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GEFCom2014 probabilistic electric load forecasting: An integrated solution with forecast combination and residual simulation

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  • Xie, Jingrui
  • Hong, Tao

Abstract

We present an integrated solution for probabilistic load forecasting. The proposed solution was the basis for Jingrui Xie’s submission to the probabilistic load forecasting track of the Global Energy Forecasting Competition 2014 (GEFCom2014), and consists of three components: pre-processing, forecasting, and post-processing. The pre-processing component includes data cleansing and temperature station selection. The forecasting component involves the development of point forecasting models, forecast combination, and temperature scenario based probabilistic forecasting. The post-processing component embodies residual simulation for probabilistic forecasting. In addition, we also discuss several other variations that were implemented during the competition.

Suggested Citation

  • Xie, Jingrui & Hong, Tao, 2016. "GEFCom2014 probabilistic electric load forecasting: An integrated solution with forecast combination and residual simulation," International Journal of Forecasting, Elsevier, vol. 32(3), pages 1012-1016.
    • Handle: RePEc:eee:intfor:v:32:y:2016:i:3:p:1012-1016
    DOI: 10.1016/j.ijforecast.2015.11.005
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    1. Hong, Tao & Pinson, Pierre & Fan, Shu, 2014. "Global Energy Forecasting Competition 2012," International Journal of Forecasting, Elsevier, vol. 30(2), pages 357-363.
    2. Hong, Tao & Wang, Pu & White, Laura, 2015. "Weather station selection for electric load forecasting," International Journal of Forecasting, Elsevier, vol. 31(2), pages 286-295.
    3. Hong, Tao & Pinson, Pierre & Fan, Shu & Zareipour, Hamidreza & Troccoli, Alberto & Hyndman, Rob J., 2016. "Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond," International Journal of Forecasting, Elsevier, vol. 32(3), pages 896-913.
    4. Tao Hong & Jason Wilson & Jingrui Xie, 2013. "Long term probabilistic load forecasting and normalization with hourly information," HSC Research Reports HSC/13/13, Hugo Steinhaus Center, Wroclaw University of Technology.
    5. Hong, Tao & Fan, Shu, 2016. "Probabilistic electric load forecasting: A tutorial review," International Journal of Forecasting, Elsevier, vol. 32(3), pages 914-938.
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    Cited by:

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