Use of Time-Series Analysis to model and Forecast Wind Speed
Z. Huang, and Z. Chalabi. Journal of Wind Engineering and Industrial Aerodynamics, (1995)
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.
%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
}