IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i11p2500-d1158614.html
   My bibliography  Save this article

An Evolutionarily Based Type-2 Fuzzy-PID for Multi-Machine Power System Stabilization

Author

Listed:
  • Ye Wang

    (School of Electrical and Mechanical Engineering, Xuchang University, Xuchang 461000, China)

  • Zhaiaibai Ma

    (Mechatronics and Automotive Engineering College, Xuchang Vocational and Technical College, Xuchang 461000, China)

  • Mostafa M. Salah

    (Electrical Engineering Department, Future University in Egypt, Cairo 11835, Egypt)

  • Ahmed Shaker

    (Engineering Physics and Mathematics Department, Faculty of Engineering, Ain Shams University, Cairo 11535, Egypt)

Abstract

In this paper, the impact of one of the challenges of the power transmission system, namely three-phase short-circuits, on the stability of the system is discussed. This fault causes the speed change of the synchronous generators, and the control system needs to quickly zero this speed difference. This paper introduces a completely new and innovative method for power system stabilizer design. In the proposed method, there is a PID controller with a type-2 fuzzy compensator whose optimal parameter values are obtained using an improved virus colony search (VCS) algorithm at any time. In the simulation section, both transient short-circuits (timely operation of breakers and protection relays) and permanent short-circuits (failure of breakers and protection relays) are applied. For transient short-circuits, the three control systems of type-1 fuzzy-PID, type-2 fuzzy-PID, and optimized type-2 fuzzy-PID based on VCS for the nominal load and heavy load modes were compared in the simulations. Apart from the three control systems mentioned earlier, the response of a standalone PID controller was also evaluated in the context of the permanent short-circuit mode. According to the simulation results, the proposed method demonstrates superior performance and high efficiency. In contrast, the standalone PID exhibits divergence.

Suggested Citation

  • Ye Wang & Zhaiaibai Ma & Mostafa M. Salah & Ahmed Shaker, 2023. "An Evolutionarily Based Type-2 Fuzzy-PID for Multi-Machine Power System Stabilization," Mathematics, MDPI, vol. 11(11), pages 1-18, May.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:11:p:2500-:d:1158614
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/11/2500/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/11/2500/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Haifeng Huang & Mohammadamin Shirkhani & Jafar Tavoosi & Omar Mahmoud, 2022. "A New Intelligent Dynamic Control Method for a Class of Stochastic Nonlinear Systems," Mathematics, MDPI, vol. 10(9), pages 1-15, April.
    2. Taofeek Afolabi & Hooman Farzaneh, 2023. "Optimal Design and Operation of an Off-Grid Hybrid Renewable Energy System in Nigeria’s Rural Residential Area, Using Fuzzy Logic and Optimization Techniques," Sustainability, MDPI, vol. 15(4), pages 1-33, February.
    3. Rahmat Aazami & Omid Heydari & Jafar Tavoosi & Mohammadamin Shirkhani & Ardashir Mohammadzadeh & Amir Mosavi, 2022. "Optimal Control of an Energy-Storage System in a Microgrid for Reducing Wind-Power Fluctuations," Sustainability, MDPI, vol. 14(10), pages 1-14, May.
    4. Xinlan Guo & Mohammadamin Shirkhani & Emad M. Ahmed, 2022. "Machine-Learning-Based Improved Smith Predictive Control for MIMO Processes," Mathematics, MDPI, vol. 10(19), pages 1-19, October.
    5. Yan Cheng & Ben Niu & Xudong Zhao & Guangdeng Zong & Adil M. Ahmad, 2023. "Event-triggered adaptive decentralised control of interconnected nonlinear systems with Bouc-Wen hysteresis input," International Journal of Systems Science, Taylor & Francis Journals, vol. 54(6), pages 1275-1288, April.
    6. Si, Zhiyuan & Yang, Ming & Yu, Yixiao & Ding, Tingting, 2021. "Photovoltaic power forecast based on satellite images considering effects of solar position," Applied Energy, Elsevier, vol. 302(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Weijun Hu & Jiale Quan & Xianlong Ma & Mostafa M. Salah & Ahmed Shaker, 2023. "Analytical Design of Optimal Model Predictive Control and Its Application in Small-Scale Helicopters," Mathematics, MDPI, vol. 11(8), pages 1-15, April.
    2. Chan Gu & Encheng Chi & Chujia Guo & Mostafa M. Salah & Ahmed Shaker, 2023. "A New Self-Tuning Deep Neuro-Sliding Mode Control for Multi-Machine Power System Stabilizer," Mathematics, MDPI, vol. 11(7), pages 1-18, March.
    3. Lingqin Xia & Guang Chen & Tao Wu & Yu Gao & Ardashir Mohammadzadeh & Ebrahim Ghaderpour, 2022. "Optimal Intelligent Control for Doubly Fed Induction Generators," Mathematics, MDPI, vol. 11(1), pages 1-16, December.
    4. Xinlan Guo & Mohammadamin Shirkhani & Emad M. Ahmed, 2022. "Machine-Learning-Based Improved Smith Predictive Control for MIMO Processes," Mathematics, MDPI, vol. 10(19), pages 1-19, October.
    5. Xin Xu & Ahmed Shaker & Marwa S. Salem, 2022. "Automatic Control of a Mobile Manipulator Robot Based on Type-2 Fuzzy Sliding Mode Technique," Mathematics, MDPI, vol. 10(20), pages 1-18, October.
    6. Mahsa Dehghan Manshadi & Milad Mousavi & M. Soltani & Amir Mosavi & Levente Kovacs, 2022. "Deep Learning for Modeling an Offshore Hybrid Wind–Wave Energy System," Energies, MDPI, vol. 15(24), pages 1-16, December.
    7. Hai, Tao & Hussein Kadir, Dler & Ghanbari, Afshin, 2023. "Modeling the emission characteristics of the hydrogen-enriched natural gas engines by multi-output least-squares support vector regression: Comprehensive statistical and operating analyses," Energy, Elsevier, vol. 276(C).
    8. Ahmed Hussain Elmetwaly & Ramy Adel Younis & Abdelazeem Abdallah Abdelsalam & Ahmed Ibrahim Omar & Mohamed Metwally Mahmoud & Faisal Alsaif & Adel El-Shahat & Mohamed Attya Saad, 2023. "Modeling, Simulation, and Experimental Validation of a Novel MPPT for Hybrid Renewable Sources Integrated with UPQC: An Application of Jellyfish Search Optimizer," Sustainability, MDPI, vol. 15(6), pages 1-30, March.
    9. Jiabao Gu & Hui Wang & Wuquan Li & Ben Niu, 2022. "Adaptive State-Feedback Stabilization for Stochastic Nonlinear Systems with Time-Varying Powers and Unknown Covariance," Mathematics, MDPI, vol. 10(16), pages 1-16, August.
    10. Yaqiong Ding & Hanguang Jia & Yunong Zhang & Binbin Qiu, 2023. "High-Order Modeling, Zeroing Dynamics Control, and Perturbations Rejection for Non-Linear Double-Holding Water Tank," Mathematics, MDPI, vol. 11(13), pages 1-18, July.
    11. Libo Yang & Mei Guo & Ardashir Mohammadzadeh & Amir Mosavi, 2022. "Taylor Series-Based Fuzzy Model Predictive Control for Wheeled Robots," Mathematics, MDPI, vol. 10(14), pages 1-13, July.
    12. Paletta, Quentin & Arbod, Guillaume & Lasenby, Joan, 2023. "Omnivision forecasting: Combining satellite and sky images for improved deterministic and probabilistic intra-hour solar energy predictions," Applied Energy, Elsevier, vol. 336(C).
    13. Saeed Danyali & Omid Aghaei & Mohammadamin Shirkhani & Rahmat Aazami & Jafar Tavoosi & Ardashir Mohammadzadeh & Amir Mosavi, 2022. "A New Model Predictive Control Method for Buck-Boost Inverter-Based Photovoltaic Systems," Sustainability, MDPI, vol. 14(18), pages 1-14, September.
    14. Khanh Hieu Nguyen & Sung Hyun Kim, 2022. "Event-Triggered Non-PDC Filter Design of Fuzzy Markovian Jump Systems under Mismatch Phenomena," Mathematics, MDPI, vol. 10(16), pages 1-25, August.
    15. Yantao Wang & Yinhan Zhang & Xuesong Qi & Meiqi Wang & Xinyue Wang, 2023. "A Bi-Level Optimization Model for Virtual Power Plant Membership Selection Considering Load Time Series," Sustainability, MDPI, vol. 15(3), pages 1-15, January.
    16. Su, Qingyu & Chen, Cong & Huang, Xin & Li, Jian, 2022. "Interval TrendRank method for grid node importance assessment considering new energy," Applied Energy, Elsevier, vol. 324(C).
    17. Liu, Jingxuan & Zang, Haixiang & Cheng, Lilin & Ding, Tao & Wei, Zhinong & Sun, Guoqiang, 2023. "A Transformer-based multimodal-learning framework using sky images for ultra-short-term solar irradiance forecasting," Applied Energy, Elsevier, vol. 342(C).
    18. Ruitao Wang & Hui Wang & Wuquan Li & Ben Niu, 2022. "Output Tracking Control of Random Nonlinear Time-Varying Systems," Mathematics, MDPI, vol. 10(14), pages 1-13, July.
    19. Zhi, Yuan & Yang, Xudong, 2023. "Scenario-based multi-objective optimization strategy for rural PV-battery systems," Applied Energy, Elsevier, vol. 345(C).
    20. Wentao Ma & Lihong Qiu & Fengyuan Sun & Sherif S. M. Ghoneim & Jiandong Duan, 2022. "PV Power Forecasting Based on Relevance Vector Machine with Sparrow Search Algorithm Considering Seasonal Distribution and Weather Type," Energies, MDPI, vol. 15(14), pages 1-24, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:11:y:2023:i:11:p:2500-:d:1158614. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.