Title :
Modeling the wind power in-feed in Germany by data decomposition and time series analysis
Author :
Yang He ; Hildmann, M. ; Andersson, G.
Author_Institution :
Dept. of Inf. Technol. & Electr. Eng. (ITET), ETH Zurich, Zurich, Switzerland
Abstract :
The total wind power in-feed in Germany possesses highly predictable seasonal and diurnal patterns. The stochastic variations of wind power have consistent pseudo-cyclic patterns that are related to oscillations of air-pressure systems. The proposed model can replicate the wind power data with the hourly resolution and of time-span of years. The primary purpose of the model is for market applications such as pricing of forward contracts several years ahead. The results of the model may also be used in applications of power system operation such as reliability analysis, day-ahead scheduling, and hour-ahead scheduling.
Keywords :
power generation economics; power markets; pricing; stochastic processes; time series; wind power plants; Germany; air-pressure system oscillation; data decomposition; day-ahead scheduling; diurnal pattern; forward contract pricing; hour-ahead scheduling; market applications; power system operation; pseudocyclic patterns; reliability analysis; seasonal pattern; time series analysis; wind power in-feed modeling; wind power stochastic variations; Cutoff frequency; Data models; Frequency estimation; Histograms; Mathematical model; Time series analysis; Wind power generation; Data Decomposition; Power Markets; Power Systems; Pricing of Forward Contracts; Reliability Analysis; Scheduling; Time Series Analysis; Wind Power;
Conference_Titel :
Power and Energy Society General Meeting, 2012 IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4673-2727-5
Electronic_ISBN :
1944-9925
DOI :
10.1109/PESGM.2012.6345077
