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Performance analysis of reverse electrodialysis stacks: Channel geometry and flow rate optimization

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

Abstract

In this paper, the optimal channel geometry and flow rate of the concentrated and diluted solutions under the maximum net power output for the reverse electrodialysis (RED) stacks at a confined size are systematically investigated. A model considering the change in volume flow rate along the flow direction is employed to illustrate the process of the RED stack. For systematisms, under the maximum net power output, we first consider the optimal channel thicknesses at a given identical inlet flow rate and then the optimal channel thicknesses and flow rates. The profiles of flow rate, concentration, power density, and hydrodynamic loss along the flow direction are discussed. The net power output and energy efficiency for different membranes under the above two optimization situations are analyzed and compared. The results reveal that the optimal channel thickness of the high-concentration (HC) compartment is slightly larger than that of the low-concentration (LC) compartment for a given identical inlet flow rate. When both channel thickness and flow rate are optimized, the optimal channel thicknesses and volume flow rates of the HC compartment are, respectively, less than those of the LC compartment and the net power output and energy efficiency are significantly improved.

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  • 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.
    • Handle: RePEc:eee:energy:v:158:y:2018:i:c:p:427-436
    DOI: 10.1016/j.energy.2018.06.067
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    References listed on IDEAS

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    1. 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.
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    3. 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.
    4. Ge, Ya & Liu, Zhichun & Sun, Henan & Liu, Wei, 2018. "Optimal design of a segmented thermoelectric generator based on three-dimensional numerical simulation and multi-objective genetic algorithm," Energy, Elsevier, vol. 147(C), pages 1060-1069.
    5. 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.
    6. Long, Rui & Li, Baode & Liu, Zhichun & Liu, Wei, 2015. "Performance analysis of a thermally regenerative electrochemical cycle for harvesting waste heat," Energy, Elsevier, vol. 87(C), pages 463-469.
    7. Long, Rui & Lai, Xiaotian & Liu, Zhichun & Liu, Wei, 2018. "Direct contact membrane distillation system for waste heat recovery: Modelling and multi-objective optimization," Energy, Elsevier, vol. 148(C), pages 1060-1068.
    8. Lorestani, A. & Ardehali, M.M., 2018. "Optimal integration of renewable energy sources for autonomous tri-generation combined cooling, heating and power system based on evolutionary particle swarm optimization algorithm," Energy, Elsevier, vol. 145(C), pages 839-855.
    9. Long, Rui & Li, Baode & Liu, Zhichun & Liu, Wei, 2016. "Performance analysis of a dual loop thermally regenerative electrochemical cycle for waste heat recovery," Energy, Elsevier, vol. 107(C), pages 388-395.
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    Cited by:

    1. Long, Rui & Zhao, Yanan & Luo, Zuoqing & Li, Lei & Liu, Zhichun & Liu, Wei, 2020. "Alternative thermal regenerative osmotic heat engines for low-grade heat harvesting," Energy, Elsevier, vol. 195(C).
    2. 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.
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    4. 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.
    5. Long, Rui & Zhao, Yanan & Li, Mingliang & Pan, Yao & Liu, Zhichun & Liu, Wei, 2021. "Evaluations of adsorbents and salt-methanol solutions for low-grade heat driven osmotic heat engines," Energy, Elsevier, vol. 229(C).
    6. 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.
    7. 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.
    8. 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).
    9. 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).

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