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Maximum power point tracking (MPPT) of a scale-up pressure retarded osmosis (PRO) osmotic power plant

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  • He, Wei
  • Wang, Yang
  • Shaheed, Mohammad Hasan

Abstract

This paper presents a maximum power point tracking (MPPT) of a scale-up pressure retarded osmosis (PRO) based osmotic power generator. Inspired by the well-known MPPT in photovoltaic (PV) array, two algorithms, perturb & observe (P&O) and incremental mass-resistance (IMR) method, are investigated. Using a series of simulations, both the algorithms are demonstrated to be capable of tracking the maximum power point (MPP) and capturing the transitions between varied MPPs due to the fluctuations of operating temperature. However, in both cases the trade-off between the rise time and the oscillation is found requiring further consideration on the selection of the step-size for perturbation pressure or incremental pressure. In order to improve the performance of the MPPT, furthermore, an optimum model-based controller (OMC) is used to estimate the initial optimum pressure for the MPPT in a scale-up PRO process. It is found that with OMC, the performance of the MPPT is improved significantly. Finally, a strategy to operate and coordinate the MPPT and OMC to deal with the rapid variations of the salinities are proposed and evaluated in terms of individual variation of the concentration or flow rate and co-variation of the both. The simulations demonstrate the preferred performance of the proposed strategy to adjust the operation subject to the rapid changes of the salinities.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:appene:v:158:y:2015:i:c:p:584-596
    DOI: 10.1016/j.apenergy.2015.08.059
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    References listed on IDEAS

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    1. Bizon, N., 2010. "On tracking robustness in adaptive extremum seeking control of the fuel cell power plants," Applied Energy, Elsevier, vol. 87(10), pages 3115-3130, October.
    2. Rizzo, Santi Agatino & Scelba, Giacomo, 2015. "ANN based MPPT method for rapidly variable shading conditions," Applied Energy, Elsevier, vol. 145(C), pages 124-132.
    3. Ahmed, Jubaer & Salam, Zainal, 2015. "An improved perturb and observe (P&O) maximum power point tracking (MPPT) algorithm for higher efficiency," Applied Energy, Elsevier, vol. 150(C), pages 97-108.
    4. Lin, Chia-Hung & Huang, Cong-Hui & Du, Yi-Chun & Chen, Jian-Liung, 2011. "Maximum photovoltaic power tracking for the PV array using the fractional-order incremental conductance method," Applied Energy, Elsevier, vol. 88(12), pages 4840-4847.
    5. 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.
    6. He, Wei & Wang, Yang & Shaheed, Mohammad Hasan, 2015. "Stand-alone seawater RO (reverse osmosis) desalination powered by PV (photovoltaic) and PRO (pressure retarded osmosis)," Energy, Elsevier, vol. 86(C), pages 423-435.
    7. Kumar, Gaurav & Trivedi, Milind B. & Panchal, Ashish K., 2015. "Innovative and precise MPP estimation using P–V curve geometry for photovoltaics," Applied Energy, Elsevier, vol. 138(C), pages 640-647.
    8. Bizon, Nicu, 2013. "Energy harvesting from the FC stack that operates using the MPP tracking based on modified extremum seeking control," Applied Energy, Elsevier, vol. 104(C), pages 326-336.
    9. Salam, Zainal & Ahmed, Jubaer & Merugu, Benny S., 2013. "The application of soft computing methods for MPPT of PV system: A technological and status review," Applied Energy, Elsevier, vol. 107(C), pages 135-148.
    10. Prante, Jeri L. & Ruskowitz, Jeffrey A. & Childress, Amy E. & Achilli, Andrea, 2014. "RO-PRO desalination: An integrated low-energy approach to seawater desalination," Applied Energy, Elsevier, vol. 120(C), pages 104-114.
    11. Bruce E. Logan & Menachem Elimelech, 2012. "Membrane-based processes for sustainable power generation using water," Nature, Nature, vol. 488(7411), pages 313-319, August.
    12. 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.
    13. Altaee, Ali & Sharif, Adel & Zaragoza, Guillermo, 2015. "Limitations of osmotic gradient resource and hydraulic pressure on the efficiency of dual stage PRO process," Renewable Energy, Elsevier, vol. 83(C), pages 1234-1244.
    14. Ahmed, Jubaer & Salam, Zainal, 2014. "A Maximum Power Point Tracking (MPPT) for PV system using Cuckoo Search with partial shading capability," Applied Energy, Elsevier, vol. 119(C), pages 118-130.
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    Cited by:

    1. Chen, Yingxue & Vepa, Ranjan & Shaheed, Mohammad Hasan, 2018. "Enhanced and speedy energy extraction from a scaled-up pressure retarded osmosis process with a whale optimization based maximum power point tracking," Energy, Elsevier, vol. 153(C), pages 618-627.
    2. Hong, Ying-Yi & Beltran, Angelo A. & Paglinawan, Arnold C., 2018. "A robust design of maximum power point tracking using Taguchi method for stand-alone PV system," Applied Energy, Elsevier, vol. 211(C), pages 50-63.
    3. Yingxue Chen & Linfeng Gou, 2021. "A Boosted Particle Swarm Method for Energy Efficiency Optimization of PRO Systems," Energies, MDPI, vol. 14(22), pages 1-13, November.
    4. 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.
    5. Maisonneuve, Jonathan & Chintalacheruvu, Sanjana, 2019. "Increasing osmotic power and energy with maximum power point tracking," Applied Energy, Elsevier, vol. 238(C), pages 683-695.
    6. Wen Yi Chia & Kuan Shiong Khoo & Shir Reen Chia & Kit Wayne Chew & Guo Yong Yew & Yeek-Chia Ho & Pau Loke Show & Wei-Hsin Chen, 2020. "Factors Affecting the Performance of Membrane Osmotic Processes for Bioenergy Development," Energies, MDPI, vol. 13(2), pages 1-22, January.
    7. Touati, Khaled & Rahaman, Md. Saifur, 2020. "Viability of pressure-retarded osmosis for harvesting energy from salinity gradients," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    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. Tufa, Ramato Ashu & Pawlowski, Sylwin & Veerman, Joost & Bouzek, Karel & Fontananova, Enrica & di Profio, Gianluca & Velizarov, Svetlozar & Goulão Crespo, João & Nijmeijer, Kitty & Curcio, Efrem, 2018. "Progress and prospects in reverse electrodialysis for salinity gradient energy conversion and storage," Applied Energy, Elsevier, vol. 225(C), pages 290-331.
    10. Touati, Khaled & Usman, Haamid Sani & Mulligan, Catherine N. & Rahaman, Md. Saifur, 2020. "Energetic and economic feasibility of a combined membrane-based process for sustainable water and energy systems," Applied Energy, Elsevier, vol. 264(C).

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