We address the issue of public or bank holidays in electricity load modeling and forecasting. Special characteristics of public holidays such as their classification into fixed-date and weekday holidays are discussed ...We address the issue of public or bank holidays in electricity load modeling and forecasting. Special characteristics of public holidays such as their classification into fixed-date and weekday holidays are discussed in detail. We present state-of-the-art techniques to deal with public holidays such as removing them from the data set,treating them as Sunday dummy or introducing separate holiday dummies. We analyze pros and cons of these approaches and provide a large load forecasting study for Germany that compares the techniques using standard performance and significance measures. Finally, we give general recommendations for the treatment of public holidays in energy forecasting to suggest how the drawbacks particular to most of the state-of-the-art methods can be mitigated. This is especially useful, as the incorporation of holiday effects can improve the forecasting accuracy during public holidays periods by more than 80%, but even for non-holidays periods, the forecasting error can be reduced by approximately 10%.展开更多
文摘We address the issue of public or bank holidays in electricity load modeling and forecasting. Special characteristics of public holidays such as their classification into fixed-date and weekday holidays are discussed in detail. We present state-of-the-art techniques to deal with public holidays such as removing them from the data set,treating them as Sunday dummy or introducing separate holiday dummies. We analyze pros and cons of these approaches and provide a large load forecasting study for Germany that compares the techniques using standard performance and significance measures. Finally, we give general recommendations for the treatment of public holidays in energy forecasting to suggest how the drawbacks particular to most of the state-of-the-art methods can be mitigated. This is especially useful, as the incorporation of holiday effects can improve the forecasting accuracy during public holidays periods by more than 80%, but even for non-holidays periods, the forecasting error can be reduced by approximately 10%.
