Wind Power Prediction based on Random Forests

DOI

10.2991/iceeecs-16.2016.73How to use a DOI?

Keywords

Wind Power Generation; Wind Power Prediction; Random Forest

Abstract

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.

Copyright

© 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/).

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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  - 10.2991/iceeecs-16.2016.73
ID  - Zhou2016/12
ER  -