014. "Exergy analysis and working fluid selection of organic Rankine cycle for low grade waste heat recovery," Energy, Elsevier, vol. 73(C), pages 475-483.
    3. 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.
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    5. Long, Rui & Li, Baode & Liu, Zhichun & Liu, Wei, 2015. "Multi-objective optimization of a continuous thermally regenerative electrochemical cycle for waste heat recovery," Energy, Elsevier, vol. 93(P1), pages 1022-1029.
    6. Long, Rui & Li, Baode & Liu, Zhichun & Liu, Wei, 2015. "Performance analysis of a solar-powered solid state heat engine for electricity generation," Energy, Elsevier, vol. 93(P1), pages 165-172.
    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. Jeong, Hoe-In & Kim, Hyun Jung & Kim, Dong-Kwon, 2014. "Numerical analysis of transport phenomena in reverse electrodialysis for system design and optimization," Energy, Elsevier, vol. 68(C), pages 229-237.
    9. Hong, Jin Gi & Zhang, Wen & Luo, Jian & Chen, Yongsheng, 2013. "Modeling of power generation from the mixing of simulated saline and freshwater with a reverse electrodialysis system: The effect of monovalent and multivalent ions," Applied Energy, Elsevier, vol. 110(C), pages 244-251.
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    2. Chen, Man & Mei, Ying & Yu, Yuqing & Zeng, Raymond Jianxiong & Zhang, Fang & Zhou, Shungui & Tang, Chuyang Y., 2019. "An internal-integrated RED/ED system for energy-saving seawater desalination: A model study," Energy, Elsevier, vol. 170(C), pages 139-148.
    3. Zhao, Yanan & Li, Mingliang & Long, Rui & Liu, Zhichun & Liu, Wei, 2021. "Dynamic modeling and analysis of an advanced adsorption-based osmotic heat engines to harvest solar energy," Renewable Energy, Elsevier, vol. 175(C), pages 638-649.
    4. Qiang Leng & Feilong Li & Zhenxin Tao & Zhanwei Wang & Xi Wu, 2024. "Advanced Wastewater Treatment: Synergistic Integration of Reverse Electrodialysis with Electrochemical Degradation Driven by Low-Grade Heat," Energies, MDPI, vol. 17(21), pages 1-24, October.
    5. Long, Rui & Lai, Xiaotian & Liu, Zhichun & Liu, Wei, 2018. "A continuous concentration gradient flow electrical energy storage system based on reverse osmosis and pressure retarded osmosis," Energy, Elsevier, vol. 152(C), pages 896-905.
    6. Hailong Gao & Zhiyong Xiao & Jie Zhang & Xiaohan Zhang & Xiangdong Liu & Xinying Liu & Jin Cui & Jianbo Li, 2023. "Optimization Study on Salinity Gradient Energy Capture from Brine and Dilute Brine," Energies, MDPI, vol. 16(12), pages 1-16, June.
    7. Ciofalo, Michele & La Cerva, Mariagiorgia & Di Liberto, Massimiliano & Gurreri, Luigi & Cipollina, Andrea & Micale, Giorgio, 2019. "Optimization of net power density in Reverse Electrodialysis," Energy, Elsevier, vol. 181(C), pages 576-588.
    8. 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.
    9. Wu, Xi & Zhang, Xinjie & Xu, Shiming & Gong, Ying & Yang, Shuaishuai & Jin, Dongxu, 2021. "Performance of a reverse electrodialysis cell working with potassium acetate−methanol−water solution," Energy, Elsevier, vol. 232(C).
    10. Zhao, Yanan & Luo, Zuoqing & Long, Rui & Liu, Zhichun & Liu, Wei, 2020. "Performance evaluations of an adsorption-based power and cooling cogeneration system under different operative conditions and working fluids," Energy, Elsevier, vol. 204(C).
    11. Lai, Xiaotian & Long, Rui & Liu, Zhichun & Liu, Wei, 2018. "Stirling engine powered reverse osmosis for brackish water desalination to utilize moderate temperature heat," Energy, Elsevier, vol. 165(PA), pages 916-930.
    12. Long, Rui & Li, Baode & Liu, Zhichun & Liu, Wei, 2018. "Performance analysis of reverse electrodialysis stacks: Channel geometry and flow rate optimization," Energy, Elsevier, vol. 158(C), pages 427-436.

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