An Error-Revision-Based Method For Very Short-Term Wind Speed Prediction Using Wavelet Transform And Support Vector Machine

被引：0

作者：

Duan, Xuewei ^{[1
]}

Li, Qingquan ^{[1
]}

Wang, Ruiqi ^{[2
]}

Zhang, Yong ^{[2
]}

Sun, Shumin ^{[2
]}

Lang, Chengyu ^{[2
]}

机构：

[1] Shandong Univ, Shandong Prov Key Lab UHV Transmiss Technol & Equ, Jinan, Peoples R China

[2] State Grid Shandong Elect Power Res Inst, Jinan 250002, Peoples R China

来源：

FOURTH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND INFORMATION SCIENCES (CCAIS 2015) | 2015年

关键词：

wind speed prediction; SVM; SMO; grid search; error revision; POWER-GENERATION; MODEL;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

With the rapid growth of wind power connected to the power system, the problems caused by the volatile nature of wind speed have drawn more and more attention from system operator and researchers. The effective wind speed and power prediction of is the key to solve all these problems. This paper proposed a method based on prediction error revision, which use wavelet transform and Grid Search optimized SMO-SVM during data processing. The simulation indicate that the proposed method performs better than the traditional forecasting model on one and three step ahead prediction.

引用

页码：197 / 202

页数：6

共 18 条

[1] A fuzzy model for wind speed prediction and power generation in wind parks using spatial correlation [J].

Damousis, IG ;

Alexiadis, MC ;

Theocharis, JB ;

Dokopoulos, PS .

IEEE TRANSACTIONS ON ENERGY CONVERSION, 2004, 19 (02) :352-361

[2] Assessment of the benefits of numerical weather predictions in wind power forecasting based on statistical methods [J].

De Giorgi, Maria Grazia ;

Ficarella, Antonio ;

Tarantino, Marco .

ENERGY, 2011, 36 (07) :3968-3978

[3]

Ding Ming, 2005, Electric Power Automation Equipment, V25, P32

[4]

Fan Gao-feng, 2008, Proceedings of the CSEE, V28, P118

[5]

Fan RE, 2005, J MACH LEARN RES, V6, P1889

[6]

Feng Shuang-lei, 2010, Proceedings of the CSEE, V30, P1

[7] Wind energy prediction using a two-hidden layer neural network [J].

Grassi, Giuseppe ;

Vecchio, Pietro .

COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2010, 15 (09) :2262-2266

[8]

Huang Wen-jie, 2010, Power System Technology, V34, P164

[9] Day-ahead wind speed forecasting using f-ARIMA models [J].

Kavasseri, Rajesh G. ;

Seetharaman, Krithika .

RENEWABLE ENERGY, 2009, 34 (05) :1388-1393

[10]

Liu Ruiye H. L., 2012, AUTOMATION ELECT POW, V36, P4

← 1 2 →