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MTDC Grids: A Metaheuristic Solution for Nonlinear Control

Author

Listed:
  • Muhammad Zain Yousaf

    (School of Electrical Engineering, Guangxi University, Nanning 530600, China)

  • Ali Raza

    (Department of Electrical Engineering, University of Engineering and Technology, Lahore 54000, Pakistan)

  • Ghulam Abbas

    (Department of Electrical Engineering, University of Lahore, Lahore 54000, Pakistan)

  • Nasim Ullah

    (Department of Electrical Engineering, College of Engineering, Taif University, Taif 21944, Saudi Arabia)

  • Ahmad Aziz Al-Ahmadi

    (Department of Electrical Engineering, College of Engineering, Taif University, Taif 21944, Saudi Arabia)

  • Abdul Rehman Yasin

    (Department of Electrical Engineering, University of Lahore, Lahore 54000, Pakistan)

  • Mohsin Jamil

    (Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John’s, NL A1B 3X5, Canada)

Abstract

This scientific paper aims to increase the voltage source converter (VSC) control efficiency in a multi-terminal high voltage direct current (MTDC) network during dynamic operations. In the proposed study, the Mayfly algorithm (MA) is used to modify the control parameters of VSC stations. Traditional strategies that modify VSC control settings using approximate linear models fail to produce optimal results because VSCs are nonlinear characteristics of the MTDC system. Particle swarm optimization (PSO) may produce optimal outcomes, but it is prone to becoming stuck in a local optimum. To modify the proportional-integral (P.I.) control parameters of the VSC station, the Mayfly algorithm, a modified form of PSO, is used. The suggested algorithm’s objective function simultaneously optimizes both the outer and inner control layers. A four-terminal MTDC test system is developed in PSCAD/EMTDC to assess the benefits of the proposed algorithm. For VSCs, a comparison of classical, PSO, and proposed MA-based tuned parameters is carried out. The integral of time multiplied by absolute error (ITAE) criterion is used to compare the performance of classical, PSO, and a proposed algorithm for VSC controller parameters/gains. With an ITAE value of 6.8521 × 10 −6 , the MA-based proposed algorithm computes the optimal values and outperforms its predecessor to adjust the VSCs controller gains. For (i) wind farm power variation, (ii) AC grid load demand variation, and (iii) ultimate permanent VSC disconnection, steady-state and dynamic performances are evaluated. According to the results, the proposed algorithm based MTDC system performs well during transients.

Suggested Citation

  • Muhammad Zain Yousaf & Ali Raza & Ghulam Abbas & Nasim Ullah & Ahmad Aziz Al-Ahmadi & Abdul Rehman Yasin & Mohsin Jamil, 2022. "MTDC Grids: A Metaheuristic Solution for Nonlinear Control," Energies, MDPI, vol. 15(12), pages 1-24, June.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:12:p:4263-:d:835494
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    References listed on IDEAS

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    1. Chi, Fang'ai & Xu, Ying, 2022. "Building performance optimization for university dormitory through integration of digital gene map into multi-objective genetic algorithm," Applied Energy, Elsevier, vol. 307(C).
    2. Syed F Faisal & Abdul R Beig & Sunil Thomas, 2020. "Time Domain Particle Swarm Optimization of PI Controllers for Bidirectional VSC HVDC Light System," Energies, MDPI, vol. 13(4), pages 1-15, February.
    3. Icaza, Daniel & Borge-Diez, David & Galindo, Santiago Pulla, 2022. "Analysis and proposal of energy planning and renewable energy plans in South America: Case study of Ecuador," Renewable Energy, Elsevier, vol. 182(C), pages 314-342.
    4. Muhammad Ahmad Khan & Xiaocong Li & Muhammad Zain Yousaf & Ali Mustafa & Mingshuo Wei, 2021. "Metaheuristic Based Solution for the Non‐Linear Controller of the Multiterminal High‐Voltage Direct Current Networks," Energies, MDPI, vol. 14(6), pages 1-20, March.
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    Cited by:

    1. Rodolfo Araneo & Salvatore Celozzi & Stefano Lauria & Erika Stracqualursi & Gianfranco Di Lorenzo & Marco Graziani, 2022. "Recent Trends in Power Systems Modeling and Analysis," Energies, MDPI, vol. 15(23), pages 1-7, December.

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