IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i11p4159-d832318.html
   My bibliography  Save this article

Model for Optimal Power Coefficient Tracking and Loss Reduction of the Wind Turbine Systems

Author

Listed:
  • Kashif Sohail

    (Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Fukuoka 816-8580, Japan)

  • Hooman Farzaneh

    (Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Fukuoka 816-8580, Japan
    Transdisciplinary Research and Education Center for Green Technologies, Kyushu University, Fukuoka 816-8580, Japan)

Abstract

This research aimed to introduce a comprehensive mathematical modeling approach based on the maximization of the power coefficient (Cp) to obtain the regulation in pitch angle and tip speed ratio (TSP), taking into account the detailed power losses at the different stages of the power train of the wind turbine. The model is used to track the optimal power coefficient of the wind turbine power train, considering both direct (without gearbox) and indirect (with gearbox) drive configurations. The result of the direct driveline was validated with a 100 W horizontal-axis wind turbine experimental system. The model estimated the optimal value of Cp at 0.48 for a pitch angle of 0 degrees and a TSR of 8.1, which could be obtained at a wind speed of around 11.2 m/s. The results also revealed that, within the lower wind regime, windage, hysteresis, and eddy current losses dominated, while during higher wind regimes, the copper, stray load, and insulator gate bipolar transistor (IGBT) losses gained high values. The developed model was applied to a 20 kW indirect drive wind turbine installed in Gwadar city in Pakistan. Compared with the direct coupling, the optimal value of Cp was obtained at a higher value of the pitch angle (1.7 degrees) and a lower value of TSR (around 6) due to the significant impact of the gear and copper losses in an indirect drivetrain.

Suggested Citation

  • Kashif Sohail & Hooman Farzaneh, 2022. "Model for Optimal Power Coefficient Tracking and Loss Reduction of the Wind Turbine Systems," Energies, MDPI, vol. 15(11), pages 1-19, June.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:11:p:4159-:d:832318
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/11/4159/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/11/4159/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gao, Linyue & Tao, Tao & Liu, Yongqian & Hu, Hui, 2021. "A field study of ice accretion and its effects on the power production of utility-scale wind turbines," Renewable Energy, Elsevier, vol. 167(C), pages 917-928.
    2. Mazhar H. Baloch & Safdar A. Abro & Ghulam Sarwar Kaloi & Nayyar H. Mirjat & Sohaib Tahir & M. Haroon Nadeem & Mehr Gul & Zubair A. Memon & Mahendar Kumar, 2017. "A Research on Electricity Generation from Wind Corridors of Pakistan (Two Provinces): A Technical Proposal for Remote Zones," Sustainability, MDPI, vol. 9(9), pages 1-31, September.
    3. Jinghan Cui & Su Liu & Jinfeng Liu & Xiangjie Liu, 2018. "A Comparative Study of MPC and Economic MPC of Wind Energy Conversion Systems," Energies, MDPI, vol. 11(11), pages 1-23, November.
    4. Sajid Abrar & Hooman Farzaneh, 2021. "Scenario Analysis of the Low Emission Energy System in Pakistan Using Integrated Energy Demand-Supply Modeling Approach," Energies, MDPI, vol. 14(11), pages 1-30, June.
    5. Ahmed Al Ameri & Aouchenni Ounissa & Cristian Nichita & Aouzellag Djamal, 2017. "Power Loss Analysis for Wind Power Grid Integration Based on Weibull Distribution," Energies, MDPI, vol. 10(4), pages 1-16, April.
    6. Esteban, Miguel & Portugal-Pereira, Joana & Mclellan, Benjamin C. & Bricker, Jeremy & Farzaneh, Hooman & Djalilova, Nigora & Ishihara, Keiichi N. & Takagi, Hiroshi & Roeber, Volker, 2018. "100% renewable energy system in Japan: Smoothening and ancillary services," Applied Energy, Elsevier, vol. 224(C), pages 698-707.
    7. Jia, Liangyue & Hao, Jia & Hall, John & Nejadkhaki, Hamid Khakpour & Wang, Guoxin & Yan, Yan & Sun, Mengyuan, 2021. "A reinforcement learning based blade twist angle distribution searching method for optimizing wind turbine energy power," Energy, Elsevier, vol. 215(PA).
    8. Tatsuya Hinokuma & Hooman Farzaneh & Ayas Shaqour, 2021. "Techno-Economic Analysis of a Fuzzy Logic Control Based Hybrid Renewable Energy System to Power a University Campus in Japan," Energies, MDPI, vol. 14(7), pages 1-23, April.
    9. Lanzafame, R. & Messina, M., 2010. "Horizontal axis wind turbine working at maximum power coefficient continuously," Renewable Energy, Elsevier, vol. 35(1), pages 301-306.
    10. Nour Khlaifat & Ali Altaee & John Zhou & Yuhan Huang & Ali Braytee, 2020. "Optimization of a Small Wind Turbine for a Rural Area: A Case Study of Deniliquin, New South Wales, Australia," Energies, MDPI, vol. 13(9), pages 1-26, May.
    11. Hung, Duong Quoc & Mithulananthan, N. & Bansal, R.C., 2013. "Analytical strategies for renewable distributed generation integration considering energy loss minimization," Applied Energy, Elsevier, vol. 105(C), pages 75-85.
    12. Lap-Arparat, Pongpak & Leephakpreeda, Thananchai, 2019. "Real-time maximized power generation of vertical axis wind turbines based on characteristic curves of power coefficients via fuzzy pulse width modulation load regulation," Energy, Elsevier, vol. 182(C), pages 975-987.
    13. Song, Dongran & Liu, Junbo & Yang, Yinggang & Yang, Jian & Su, Mei & Wang, Yun & Gui, Ning & Yang, Xuebing & Huang, Lingxiang & Hoon Joo, Young, 2021. "Maximum wind energy extraction of large-scale wind turbines using nonlinear model predictive control via Yin-Yang grey wolf optimization algorithm," Energy, Elsevier, vol. 221(C).
    14. Yuichiro Yoshida & Hooman Farzaneh, 2020. "Optimal Design of a Stand-Alone Residential Hybrid Microgrid System for Enhancing Renewable Energy Deployment in Japan," Energies, MDPI, vol. 13(7), pages 1-18, April.
    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. 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.
    2. Tatsuya Hinokuma & Hooman Farzaneh & Ayas Shaqour, 2021. "Techno-Economic Analysis of a Fuzzy Logic Control Based Hybrid Renewable Energy System to Power a University Campus in Japan," Energies, MDPI, vol. 14(7), pages 1-23, April.
    3. Jihed Hmad & Azeddine Houari & Allal El Moubarek Bouzid & Abdelhakim Saim & Hafedh Trabelsi, 2023. "A Review on Mode Transition Strategies between Grid-Connected and Standalone Operation of Voltage Source Inverters-Based Microgrids," Energies, MDPI, vol. 16(13), pages 1-41, June.
    4. Hung, Duong Quoc & Mithulananthan, N. & Bansal, R.C., 2014. "An optimal investment planning framework for multiple distributed generation units in industrial distribution systems," Applied Energy, Elsevier, vol. 124(C), pages 62-72.
    5. Bogdanov, Dmitrii & Toktarova, Alla & Breyer, Christian, 2019. "Transition towards 100% renewable power and heat supply for energy intensive economies and severe continental climate conditions: Case for Kazakhstan," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    6. Yanfeng Liu & Yaxing Wang & Xi Luo, 2020. "Design and Operation Optimization of Distributed Solar Energy System Based on Dynamic Operation Strategy," Energies, MDPI, vol. 14(1), pages 1-26, December.
    7. Khasanzoda, Nasrullo & Safaraliev, Murodbek & Zicmane, Inga & Beryozkina, Svetlana & Rahimov, Jamshed & Ahyoev, Javod, 2022. "Use of smart grid based wind resources in isolated power systems," Energy, Elsevier, vol. 253(C).
    8. Li, Aitong & Xu, Yuan & Shiroyama, Hideaki, 2019. "Solar lobby and energy transition in Japan," Energy Policy, Elsevier, vol. 134(C).
    9. Miloud Rezkallah & Sanjeev Singh & Ambrish Chandra & Bhim Singh & Hussein Ibrahim, 2020. "Off-Grid System Configurations for Coordinated Control of Renewable Energy Sources," Energies, MDPI, vol. 13(18), pages 1-25, September.
    10. Constantino Dário Justo & José Eduardo Tafula & Pedro Moura, 2022. "Planning Sustainable Energy Systems in the Southern African Development Community: A Review of Power Systems Planning Approaches," Energies, MDPI, vol. 15(21), pages 1-28, October.
    11. Sultana, U. & Khairuddin, Azhar B. & Aman, M.M. & Mokhtar, A.S. & Zareen, N., 2016. "A review of optimum DG placement based on minimization of power losses and voltage stability enhancement of distribution system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 63(C), pages 363-378.
    12. Galih Bangga, 2022. "Progress and Outlook in Wind Energy Research," Energies, MDPI, vol. 15(18), pages 1-5, September.
    13. Abdmouleh, Zeineb & Gastli, Adel & Ben-Brahim, Lazhar & Haouari, Mohamed & Al-Emadi, Nasser Ahmed, 2017. "Review of optimization techniques applied for the integration of distributed generation from renewable energy sources," Renewable Energy, Elsevier, vol. 113(C), pages 266-280.
    14. Lanzafame, R. & Mauro, S. & Messina, M., 2013. "Wind turbine CFD modeling using a correlation-based transitional model," Renewable Energy, Elsevier, vol. 52(C), pages 31-39.
    15. Brumana, Giovanni & Franchini, Giuseppe & Ghirardi, Elisa & Perdichizzi, Antonio, 2022. "Techno-economic optimization of hybrid power generation systems: A renewables community case study," Energy, Elsevier, vol. 246(C).
    16. Xydas, Erotokritos & Marmaras, Charalampos & Cipcigan, Liana M., 2016. "A multi-agent based scheduling algorithm for adaptive electric vehicles charging," Applied Energy, Elsevier, vol. 177(C), pages 354-365.
    17. Shin, Heesoo & Rüttgers, Mario & Lee, Sangseung, 2023. "Effects of spatiotemporal correlations in wind data on neural network-based wind predictions," Energy, Elsevier, vol. 279(C).
    18. Fan, Feilong & Huang, Wentao & Tai, Nengling & Zheng, Xiaodong & Hu, Yan & Ma, Zhoujun, 2018. "A conditional depreciation balancing strategy for the equitable operation of extended hybrid energy storage systems," Applied Energy, Elsevier, vol. 228(C), pages 1937-1952.
    19. Wajahat Ullah Khan Tareen & Zuha Anjum & Nabila Yasin & Leenah Siddiqui & Ifzana Farhat & Suheel Abdullah Malik & Saad Mekhilef & Mehdi Seyedmahmoudian & Ben Horan & Mohamed Darwish & Muhammad Aamir &, 2018. "The Prospective Non-Conventional Alternate and Renewable Energy Sources in Pakistan—A Focus on Biomass Energy for Power Generation, Transportation, and Industrial Fuel," Energies, MDPI, vol. 11(9), pages 1-49, September.
    20. Rémi Delage & Taichi Matsuoka & Toshihiko Nakata, 2021. "Spatial–Temporal Estimation and Analysis of Japan Onshore and Offshore Wind Energy Potential," Energies, MDPI, vol. 14(8), pages 1-12, April.

    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:15:y:2022:i:11:p:4159-:d:832318. 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.