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Application of Neuro-Fuzzy Controller to Replace SMIB and Interconnected Multi-Machine Power System Stabilizers

Author

Listed:
  • Aliyu Sabo

    (Advanced Lightning and Power Energy System (ALPER), Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia
    Department of Electrical and Electronic Engineering, Nigerian Defence Academy, P.M.B. 2109 Kaduna, Nigeria)

  • Noor Izzri Abdul Wahab

    (Advanced Lightning and Power Energy System (ALPER), Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia)

  • Mohammad Lutfi Othman

    (Advanced Lightning and Power Energy System (ALPER), Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia)

  • Mai Zurwatul Ahlam Mohd Jaffar

    (Department of Mathematics, Faculty of Science, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia)

  • Hakan Acikgoz

    (Department of Electrical Electronics Engineering, Faculty of Engineering and Natural Sciences, Gaziantep Islam Science and Technology University, 27010 Gaziantep, Turkey)

  • Hamzeh Beiranvand

    (Department of Electrical Engineering, Lorestan University, Khoramabad 68151-44316, Iran)

Abstract

In this research, an effective application and performance assessment of the Neuro-Fuzzy Controller (NFC) damping controller is designed to replace a single machine infinite bus (SMIB) power system stabilizer (PSS), and coordinated multi PSSs in large interconnected power systems are presented. The limitation of the conventional PSSs on SMIB and interconnected multi-machine test power systems are exposed and disclosed by the proposed NFC stabilizer. The NFC is a nonlinear robust controller which does not require a mathematical model of the test power system to be controlled, unlike the conventional PSSs’ damping controller. The Proposed NFC is designed to improve the stability of SMIB, an interconnected IEEE 3-machine, 9-bus power system, and an interconnected two-area 10-machine system of 39-bus New England IEEE test power system under multiple operating conditions. The proposed NFC damping controller performance is compared with the conventional PSS damping controller to confirm the capability of the proposed stabilizer and realize an improved system stability enhancement. The conventional PSSs’ design problem is transformed into an optimization problem where an eigenvalue-based objective function is developed and applied to design the SMIB-PSS and the interconnected multi-machine PSSs. The time-domain phasor simulation was done in the SIMULINK domain, and the simulation results show that the transient responses of the system rise time, settling time, peak time, and peak magnitude were all impressively improved by an acceptable amount for all the test system with the proposed NFC stabilizer. Thus, the NFC was able to effectively control the LFOs and produce an enhanced performance compared to the conventional PSS damping controller. Similarly, the result validates the effectiveness of the proposed NFC damping controller for LFO control, which demonstrates more robustness and efficiency than the classical PSS damping controller. Therefore, the application and performance of the NFC has appeared as a promising method and can be considered as a remarkable method for the optimal design damping stabilizer for small and large power systems.

Suggested Citation

  • Aliyu Sabo & Noor Izzri Abdul Wahab & Mohammad Lutfi Othman & Mai Zurwatul Ahlam Mohd Jaffar & Hakan Acikgoz & Hamzeh Beiranvand, 2020. "Application of Neuro-Fuzzy Controller to Replace SMIB and Interconnected Multi-Machine Power System Stabilizers," Sustainability, MDPI, vol. 12(22), pages 1-42, November.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:22:p:9591-:d:446693
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    References listed on IDEAS

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    1. Aliyu Sabo & Theophilus Ebuka Odoh & Hossien Shahinzadeh & Zahra Azimi & Majid Moazzami, 2023. "Implementing Optimization Techniques in PSS Design for Multi-Machine Smart Power Systems: A Comparative Study," Energies, MDPI, vol. 16(5), pages 1-25, March.

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