Wind Power Prediction with Cross-Correlation Weighted Nearest Neighbors
| dc.contributor.author | Treiber, Nils André | |
| dc.contributor.author | Kramer, Oliver | |
| dc.contributor.editor | Gómez, Jorge Marx | |
| dc.contributor.editor | Sonnenschein, Michael | |
| dc.contributor.editor | Vogel, Ute | |
| dc.contributor.editor | Winter, Andreas | |
| dc.contributor.editor | Rapp, Barbara | |
| dc.contributor.editor | Giesen, Nils | |
| dc.date.accessioned | 2019-09-16T03:13:06Z | |
| dc.date.available | 2019-09-16T03:13:06Z | |
| dc.date.issued | 2014 | |
| dc.description.abstract | A precise wind power prediction is important for the integration of wind energy into the power grid. Besides numerical weather models for short-term predictions, there is a trend towards the development of statistical data-driven models that can outperform the classical forecast models [1]. In this paper, we improve a statistical prediction model proposed by Kramer and Gieseke [5], by employing a cross-correlation weighted k-nearest neighbor regression model (x-kNN). We demonstrate its superior performance by the comparison with the standard u-kNN method. Even if different pre-processing steps are considered, our regression technique achieves a comparably high accuracy. | de |
| dc.description.uri | http://enviroinfo.eu/sites/default/files/pdfs/vol8514/0063.pdf | de |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/25799 | |
| dc.publisher | BIS-Verlag | |
| dc.relation.ispartof | Proceedings of the 28th Conference on Environmental Informatics - Informatics for Environmental Protection, Sustainable Development and Risk Management | |
| dc.relation.ispartofseries | EnviroInfo | |
| dc.title | Wind Power Prediction with Cross-Correlation Weighted Nearest Neighbors | de |
| dc.type | Text/Conference Paper | |
| gi.citation.publisherPlace | Oldenburg | |
| gi.conference.date | 2014 | |
| gi.conference.location | Oldenburg | |
| gi.conference.sessiontitle | Renewable Energy |