Reconciliation of wind power forecasts in spatial hierarchies
Summary We consider reconciliation of wind power forecasts in a spatial hierarchy with three aggregation levels. We produce base forecasts for the bottom level consisting of 407 substations (connection points for local groups of wind turbines). State‐of‐the‐art forecasts from a commercial forecast p...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-06-01
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| Series: | Wind Energy |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/we.2819 |
| _version_ | 1797831711651790848 |
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| author | Mads E. Hansen Nystrup Peter Jan K. Møller Madsen Henrik |
| author_facet | Mads E. Hansen Nystrup Peter Jan K. Møller Madsen Henrik |
| author_sort | Mads E. Hansen |
| collection | DOAJ |
| description | Summary We consider reconciliation of wind power forecasts in a spatial hierarchy with three aggregation levels. We produce base forecasts for the bottom level consisting of 407 substations (connection points for local groups of wind turbines). State‐of‐the‐art forecasts from a commercial forecast provider are available for the middle and top levels, which consist of 15 regions and the entire Western Denmark (DK1), respectively. We find that the accuracy of the total forecast can be improved through spatial reconciliation, even with a relatively simple model used at the lowest level of the hierarchy. Computing the base forecasts for the substations using wind speed as the only predictor, the RMSE of the DK1 forecast is reduced by 20.5%, while the RMSE of the regional forecasts is reduced by 4.7%, on average, through reconciliation. The increase in accuracy is partly due to reduced errors in the individual regional forecasts and partly due to reduced residual correlation between the reconciled regional forecasts. We test adaptive estimation of the covariance matrix of the base forecast errors and find that it has a limited impact on the accuracy, hinting toward a time‐stable covariance structure. |
| first_indexed | 2024-04-09T13:56:07Z |
| format | Article |
| id | doaj.art-d25732f69807485980a7effc817a6456 |
| institution | Directory Open Access Journal |
| issn | 1095-4244 1099-1824 |
| language | English |
| last_indexed | 2024-04-09T13:56:07Z |
| publishDate | 2023-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | Wind Energy |
| spelling | doaj.art-d25732f69807485980a7effc817a64562023-05-08T05:34:06ZengWileyWind Energy1095-42441099-18242023-06-0126661563210.1002/we.2819Reconciliation of wind power forecasts in spatial hierarchiesMads E. Hansen0Nystrup Peter1Jan K. Møller2Madsen Henrik3DTU Compute Technical University of Denmark Lyngby DenmarkDTU Compute Technical University of Denmark Lyngby DenmarkDTU Compute Technical University of Denmark Lyngby DenmarkDTU Compute Technical University of Denmark Lyngby DenmarkSummary We consider reconciliation of wind power forecasts in a spatial hierarchy with three aggregation levels. We produce base forecasts for the bottom level consisting of 407 substations (connection points for local groups of wind turbines). State‐of‐the‐art forecasts from a commercial forecast provider are available for the middle and top levels, which consist of 15 regions and the entire Western Denmark (DK1), respectively. We find that the accuracy of the total forecast can be improved through spatial reconciliation, even with a relatively simple model used at the lowest level of the hierarchy. Computing the base forecasts for the substations using wind speed as the only predictor, the RMSE of the DK1 forecast is reduced by 20.5%, while the RMSE of the regional forecasts is reduced by 4.7%, on average, through reconciliation. The increase in accuracy is partly due to reduced errors in the individual regional forecasts and partly due to reduced residual correlation between the reconciled regional forecasts. We test adaptive estimation of the covariance matrix of the base forecast errors and find that it has a limited impact on the accuracy, hinting toward a time‐stable covariance structure.https://doi.org/10.1002/we.2819forecast reconciliationforecastingspatial hierarchywind power |
| spellingShingle | Mads E. Hansen Nystrup Peter Jan K. Møller Madsen Henrik Reconciliation of wind power forecasts in spatial hierarchies Wind Energy forecast reconciliation forecasting spatial hierarchy wind power |
| title | Reconciliation of wind power forecasts in spatial hierarchies |
| title_full | Reconciliation of wind power forecasts in spatial hierarchies |
| title_fullStr | Reconciliation of wind power forecasts in spatial hierarchies |
| title_full_unstemmed | Reconciliation of wind power forecasts in spatial hierarchies |
| title_short | Reconciliation of wind power forecasts in spatial hierarchies |
| title_sort | reconciliation of wind power forecasts in spatial hierarchies |
| topic | forecast reconciliation forecasting spatial hierarchy wind power |
| url | https://doi.org/10.1002/we.2819 |
| work_keys_str_mv | AT madsehansen reconciliationofwindpowerforecastsinspatialhierarchies AT nystruppeter reconciliationofwindpowerforecastsinspatialhierarchies AT jankmøller reconciliationofwindpowerforecastsinspatialhierarchies AT madsenhenrik reconciliationofwindpowerforecastsinspatialhierarchies |