Title :
Short-time wind speed prediction for wind farm based on improved neural network
Author :
Xiaojuan, Han ; Xiyun, Yang ; Juncheng, Liu
Author_Institution :
Control & Comput. Eng. Coll., North China Electr. Power Univ., Beijing, China
Abstract :
The wind speed prediction method based on improved neural network was proposed in this paper by analyzing the relationships between wind direction and wind speed changes. A new network model was created by customizing the network object properties. Wind speed and wind direction were regarded as the network input at the same time using a single network layer to deal with trends in wind direction so as to realize wind speed prediction. Three different kinds of improved network models were provided in this paper, the validity of which was verified by the actual data in wind farm. Simulation results show that: It can significantly improve the network prediction accuracy by continuously improving the structure of neural networks.
Keywords :
neural nets; power engineering computing; wind power plants; improved neural network; network prediction accuracy; short-time wind speed prediction; single network layer; wind direction; wind farm; wind speed; Accuracy; Artificial neural networks; Delay; Predictive models; Wind forecasting; Wind power generation; Wind speed; improved neural network; wind direction; wind speed prediction;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
DOI :
10.1109/WCICA.2010.5554531