Title :
The Online Forecasting Research of Short-Term Wind Speed and Power Generation at Wind Farm Based on Phase Space Reconstruction
Author :
Yajun, Han ; Jing, Liu
Abstract :
It is difficult to be accurately predicted for wind power generation´s random, intermittent and volatility. According to the strong chaotic characteristics of wind speed, the optimal time delay and embedding dimensions of wind speed are determined by using a short-term prediction of phase space reconstruction theory. After the sample space is reconstructed, the short-term wind speed is carried out by BP neural network. The experimental results show that the higher forecasting accuracy of short-term power generation can be obtained.
Keywords :
Biological neural networks; Delays; Forecasting; Power generation; Time series analysis; Wind speed; BP neural network; Phase space reconstruction; complex self-correlation method; false zero method; wind speed forecast;
Conference_Titel :
Measuring Technology and Mechatronics Automation (ICMTMA), 2015 Seventh International Conference on
Conference_Location :
Nanchang, China
Print_ISBN :
978-1-4673-7142-1
DOI :
10.1109/ICMTMA.2015.300