Wind Power Prediction based on Random Forests
- https://doi.org/10.2991/iceeecs-16.2016.73How to use a DOI?
- Wind Power Generation; Wind Power Prediction; Random Forest
With a massive increase of wind power, the prediction of wind power is becoming increasingly important. The algorithm of Random forests has many advantages such as less adjustable parameters, higher precision of prediction and better generalization ability. This algorithm has been widely applied in numerous fields such as medical science, management and economics. However there is no application in short-term wind power prediction yet. In this paper, the random forest algorithm will be applied to the short-term wind power prediction. The random forest regression model is established. The powers of a wind farm are predicted. The effectiveness of random forest regression algorithm adopted is verified in wind power prediction.
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Zehong Zhou AU - Xiaohui Li AU - Huaren Wu PY - 2016/12 DA - 2016/12 TI - Wind Power Prediction based on Random Forests BT - Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016) PB - Atlantis Press SP - 352 EP - 356 SN - 2352-538X UR - https://doi.org/10.2991/iceeecs-16.2016.73 DO - https://doi.org/10.2991/iceeecs-16.2016.73 ID - Zhou2016/12 ER -