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Residual load probabilistic forecast for reserve assessment: A real case study

Author

Listed:
  • Pierro, Marco
  • De Felice, Matteo
  • Maggioni, Enrico
  • Moser, David
  • Perotto, Alessandro
  • Spada, Francesco
  • Cornaro, Cristina

Abstract

Distributed generation from wind and solar acts on regional electric demand as a reduced consumption, giving rise to a “load shadowing effect”. The net load becomes much more difficult to predict due to its dependence on the meteorological conditions. As a consequence, the growing penetration of variable generation increases the imbalance between demand and scheduled supply (net load forecast) and the reserve margins (net load uncertainty).

Suggested Citation

  • Pierro, Marco & De Felice, Matteo & Maggioni, Enrico & Moser, David & Perotto, Alessandro & Spada, Francesco & Cornaro, Cristina, 2020. "Residual load probabilistic forecast for reserve assessment: A real case study," Renewable Energy, Elsevier, vol. 149(C), pages 508-522.
    • Handle: RePEc:eee:renene:v:149:y:2020:i:c:p:508-522
    DOI: 10.1016/j.renene.2019.12.056
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    References listed on IDEAS

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    Cited by:

    1. Hu, Jiaxiang & Hu, Weihao & Cao, Di & Sun, Xinwu & Chen, Jianjun & Huang, Yuehui & Chen, Zhe & Blaabjerg, Frede, 2024. "Probabilistic net load forecasting based on transformer network and Gaussian process-enabled residual modeling learning method," Renewable Energy, Elsevier, vol. 225(C).
    2. Pierro, Marco & Perez, Richard & Perez, Marc & Moser, David & Cornaro, Cristina, 2021. "Imbalance mitigation strategy via flexible PV ancillary services: The Italian case study," Renewable Energy, Elsevier, vol. 179(C), pages 1694-1705.
    3. Marco Pierro & David Moser & Richard Perez & Cristina Cornaro, 2020. "The Value of PV Power Forecast and the Paradox of the “Single Pricing” Scheme: The Italian Case Study," Energies, MDPI, vol. 13(15), pages 1-27, August.
    4. Gandhi, Oktoviano & Zhang, Wenjie & Kumar, Dhivya Sampath & Rodríguez-Gallegos, Carlos D. & Yagli, Gokhan Mert & Yang, Dazhi & Reindl, Thomas & Srinivasan, Dipti, 2024. "The value of solar forecasts and the cost of their errors: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    5. Marco Pierro & Fabio Romano Liolli & Damiano Gentili & Marcello Petitta & Richard Perez & David Moser & Cristina Cornaro, 2022. "Impact of PV/Wind Forecast Accuracy and National Transmission Grid Reinforcement on the Italian Electric System," Energies, MDPI, vol. 15(23), pages 1-28, November.

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