Short-term wind power forecasting based on HHT

DOI

10.2991/iccte-16.2016.156How to use a DOI?

Keywords

Wind power, Hilbert-Huang transform, combination forecasting, EMD

Abstract

Wind power has important effects on the stability and economic operation of power grid with its strong randomness and volatility, which become the important restriction factor of wind power generation. In order to have a good prediction effect on the volatility and uncertainty signal, the article proposes a combination forecasting model based on Hilbert-Huang transform, The power sequence data is decomposed into a number of intrinsic mode function components by the empirical mode decomposition (EMD) method, then different sequence can be forecasting by appropriate models and obtain the final prediction value by adding up the prediction results of each component. The model uses the actual data of wind farm in china to test. The simulation results indicate that the short-term wind power forecasting model established in the paper has higher prediction accuracy.

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/).

Download article (PDF)

TY  - CONF
AU  - Xiaohui Liao
AU  - Dongqiang Yang
AU  - Hongguang Xi
PY  - 2016/01
DA  - 2016/01
TI  - Short-term wind power forecasting based on HHT
BT  - Proceedings of the 2016 International Conference on Civil, Transportation and Environment
PB  - Atlantis Press
SP  - 901
EP  - 905
SN  - 2352-5401
UR  - https://doi.org/10.2991/iccte-16.2016.156
DO  - 10.2991/iccte-16.2016.156
ID  - Liao2016/01
ER  -