TY - GEN
T1 - Application of independent component analysis in short-term power forecasting of wind farm
AU - Chen, Guochu
AU - Wang, Peng
AU - Yu, Jinshou
PY - 2011
Y1 - 2011
N2 - For the difficult problems of measuring and forecasting values interfered by a number of factors, this paper proposed a method of power forecasting based on independent component analysis and least squares support vector machine, and results are modified using the regression. Each independent component from source signals is predicted using least squares support vector machine, the final prediction results obtained by modifying the preliminary predicting power according to the relationship between wind speed and its power. Using the data from a wind farm on the Northeast China wind farm, the simulation results show that this method has higher prediction accuracy, and the mean absolute error from 9.25% down to 5.48%, compared with the simple least squares support vector machine models.
AB - For the difficult problems of measuring and forecasting values interfered by a number of factors, this paper proposed a method of power forecasting based on independent component analysis and least squares support vector machine, and results are modified using the regression. Each independent component from source signals is predicted using least squares support vector machine, the final prediction results obtained by modifying the preliminary predicting power according to the relationship between wind speed and its power. Using the data from a wind farm on the Northeast China wind farm, the simulation results show that this method has higher prediction accuracy, and the mean absolute error from 9.25% down to 5.48%, compared with the simple least squares support vector machine models.
KW - Forecasting
KW - Independent component analysis
KW - Least squares support vector machine
KW - Nonlinear regression
KW - Wind power
UR - http://www.scopus.com/inward/record.url?scp=79959710818&partnerID=8YFLogxK
U2 - 10.4028/www.scientific.net/AMM.63-64.124
DO - 10.4028/www.scientific.net/AMM.63-64.124
M3 - Conference contribution
AN - SCOPUS:79959710818
SN - 9783037851371
T3 - Applied Mechanics and Materials
SP - 124
EP - 128
BT - Advanced Research on Mechanical Engineering, Industry and Manufacturing Engineering
T2 - 2011 International Conference on Mechanical Engineering, Industry and Manufacturing Engineering, MEIME2011
Y2 - 23 July 2011 through 24 July 2011
ER -