Selection of Calibration Windows for Day-Ahead Electricity Price Forecasting
We conduct an extensive empirical study on the selection of calibration windows for day-ahead electricity price forecasting, which involves six year-long datasets from three major power markets and four autoregressive expert models fitted either to raw or transformed prices. Since the variability of...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-09-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1996-1073/11/9/2364 |
| _version_ | 1798039597054164992 |
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| author | Grzegorz Marcjasz Tomasz Serafin Rafał Weron |
| author_facet | Grzegorz Marcjasz Tomasz Serafin Rafał Weron |
| author_sort | Grzegorz Marcjasz |
| collection | DOAJ |
| description | We conduct an extensive empirical study on the selection of calibration windows for day-ahead electricity price forecasting, which involves six year-long datasets from three major power markets and four autoregressive expert models fitted either to raw or transformed prices. Since the variability of prediction errors across windows of different lengths and across datasets can be substantial, selecting ex-ante one window is risky. Instead, we argue that averaging forecasts across different calibration windows is a robust alternative and introduce a new, well-performing weighting scheme for averaging these forecasts. |
| first_indexed | 2024-04-11T21:56:04Z |
| format | Article |
| id | doaj.art-9ad6b6ac6e6046a18e8c616cd0eb4332 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T21:56:04Z |
| publishDate | 2018-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-9ad6b6ac6e6046a18e8c616cd0eb43322022-12-22T04:01:06ZengMDPI AGEnergies1996-10732018-09-01119236410.3390/en11092364en11092364Selection of Calibration Windows for Day-Ahead Electricity Price ForecastingGrzegorz Marcjasz0Tomasz Serafin1Rafał Weron2Department of Operations Research, Faculty of Computer Science and Management, Wrocław University of Science and Technology, 50-370 Wrocław, PolandDepartment of Operations Research, Faculty of Computer Science and Management, Wrocław University of Science and Technology, 50-370 Wrocław, PolandDepartment of Operations Research, Faculty of Computer Science and Management, Wrocław University of Science and Technology, 50-370 Wrocław, PolandWe conduct an extensive empirical study on the selection of calibration windows for day-ahead electricity price forecasting, which involves six year-long datasets from three major power markets and four autoregressive expert models fitted either to raw or transformed prices. Since the variability of prediction errors across windows of different lengths and across datasets can be substantial, selecting ex-ante one window is risky. Instead, we argue that averaging forecasts across different calibration windows is a robust alternative and introduce a new, well-performing weighting scheme for averaging these forecasts.http://www.mdpi.com/1996-1073/11/9/2364electricity price forecastingforecast averagingcalibration windowautoregressionvariance stabilizing transformationconditional predictive ability |
| spellingShingle | Grzegorz Marcjasz Tomasz Serafin Rafał Weron Selection of Calibration Windows for Day-Ahead Electricity Price Forecasting Energies electricity price forecasting forecast averaging calibration window autoregression variance stabilizing transformation conditional predictive ability |
| title | Selection of Calibration Windows for Day-Ahead Electricity Price Forecasting |
| title_full | Selection of Calibration Windows for Day-Ahead Electricity Price Forecasting |
| title_fullStr | Selection of Calibration Windows for Day-Ahead Electricity Price Forecasting |
| title_full_unstemmed | Selection of Calibration Windows for Day-Ahead Electricity Price Forecasting |
| title_short | Selection of Calibration Windows for Day-Ahead Electricity Price Forecasting |
| title_sort | selection of calibration windows for day ahead electricity price forecasting |
| topic | electricity price forecasting forecast averaging calibration window autoregression variance stabilizing transformation conditional predictive ability |
| url | http://www.mdpi.com/1996-1073/11/9/2364 |
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