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Dynamic Load Frequency Regulation in Two Area Power Systems via Pelican-Optimized PID Control.

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Title: Dynamic Load Frequency Regulation in Two Area Power Systems via Pelican-Optimized PID Control.
Authors: Pandey, Manish Kumar1 manish_phdeed@nith.ac.in, Mahia, Ram Niwash1 ram@nith.ac.in
Source: Serbian Journal of Electrical Engineering. Jun2026, Vol. 23 Issue 2, p203-226. 24p.
Subjects: PID controllers, Interconnected power systems, Metaheuristic algorithms, Electric power system control
Abstract: This article presents Pelican Optimization Algorithm (POA) for Load Frequency Control (LFC) in two area interconnected power systems. Extensive simulations in MATLAB indicate that the POA surpasses numerous established metaheuristic optimization algorithms, involving the Grey Wolf Optimizer (GWO), Hippopotamus Optimization Algorithm (HOA), Salp Swarm Algorithm (SSA), Particle Swarm Optimization (PSO), Teaching-Learning Optimization Algorithm (TLOA) and Whale Optimization Algorithm (WOA) regarding the mitigation of frequency deviations and improvement of dynamic response. The robustness of the POA based LFC is validated under scenarios of random load disturbances, varying system parameters, typical power system nonlinearities like generation rate constraints (GRC) and governor deadband (GDB), and with renewable energy sources. The studies highlighted in the article demonstrate superior adaptability and effectiveness of POA to optimally tune the gains of PID controller. The statistical analysis demonstrate that the proposed POA achieves convergence to the global optimum with reduced execution time (~12% less than the second best HOA) and exhibits lower mean (~15.2% less than the second best SSA) and standard deviation (~3.09% less than the second best HOA) over multiple independent runs. Stability analysis using Bode plots confirms that the proposed control strategy maintains adequate stability margins. [ABSTRACT FROM AUTHOR]
Copyright of Serbian Journal of Electrical Engineering is the property of Serbian Journal of Electrical Engineering 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.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 195752612
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  Data: Dynamic Load Frequency Regulation in Two Area Power Systems via Pelican-Optimized PID Control.
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  Data: <searchLink fieldCode="AR" term="%22Pandey%2C+Manish+Kumar%22">Pandey, Manish Kumar</searchLink><relatesTo>1</relatesTo><i> manish_phdeed@nith.ac.in</i><br /><searchLink fieldCode="AR" term="%22Mahia%2C+Ram+Niwash%22">Mahia, Ram Niwash</searchLink><relatesTo>1</relatesTo><i> ram@nith.ac.in</i>
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  Data: <searchLink fieldCode="JN" term="%22Serbian+Journal+of+Electrical+Engineering%22">Serbian Journal of Electrical Engineering</searchLink>. Jun2026, Vol. 23 Issue 2, p203-226. 24p.
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  Data: <searchLink fieldCode="DE" term="%22PID+controllers%22">PID controllers</searchLink><br /><searchLink fieldCode="DE" term="%22Interconnected+power+systems%22">Interconnected power systems</searchLink><br /><searchLink fieldCode="DE" term="%22Metaheuristic+algorithms%22">Metaheuristic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Electric+power+system+control%22">Electric power system control</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This article presents Pelican Optimization Algorithm (POA) for Load Frequency Control (LFC) in two area interconnected power systems. Extensive simulations in MATLAB indicate that the POA surpasses numerous established metaheuristic optimization algorithms, involving the Grey Wolf Optimizer (GWO), Hippopotamus Optimization Algorithm (HOA), Salp Swarm Algorithm (SSA), Particle Swarm Optimization (PSO), Teaching-Learning Optimization Algorithm (TLOA) and Whale Optimization Algorithm (WOA) regarding the mitigation of frequency deviations and improvement of dynamic response. The robustness of the POA based LFC is validated under scenarios of random load disturbances, varying system parameters, typical power system nonlinearities like generation rate constraints (GRC) and governor deadband (GDB), and with renewable energy sources. The studies highlighted in the article demonstrate superior adaptability and effectiveness of POA to optimally tune the gains of PID controller. The statistical analysis demonstrate that the proposed POA achieves convergence to the global optimum with reduced execution time (~12% less than the second best HOA) and exhibits lower mean (~15.2% less than the second best SSA) and standard deviation (~3.09% less than the second best HOA) over multiple independent runs. Stability analysis using Bode plots confirms that the proposed control strategy maintains adequate stability margins. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Serbian Journal of Electrical Engineering is the property of Serbian Journal of Electrical Engineering 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: 10.2298/SJEE2602203P
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 24
        StartPage: 203
    Subjects:
      – SubjectFull: PID controllers
        Type: general
      – SubjectFull: Interconnected power systems
        Type: general
      – SubjectFull: Metaheuristic algorithms
        Type: general
      – SubjectFull: Electric power system control
        Type: general
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      – TitleFull: Dynamic Load Frequency Regulation in Two Area Power Systems via Pelican-Optimized PID Control.
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              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
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