Wind Power Real-time Prediction Based on Improved Time Series and Grey Model
Authors
Lanlan Chen, Zixia Pei, Anjia Mao, Yan Liu, Zhuohang Wu
Corresponding Author
Lanlan Chen
Available Online July 2015.
- DOI
- 10.2991/icaees-15.2015.81How to use a DOI?
- Keywords
- wind power, time series, grey model, combination model
- Abstract
This paper aims to establish a suitable wind power forecasting model used to forecast the power of the wind farm. An improved real-time series model is built by linear function and Fourier function. For raw data, the picture of historical data is adopted to correct them. In order to improve the prediction accuracy of wind power, it proposes the linear combination model based on improved time series model and grey model. The model uses a fixed weight method. Mathematical analysis and calculation results show that combination model, which has certain reference value, is simple and can improve the prediction accuracy overall.
- Copyright
- © 2015, 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 - Lanlan Chen AU - Zixia Pei AU - Anjia Mao AU - Yan Liu AU - Zhuohang Wu PY - 2015/07 DA - 2015/07 TI - Wind Power Real-time Prediction Based on Improved Time Series and Grey Model BT - Proceedings of the 3rd International Conference on Advances in Energy and Environmental Science 2015 PB - Atlantis Press SP - 433 EP - 438 SN - 2352-5401 UR - https://doi.org/10.2991/icaees-15.2015.81 DO - 10.2991/icaees-15.2015.81 ID - Chen2015/07 ER -