IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i14p7622-d590392.html
   My bibliography  Save this article

PV/Wind-Integrated Low-Inertia System Frequency Control: PSO-Optimized Fractional-Order PI-Based SMES Approach

Author

Listed:
  • Md Shafiul Alam

    (K.A.CARE Energy Research & Innovation Center, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi Arabia)

  • Fahad Saleh Al-Ismail

    (K.A.CARE Energy Research & Innovation Center, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi Arabia
    Department of Electrical Engineering, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi Arabia
    Center for Environment & Marine Studies, Research Institute, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi Arabia
    Center for Renewable Energy & Power Systems, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi Arabia)

  • Mohammad Ali Abido

    (K.A.CARE Energy Research & Innovation Center, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi Arabia
    Department of Electrical Engineering, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi Arabia
    Center for Renewable Energy & Power Systems, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi Arabia)

Abstract

A paradigm shift in power engineering transforms conventional fossil fuel-based power systems gradually into more sustainable and environmentally friendly systems due to more renewable energy source (RES) integration. However, the control structure of high-level RES integrated system becomes complex, and the total system inertia is reduced due to the removal of conventional synchronous generators. Thus, such a system poses serious frequency instabilities due to the high rate of change of frequency (RoCoF). To handle this frequency instability issue, this work proposes an optimized fractional-order proportional integral (FOPI) controller-based superconducting magnetic energy storage (SMES) approach. The proposed FOPI-based SMES technique to support virtual inertia is superior to and more robust than the conventional technique. The FOPI parameters are optimized using the particle swarm optimization (PSO) technique. The SMES is modeled and integrated into the optimally designed FOPI to support the virtual inertia of the system. Fluctuating RESs are considered to show the effectiveness of the proposed approach. Extensive time-domain simulations were carried out in MATLAB Simulink with different load and generation mismatch levels. Systems with different inertia levels were simulated to guarantee the frequency stability of the system with the proposed FOPI-based SMES control technique. Several performance indices, such as overshoot, undershoot, and settling time, were considered in the analysis.

Suggested Citation

  • Md Shafiul Alam & Fahad Saleh Al-Ismail & Mohammad Ali Abido, 2021. "PV/Wind-Integrated Low-Inertia System Frequency Control: PSO-Optimized Fractional-Order PI-Based SMES Approach," Sustainability, MDPI, vol. 13(14), pages 1-21, July.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:14:p:7622-:d:590392
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/14/7622/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/14/7622/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kumar, K. Prakash & Saravanan, B., 2017. "Recent techniques to model uncertainties in power generation from renewable energy sources and loads in microgrids – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 348-358.
    2. Kanwar, Neeraj & Gupta, Nikhil & Niazi, K.R. & Swarnkar, Anil & Bansal, R.C., 2017. "Simultaneous allocation of distributed energy resource using improved particle swarm optimization," Applied Energy, Elsevier, vol. 185(P2), pages 1684-1693.
    3. Thongchart Kerdphol & Masayuki Watanabe & Yasunori Mitani & Veena Phunpeng, 2019. "Applying Virtual Inertia Control Topology to SMES System for Frequency Stability Improvement of Low-Inertia Microgrids Driven by High Renewables," Energies, MDPI, vol. 12(20), pages 1-16, October.
    4. Luis. A. G. Gomez & Ahda P. Grilo & M. B. C. Salles & A. J. Sguarezi Filho, 2020. "Combined Control of DFIG-Based Wind Turbine and Battery Energy Storage System for Frequency Response in Microgrids," Energies, MDPI, vol. 13(4), pages 1-17, February.
    5. Hossain, Md Alamgir & Pota, Hemanshu Roy & Squartini, Stefano & Zaman, Forhad & Guerrero, Josep M., 2019. "Energy scheduling of community microgrid with battery cost using particle swarm optimisation," Applied Energy, Elsevier, vol. 254(C).
    6. Lei Chen & Hongkun Chen & Jun Yang & Yanjuan Yu & Kaiwei Zhen & Yang Liu & Li Ren, 2017. "Coordinated Control of Superconducting Fault Current Limiter and Superconducting Magnetic Energy Storage for Transient Performance Enhancement of Grid-Connected Photovoltaic Generation System," Energies, MDPI, vol. 10(1), pages 1-23, January.
    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. 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.
    2. Luigi Fortuna & Arturo Buscarino, 2022. "Sustainable Energy Systems," Energies, MDPI, vol. 15(23), pages 1-7, December.
    3. Zhou, Yuan & Wang, Jiangjiang & Dong, Fuxiang & Qin, Yanbo & Ma, Zherui & Ma, Yanpeng & Li, Jianqiang, 2021. "Novel flexibility evaluation of hybrid combined cooling, heating and power system with an improved operation strategy," Applied Energy, Elsevier, vol. 300(C).
    4. Md Shafiul Alam & Mohammad Ali Yousef Abido, 2017. "Fault Ride-through Capability Enhancement of Voltage Source Converter-High Voltage Direct Current Systems with Bridge Type Fault Current Limiters," Energies, MDPI, vol. 10(11), pages 1-19, November.
    5. Asaad Mohammad & Ramon Zamora & Tek Tjing Lie, 2020. "Integration of Electric Vehicles in the Distribution Network: A Review of PV Based Electric Vehicle Modelling," Energies, MDPI, vol. 13(17), pages 1-20, September.
    6. Shang, Yuwei & Wu, Wenchuan & Guo, Jianbo & Ma, Zhao & Sheng, Wanxing & Lv, Zhe & Fu, Chenran, 2020. "Stochastic dispatch of energy storage in microgrids: An augmented reinforcement learning approach," Applied Energy, Elsevier, vol. 261(C).
    7. Yan, Rujing & Wang, Jiangjiang & Wang, Jiahao & Tian, Lei & Tang, Saiqiu & Wang, Yuwei & Zhang, Jing & Cheng, Youliang & Li, Yuan, 2022. "A two-stage stochastic-robust optimization for a hybrid renewable energy CCHP system considering multiple scenario-interval uncertainties," Energy, Elsevier, vol. 247(C).
    8. Singh, Pushpendra & Meena, Nand K. & Yang, Jin & Vega-Fuentes, Eduardo & Bishnoi, Shree Krishna, 2020. "Multi-criteria decision making monarch butterfly optimization for optimal distributed energy resources mix in distribution networks," Applied Energy, Elsevier, vol. 278(C).
    9. Prakash, K. & Ali, M. & Hossain, M A & Kumar, Nallapaneni Manoj & Islam, M.R. & Macana, C.A. & Chopra, Shauhrat S. & Pota, H.R., 2022. "Planning battery energy storage system in line with grid support parameters enables circular economy aligned ancillary services in low voltage networks," Renewable Energy, Elsevier, vol. 201(P1), pages 802-820.
    10. Feifeng Zheng & Zhaojie Wang & Ming Liu, 2022. "Overnight charging scheduling of battery electric buses with uncertain charging time," Operational Research, Springer, vol. 22(5), pages 4865-4903, November.
    11. Dillip Kumar Mishra & Daria Złotecka & Li Li, 2022. "Significance of SMES Devices for Power System Frequency Regulation Scheme considering Distributed Energy Resources in a Deregulated Environment," Energies, MDPI, vol. 15(5), pages 1-32, February.
    12. Zhu, Jiawei & Lin, Yishuai & Lei, Weidong & Liu, Youquan & Tao, Mengling, 2019. "Optimal household appliances scheduling of multiple smart homes using an improved cooperative algorithm," Energy, Elsevier, vol. 171(C), pages 944-955.
    13. Songkai Wang & Rong Jia & Xiaoyu Shi & Chang Luo & Yuan An & Qiang Huang & Pengcheng Guo & Xueyan Wang & Xuewen Lei, 2022. "Research on Capacity Allocation Optimization of Commercial Virtual Power Plant (CVPP)," Energies, MDPI, vol. 15(4), pages 1-18, February.
    14. Jiao, Feixiang & Zou, Yuan & Zhang, Xudong & Zhang, Bin, 2022. "Online optimal dispatch based on combined robust and stochastic model predictive control for a microgrid including EV charging station," Energy, Elsevier, vol. 247(C).
    15. Amr Saleh & Walid A. Omran & Hany M. Hasanien & Marcos Tostado-Véliz & Abdulaziz Alkuhayli & Francisco Jurado, 2022. "Manta Ray Foraging Optimization for the Virtual Inertia Control of Islanded Microgrids Including Renewable Energy Sources," Sustainability, MDPI, vol. 14(7), pages 1-19, April.
    16. Collath, Nils & Cornejo, Martin & Engwerth, Veronika & Hesse, Holger & Jossen, Andreas, 2023. "Increasing the lifetime profitability of battery energy storage systems through aging aware operation," Applied Energy, Elsevier, vol. 348(C).
    17. Li, Shenglin & Zhu, Jizhong & Chen, Ziyu & Luo, Tengyan, 2021. "Double-layer energy management system based on energy sharing cloud for virtual residential microgrid," Applied Energy, Elsevier, vol. 282(PA).
    18. Md. Shafiul Alam & Tanzi Ahmed Chowdhury & Abhishak Dhar & Fahad Saleh Al-Ismail & M. S. H. Choudhury & Md Shafiullah & Md. Ismail Hossain & Md. Alamgir Hossain & Aasim Ullah & Syed Masiur Rahman, 2023. "Solar and Wind Energy Integrated System Frequency Control: A Critical Review on Recent Developments," Energies, MDPI, vol. 16(2), pages 1-31, January.
    19. Mansouri, S.A. & Ahmarinejad, A. & Nematbakhsh, E. & Javadi, M.S. & Esmaeel Nezhad, A. & Catalão, J.P.S., 2022. "A sustainable framework for multi-microgrids energy management in automated distribution network by considering smart homes and high penetration of renewable energy resources," Energy, Elsevier, vol. 245(C).
    20. Veerasamy, Veerapandiyan & Abdul Wahab, Noor Izzri & Ramachandran, Rajeswari & Othman, Mohammad Lutfi & Hizam, Hashim & Devendran, Vidhya Sagar & Irudayaraj, Andrew Xavier Raj & Vinayagam, Arangarajan, 2021. "Recurrent network based power flow solution for voltage stability assessment and improvement with distributed energy sources," Applied Energy, Elsevier, vol. 302(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:jsusta:v:13:y:2021:i:14:p:7622-:d:590392. 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.