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Forecasting the electricity load from one day to one week ahead for the Spanish system operator

Citations

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  1. Ohtsuka, Yoshihiro & Oga, Takashi & Kakamu, Kazuhiko, 2010. "Forecasting electricity demand in Japan: A Bayesian spatial autoregressive ARMA approach," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2721-2735, November.
  2. 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).
  3. Carlos Barros & Luis Gil-Alana, 2013. "Inflation Forecasting in Angola: A Fractional Approach," African Development Review, African Development Bank, vol. 25(1), pages 91-104.
  4. Do, Linh Phuong Catherine & Lin, Kuan-Heng & Molnár, Peter, 2016. "Electricity consumption modelling: A case of Germany," Economic Modelling, Elsevier, vol. 55(C), pages 92-101.
  5. Webel, Karsten & Smyk, Anna, 2023. "Towards seasonal adjustment of infra-monthly time series with JDemetra+," Discussion Papers 24/2023, Deutsche Bundesbank.
  6. Eduardo Caro & Jesús Juan, 2020. "Short-Term Load Forecasting for Spanish Insular Electric Systems," Energies, MDPI, vol. 13(14), pages 1-26, July.
  7. Bessec, Marie & Fouquau, Julien, 2018. "Short-run electricity load forecasting with combinations of stationary wavelet transforms," European Journal of Operational Research, Elsevier, vol. 264(1), pages 149-164.
  8. Florian Ziel & Rick Steinert & Sven Husmann, 2014. "Efficient Modeling and Forecasting of the Electricity Spot Price," Papers 1402.7027, arXiv.org, revised Oct 2014.
  9. Lalitpat Aswanuwath & Warut Pannakkong & Jirachai Buddhakulsomsiri & Jessada Karnjana & Van-Nam Huynh, 2023. "An Improved Hybrid Approach for Daily Electricity Peak Demand Forecasting during Disrupted Situations: A Case Study of COVID-19 Impact in Thailand," Energies, MDPI, vol. 17(1), pages 1-31, December.
  10. Batalla-Bejerano, Joan & Costa-Campi, Maria Teresa & Trujillo-Baute, Elisa, 2016. "Collateral effects of liberalisation: Metering, losses, load profiles and cost settlement in Spain’s electricity system," Energy Policy, Elsevier, vol. 94(C), pages 421-431.
  11. Mauro Bernardi & Francesco Lisi, 2020. "Point and Interval Forecasting of Zonal Electricity Prices and Demand Using Heteroscedastic Models: The IPEX Case," Energies, MDPI, vol. 13(23), pages 1-34, November.
  12. Shao, Zhen & Chao, Fu & Yang, Shan-Lin & Zhou, Kai-Le, 2017. "A review of the decomposition methodology for extracting and identifying the fluctuation characteristics in electricity demand forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 123-136.
  13. Miller, Reid & Golab, Lukasz & Rosenberg, Catherine, 2017. "Modelling weather effects for impact analysis of residential time-of-use electricity pricing," Energy Policy, Elsevier, vol. 105(C), pages 534-546.
  14. Trapero, Juan R. & Pedregal, Diego J., 2009. "Frequency domain methods applied to forecasting electricity markets," Energy Economics, Elsevier, vol. 31(5), pages 727-735, September.
  15. Webel, Karsten, 2022. "A review of some recent developments in the modelling and seasonal adjustment of infra-monthly time series," Discussion Papers 31/2022, Deutsche Bundesbank.
  16. Li, Z. & Hurn, A.S. & Clements, A.E., 2017. "Forecasting quantiles of day-ahead electricity load," Energy Economics, Elsevier, vol. 67(C), pages 60-71.
  17. Psiloglou, B.E. & Giannakopoulos, C. & Majithia, S. & Petrakis, M., 2009. "Factors affecting electricity demand in Athens, Greece and London, UK: A comparative assessment," Energy, Elsevier, vol. 34(11), pages 1855-1863.
  18. Nguyen, Hang T. & Nabney, Ian T., 2010. "Short-term electricity demand and gas price forecasts using wavelet transforms and adaptive models," Energy, Elsevier, vol. 35(9), pages 3674-3685.
  19. repec:qut:auncer:wp103 is not listed on IDEAS
  20. Taylor, James W., 2008. "An evaluation of methods for very short-term load forecasting using minute-by-minute British data," International Journal of Forecasting, Elsevier, vol. 24(4), pages 645-658.
  21. Vaz, Lucélia Viviane & Filho, Getulio Borges da Silveira, 2017. "Functional Autoregressive Models: An Application to Brazilian Hourly Electricity Load," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 37(2), November.
  22. Huber, Jakob & Stuckenschmidt, Heiner, 2020. "Daily retail demand forecasting using machine learning with emphasis on calendric special days," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1420-1438.
  23. Clements, A.E. & Hurn, A.S. & Li, Z., 2016. "Forecasting day-ahead electricity load using a multiple equation time series approach," European Journal of Operational Research, Elsevier, vol. 251(2), pages 522-530.
  24. Ozhegov, Evgeniy & Popova, Evgeniya, 2017. "Demand for electricity and weather conditions: Nonparametric analysis," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 46, pages 55-73.
  25. López, Miguel, 2020. "Daylight effect on the electricity demand in Spain and assessment of Daylight Saving Time policies," Energy Policy, Elsevier, vol. 140(C).
  26. Do, Linh Phuong Catherine & Lyócsa, Štefan & Molnár, Peter, 2021. "Residual electricity demand: An empirical investigation," Applied Energy, Elsevier, vol. 283(C).
  27. Verstraete, Gylian & Aghezzaf, El-Houssaine & Desmet, Bram, 2019. "A data-driven framework for predicting weather impact on high-volume low-margin retail products," Journal of Retailing and Consumer Services, Elsevier, vol. 48(C), pages 169-177.
  28. Ashish Shrestha & Bishal Ghimire & Francisco Gonzalez-Longatt, 2021. "A Bayesian Model to Forecast the Time Series Kinetic Energy Data for a Power System," Energies, MDPI, vol. 14(11), pages 1-15, June.
  29. Kim, Myung Suk, 2013. "Modeling special-day effects for forecasting intraday electricity demand," European Journal of Operational Research, Elsevier, vol. 230(1), pages 170-180.
  30. Miguel López & Sergio Valero & Carlos Sans & Carolina Senabre, 2020. "Use of Available Daylight to Improve Short-Term Load Forecasting Accuracy," Energies, MDPI, vol. 14(1), pages 1-14, December.
  31. Bakhat, Mohcine & Rosselló, Jaume, 2011. "Estimation of tourism-induced electricity consumption: The case study of Balearics Islands, Spain," Energy Economics, Elsevier, vol. 33(3), pages 437-444, May.
  32. Jose Juan Caceres-Hernandez & Gloria Martin-Rodriguez & Jonay Hernandez-Martin, 2022. "A proposal for measuring and comparing seasonal variations in hourly economic time series," Empirical Economics, Springer, vol. 62(4), pages 1995-2021, April.
  33. Alves da Silva, Alexandre P. & Ferreira, Vitor H. & Velasquez, Roberto M.G., 2008. "Input space to neural network based load forecasters," International Journal of Forecasting, Elsevier, vol. 24(4), pages 616-629.
  34. Brabec, Marek & Konár, Ondrej & Pelikán, Emil & Malý, Marek, 2008. "A nonlinear mixed effects model for the prediction of natural gas consumption by individual customers," International Journal of Forecasting, Elsevier, vol. 24(4), pages 659-678.
  35. Arora, Siddharth & Taylor, James W., 2018. "Rule-based autoregressive moving average models for forecasting load on special days: A case study for France," European Journal of Operational Research, Elsevier, vol. 266(1), pages 259-268.
  36. Liang, Zhuoran & Tian, Zhan & Sun, Laixiang & Feng, Kuishuang & Zhong, Honglin & Gu, Tingting & Liu, Xiaochen, 2016. "Heat wave, electricity rationing, and trade-offs between environmental gains and economic losses: The example of Shanghai," Applied Energy, Elsevier, vol. 184(C), pages 951-959.
  37. Soares, Lacir J. & Medeiros, Marcelo C., 2008. "Modeling and forecasting short-term electricity load: A comparison of methods with an application to Brazilian data," International Journal of Forecasting, Elsevier, vol. 24(4), pages 630-644.
  38. Óscar Trull & J. Carlos García-Díaz & Alicia Troncoso, 2019. "Application of Discrete-Interval Moving Seasonalities to Spanish Electricity Demand Forecasting during Easter," Energies, MDPI, vol. 12(6), pages 1-16, March.
  39. Diego Aineto & Javier Iranzo-Sánchez & Lenin G. Lemus-Zúñiga & Eva Onaindia & Javier F. Urchueguía, 2019. "On the Influence of Renewable Energy Sources in Electricity Price Forecasting in the Iberian Market," Energies, MDPI, vol. 12(11), pages 1-20, May.
  40. Thomas Mobius & Mira Watermeyer & Oliver Grothe & Felix Musgens, 2023. "Enhancing Energy System Models Using Better Load Forecasts," Papers 2302.11017, arXiv.org.
  41. Oscar Trull & Angel Peiró-Signes & J. Carlos García-Díaz, 2019. "Electricity Forecasting Improvement in a Destination Using Tourism Indicators," Sustainability, MDPI, vol. 11(13), pages 1-16, July.
  42. Ahmad, Tanveer & Zhang, Hongcai, 2020. "Novel deep supervised ML models with feature selection approach for large-scale utilities and buildings short and medium-term load requirement forecasts," Energy, Elsevier, vol. 209(C).
  43. Miguel Carrión & Rafael Zárate-Miñano & Ruth Domínguez, 2018. "A Practical Formulation for Ex-Ante Scheduling of Energy and Reserve in Renewable-Dominated Power Systems: Case Study of the Iberian Peninsula," Energies, MDPI, vol. 11(8), pages 1-22, July.
  44. Ziel, Florian & Steinert, Rick & Husmann, Sven, 2015. "Efficient modeling and forecasting of electricity spot prices," Energy Economics, Elsevier, vol. 47(C), pages 98-111.
  45. Taylor, James W., 2010. "Triple seasonal methods for short-term electricity demand forecasting," European Journal of Operational Research, Elsevier, vol. 204(1), pages 139-152, July.
  46. Cruz E. Borges & Yoseba K. Penya & Iván Fernández & Juan Prieto & Oscar Bretos, 2013. "Assessing Tolerance-Based Robust Short-Term Load Forecasting in Buildings," Energies, MDPI, vol. 6(4), pages 1-20, April.
  47. Miguel López & Carlos Sans & Sergio Valero & Carolina Senabre, 2018. "Empirical Comparison of Neural Network and Auto-Regressive Models in Short-Term Load Forecasting," Energies, MDPI, vol. 11(8), pages 1-19, August.
  48. Mauro Bernardi & Lea Petrella, 2015. "Multiple seasonal cycles forecasting model: the Italian electricity demand," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(4), pages 671-695, November.
  49. Miguel López & Carlos Sans & Sergio Valero & Carolina Senabre, 2019. "Classification of Special Days in Short-Term Load Forecasting: The Spanish Case Study," Energies, MDPI, vol. 12(7), pages 1-31, April.
  50. Huurman, Christian & Ravazzolo, Francesco & Zhou, Chen, 2012. "The power of weather," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3793-3807.
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