Title :
A literature review of wind forecasting technology in the world
Author :
Wu, Yuan-Kang ; Hong, Jing-Shan
Author_Institution :
Nat. Penghu Univ., Taipei
Abstract :
Large intermittent generations have grown the influence on the grid security, system operation, and market economics. Although wind energy may not be dispatched, the cost impacts of wind can be substantially reduced if the wind energy can be scheduled using accurate wind forecasting. In other words, the improvement of the performance of wind power forecasting tool has significant technology and economic impact on the system operation with increased wind power penetration. Forecasting has been a vital part of business planning in today´s competitive environment, especially in areas characterized by a high concentration of wind generation and a limited capacity of network. The target of this paper is to present a critical literature review and an up-to-date bibliography on wind forecasting technologies over the world. Various forecasting aspects concerning the wind speed and power have been highlighted. These technologies based on numeric weather prediction (NWP) methods, statistical methods, methods based upon artificial neural networks (ANNs), and hybrid forecasting approaches will be discussed. Furthermore, the difference between wind speed and power forecasting, the lead time of forecasting, and the further research will also be discussed in this paper.
Keywords :
neural nets; power engineering computing; power generation economics; power generation planning; power grids; wind power plants; artificial neural networks; business planning; grid security; market economics; numeric weather prediction methods; statistical methods; system operation; wind forecasting technology; wind power forecasting; wind power penetration; Economic forecasting; Environmental economics; Power generation economics; Power system economics; Technology forecasting; Weather forecasting; Wind energy; Wind energy generation; Wind forecasting; Wind speed; numeric weather prediction; statistical methods; wind power forecasting;
Conference_Titel :
Power Tech, 2007 IEEE Lausanne
Conference_Location :
Lausanne
Print_ISBN :
978-1-4244-2189-3
Electronic_ISBN :
978-1-4244-2190-9
DOI :
10.1109/PCT.2007.4538368