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Global energy forecasting competition 2017: Hierarchical probabilistic load forecasting

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  1. Trull, Oscar & García-Díaz, J. Carlos & Troncoso, Alicia, 2021. "One-day-ahead electricity demand forecasting in holidays using discrete-interval moving seasonalities," Energy, Elsevier, vol. 231(C).
  2. de Hoog, Julian & Abdulla, Khalid, 2019. "Data visualization and forecast combination for probabilistic load forecasting in GEFCom2017 final match," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1451-1459.
  3. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2022. "Predicting/hypothesizing the findings of the M5 competition," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1337-1345.
  4. Landgraf, Andrew J., 2019. "An ensemble approach to GEFCom2017 probabilistic load forecasting," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1432-1438.
  5. Kanda, Isao & Veguillas, J.M. Quintana, 2019. "Data preprocessing and quantile regression for probabilistic load forecasting in the GEFCom2017 final match," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1460-1468.
  6. Dimoulkas, I. & Mazidi, P. & Herre, L., 2019. "Neural networks for GEFCom2017 probabilistic load forecasting," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1409-1423.
  7. Hyndman, Rob J., 2020. "A brief history of forecasting competitions," International Journal of Forecasting, Elsevier, vol. 36(1), pages 7-14.
  8. Monika Zimmermann & Florian Ziel, 2024. "Efficient mid-term forecasting of hourly electricity load using generalized additive models," Papers 2405.17070, arXiv.org.
  9. Roberto Baviera & Pietro Manzoni, 2022. "Tree-Based Learning in RNNs for Power Consumption Forecasting," Papers 2209.01378, arXiv.org.
  10. Wang, Xiaoqian & Kang, Yanfei & Hyndman, Rob J. & Li, Feng, 2023. "Distributed ARIMA models for ultra-long time series," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1163-1184.
  11. Müller, Alfred & Reuber, Matthias, 2023. "A copula-based time series model for global horizontal irradiation," International Journal of Forecasting, Elsevier, vol. 39(2), pages 869-883.
  12. Cameron Roach & Rob Hyndman & Souhaib Ben Taieb, 2021. "Non‐linear mixed‐effects models for time series forecasting of smart meter demand," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1118-1130, September.
  13. Nystrup, Peter & Lindström, Erik & Møller, Jan K. & Madsen, Henrik, 2021. "Dimensionality reduction in forecasting with temporal hierarchies," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1127-1146.
  14. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
  15. Smyl, Slawek & Hua, N. Grace, 2019. "Machine learning methods for GEFCom2017 probabilistic load forecasting," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1424-1431.
  16. Kong, Xiangyu & Li, Chuang & Wang, Chengshan & Zhang, Yusen & Zhang, Jian, 2020. "Short-term electrical load forecasting based on error correction using dynamic mode decomposition," Applied Energy, Elsevier, vol. 261(C).
  17. Saima Akhtar & Sulman Shahzad & Asad Zaheer & Hafiz Sami Ullah & Heybet Kilic & Radomir Gono & Michał Jasiński & Zbigniew Leonowicz, 2023. "Short-Term Load Forecasting Models: A Review of Challenges, Progress, and the Road Ahead," Energies, MDPI, vol. 16(10), pages 1-29, May.
  18. Tiago Silveira Gontijo & Marcelo Azevedo Costa, 2020. "Forecasting Hierarchical Time Series in Power Generation," Energies, MDPI, vol. 13(14), pages 1-17, July.
  19. Juan A. Dominguez-Jimenez & Javier E. Campillo & Oscar Danilo Montoya & Enrique Delahoz & Jesus C. Hernández, 2020. "Seasonality Effect Analysis and Recognition of Charging Behaviors of Electric Vehicles: A Data Science Approach," Sustainability, MDPI, vol. 12(18), pages 1-18, September.
  20. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios & Chen, Zhi & Gaba, Anil & Tsetlin, Ilia & Winkler, Robert L., 2022. "The M5 uncertainty competition: Results, findings and conclusions," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1365-1385.
  21. Athanasopoulos, George & Hyndman, Rob J. & Kourentzes, Nikolaos & Panagiotelis, Anastasios, 2024. "Forecast reconciliation: A review," International Journal of Forecasting, Elsevier, vol. 40(2), pages 430-456.
  22. Sobhani, Masoud & Hong, Tao & Martin, Claude, 2020. "Temperature anomaly detection for electric load forecasting," International Journal of Forecasting, Elsevier, vol. 36(2), pages 324-333.
  23. Zacharie De Grève & Jérémie Bottieau & David Vangulick & Aurélien Wautier & Pierre-David Dapoz & Adriano Arrigo & Jean-François Toubeau & François Vallée, 2020. "Machine Learning Techniques for Improving Self-Consumption in Renewable Energy Communities," Energies, MDPI, vol. 13(18), pages 1-17, September.
  24. Moreno-Carbonell, Santiago & Sánchez-Úbeda, Eugenio F. & Muñoz, Antonio, 2020. "Rethinking weather station selection for electric load forecasting using genetic algorithms," International Journal of Forecasting, Elsevier, vol. 36(2), pages 695-712.
  25. Makridakis, Spyros & Hyndman, Rob J. & Petropoulos, Fotios, 2020. "Forecasting in social settings: The state of the art," International Journal of Forecasting, Elsevier, vol. 36(1), pages 15-28.
  26. Santiago Moreno-Carbonell & Eugenio F. Sánchez-Úbeda & Antonio Muñoz, 2020. "Time Series Decomposition of the Daily Outdoor Air Temperature in Europe for Long-Term Energy Forecasting in the Context of Climate Change," Energies, MDPI, vol. 13(7), pages 1-28, March.
  27. Yanwei Jia & Jussi Keppo & Ville Satopää, 2023. "Herding in Probabilistic Forecasts," Management Science, INFORMS, vol. 69(5), pages 2713-2732, May.
  28. Xu, Xiuqin & Chen, Ying & Goude, Yannig & Yao, Qiwei, 2021. "Day-ahead probabilistic forecasting for French half-hourly electricity loads and quantiles for curve-to-curve regression," LSE Research Online Documents on Economics 120774, London School of Economics and Political Science, LSE Library.
  29. Mallen, Alex T. & Lange, Henning & Kutz, J. Nathan, 2024. "Deep Probabilistic Koopman: Long-term time-series forecasting under periodic uncertainties," International Journal of Forecasting, Elsevier, vol. 40(3), pages 859-868.
  30. Xu, Xiuqin & Chen, Ying & Goude, Yannig & Yao, Qiwei, 2021. "Day-ahead probabilistic forecasting for French half-hourly electricity loads and quantiles for curve-to-curve regression," Applied Energy, Elsevier, vol. 301(C).
  31. Richard Bean, 2023. "Forecasting the Monash Microgrid for the IEEE-CIS Technical Challenge," Energies, MDPI, vol. 16(3), pages 1-23, January.
  32. Roach, Cameron, 2019. "Reconciled boosted models for GEFCom2017 hierarchical probabilistic load forecasting," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1439-1450.
  33. Buzna, Luboš & De Falco, Pasquale & Ferruzzi, Gabriella & Khormali, Shahab & Proto, Daniela & Refa, Nazir & Straka, Milan & van der Poel, Gijs, 2021. "An ensemble methodology for hierarchical probabilistic electric vehicle load forecasting at regular charging stations," Applied Energy, Elsevier, vol. 283(C).
  34. Mike Ludkovski & Glen Swindle & Eric Grannan, 2022. "Large Scale Probabilistic Simulation of Renewables Production," Papers 2205.04736, arXiv.org.
  35. Yang, Dazhi & Wang, Wenting & Gueymard, Christian A. & Hong, Tao & Kleissl, Jan & Huang, Jing & Perez, Marc J. & Perez, Richard & Bright, Jamie M. & Xia, Xiang’ao & van der Meer, Dennis & Peters, Ian , 2022. "A review of solar forecasting, its dependence on atmospheric sciences and implications for grid integration: Towards carbon neutrality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
  36. Xin Ma & Yubin Cai & Hong Yuan & Yanqiao Deng, 2023. "Partially Linear Component Support Vector Machine for Primary Energy Consumption Forecasting of the Electric Power Sector in the United States," Sustainability, MDPI, vol. 15(9), pages 1-26, April.
  37. Yang, Dazhi & van der Meer, Dennis, 2021. "Post-processing in solar forecasting: Ten overarching thinking tools," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
  38. Spyros Makridakis & Chris Fry & Fotios Petropoulos & Evangelos Spiliotis, 2022. "The Future of Forecasting Competitions: Design Attributes and Principles," INFORMS Joural on Data Science, INFORMS, vol. 1(1), pages 96-113, April.
  39. Ankitha Nandipura Prasanna & Priscila Grecov & Angela Dieyu Weng & Christoph Bergmeir, 2022. "Causal Effect Estimation with Global Probabilistic Forecasting: A Case Study of the Impact of Covid-19 Lockdowns on Energy Demand," Papers 2209.08885, arXiv.org, revised Oct 2022.
  40. Xiao, Tong & Xu, Peng & He, Ruikai & Sha, Huajing, 2022. "Status quo and opportunities for building energy prediction in limited data Context—Overview from a competition," Applied Energy, Elsevier, vol. 305(C).
  41. Xing, Yazhou & Zhang, Su & Wen, Peng & Shao, Limin & Rouyendegh, Babak Daneshvar, 2020. "Load prediction in short-term implementing the multivariate quantile regression," Energy, Elsevier, vol. 196(C).
  42. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2022. "The M5 competition: Background, organization, and implementation," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1325-1336.
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