%0 Journal Article %1 Huang.Chalabi1995 %A Huang, Z. %A Chalabi, Z. S. %D 1995 %J Journal of Wind Engineering and Industrial Aerodynamics %K ARIMA Wind forecasting, models, series series, simulation, spectrum time %P 311--322 %T Use of Time-Series Analysis to model and Forecast Wind Speed %V 56 %X A linear, time-varying autoregressive (AR) process is used to model and forecast wind speed. This modelling approach takes into account the non-stationary nature of wind speed, The time-varying parameters of the AR model are modelled by smoothed, integrated random walk processes. A Kalman filter is used to estimate the time-varying parameters of the AR model. The algorithm is used to forecast wind speed from 1 h to a few hours ahead.

@article{Huang.Chalabi1995, abstract = {A linear, time-varying autoregressive (AR) process is used to model and forecast wind speed. This modelling approach takes into account the non-stationary nature of wind speed, The time-varying parameters of the AR model are modelled by smoothed, integrated random walk processes. A Kalman filter is used to estimate the time-varying parameters of the AR model. The algorithm is used to forecast wind speed from 1 h to a few hours ahead.}, added-at = {2011-09-01T13:26:03.000+0200}, author = {Huang, Z. and Chalabi, Z. S.}, biburl = {https://www.bibsonomy.org/bibtex/20c717f0bff24e79ee4aa063bbee04f6d/procomun}, file = {Huang.Chalabi1995.pdf:Huang.Chalabi1995.pdf:PDF}, interhash = {9a151071107e0b44b13d1d4ab4c6448b}, intrahash = {0c717f0bff24e79ee4aa063bbee04f6d}, journal = {Journal of Wind Engineering and Industrial Aerodynamics}, keywords = {ARIMA Wind forecasting, models, series series, simulation, spectrum time}, owner = {oscar}, pages = {311--322}, refid = {Huang.Chalabi1995}, timestamp = {2011-09-02T08:25:25.000+0200}, title = {Use of Time-Series Analysis to model and Forecast Wind Speed}, volume = 56, year = 1995 }