Title :
A comparative metric to quantify the variability of wind power
Author :
Doody, P. ; Santoso, S.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Texas at Austin, Austin, TX, USA
Abstract :
The stochastic nature of wind power severely affects the stability of the electric grid. It is well known that power quality and project economics are adversely affected by increased intermittency and variability. Thus, an accurate, simple, and powerful metric for comparing the variability of different power sources would serve as a useful figure of merit. The current coefficient of variation metric has significant shortcomings for quantifying the variability of a stochastic power source´s output. This paper exposed those shortcomings in detail and a new metric is proposed for quantifying the variability of power from a wind farm in particular or for an intermittent power source in general. The proposed metric is calculated from the spectral decomposition of a power source´s autocorrelation function. The intermittency metric compares the components of the wind power that vary with infra-diurnal frequencies to the mean power output.
Keywords :
correlation methods; power generation economics; power grids; power supply quality; power system measurement; power system stability; wind power plants; autocorrelation function; electric grid stability; infra-diurnal frequency; power quality; project economics; spectral decomposition; stochastic power sources; wind farm; wind power variability; Autocorrelation; Frequency; Power generation; Power generation economics; Stability; Stochastic processes; Wind energy; Wind energy generation; Wind farms; Wind power generation;
Conference_Titel :
Power & Energy Society General Meeting, 2009. PES '09. IEEE
Conference_Location :
Calgary, AB
Print_ISBN :
978-1-4244-4241-6
DOI :
10.1109/PES.2009.5275581