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Positive Correlations between Short-Term and Average Long-Term Fluctuations in Wind Power Output

Author

Listed:
  • Chiyori T. Urabe

    (Institute of Industrial Science, The University of Tokyo, Tokyo 1538505, Japan)

  • Tetsuo Saitou

    (Institute of Industrial Science, The University of Tokyo, Tokyo 1538505, Japan
    Current address: Renewable Energy Institute, Tokyo 1050001, Japan.)

  • Kazuto Kataoka

    (Institute of Industrial Science, The University of Tokyo, Tokyo 1538505, Japan)

  • Takashi Ikegami

    (Division of Advanced Mechanical Systems Engineering, Institute of Engineering, Tokyo University of Agriculture and Technology, Tokyo 1848588, Japan)

  • Kazuhiko Ogimoto

    (Institute of Industrial Science, The University of Tokyo, Tokyo 1538505, Japan)

Abstract

Wind power has been increasingly deployed in the last decade to decarbonize the electricity sector. Wind power output changes intermittently depending on weather conditions. In electrical power systems with high shares of variable renewable energy sources, such as wind power, system operators aim to respond flexibly to fluctuations in output. Here, we investigated very short-term fluctuations, short-term fluctuations (STFs), and long-term fluctuations (LTFs) in wind power output by analyzing historical output data for two northern and one southern balancing areas in Japan. We found a relationship between STFs and the average LTFs. The percentiles of the STFs in each month are approximated by linear functions of the monthly average LTFs. Furthermore, the absolute value of the slope of this function decreases with wind power capacity in the balancing area. The LTFs reflect the trend in wind power output. The results indicate that the flexibility required for power systems can be estimated based on wind power predictions. This finding could facilitate the design of the balancing market in Japan.

Suggested Citation

  • Chiyori T. Urabe & Tetsuo Saitou & Kazuto Kataoka & Takashi Ikegami & Kazuhiko Ogimoto, 2021. "Positive Correlations between Short-Term and Average Long-Term Fluctuations in Wind Power Output," Energies, MDPI, vol. 14(7), pages 1-15, March.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:7:p:1861-:d:525149
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    References listed on IDEAS

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    1. Ikegami, Takashi & Urabe, Chiyori T. & Saitou, Tetsuo & Ogimoto, Kazuhiko, 2018. "Numerical definitions of wind power output fluctuations for power system operations," Renewable Energy, Elsevier, vol. 115(C), pages 6-15.
    2. Yu, Dayang & Liang, Jun & Han, Xueshan & Zhao, Jianguo, 2011. "Profiling the regional wind power fluctuation in China," Energy Policy, Elsevier, vol. 39(1), pages 299-306, January.
    3. Sinden, Graham, 2007. "Characteristics of the UK wind resource: Long-term patterns and relationship to electricity demand," Energy Policy, Elsevier, vol. 35(1), pages 112-127, January.
    4. Ohba, Masamichi & Kadokura, Shinji & Nohara, Daisuke, 2016. "Impacts of synoptic circulation patterns on wind power ramp events in East Japan," Renewable Energy, Elsevier, vol. 96(PA), pages 591-602.
    5. Katrin Schmietendorf & Joachim Peinke & Oliver Kamps, 2017. "The impact of turbulent renewable energy production on power grid stability and quality," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 90(11), pages 1-6, November.
    6. Olauson, Jon & Bergkvist, Mikael, 2016. "Correlation between wind power generation in the European countries," Energy, Elsevier, vol. 114(C), pages 663-670.
    7. Wu, Zhaoyuan & Zhou, Ming & Li, Gengyin & Zhao, Tong & Zhang, Yan & Liu, Xiaojuan, 2020. "Interaction between balancing market design and market behaviour of wind power producers in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    8. Katzenstein, Warren & Fertig, Emily & Apt, Jay, 2010. "The variability of interconnected wind plants," Energy Policy, Elsevier, vol. 38(8), pages 4400-4410, August.
    9. Buttler, Alexander & Dinkel, Felix & Franz, Simon & Spliethoff, Hartmut, 2016. "Variability of wind and solar power – An assessment of the current situation in the European Union based on the year 2014," Energy, Elsevier, vol. 106(C), pages 147-161.
    10. Carraretto, Cristian, 2006. "Power plant operation and management in a deregulated market," Energy, Elsevier, vol. 31(6), pages 1000-1016.
    11. Hu, Jing & Harmsen, Robert & Crijns-Graus, Wina & Worrell, Ernst, 2019. "Geographical optimization of variable renewable energy capacity in China using modern portfolio theory," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    12. Widén, Joakim & Carpman, Nicole & Castellucci, Valeria & Lingfors, David & Olauson, Jon & Remouit, Flore & Bergkvist, Mikael & Grabbe, Mårten & Waters, Rafael, 2015. "Variability assessment and forecasting of renewables: A review for solar, wind, wave and tidal resources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 356-375.
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