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Intermittent Smoothing Approaches for Wind Power Output: A Review

Author

Listed:
  • Muhammad Jabir

    (Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia)

  • Hazlee Azil Illias

    (Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia)

  • Safdar Raza

    (Department of Electrical Engineering, NFC IET, Multan 60000, Pakistan)

  • Hazlie Mokhlis

    (Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia)

Abstract

Wind energy is one of the most common types of renewable energy resource. Due to its sustainability and environmental benefits, it is an emerging source for electric power generation. Rapid and random changes of wind speed makes it an irregular and inconsistent power source when connected to the grid, causing different technical problems in protection, power quality and generation dispatch control. Due to these problems, effective intermittent smoothing approaches for wind power output are crucially needed to minimize such problems. This paper reviews various intermittent smoothing approaches used in smoothing the output power fluctuations caused by wind energy. Problems associated with the inclusion of wind energy resources to grid are also briefly reviewed. From this review, it has been found that battery energy storage system is the most suitable and effective smoothing approach, provided that an effective control strategy is available for optimal utilization of battery energy system. This paper further demonstrates different control strategies built for battery energy storage system to obtain the smooth output wind power.

Suggested Citation

  • Muhammad Jabir & Hazlee Azil Illias & Safdar Raza & Hazlie Mokhlis, 2017. "Intermittent Smoothing Approaches for Wind Power Output: A Review," Energies, MDPI, vol. 10(10), pages 1-23, October.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:10:p:1572-:d:114760
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    References listed on IDEAS

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    Cited by:

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    2. Guangyi Wu & Xiangxin Shao & Hong Jiang & Shaoxin Chen & Yibing Zhou & Hongyang Xu, 2020. "Control Strategy of the Pumped Storage Unit to Deal with the Fluctuation of Wind and Photovoltaic Power in Microgrid," Energies, MDPI, vol. 13(2), pages 1-23, January.
    3. Diego Jose da Silva & Edmarcio Antonio Belati & Jesús M. López-Lezama, 2023. "A Mathematical Programming Approach for the Optimal Operation of Storage Systems, Photovoltaic and Wind Power Generation," Energies, MDPI, vol. 16(3), pages 1-24, January.
    4. Lai, Chun Sing & Locatelli, Giorgio, 2021. "Economic and financial appraisal of novel large-scale energy storage technologies," Energy, Elsevier, vol. 214(C).
    5. Frate, G.F. & Cherubini, P. & Tacconelli, C. & Micangeli, A. & Ferrari, L. & Desideri, U., 2019. "Ramp rate abatement for wind power plants: A techno-economic analysis," Applied Energy, Elsevier, vol. 254(C).
    6. Jae Woong Shim & Heejin Kim & Kyeon Hur, 2019. "Incorporating State-of-Charge Balancing into the Control of Energy Storage Systems for Smoothing Renewable Intermittency," Energies, MDPI, vol. 12(7), pages 1-13, March.
    7. Andrea Mannelli & Francesco Papi & George Pechlivanoglou & Giovanni Ferrara & Alessandro Bianchini, 2021. "Discrete Wavelet Transform for the Real-Time Smoothing of Wind Turbine Power Using Li-Ion Batteries," Energies, MDPI, vol. 14(8), pages 1-32, April.
    8. Li, Chaolei & Wu, Anqi & Xi, Chengqiao & Guan, Wanbing & Chen, Liang & Singhal, Subhash C., 2022. "High reversible cycling performance of carbon dioxide electrolysis by flat-tube solid oxide cell," Applied Energy, Elsevier, vol. 314(C).
    9. Abdullah Al-Shereiqi & Amer Al-Hinai & Mohammed Albadi & Rashid Al-Abri, 2021. "Optimal Sizing of Hybrid Wind-Solar Power Systems to Suppress Output Fluctuation," Energies, MDPI, vol. 14(17), pages 1-16, August.
    10. Siqin, Zhuoya & Niu, DongXiao & Wang, Xuejie & Zhen, Hao & Li, MingYu & Wang, Jingbo, 2022. "A two-stage distributionally robust optimization model for P2G-CCHP microgrid considering uncertainty and carbon emission," Energy, Elsevier, vol. 260(C).

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