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Enhanced and speedy energy extraction from a scaled-up pressure retarded osmosis process with a whale optimization based maximum power point tracking

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  • Chen, Yingxue
  • Vepa, Ranjan
  • Shaheed, Mohammad Hasan

Abstract

This paper proposes a novel maximum power point tracking scheme for efficient and speedy extraction of maximum power from a pressure retarded osmosis process subject to rapid salinity variation. The scheme is designed using the Whale Optimization with Differential Evolution algorithm, a nature-inspired metaheuristic technique. The algorithm has facilitated the developed maximum power point tracking controller with features that have helped overcome limitations such as lower tracking efficiency and steady state oscillations as encountered in the conventional methods. Previously, a number of widely used algorithms including perturb & observe, incremental mass resistance and mass feedback controller were used to design maximum power point control schemes for a PRO process to reduce power loss due to rapid salinity variation. However, in using these techniques, a trade-off between the oscillations and the respond time was required to adjust the operation. The proposed scheme is used to solve this problem and is implemented in simulation on a scaled-up PRO system. The performance of the scheme is compared with some popularly used maximum power point tracking controllers. It is observed from results that the proposed method not only outperforms other widely used methods but is also more robust.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:153:y:2018:i:c:p:618-627
    DOI: 10.1016/j.energy.2018.04.052
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    References listed on IDEAS

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    1. Oliva, Diego & Abd El Aziz, Mohamed & Ella Hassanien, Aboul, 2017. "Parameter estimation of photovoltaic cells using an improved chaotic whale optimization algorithm," Applied Energy, Elsevier, vol. 200(C), pages 141-154.
    2. Nagy, Endre & Dudás, József & Hegedüs, Imre, 2016. "Improvement of the energy generation by pressure retarded osmosis," Energy, Elsevier, vol. 116(P2), pages 1323-1333.
    3. 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.
    4. Altaee, Ali & Millar, Graeme J. & Zaragoza, Guillermo, 2016. "Integration and optimization of pressure retarded osmosis with reverse osmosis for power generation and high efficiency desalination," Energy, Elsevier, vol. 103(C), pages 110-118.
    5. Touati, Khaled & Tadeo, Fernando & Elfil, Hamza, 2017. "Osmotic energy recovery from Reverse Osmosis using two-stage Pressure Retarded Osmosis," Energy, Elsevier, vol. 132(C), pages 213-224.
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    Cited by:

    1. 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.
    2. Maisonneuve, Jonathan & Chintalacheruvu, Sanjana, 2019. "Increasing osmotic power and energy with maximum power point tracking," Applied Energy, Elsevier, vol. 238(C), pages 683-695.
    3. 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.

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