IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i1p80-d87508.html
   My bibliography  Save this article

A Frequency Control Approach for Hybrid Power System Using Multi-Objective Optimization

Author

Listed:
  • Mohammed Elsayed Lotfy

    (Department of Electrical Power and Machines, Zagazig University, Zagazig 44519, Egypt
    Department of Electrical and Electronics Engineering, University of the Ryukyus, Okinawa 903-0213, Japan)

  • Tomonobu Senjyu

    (Department of Electrical and Electronics Engineering, University of the Ryukyus, Okinawa 903-0213, Japan)

  • Mohammed Abdel-Fattah Farahat

    (Department of Electrical Power and Machines, Zagazig University, Zagazig 44519, Egypt)

  • Amal Farouq Abdel-Gawad

    (Department of Electrical Power and Machines, Zagazig University, Zagazig 44519, Egypt)

  • Atsuhi Yona

    (Department of Electrical and Electronics Engineering, University of the Ryukyus, Okinawa 903-0213, Japan)

Abstract

A hybrid power system uses many wind turbine generators (WTG) and solar photovoltaics (PV) in isolated small areas. However, the output power of these renewable sources is not constant and can diverge quickly, which has a serious effect on system frequency and the continuity of demand supply. In order to solve this problem, this paper presents a new frequency control scheme for a hybrid power system to ensure supplying a high-quality power in isolated areas. The proposed power system consists of a WTG, PV, aqua-electrolyzer (AE), fuel cell (FC), battery energy storage system (BESS), flywheel (FW) and diesel engine generator (DEG). Furthermore, plug-in hybrid electric vehicles (EVs) are implemented at the customer side. A full-order observer is utilized to estimate the supply error. Then, the estimated supply error is considered in a frequency domain. The high-frequency component is reduced by BESS and FW; while the low-frequency component of supply error is mitigated using FC, EV and DEG. Two PI controllers are implemented in the proposed system to control the system frequency and reduce the supply error. The epsilon multi-objective genetic algorithm ( ε -MOGA) is applied to optimize the controllers’ parameters. The performance of the proposed control scheme is compared with that of recent well-established techniques, such as a PID controller tuned by the quasi-oppositional harmony search algorithm (QOHSA). The effectiveness and robustness of the hybrid power system are investigated under various operating conditions.

Suggested Citation

  • Mohammed Elsayed Lotfy & Tomonobu Senjyu & Mohammed Abdel-Fattah Farahat & Amal Farouq Abdel-Gawad & Atsuhi Yona, 2017. "A Frequency Control Approach for Hybrid Power System Using Multi-Objective Optimization," Energies, MDPI, vol. 10(1), pages 1-22, January.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:1:p:80-:d:87508
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/1/80/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/10/1/80/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Al-Alawi, Ali & M Al-Alawi, Saleh & M Islam, Syed, 2007. "Predictive control of an integrated PV-diesel water and power supply system using an artificial neural network," Renewable Energy, Elsevier, vol. 32(8), pages 1426-1439.
    2. Jun Yang & Zhili Zeng & Yufei Tang & Jun Yan & Haibo He & Yunliang Wu, 2015. "Load Frequency Control in Isolated Micro-Grids with Electrical Vehicles Based on Multivariable Generalized Predictive Theory," Energies, MDPI, vol. 8(3), pages 1-20, March.
    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. Lei Liu & Hidehito Matayoshi & Mohammed Elsayed Lotfy & Manoj Datta & Tomonobu Senjyu, 2018. "Load Frequency Control Using Demand Response and Storage Battery by Considering Renewable Energy Sources," Energies, MDPI, vol. 11(12), pages 1-40, December.
    2. Alhassan H. Alattar & S. I. Selem & Hamid M. B. Metwally & Ahmed Ibrahim & Raef Aboelsaud & Mohamed A. Tolba & Ali M. El-Rifaie, 2019. "Performance Enhancement of Micro Grid System with SMES Storage System Based on Mine Blast Optimization Algorithm," Energies, MDPI, vol. 12(16), pages 1-23, August.
    3. Andrés Peña Asensio & Santiago Arnaltes Gómez & Jose Luis Rodriguez-Amenedo & Manuel García Plaza & Joaquín Eloy-García Carrasco & Jaime Manuel Alonso-Martínez de las Morenas, 2018. "A Voltage and Frequency Control Strategy for Stand-Alone Full Converter Wind Energy Conversion Systems," Energies, MDPI, vol. 11(3), pages 1-19, February.
    4. Tiejiang Yuan & Qingxi Duan & Xiangping Chen & Xufeng Yuan & Wenping Cao & Juan Hu & Quanmin Zhu, 2017. "Coordinated Control of a Wind-Methanol-Fuel Cell System with Hydrogen Storage," Energies, MDPI, vol. 10(12), pages 1-21, December.
    5. Komboigo Charles & Naomitsu Urasaki & Tomonobu Senjyu & Mohammed Elsayed Lotfy & Lei Liu, 2018. "Robust Load Frequency Control Schemes in Power System Using Optimized PID and Model Predictive Controllers," Energies, MDPI, vol. 11(11), pages 1-18, November.
    6. Mohamed Khamies & Salah Kamel & Mohamed H. Hassan & Mohamed F. Elnaggar, 2022. "A Developed Frequency Control Strategy for Hybrid Two-Area Power System with Renewable Energy Sources Based on an Improved Social Network Search Algorithm," Mathematics, MDPI, vol. 10(9), pages 1-31, May.
    7. Takashi Mitani & Muhammad Aziz & Takuya Oda & Atsuki Uetsuji & Yoko Watanabe & Takao Kashiwagi, 2017. "Annual Assessment of Large-Scale Introduction of Renewable Energy: Modeling of Unit Commitment Schedule for Thermal Power Generators and Pumped Storages," Energies, MDPI, vol. 10(6), pages 1-19, May.
    8. Mohammed Elsayed Lotfy & Tomonobu Senjyu & Mohammed Abdel-Fattah Farahat & Amal Farouq Abdel-Gawad & Hidehito Matayoshi, 2017. "A Polar Fuzzy Control Scheme for Hybrid Power System Using Vehicle-To-Grid Technique," Energies, MDPI, vol. 10(8), pages 1-25, July.
    9. Dejian Yang & Moses Kang & Eduard Muljadi & Wenzhong Gao & Junhee Hong & Jaeseok Choi & Yong Cheol Kang, 2017. "Short-Term Frequency Response of a DFIG-Based Wind Turbine Generator for Rapid Frequency Stabilization," Energies, MDPI, vol. 10(11), pages 1-14, November.
    10. Xingning Han & Shiwu Liao & Xiaomeng Ai & Wei Yao & Jinyu Wen, 2017. "Determining the Minimal Power Capacity of Energy Storage to Accommodate Renewable Generation," Energies, MDPI, vol. 10(4), pages 1-17, April.
    11. Danny Ochoa & Sergio Martinez, 2018. "Proposals for Enhancing Frequency Control in Weak and Isolated Power Systems: Application to the Wind-Diesel Power System of San Cristobal Island-Ecuador," Energies, MDPI, vol. 11(4), pages 1-25, April.
    12. Thai-Thanh Nguyen & Hyeong-Jun Yoo & Hak-Man Kim, 2017. "Analyzing the Impacts of System Parameters on MPC-Based Frequency Control for a Stand-Alone Microgrid," Energies, MDPI, vol. 10(4), pages 1-17, March.
    13. Touqeer Ahmed Jumani & Mohd Wazir Mustafa & Nawaf N. Hamadneh & Samer H. Atawneh & Madihah Md. Rasid & Nayyar Hussain Mirjat & Muhammad Akram Bhayo & Ilyas Khan, 2020. "Computational Intelligence-Based Optimization Methods for Power Quality and Dynamic Response Enhancement of ac Microgrids," Energies, MDPI, vol. 13(16), pages 1-22, August.

    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. Xin Wang & Jun Yang & Lei Chen & Jifeng He, 2017. "Application of Liquid Hydrogen with SMES for Efficient Use of Renewable Energy in the Energy Internet," Energies, MDPI, vol. 10(2), pages 1-20, February.
    2. Ioannis Skouros & Athanasios Karlis, 2020. "A Study on the V2G Technology Incorporation in a DC Nanogrid and on the Provision of Voltage Regulation to the Power Grid," Energies, MDPI, vol. 13(10), pages 1-23, May.
    3. Kashyap, Yashwant & Bansal, Ankit & Sao, Anil K., 2015. "Solar radiation forecasting with multiple parameters neural networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 825-835.
    4. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.
    5. Jiandong Yang & Mingjiang Wang & Chao Wang & Wencheng Guo, 2015. "Linear Modeling and Regulation Quality Analysis for Hydro-Turbine Governing System with an Open Tailrace Channel," Energies, MDPI, vol. 8(10), pages 1-16, October.
    6. Hongyue Li & Xihuai Wang & Jianmei Xiao, 2018. "Differential Evolution-Based Load Frequency Robust Control for Micro-Grids with Energy Storage Systems," Energies, MDPI, vol. 11(7), pages 1-19, June.
    7. Shitao Ruan, 2023. "Robust Fractional-Order Proportional-Integral Controller Tuning for Load Frequency Control of a Microgrid System with Communication Delay," Energies, MDPI, vol. 16(14), pages 1-17, July.
    8. Vasudevan, Krishnakumar R. & Ramachandaramurthy, Vigna K. & Venugopal, Gomathi & Ekanayake, J.B. & Tiong, S.K., 2021. "Variable speed pumped hydro storage: A review of converters, controls and energy management strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    9. Karabacak, Kerim & Cetin, Numan, 2014. "Artificial neural networks for controlling wind–PV power systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 804-827.
    10. Paolo Scarabaggio & Raffaele Carli & Graziana Cavone & Mariagrazia Dotoli, 2020. "Smart Control Strategies for Primary Frequency Regulation through Electric Vehicles: A Battery Degradation Perspective," Energies, MDPI, vol. 13(17), pages 1-19, September.
    11. Thai-Thanh Nguyen & Hyeong-Jun Yoo & Hak-Man Kim, 2017. "Analyzing the Impacts of System Parameters on MPC-Based Frequency Control for a Stand-Alone Microgrid," Energies, MDPI, vol. 10(4), pages 1-17, March.
    12. Yap, Wai Kean & Karri, Vishy, 2015. "An off-grid hybrid PV/diesel model as a planning and design tool, incorporating dynamic and ANN modelling techniques," Renewable Energy, Elsevier, vol. 78(C), pages 42-50.
    13. Poompavai, T. & Kowsalya, M., 2019. "Control and energy management strategies applied for solar photovoltaic and wind energy fed water pumping system: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 107(C), pages 108-122.
    14. Yuxin Wen & Peixiao Fan & Jia Hu & Song Ke & Fuzhang Wu & Xu Zhu, 2022. "An Optimal Scheduling Strategy of a Microgrid with V2G Based on Deep Q-Learning," Sustainability, MDPI, vol. 14(16), pages 1-18, August.
    15. Kebai Li & Tianyi Ma & Guo Wei, 2018. "Robust Economic Control Decision Method of Uncertain System on Urban Domestic Water Supply," IJERPH, MDPI, vol. 15(4), pages 1-15, March.
    16. Saqib Yousuf & Viqar Yousuf & Neeraj Gupta & Talal Alharbi & Omar Alrumayh, 2023. "Enhanced Control Designs to Abate Frequency Oscillations in Compensated Power System," Energies, MDPI, vol. 16(5), pages 1-20, February.
    17. Erdinc, O. & Uzunoglu, M., 2012. "Optimum design of hybrid renewable energy systems: Overview of different approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1412-1425.
    18. Md Mijanur Rahman & A. Hasib Chowdhury & Md Alamgir Hossain, 2017. "Improved Load Frequency Control Using a Fast Acting Active Disturbance Rejection Controller," Energies, MDPI, vol. 10(11), pages 1-18, October.
    19. Adlan Pradana & Mejbaul Haque & Mithulanathan Nadarajah, 2023. "Control Strategies of Electric Vehicles Participating in Ancillary Services: A Comprehensive Review," Energies, MDPI, vol. 16(4), pages 1-36, February.
    20. Dhanasekaran Boopathi & Kaliannan Jagatheesan & Baskaran Anand & Sourav Samanta & Nilanjan Dey, 2023. "Frequency Regulation of Interlinked Microgrid System Using Mayfly Algorithm-Based PID Controller," Sustainability, MDPI, vol. 15(11), pages 1-19, May.

    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:10:y:2017:i:1:p:80-:d:87508. 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.