Forecast on Short-Term Wind Speed and Wind Farm Power Generation

DOI

10.2991/nceece-15.2016.15How to use a DOI?

Keywords

Winds Power; Wing Speed; Forecast

Abstract

Winds forecast is of great significance for operating a wind farm and power systems. The accurately predict wind speed can effectively reduce the adverse impact of wind farms on the power system, while increase the wind farm in the electricity market competitiveness. This paper studied time series and neural network forecasting for wind speed, and as a basis for proposed change right combination of multi-model prediction of wind speed forecasting. This method takes into account the characteristics of each individual prediction methods, different combinations of individual prediction methods to improve the prediction accuracy. Finally, wind power predicted by the results of comparative analysis found that for the prediction accuracy of wind speed is higher than the wind power 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/).

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TY  - CONF
AU  - Yiping Cheng
PY  - 2015/12
DA  - 2015/12
TI  - Forecast on Short-Term Wind Speed and Wind Farm Power Generation
BT  - Proceedings of the 2015 4th National Conference on Electrical, Electronics and Computer Engineering
PB  - Atlantis Press
SP  - 80
EP  - 86
SN  - 2352-5401
UR  - https://doi.org/10.2991/nceece-15.2016.15
DO  - 10.2991/nceece-15.2016.15
ID  - Cheng2015/12
ER  -