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Optimal design of a scaled-up PRO system using swarm intelligence approach

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Abstract

In this study, the pressure-retarded osmosis (PRO) process is optimized using Harris hawks optimization (HHO)-based maximum power point tracking (MPPT) technology. To make the practical implementation of salinity-gradient-based energy harvesting using PRO feasible, MPPT is envisaged to play a substantial role. Therefore, this study focuses on the development of a novel MPPT controller using swarm intelligence. The HHO algorithm is the latest approach that mimics the unique chasing strategy of Harris hawks in nature. To test the cost effectiveness of the proposed method, two case studies with various operational scenarios are presented. Compared with the performance of selected well-known and recent approaches, such as perturb & observe, incremental mass resistance, and whale optimization algorithm techniques, that of the proposed metaheuristic-based MPPT technique is found to be highly competitive. Results also show that the proposed algorithm can overcome other methods’ limitations, such as low tracking efficiency; low robustness when encountered in various operational conditions, including temperature and salinity; and steady-state oscillations. Furthermore, the proposed MPPT strategy is suitable for use in other fields of renewable energy harvesting.

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Acknowledgements

This work was supported in part by National Natural Science Foundation of China (Grant Nos. 61933010, 61803305), Shaanxi Natural Science Foundation (Grant Nos. 2020JQ-223, 2019JZ-08, 2020JQ-213), and Aeronautical Science Foundation of China (Grant No. 201905053005).

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Authors and Affiliations

  1. School of Power and Energy, Northwestern Polytechnical University, Xi’an, 710129, China

    Yingxue Chen

  2. School of Automatic, Northwestern Polytechnical University, Xi’an, 710129, China

    Zhongke Shi & Bin Xu

  3. School of Engineering and Materials Science, Queen Mary University of London, London, E1 4NS, UK

    Mohammad Hasan Shaheed

Authors
  1. Yingxue Chen
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  2. Zhongke Shi
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  3. Bin Xu
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  4. Mohammad Hasan Shaheed
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Correspondence to Yingxue Chen.

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Chen, Y., Shi, Z., Xu, B. et al. Optimal design of a scaled-up PRO system using swarm intelligence approach. Sci. China Inf. Sci. 64, 222203 (2021). https://doi.org/10.1007/s11432-020-3110-x

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  • DOI: https://doi.org/10.1007/s11432-020-3110-x

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