IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i18p13892-d1242678.html
   My bibliography  Save this article

Frequency Stability Enhancement Using Differential-Evolution- and Genetic-Algorithm-Optimized Intelligent Controllers in Multiple Virtual Synchronous Machine Systems

Author

Listed:
  • Solomon Feleke

    (Department of Electrical and Computer Engineering, Debre Berhan University, Debre Berhan 445, Ethiopia)

  • Balamurali Pydi

    (Department of Electrical & Electronics Engineering, Aditya Institute of Technology & Management (A), Tekkali 532201, AP, India)

  • Raavi Satish

    (Department of Electrical & Electronics Engineering, Anil Neerukonda Institute of Technology and Science (A), Visakhapatnam 531162, AP, India)

  • Hossam Kotb

    (Department of Electrical Power and Machines, Faculty of Engineering, Alexandria University, Alexandria 21544, Egypt)

  • Mohammed Alenezi

    (Wolfson Centre for Magnetics, School of Engineering, Cardiff University, Cardiff CF24 3AA, Wales, UK)

  • Mokhtar Shouran

    (Engineering and Information Technology Research Center (EITRC), Bani Walid, Libya
    Department of Control Engineering, College of Electronics Technology, Bani Walid, Libya)

Abstract

In this paper, multiple virtual synchronous machines ( VISMAs ) with fuzzy proportional integral derivative (FPID) controllers optimized by differential evolution (DE) are proposed to maintain frequency stability in the grid in the presence of renewable penetration, such as wind and solar photovoltaic (PV) systems, residential loads, and industrial loads, by reducing the area control error in the objective function. Simulations are conducted using MATLAB/Simulink, and in the optimization process, the integral of the time-weighted absolute error ( ITAE ) is used as the objective function. In the work to obtain optimized values of renewable energy sources (RESs), fuzzy membership functions, controller gain parameters, and loads for system modeling, differential evolution and genetic algorithm (GA) methods are applied and the results were compared. It was shown that better results were achieved while FPID controllers were optimized by DE in the presence of multiple VISMAs than DE in the presence of single VISMAs and GA in multiple VISMAs . Moreover, the study is compared to integral control methods in which, compared to all controllers, the proposed controller reduces undershoot by 0.0674 Hz more than a single VISMAs , in which it is improved approximately by 97.82%. Similarly, the proposed controller improves the system settling time, rise time, and overshoot by more than 99.5% compared to the classical integral controller. To examine the robust operation of the system under the proposed controller, the system was run under a wide range of disturbances and uncertainties using random load perturbation of ± 20%, in which the proposed controller retains the system frequency by reducing or damping the system oscillation.

Suggested Citation

  • Solomon Feleke & Balamurali Pydi & Raavi Satish & Hossam Kotb & Mohammed Alenezi & Mokhtar Shouran, 2023. "Frequency Stability Enhancement Using Differential-Evolution- and Genetic-Algorithm-Optimized Intelligent Controllers in Multiple Virtual Synchronous Machine Systems," Sustainability, MDPI, vol. 15(18), pages 1-18, September.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13892-:d:1242678
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/18/13892/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/18/13892/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gaber Magdy & Abualkasim Bakeer & Morsy Nour & Eduard Petlenkov, 2020. "A New Virtual Synchronous Generator Design Based on the SMES System for Frequency Stability of Low-Inertia Power Grids," Energies, MDPI, vol. 13(21), pages 1-17, October.
    2. Guanfeng Zhang & Junyou Yang & Haixin Wang & Jia Cui, 2020. "Presynchronous Grid-Connection Strategy of Virtual Synchronous Generator Based on Virtual Impedance," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-9, November.
    3. Huiyu Miao & Fei Mei & Yun Yang & Hongfei Chen & Jianyong Zheng, 2019. "A Comprehensive VSM Control Strategy Designed for Unbalanced Grids," Energies, MDPI, vol. 12(6), pages 1-17, March.
    4. Solomon Feleke & Raavi Satish & Balamurali Pydi & Degarege Anteneh & Almoataz Y. Abdelaziz & Adel El-Shahat, 2023. "Damping of Frequency and Power System Oscillations with DFIG Wind Turbine and DE Optimization," Sustainability, MDPI, vol. 15(6), pages 1-19, March.
    5. Wenju Sang & Wenyong Guo & Shaotao Dai & Chenyu Tian & Suhang Yu & Yuping Teng, 2022. "Virtual Synchronous Generator, a Comprehensive Overview," Energies, MDPI, vol. 15(17), pages 1-29, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xiaoqing Wang & Xin Du & Haiyun Wang & Sizhe Yan & Tianyuan Fan, 2024. "Research on Coordinated Optimization of Source-Load-Storage Considering Renewable Energy and Load Similarity," Energies, MDPI, vol. 17(6), pages 1-16, March.

    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. Myada Shadoul & Razzaqul Ahshan & Rashid S. AlAbri & Abdullah Al-Badi & Mohammed Albadi & Mohsin Jamil, 2022. "A Comprehensive Review on a Virtual-Synchronous Generator: Topologies, Control Orders and Techniques, Energy Storages, and Applications," Energies, MDPI, vol. 15(22), pages 1-27, November.
    2. Daniele Linaro & Federico Bizzarri & Davide Giudice & Cosimo Pisani & Giorgio M. Giannuzzi & Samuele Grillo & Angelo M. Brambilla, 2023. "Continuous estimation of power system inertia using convolutional neural networks," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    3. 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.
    4. Rongliang Shi & Caihua Lan & Ji Huang & Chengwei Ju, 2023. "Analysis and Optimization Strategy of Active Power Dynamic Response for VSG under a Weak Grid," Energies, MDPI, vol. 16(12), pages 1-18, June.
    5. Amr Saleh & Hany M. Hasanien & Rania A. Turky & Balgynbek Turdybek & Mohammed Alharbi & Francisco Jurado & Walid A. Omran, 2023. "Optimal Model Predictive Control for Virtual Inertia Control of Autonomous Microgrids," Sustainability, MDPI, vol. 15(6), pages 1-25, March.
    6. Vjatseslav Skiparev & Ram Machlev & Nilanjan Roy Chowdhury & Yoash Levron & Eduard Petlenkov & Juri Belikov, 2021. "Virtual Inertia Control Methods in Islanded Microgrids," Energies, MDPI, vol. 14(6), pages 1-20, March.
    7. Abualkasim Bakeer & Gaber Magdy & Andrii Chub & Francisco Jurado & Mahmoud Rihan, 2022. "Optimal Ultra-Local Model Control Integrated with Load Frequency Control of Renewable Energy Sources Based Microgrids," Energies, MDPI, vol. 15(23), pages 1-20, December.
    8. Yalin Liang & Yuyao He & Yun Niu, 2022. "Robust Errorless-Control-Targeted Technique Based on MPC for Microgrid with Uncertain Electric Vehicle Energy Storage Systems," Energies, MDPI, vol. 15(4), pages 1-23, February.
    9. Yun Zeng & Jing Qian & Fengrong Yu & Hong Mei & Shige Yu, 2021. "Damping Formation Mechanism and Damping Injection of Virtual Synchronous Generator Based on Generalized Hamiltonian Theory," Energies, MDPI, vol. 14(21), pages 1-14, October.
    10. Makolo, Peter & Zamora, Ramon & Lie, Tek-Tjing, 2021. "The role of inertia for grid flexibility under high penetration of variable renewables - A review of challenges and solutions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    11. Md. Shafiul Alam & Abdullah A. Almehizia & Fahad Saleh Al-Ismail & Md. Alamgir Hossain & Muhammad Azharul Islam & Md. Shafiullah & Aasim Ullah, 2022. "Frequency Stabilization of AC Microgrid Clusters: An Efficient Fractional Order Supercapacitor Controller Approach," Energies, MDPI, vol. 15(14), pages 1-22, July.
    12. Grzegorz Drałus & Damian Mazur & Jacek Kusznier & Jakub Drałus, 2023. "Application of Artificial Intelligence Algorithms in Multilayer Perceptron and Elman Networks to Predict Photovoltaic Power Plant Generation," Energies, MDPI, vol. 16(18), pages 1-23, September.
    13. Kabir Momoh & Shamsul Aizam Zulkifli & Petr Korba & Felix Rafael Segundo Sevilla & Arif Nur Afandi & Alfredo Velazquez-Ibañez, 2023. "State-of-the-Art Grid Stability Improvement Techniques for Electric Vehicle Fast-Charging Stations for Future Outlooks," Energies, MDPI, vol. 16(9), pages 1-29, May.
    14. Weichao He & Yuemin Zheng & Jin Tao & Yujuan Zhou & Jiayan Wen & Qinglin Sun, 2023. "A Novel Fractional-Order Active Disturbance Rejection Load Frequency Control Based on An Improved Marine Predator Algorithm," Sustainability, MDPI, vol. 15(13), pages 1-23, June.

    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:jsusta:v:15:y:2023:i:18:p:13892-:d:1242678. 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.