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C-E (curtailment – Energy share) map: An objective and quantitative measure to evaluate wind and solar curtailment

Author

Listed:
  • Yasuda, Yoh
  • Bird, Lori
  • Carlini, Enrico Maria
  • Eriksen, Peter Børre
  • Estanqueiro, Ana
  • Flynn, Damian
  • Fraile, Daniel
  • Gómez Lázaro, Emilio
  • Martín-Martínez, Sergio
  • Hayashi, Daisuke
  • Holttinen, Hannele
  • Lew, Debra
  • McCam, John
  • Menemenlis, Nickie
  • Miranda, Raul
  • Orths, Antje
  • Smith, J. Charles
  • Taibi, Emanuele
  • Vrana, Til Kristian

Abstract

As the share of VRE (variable renewable energy) has grown rapidly, curtailment issues have arisen worldwide. This paper evaluates and compares curtailment situations in selected countries using an objective and quantitative evaluation tool named the “C-E map” (curtailment-energy share map). The C-E map is a correlation map between curtailment ratios that mean curtailed wind (or solar) energy per available energy and energy shares of wind (or solar). The C-E map can draw a historical trend curve in a given country/area, as an at-a-glance tool to enable historical and/or international comparison. The C-E map also can classify the given countries/areas into several categories, according to the current levels of curtailment ratio and historical trends. The C-E map helps institutional and objective understanding of curtailment for non-experts including policy makers.

Suggested Citation

  • Yasuda, Yoh & Bird, Lori & Carlini, Enrico Maria & Eriksen, Peter Børre & Estanqueiro, Ana & Flynn, Damian & Fraile, Daniel & Gómez Lázaro, Emilio & Martín-Martínez, Sergio & Hayashi, Daisuke & Holtti, 2022. "C-E (curtailment – Energy share) map: An objective and quantitative measure to evaluate wind and solar curtailment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    • Handle: RePEc:eee:rensus:v:160:y:2022:i:c:s1364032122001356
    DOI: 10.1016/j.rser.2022.112212
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    References listed on IDEAS

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    Cited by:

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    4. Jiang, Hou & Zhang, Xiaotong & Yao, Ling & Lu, Ning & Qin, Jun & Liu, Tang & Zhou, Chenghu, 2023. "High-resolution analysis of rooftop photovoltaic potential based on hourly generation simulations and load profiles," Applied Energy, Elsevier, vol. 348(C).

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