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Extreme Quantiles Dynamic Line Rating Forecasts and Application on Network Operation

Author

Listed:
  • Romain Dupin

    (MINES ParisTech, PSL University, Centre for Processes, Renewable Energies and Energy Systems (PERSEE), CS 10207 rue Claude Daunesse, Cedex, 06904 Sophia Antipolis, France)

  • Laura Cavalcante

    (INESC TEC, Centre for Power and Energy Systems, Campus da FEUP, Rua Dr Roberto Frias, 4200-465 Porto, Portugal)

  • Ricardo J. Bessa

    (INESC TEC, Centre for Power and Energy Systems, Campus da FEUP, Rua Dr Roberto Frias, 4200-465 Porto, Portugal)

  • Georges Kariniotakis

    (MINES ParisTech, PSL University, Centre for Processes, Renewable Energies and Energy Systems (PERSEE), CS 10207 rue Claude Daunesse, Cedex, 06904 Sophia Antipolis, France)

  • Andrea Michiorri

    (MINES ParisTech, PSL University, Centre for Processes, Renewable Energies and Energy Systems (PERSEE), CS 10207 rue Claude Daunesse, Cedex, 06904 Sophia Antipolis, France)

Abstract

This paper presents a study on dynamic line rating (DLR) forecasting procedure aimed at developing a new methodology able to forecast future ampacity values for rare and extreme events. This is motivated by the belief that to apply DLR network operators must be able to forecast their values and this must be based on conservative approaches able to guarantee the safe operation of the network. The proposed methodology can be summarised as follows: firstly, probabilistic forecasts of conductors’ ampacity are calculated with a non-parametric model, secondly, the lower part of the distribution is replaced with a new distribution calculated with a parametric model. The paper presents also an evaluation of the proposed methodology in network operation, suggesting an application method and highlighting the advantages. The proposed forecasting methodology delivers a high improvement of the lowest quantiles’ reliability, allowing perfect reliability for the 1% quantile and a reduction of roughly 75% in overconfidence for the 0.1% quantile.

Suggested Citation

  • Romain Dupin & Laura Cavalcante & Ricardo J. Bessa & Georges Kariniotakis & Andrea Michiorri, 2020. "Extreme Quantiles Dynamic Line Rating Forecasts and Application on Network Operation," Energies, MDPI, vol. 13(12), pages 1-21, June.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:12:p:3090-:d:371877
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    References listed on IDEAS

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    3. Banerjee, Binayak & Jayaweera, Dilan & Islam, Syed, 2015. "Risk constrained short-term scheduling with dynamic line ratings for increased penetration of wind power," Renewable Energy, Elsevier, vol. 83(C), pages 1139-1146.
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