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A Novel Solution for Solving the Frequency Regulation Problem of Renewable Interlinked Power System Using Fusion of AI

Author

Listed:
  • Mohammed Ozayr Abdul Kader

    (Department of Electrical Power Engineering, Durban University of Technology, Durban 4001, South Africa)

  • Kayode Timothy Akindeji

    (Department of Electrical Power Engineering, Durban University of Technology, Durban 4001, South Africa)

  • Gulshan Sharma

    (Department of Electrical Engineering Technology, University of Johannesburg, Johannesburg 2006, South Africa)

Abstract

The requirement for clean energy has increased drastically over the years due to the emission of CO 2 and the degrading of the environment by introducing Renewable Energy Systems (RES) into the existing power grid. While these systems are a positive change, they come at a cost, with some issues relating to the stability of the grid and feasibility. Hence, this research paper closely investigates the modeling and interlinking of photovoltaic (PV)-based solar power and Double-Fed Induction Generator (DFIG)-based wind turbines with the conventional power systems. RES has been known to contribute to a highly non-linear system and complexity. To return the power systems to their original state after a load disturbance, a novel control technique based on the fractional-order Type-2 Fuzzy logic system, well developed via particle swarm optimization (PSO), has been utilized for solving the frequency control problem of a renewable interlinked power system. The efficacy of the proposed technique is validated for various possible operating conditions and the system results are compared with some of the recent methods with and without including non-linearity, and the performance of the controllers is superimposed on frequency/time graphs for ease of understanding to show the benefits of the proposed research work.

Suggested Citation

  • Mohammed Ozayr Abdul Kader & Kayode Timothy Akindeji & Gulshan Sharma, 2022. "A Novel Solution for Solving the Frequency Regulation Problem of Renewable Interlinked Power System Using Fusion of AI," Energies, MDPI, vol. 15(9), pages 1-19, May.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:3376-:d:809333
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    Citations

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    Cited by:

    1. Xinghua Liu & Siwei Qiao & Zhiwei Liu, 2023. "A Survey on Load Frequency Control of Multi-Area Power Systems: Recent Challenges and Strategies," Energies, MDPI, vol. 16(5), pages 1-22, February.
    2. Naser Azim Mohseni & Navid Bayati, 2022. "Robust Multi-Objective H 2 /H ∞ Load Frequency Control of Multi-Area Interconnected Power Systems Using TS Fuzzy Modeling by Considering Delay and Uncertainty," Energies, MDPI, vol. 15(15), pages 1-18, July.
    3. Nebiyu Kedir & Phuong H. D. Nguyen & Citlaly Pérez & Pedro Ponce & Aminah Robinson Fayek, 2023. "Systematic Literature Review on Fuzzy Hybrid Methods in Photovoltaic Solar Energy: Opportunities, Challenges, and Guidance for Implementation," Energies, MDPI, vol. 16(9), pages 1-38, April.

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