Papers
Topics
Authors
Recent
Search
2000 character limit reached

ReModels: Quantile Regression Averaging models

Published 18 May 2024 in cs.LG | (2405.11372v1)

Abstract: Electricity price forecasts play a crucial role in making key business decisions within the electricity markets. A focal point in this domain are probabilistic predictions, which delineate future price values in a more comprehensive manner than simple point forecasts. The golden standard in probabilistic approaches to predict energy prices is the Quantile Regression Averaging (QRA) method. In this paper, we present a Python package that encompasses the implementation of QRA, along with modifications of this approach that have appeared in the literature over the past few years. The proposed package also facilitates the acquisition and preparation of data related to electricity markets, as well as the evaluation of model predictions.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (25)
  1. doi:https://doi.org/10.1016/j.rser.2017.05.234.
  2. doi:https://doi.org/10.1016/j.ijforecast.2016.02.001.
  3. doi:https://doi.org/10.1007/s00180-014-0523-0.
  4. doi:https://doi.org/10.1016/j.ijforecast.2019.07.002.
  5. doi:https://doi.org/10.3390/en12132561.
  6. doi:https://doi.org/10.1016/j.ijforecast.2014.12.004.
  7. doi:https://doi.org/10.48550/arXiv.2303.08565.
  8. doi:https://doi.org/10.1016/j.eneco.2021.105121.
  9. doi:https://doi.org/10.1080/07350015.2019.1660177.
  10. doi:https://doi.org/10.48550/arXiv.2302.00411.
  11. doi:https://doi.org/10.1016/0169-7439(87)80084-9.
  12. doi:https://doi.org/10.1109/TPWRS.2017.2734563.
  13. doi:https://doi.org/10.1016/j.apenergy.2021.116983.
  14. doi:https://doi.org/10.1109/TSG.2015.2437877.
  15. doi:https://doi.org/10.1016/j.energy.2018.07.019.
  16. doi:https://doi.org/10.1016/j.enconman.2016.01.023.
  17. doi:https://doi.org/10.1016/j.apenergy.2021.117880.
  18. doi:https://doi.org/10.1016/j.eneco.2023.106843.
  19. doi:https://dx.doi.org/10.2139/ssrn.4592411.
  20. doi:https://doi.org/10.1016/j.ijforecast.2020.09.006.
  21. doi:https://doi.org/10.48550/arXiv.2311.07289.
  22. doi:10.1109/TSG.2018.2833869.
  23. doi:10.1109/TSG.2016.2527820.
  24. doi:https://doi.org/10.1007/s40565-018-0380-x.
  25. doi:10.1109/TSG.2018.2859749.

Summary

No one has generated a summary of this paper yet.

Paper to Video (Beta)

No one has generated a video about this paper yet.

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Collections

Sign up for free to add this paper to one or more collections.