A novel MPC-based cascaded control for multi-area smart grids: Tackling renewable energy and EV integration challenges.

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Title: A novel MPC-based cascaded control for multi-area smart grids: Tackling renewable energy and EV integration challenges.
Authors: Tolba, Muhammad S.1 (AUTHOR) g202313790@kfupm.edu.sa, Gulzar, Muhammad Majid1,2,3 (AUTHOR) muhammad.gulzar@kfupm.edu.sa, Arishi, Ali4,5 (AUTHOR) awaje@kku.edu.sa, Soliman, Mohamed1 (AUTHOR) g202215300@kfupm.edu.sa, Murtaza, Ali Faisal6 (AUTHOR) a.murtaza@qu.edu.sa
Source: ISA Transactions. Oct2025, Vol. 165, p143-169. 27p.
Subjects: Renewable energy sources, Electric vehicles, Smart power grids, Optimization algorithms, Cascade control, Feedback control systems, Stability of linear systems
Abstract: This paper presents an advanced cascaded control scheme for load frequency regulation in multi-area power systems incorporating renewable energy sources (RES) and electric vehicles (EVs). The proposed design (Model predictive control cascaded with one plus proportional-integral control cascaded with tilt control in parallel with one plus fractional-order integral derivative controller (MPC-((1+PI)-(T+(1+I λ D μ)))) combines predictive, tilt, and fractional-order dynamics to improve adaptability and robustness under uncertainties. Controller parameters are tuned using the Lyrebird Optimization Algorithm (LOA), ensuring fast convergence and effective global search. Simulation results under varying operational conditions, including nonlinearity effects such as Generation Rate Constraints (GRC), Governor Dead Band (GDB), and Communication Time Delays (CTD), confirm the controller's superiority. It achieves a 96.4 % ITAE reduction, 98.6 % undershoot mitigation, and a settling time of just 5.8 s outperforming existing benchmark strategies (GOA: PDf+(0.75+PI), CBOA: PI-PD, JSA: PI, and ARA: 1+PID). • A hybrid MPC–fractional order cascaded controller is developed for smart grid frequency regulation. • Lyrebird Optimization Algorithm is used to fine-tune controller gains for robustness and precision. • The proposed method outperforms GOA, CBOA, JSA, and ARA controllers in ITAE and dynamic response. • Robustness is validated under load changes, nonlinearities, and system uncertainties. • Stability is ensured through detailed analysis under high RES penetration. [ABSTRACT FROM AUTHOR]
Copyright of ISA Transactions is the property of Elsevier B.V. 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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Items – Name: Title
  Label: Title
  Group: Ti
  Data: A novel MPC-based cascaded control for multi-area smart grids: Tackling renewable energy and EV integration challenges.
– Name: Author
  Label: Authors
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  Data: <searchLink fieldCode="AR" term="%22Tolba%2C+Muhammad+S%2E%22">Tolba, Muhammad S.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> g202313790@kfupm.edu.sa</i><br /><searchLink fieldCode="AR" term="%22Gulzar%2C+Muhammad+Majid%22">Gulzar, Muhammad Majid</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> muhammad.gulzar@kfupm.edu.sa</i><br /><searchLink fieldCode="AR" term="%22Arishi%2C+Ali%22">Arishi, Ali</searchLink><relatesTo>4,5</relatesTo> (AUTHOR)<i> awaje@kku.edu.sa</i><br /><searchLink fieldCode="AR" term="%22Soliman%2C+Mohamed%22">Soliman, Mohamed</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> g202215300@kfupm.edu.sa</i><br /><searchLink fieldCode="AR" term="%22Murtaza%2C+Ali+Faisal%22">Murtaza, Ali Faisal</searchLink><relatesTo>6</relatesTo> (AUTHOR)<i> a.murtaza@qu.edu.sa</i>
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  Data: <searchLink fieldCode="JN" term="%22ISA+Transactions%22">ISA Transactions</searchLink>. Oct2025, Vol. 165, p143-169. 27p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Renewable+energy+sources%22">Renewable energy sources</searchLink><br /><searchLink fieldCode="DE" term="%22Electric+vehicles%22">Electric vehicles</searchLink><br /><searchLink fieldCode="DE" term="%22Smart+power+grids%22">Smart power grids</searchLink><br /><searchLink fieldCode="DE" term="%22Optimization+algorithms%22">Optimization algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Cascade+control%22">Cascade control</searchLink><br /><searchLink fieldCode="DE" term="%22Feedback+control+systems%22">Feedback control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Stability+of+linear+systems%22">Stability of linear systems</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This paper presents an advanced cascaded control scheme for load frequency regulation in multi-area power systems incorporating renewable energy sources (RES) and electric vehicles (EVs). The proposed design (Model predictive control cascaded with one plus proportional-integral control cascaded with tilt control in parallel with one plus fractional-order integral derivative controller (MPC-((1+PI)-(T+(1+I λ D μ)))) combines predictive, tilt, and fractional-order dynamics to improve adaptability and robustness under uncertainties. Controller parameters are tuned using the Lyrebird Optimization Algorithm (LOA), ensuring fast convergence and effective global search. Simulation results under varying operational conditions, including nonlinearity effects such as Generation Rate Constraints (GRC), Governor Dead Band (GDB), and Communication Time Delays (CTD), confirm the controller's superiority. It achieves a 96.4 % ITAE reduction, 98.6 % undershoot mitigation, and a settling time of just 5.8 s outperforming existing benchmark strategies (GOA: PDf+(0.75+PI), CBOA: PI-PD, JSA: PI, and ARA: 1+PID). • A hybrid MPC–fractional order cascaded controller is developed for smart grid frequency regulation. • Lyrebird Optimization Algorithm is used to fine-tune controller gains for robustness and precision. • The proposed method outperforms GOA, CBOA, JSA, and ARA controllers in ITAE and dynamic response. • Robustness is validated under load changes, nonlinearities, and system uncertainties. • Stability is ensured through detailed analysis under high RES penetration. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of ISA Transactions is the property of Elsevier B.V. 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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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.isatra.2025.06.024
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 27
        StartPage: 143
    Subjects:
      – SubjectFull: Renewable energy sources
        Type: general
      – SubjectFull: Electric vehicles
        Type: general
      – SubjectFull: Smart power grids
        Type: general
      – SubjectFull: Optimization algorithms
        Type: general
      – SubjectFull: Cascade control
        Type: general
      – SubjectFull: Feedback control systems
        Type: general
      – SubjectFull: Stability of linear systems
        Type: general
    Titles:
      – TitleFull: A novel MPC-based cascaded control for multi-area smart grids: Tackling renewable energy and EV integration challenges.
        Type: main
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      – PersonEntity:
          Name:
            NameFull: Tolba, Muhammad S.
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            NameFull: Gulzar, Muhammad Majid
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            NameFull: Arishi, Ali
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            NameFull: Soliman, Mohamed
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            NameFull: Murtaza, Ali Faisal
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          Dates:
            – D: 01
              M: 10
              Text: Oct2025
              Type: published
              Y: 2025
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              Value: 00190578
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              Value: 165
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