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Enhanced Stability and Performance of the Tidal Energy Conversion System Using Adaptive Optimum Relation-Based MPPT Algorithms.

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Title: Enhanced Stability and Performance of the Tidal Energy Conversion System Using Adaptive Optimum Relation-Based MPPT Algorithms.
Authors: Ramli, Noor Lina1 (AUTHOR), Mohamed, Mohd Rusllim1 (AUTHOR) rusllim@umpsa.edu.my, Ibrahim, Wan Ismail1 (AUTHOR), Kurukuri, Peddakapu2 (AUTHOR)
Source: Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ). Nov2025, Vol. 50 Issue 21, p18037-18051. 15p.
Subjects: Tidal power, Maximum power point trackers, Optimization algorithms, Resource allocation, Energy conversion, Water power, Energy harvesting
Abstract: Tidal energy is a highly predictable and sustainable resource with significant potential to meet global energy demands. This study proposes an adaptive optimum relation-based (A-ORB) maximum power point tracking algorithm to enhance the efficiency, stability, and adaptability of tidal energy conversion systems. The A-ORB algorithm integrates the optimum relation-based (ORB) approach with Hill Climb Search (HCS), along with an adaptive gain adjustment mechanism that dynamically tunes the parameter K based on power variation (ΔP). This hybrid strategy enables faster convergence, improved responsiveness to tidal fluctuations, and reduced power oscillations. The novelty of the proposed method lies in the combination of ORB and HCS with adaptive gain tuning, which collectively improves MPPT performance under variable tidal conditions. Simulation results show that A-ORB outperforms conventional techniques such as small step perturb and observe (SS-PO), small step incremental conductance (SS-InC), and bio-inspired particle swarm optimization (BI-PSO) in both tracking accuracy and power output. Specifically, A-ORB achieves a convergence time of 0.32 s and a maximum power output of 4833 W, compared to 4658 W (0.41 s) for SS-PO, 4561 W (0.5 s) for SS-InC, and 4699 W (0.37 s) for BI-PSO. Moreover, A-ORB exhibits significantly lower power oscillations (3.9 W) compared to 17.88 W (SS-PO), 21.96 W (SS-InC), and 10.4 W (BI-PSO). These findings demonstrate the potential of A-ORB to enhance MPPT efficiency, reduce transient response time, and improve adaptability in dynamic tidal energy environments. [ABSTRACT FROM AUTHOR]
Copyright of Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ) is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Enhanced Stability and Performance of the Tidal Energy Conversion System Using Adaptive Optimum Relation-Based MPPT Algorithms.
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  Data: <searchLink fieldCode="DE" term="%22Tidal+power%22">Tidal power</searchLink><br /><searchLink fieldCode="DE" term="%22Maximum+power+point+trackers%22">Maximum power point trackers</searchLink><br /><searchLink fieldCode="DE" term="%22Optimization+algorithms%22">Optimization algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Resource+allocation%22">Resource allocation</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+conversion%22">Energy conversion</searchLink><br /><searchLink fieldCode="DE" term="%22Water+power%22">Water power</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+harvesting%22">Energy harvesting</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: Tidal energy is a highly predictable and sustainable resource with significant potential to meet global energy demands. This study proposes an adaptive optimum relation-based (A-ORB) maximum power point tracking algorithm to enhance the efficiency, stability, and adaptability of tidal energy conversion systems. The A-ORB algorithm integrates the optimum relation-based (ORB) approach with Hill Climb Search (HCS), along with an adaptive gain adjustment mechanism that dynamically tunes the parameter K based on power variation (ΔP). This hybrid strategy enables faster convergence, improved responsiveness to tidal fluctuations, and reduced power oscillations. The novelty of the proposed method lies in the combination of ORB and HCS with adaptive gain tuning, which collectively improves MPPT performance under variable tidal conditions. Simulation results show that A-ORB outperforms conventional techniques such as small step perturb and observe (SS-PO), small step incremental conductance (SS-InC), and bio-inspired particle swarm optimization (BI-PSO) in both tracking accuracy and power output. Specifically, A-ORB achieves a convergence time of 0.32 s and a maximum power output of 4833 W, compared to 4658 W (0.41 s) for SS-PO, 4561 W (0.5 s) for SS-InC, and 4699 W (0.37 s) for BI-PSO. Moreover, A-ORB exhibits significantly lower power oscillations (3.9 W) compared to 17.88 W (SS-PO), 21.96 W (SS-InC), and 10.4 W (BI-PSO). These findings demonstrate the potential of A-ORB to enhance MPPT efficiency, reduce transient response time, and improve adaptability in dynamic tidal energy environments. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ) is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s13369-025-10265-z
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        Text: English
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        StartPage: 18037
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      – SubjectFull: Tidal power
        Type: general
      – SubjectFull: Maximum power point trackers
        Type: general
      – SubjectFull: Optimization algorithms
        Type: general
      – SubjectFull: Resource allocation
        Type: general
      – SubjectFull: Energy conversion
        Type: general
      – SubjectFull: Water power
        Type: general
      – SubjectFull: Energy harvesting
        Type: general
    Titles:
      – TitleFull: Enhanced Stability and Performance of the Tidal Energy Conversion System Using Adaptive Optimum Relation-Based MPPT Algorithms.
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            NameFull: Ramli, Noor Lina
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            NameFull: Mohamed, Mohd Rusllim
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            NameFull: Ibrahim, Wan Ismail
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            – D: 01
              M: 11
              Text: Nov2025
              Type: published
              Y: 2025
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