Title :
Synthetic wind speed time series with Markov and ARMA models: Comparison for different use cases
Author :
Rab, Nikolaus ; Leimgruber, Fabian ; Esterl, Tara
Author_Institution :
Inst. of Energy Syst. & Electr. Drives, Vienna Univ. of Technol., Vienna, Austria
Abstract :
The impact of stochastic available generation of wind power on system operation and planning gained rising importance due to the increasing amount of wind power plants. Many models used for synthetic wind speed time series are based on ARMA-GARCH processes or Markov chains. These two approaches are compared regarding their feasibility to depict the statistical properties of the original wind speed distributions and their time series characteristics. Several data sets from different locations with different characteristics are considered. It can be shown that the ARMA-GARCH model can depict the wind speed series more applicable especially for covering the observed autocorrelations and inter-annual trends. However the parametric distribution for the ARMA-GARCH approach has to be selected carefully. The well-established Weibull distribution can be shown to be inappropriate for some sites.
Keywords :
Markov processes; Weibull distribution; autoregressive moving average processes; power generation planning; time series; wind power plants; ARMA-GARCH process; Markov chain; Weibull distribution; parametric distribution; power system operation; power system planning; synthetic wind speed time series; wind power generation; wind power plant; wind speed distribution statistical properties; Correlation; Data models; Hidden Markov models; Markov processes; Time series analysis; Weibull distribution; Wind speed; ARMA-GARCH processes; Markov chains; Wind speed; diurnal trends; synthetic time series; time series analysis;
Conference_Titel :
European Energy Market (EEM), 2015 12th International Conference on the
Conference_Location :
Lisbon
DOI :
10.1109/EEM.2015.7216770