JOURNAL BROWSE
Search
Advanced SearchSearch Tips
A Study on Centralized Wind Power Forecasting Based on Time Series Models
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
A Study on Centralized Wind Power Forecasting Based on Time Series Models
Wi, Young-Min; Lee, Jaehee;
  PDF(new window)
 Abstract
As the number of wind farms operating has increased, the interest of the central unit commitment and dispatch for wind power has increased as well. Wind power forecast is necessary for effective power system management and operation with high wind power penetrations. This paper presents the centralized wind power forecasting method, which is a forecast to combine all wind farms in the area into one, using time series models. Also, this paper proposes a prediction model modified with wind forecast error compensation. To demonstrate the improvement of wind power forecasting accuracy, the proposed method is compared with persistence model and new reference model which are commonly used as reference in wind power forecasting using Jeju Island data. The results of case studies are presented to show the effectiveness of the proposed wind power forecasting method.
 Keywords
Wind power forecasting;Centralized wind power forecasting;Time series;
 Language
Korean
 Cited by
 References
1.
Ministry of Knowledge Economy, "The 6th basic plan of long-term electricity supply and demand", 2013

2.
Korea Power Exchange, "Power market operating performance", 2014.

3.
G Sideratos and N Hatziargyriou, "An advanced statistical method for wind power forecasting", IEEE Transaction on Power Systems, Vol. 22, No. 1, pp. 258-265. 2007. crossref(new window)

4.
M Negnevitsky and C Potter, "Innovative short-term wind generation prediction techniques", IEEE Power System Conference and Exposition, pp. 60-65, 2006

5.
Y. Wi, "Short-term wind farm power forecasting using multivariate analysis to improve wind power efficiency", Journal of the KIIEE, Vol. 29, No. 7, pp. 54-61. 2015.

6.
NREL, "Status of centralized wind power forecasting in North America", 2010.

7.
T. S. Nielsen, A. Joensen, H. Madsen, L. Landberg, and G. Giebel, "A new reference model for wind power forecasting", Wind Energy, Vol. 1, No. 1, pp. 29-34, 1998. crossref(new window)