IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i3p1177-d1042915.html
   My bibliography  Save this article

A Hybrid Grey Wolf Assisted-Sparrow Search Algorithm for Frequency Control of RE Integrated System

Author

Listed:
  • Bashar Abbas Fadheel

    (Advanced Lightning, Power, and Energy Research (ALPER), Department of Electrical and Electronics Engineering, Faculty of Engineering, Universiti Putra Malaysia (UPM), Serdang 43400, Malaysia
    Department of Biomedical Engineering, University of Kerbala, Karbala 56001, Iraq)

  • Noor Izzri Abdul Wahab

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

  • Ali Jafer Mahdi

    (Department of Biomedical Engineering, University of Kerbala, Karbala 56001, Iraq
    Department of Scientific Affairs, Al-Zahraa University for Women, Karbala 56001, Iraq)

  • Manoharan Premkumar

    (Department of Electrical and Electronic Engineering, Dayananda Sagar College of Engineering, Bengaluru 560078, India)

  • Mohd Amran Bin Mohd Radzi

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

  • Azura Binti Che Soh

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

  • Veerapandiyan Veerasamy

    (School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore)

  • Andrew Xavier Raj Irudayaraj

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

Abstract

Nowadays, renewable energy (RE) sources are heavily integrated into the power system due to the deregulation of the energy market along with environmental and economic benefits. The intermittent nature of RE and the stochastic behavior of loads create frequency aberrations in interconnected hybrid power systems (HPS). This paper attempts to develop an optimization technique to tune the controller optimally to regulate frequency. A hybrid Sparrow Search Algorithm-Grey Wolf Optimizer (SSAGWO) is proposed to optimize the gain values of the proportional integral derivative controller. The proposed algorithm helps to improve the original algorithms’ exploration and exploitation. The optimization technique is coded in MATLAB and applied for frequency regulation of a two-area HPS developed in Simulink. The efficacy of the proffered hybrid SSAGWO is first assessed on standard benchmark functions and then applied to the frequency control of the HPS model. The results obtained from the multi-area multi-source HPS demonstrate that the proposed hybrid SSAGWO optimized PID controller performs significantly by 53%, 60%, 20%, and 70% in terms of settling time, peak undershoot, control effort, and steady-state error values, respectively, than other state-of-the-art algorithms presented in the literature. The robustness of the proffered method is also evaluated under the random varying load, variation of HPS system parameters, and weather intermittency of RE resources in real-time conditions. Furthermore, the controller’s efficacy was also demonstrated by performing a sensitivity analysis of the proposed system with variations of 75% and 125% in the inertia constant and system loading, respectively, from the nominal values. The results show that the proposed technique damped out the transient oscillations with minimum settling time. Moreover, the stability of the system is analyzed in the frequency domain using Bode analysis.

Suggested Citation

  • Bashar Abbas Fadheel & Noor Izzri Abdul Wahab & Ali Jafer Mahdi & Manoharan Premkumar & Mohd Amran Bin Mohd Radzi & Azura Binti Che Soh & Veerapandiyan Veerasamy & Andrew Xavier Raj Irudayaraj, 2023. "A Hybrid Grey Wolf Assisted-Sparrow Search Algorithm for Frequency Control of RE Integrated System," Energies, MDPI, vol. 16(3), pages 1-28, January.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:3:p:1177-:d:1042915
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/3/1177/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/3/1177/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mohamed Mokhtar & Mostafa I. Marei & Mariam A. Sameh & Mahmoud A. Attia, 2022. "An Adaptive Load Frequency Control for Power Systems with Renewable Energy Sources," Energies, MDPI, vol. 15(2), pages 1-22, January.
    2. Xie, Qiyue & Guo, Ziqi & Liu, Daifei & Chen, Zhisheng & Shen, Zhongli & Wang, Xiaoli, 2021. "Optimization of heliostat field distribution based on improved Gray Wolf optimization algorithm," Renewable Energy, Elsevier, vol. 176(C), pages 447-458.
    3. Nandakumar Sundararaju & Arangarajan Vinayagam & Veerapandiyan Veerasamy & Gunasekaran Subramaniam, 2022. "A Chaotic Search-Based Hybrid Optimization Technique for Automatic Load Frequency Control of a Renewable Energy Integrated Power System," Sustainability, MDPI, vol. 14(9), pages 1-27, May.
    4. Deepak Kumar Gupta & Amitkumar V. Jha & Bhargav Appasani & Avireni Srinivasulu & Nicu Bizon & Phatiphat Thounthong, 2021. "Load Frequency Control Using Hybrid Intelligent Optimization Technique for Multi-Source Power Systems," Energies, MDPI, vol. 14(6), pages 1-16, March.
    5. Zhenghao Wang & Yonghui Liu & Zihao Yang & Wanhao Yang, 2021. "Load Frequency Control of Multi-Region Interconnected Power Systems with Wind Power and Electric Vehicles Based on Sliding Mode Control," Energies, MDPI, vol. 14(8), pages 1-15, April.
    6. Mokhtar Shouran & Fatih Anayi & Michael Packianather, 2021. "The Bees Algorithm Tuned Sliding Mode Control for Load Frequency Control in Two-Area Power System," Energies, MDPI, vol. 14(18), pages 1-29, September.
    7. Veerapandiyan Veerasamy & Noor Izzri Abdul Wahab & Rajeswari Ramachandran & Arangarajan Vinayagam & Mohammad Lutfi Othman & Hashim Hizam & Jeevitha Satheeshkumar, 2019. "Automatic Load Frequency Control of a Multi-Area Dynamic Interconnected Power System Using a Hybrid PSO-GSA-Tuned PID Controller," Sustainability, MDPI, vol. 11(24), pages 1-20, December.
    8. Lu, Peng & Ye, Lin & Zhao, Yongning & Dai, Binhua & Pei, Ming & Tang, Yong, 2021. "Review of meta-heuristic algorithms for wind power prediction: Methodologies, applications and challenges," Applied Energy, Elsevier, vol. 301(C).
    9. Arya, Yogendra, 2017. "AGC performance enrichment of multi-source hydrothermal gas power systems using new optimized FOFPID controller and redox flow batteries," Energy, Elsevier, vol. 127(C), pages 704-715.
    10. 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.
    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. Nandakumar Sundararaju & Arangarajan Vinayagam & Veerapandiyan Veerasamy & Gunasekaran Subramaniam, 2022. "A Chaotic Search-Based Hybrid Optimization Technique for Automatic Load Frequency Control of a Renewable Energy Integrated Power System," Sustainability, MDPI, vol. 14(9), pages 1-27, May.
    2. 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.
    3. Jikai Sun & Mingrui Chen & Linghe Kong & Zhijian Hu & Veerapandiyan Veerasamy, 2023. "Regional Load Frequency Control of BP-PI Wind Power Generation Based on Particle Swarm Optimization," Energies, MDPI, vol. 16(4), pages 1-15, February.
    4. Ajay Kumar & Deepak Kumar Gupta & Sriparna Roy Ghatak & Bhargav Appasani & Nicu Bizon & Phatiphat Thounthong, 2022. "A Novel Improved GSA-BPSO Driven PID Controller for Load Frequency Control of Multi-Source Deregulated Power System," Mathematics, MDPI, vol. 10(18), pages 1-41, September.
    5. Wei Fan & Zhijian Hu & Veerapandiyan Veerasamy, 2022. "PSO-Based Model Predictive Control for Load Frequency Regulation with Wind Turbines," Energies, MDPI, vol. 15(21), pages 1-15, November.
    6. Balvinder Singh & Adam Slowik & Shree Krishna Bishnoi, 2022. "A Dual-Stage Controller for Frequency Regulation in a Two-Area Realistic Diverse Hybrid Power System Using Bull–Lion Optimization," Energies, MDPI, vol. 15(21), pages 1-24, October.
    7. Yicong Wang & Chang Liu & Ji Han & Haoyu Tan & Fangchao Ke & Dongyin Zhang & Cong Wei & Shihong Miao, 2022. "A Distributed Frequency Regulation Method for Multi-Area Power System Considering Optimization of Communication Structure," Energies, MDPI, vol. 15(18), pages 1-18, September.
    8. Pan, Lin & Xiong, Yong & Zhu, Ze & Wang, Leichong, 2022. "Research on variable pitch control strategy of direct-driven offshore wind turbine using KELM wind speed soft sensor," Renewable Energy, Elsevier, vol. 184(C), pages 1002-1017.
    9. 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.
    10. Narendra Kumar Jena & Subhadra Sahoo & Binod Kumar Sahu & Amiya Kumar Naik & Mohit Bajaj & Stanislav Misak & Vojtech Blazek & Lukas Prokop, 2023. "Impact of a Redox Flow Battery on the Frequency Stability of a Five-Area System Integrated with Renewable Sources," Energies, MDPI, vol. 16(14), pages 1-29, July.
    11. Chen, Fuhao & Yan, Jie & Liu, Yongqian & Yan, Yamin & Tjernberg, Lina Bertling, 2024. "A novel meta-learning approach for few-shot short-term wind power forecasting," Applied Energy, Elsevier, vol. 362(C).
    12. Kandasamy, Jeevitha & Ramachandran, Rajeswari & Veerasamy, Veerapandiyan & Irudayaraj, Andrew Xavier Raj, 2024. "Distributed leader-follower based adaptive consensus control for networked microgrids," Applied Energy, Elsevier, vol. 353(PA).
    13. Yongmao Xiao & Renqing Zhao & Wei Yan & Xiaoyong Zhu, 2022. "Analysis and Evaluation of Energy Consumption and Carbon Emission Levels of Products Produced by Different Kinds of Equipment Based on Green Development Concept," Sustainability, MDPI, vol. 14(13), pages 1-18, June.
    14. Christopher Jung, 2024. "Recent Development and Future Perspective of Wind Power Generation," Energies, MDPI, vol. 17(21), pages 1-5, October.
    15. Zilong, Ti & Yubing, Song & Xiaowei, Deng, 2022. "Spatial-temporal wave height forecast using deep learning and public reanalysis dataset," Applied Energy, Elsevier, vol. 326(C).
    16. Xiao, Yulong & Zou, Chongzhe & Chi, Hetian & Fang, Rengcun, 2023. "Boosted GRU model for short-term forecasting of wind power with feature-weighted principal component analysis," Energy, Elsevier, vol. 267(C).
    17. Umme Mumtahina & Sanath Alahakoon & Peter Wolfs, 2024. "Hyperparameter Tuning of Load-Forecasting Models Using Metaheuristic Optimization Algorithms—A Systematic Review," Mathematics, MDPI, vol. 12(21), pages 1-51, October.
    18. Vincent N. Ogar & Sajjad Hussain & Kelum A. A. Gamage, 2023. "Load Frequency Control Using the Particle Swarm Optimisation Algorithm and PID Controller for Effective Monitoring of Transmission Line," Energies, MDPI, vol. 16(15), pages 1-17, August.
    19. Tian Ji & Haoran Wei & Jun Wang & Shaoqing Tian & Yi Yao & Shukai Hu, 2023. "Research into the Beetle Antennae Optimization-Based PID Servo System Control of an Industrial Robot," Mathematics, MDPI, vol. 11(19), pages 1-24, September.
    20. Ma, Hongqiang & Xie, Yue & Duan, Kerun & Song, Xingpeng & Ding, Ruixiang & Hou, Caiqin, 2022. "Dynamic control method of flue gas heat transfer system in the waste heat recovery process," Energy, Elsevier, vol. 259(C).

    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:jeners:v:16:y:2023:i:3:p:1177-:d:1042915. 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.