DocumentCode :
267649
Title :
Statistical analysis of large scale wind power generation using Monte Carlo Simulations
Author :
Koivisto, Matti ; Ekstrom, Jussi ; Saarijarvi, Eero ; Haarla, Liisa ; Seppanen, Janne ; Mellin, Ilkka
Author_Institution :
Dept. of Electr. Eng., Aalto Univ., Espoo, Finland
fYear :
2014
fDate :
18-22 Aug. 2014
Firstpage :
1
Lastpage :
7
Abstract :
As more wind power generation is installed, the effect of wind power on the electric power system is becoming increasingly important. This paper presents two time series models that can be used in Monte Carlo simulations to assess the risk of very high or low wind speeds occurring contemporaneously in multiple locations. The suitability of the models is assessed for existing measured locations and new non-measured locations. The simulation results are verified against measurements from 19 locations from Finland. Also, an example scenario is given to show the effect of geographical spread on the aggregate power generation of multiple wind power generation units.
Keywords :
Monte Carlo methods; time series; wind power plants; Finland; Monte Carlo simulations; aggregate power generation; geographical spread; large scale wind power generation; multiple wind power generation units; statistical analysis; time series models; Analytical models; Correlation; Data models; Monte Carlo methods; Time series analysis; Wind power generation; Wind speed; Copula; Generalized Pareto distribution; Monte Carlo simulation; Multivariate autoregressive model; Weibull distribution; Wind power; Wind speed;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Systems Computation Conference (PSCC), 2014
Conference_Location :
Wroclaw
Type :
conf
DOI :
10.1109/PSCC.2014.7038461
Filename :
7038461
Link To Document :
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