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Better seasonal forecasts for the renewable energy industry

Author

Listed:
  • Anton Orlov

    (Center for International Climate Research Oslo (CICERO))

  • Jana Sillmann

    (Center for International Climate Research Oslo (CICERO))

  • Ilaria Vigo

    (Barcelona Supercomputing Center)

Abstract

Anomalous seasons such as extremely cold winters or low-wind summers can seriously disrupt renewable energy productivity and reliability. Better seasonal forecasts providing more accurate information tailored to stakeholder needs can help the renewable energy industry prepare for such extremes.

Suggested Citation

  • Anton Orlov & Jana Sillmann & Ilaria Vigo, 2020. "Better seasonal forecasts for the renewable energy industry," Nature Energy, Nature, vol. 5(2), pages 108-110, February.
    • Handle: RePEc:nat:natene:v:5:y:2020:i:2:d:10.1038_s41560-020-0561-5
    DOI: 10.1038/s41560-020-0561-5
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    Cited by:

    1. Gao, Sichen & Huang, Guohe & Zhang, Xiaoyue & Han, Dengcheng, 2022. "Small modular reactors enable the transition to a low-carbon power system across Canada," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    2. Zuin, Gianlucca & Buechler, Rob & Sun, Tao & Zanocco, Chad & Galuppo, Francisco & Veloso, Adriano & Rajagopal, Ram, 2023. "Extreme event counterfactual analysis of electricity consumption in Brazil: Historical impacts and future outlook under climate change," Energy, Elsevier, vol. 281(C).
    3. Liu, Jiarui & Fu, Yuchen, 2023. "Renewable energy forecasting: A self-supervised learning-based transformer variant," Energy, Elsevier, vol. 284(C).
    4. Liu, Ying & Lin, Boqiang & Xu, Bin, 2021. "Modeling the impact of energy abundance on economic growth and CO2 emissions by quantile regression: Evidence from China," Energy, Elsevier, vol. 227(C).
    5. Yu, Bolin & Fang, Debin & Meng, Jingxuan, 2021. "Analysis of the generation efficiency of disaggregated renewable energy and its spatial heterogeneity influencing factors: A case study of China," Energy, Elsevier, vol. 234(C).
    6. Prasad, Abhnil Amtesh & Yang, Yuqing & Kay, Merlinde & Menictas, Chris & Bremner, Stephen, 2021. "Synergy of solar photovoltaics-wind-battery systems in Australia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    7. Li, Muyuan & Yao, Jinfeng & Shen, Yanbo & Yuan, Bin & Simmonds, Ian & Liu, Yunyun, 2023. "Impact of synoptic circulation patterns on renewable energy-related variables over China," Renewable Energy, Elsevier, vol. 215(C).
    8. Yu, Bolin & Fang, Debin & Yu, Hongwei & Zhao, Chaoyang, 2021. "Temporal-spatial determinants of renewable energy penetration in electricity production: Evidence from EU countries," Renewable Energy, Elsevier, vol. 180(C), pages 438-451.
    9. Thi Ngoc Nguyen & Felix Musgens, 2021. "What drives the accuracy of PV output forecasts?," Papers 2111.02092, arXiv.org.
    10. Neta, Ayana & Levi, Yoav & Morin, Efrat & Morin, Shai, 2023. "Seasonal forecasting of pest population dynamics based on downscaled SEAS5 forecasts," Ecological Modelling, Elsevier, vol. 480(C).
    11. Katopodis, Theodoros & Markantonis, Iason & Vlachogiannis, Diamando & Politi, Nadia & Sfetsos, Athanasios, 2021. "Assessing climate change impacts on wind characteristics in Greece through high resolution regional climate modelling," Renewable Energy, Elsevier, vol. 179(C), pages 427-444.
    12. Lledó, Llorenç & Ramon, Jaume & Soret, Albert & Doblas-Reyes, Francisco-Javier, 2022. "Seasonal prediction of renewable energy generation in Europe based on four teleconnection indices," Renewable Energy, Elsevier, vol. 186(C), pages 420-430.

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