TY - GEN
T1 - A study of grey theory used in prediction of annual wind power generation
AU - Tian, Chengwei
AU - Dong, Lei
AU - Gao, Shuang
AU - Liao, Xiaozhong
PY - 2011
Y1 - 2011
N2 - With the coming mature of the wind energy technology, wind energy has become one of the most promising renewable energy. In order to conduct post appraisals and operation management to a large wind farm, accurate prediction of the annual wind power generation is necessary. In this paper, grey model GM (1,1) for predicting annual wind power generation is set up. Moreover, in order to improve the prediction accuracy, a effective method of processing the original wind power data series is proposed. The prediction result with the original data series processed is compared to the unprocessed one. We obtain that the normalized average absolute error of the prediction result with the original data series processed is 7.0315%, improved 0.7679% relative to that original data series unprocessed.
AB - With the coming mature of the wind energy technology, wind energy has become one of the most promising renewable energy. In order to conduct post appraisals and operation management to a large wind farm, accurate prediction of the annual wind power generation is necessary. In this paper, grey model GM (1,1) for predicting annual wind power generation is set up. Moreover, in order to improve the prediction accuracy, a effective method of processing the original wind power data series is proposed. The prediction result with the original data series processed is compared to the unprocessed one. We obtain that the normalized average absolute error of the prediction result with the original data series processed is 7.0315%, improved 0.7679% relative to that original data series unprocessed.
KW - grey predicting model
KW - information renewal model
KW - wind power generation prediction
UR - http://www.scopus.com/inward/record.url?scp=79959915369&partnerID=8YFLogxK
U2 - 10.1109/ICEICE.2011.5777141
DO - 10.1109/ICEICE.2011.5777141
M3 - Conference contribution
AN - SCOPUS:79959915369
SN - 9781424480395
T3 - 2011 International Conference on Electric Information and Control Engineering, ICEICE 2011 - Proceedings
SP - 1952
EP - 1955
BT - 2011 International Conference on Electric Information and Control Engineering, ICEICE 2011 - Proceedings
T2 - 2011 International Conference on Electric Information and Control Engineering, ICEICE 2011
Y2 - 15 April 2011 through 17 April 2011
ER -
