Wind Power Forecasting Using Wavelet Transforms and Neural Networks with Tapped Delay

查看全文 作　　者：Sumit [1]Saroha;[2]S.K.Aggarwal

机构地区：[1]Electrical&Electronics Engineering Department,SRM University,Delhi NCR Campus,India;[2]EIED Department,Thapar University,Patiala,Punjab,147001,India

出　　处：《CSEE Journal of Power and Energy Systems》索引2018年第4卷第2期,共13页

摘　　要：With an objective to improve wind power estimation accuracy and reliability,this paper presents Linear Neural Networks with Tapped Delay(LNNTD)in combination with wavelet transform(WT)for probabilistic wind power forecasting in a time series framework.For comparison purposes,results of the proposed model are compared with the benchmark model,different neural networks and WT based models considering performance indices such as accuracy,execution time and R^(2) statistic.For the reliability and proper validation of the proposed model,this paper highlights the probabilistic forecast attributes at different skill tests.The historical data of the Ontario Electricity Market(OEM)for the period 2011–2014 were used and tested for two years from November 2012 to October 2014 with one month moving window considering all seasonal aspects.The experimental results clearly show that the results of the proposed model have been found to be better than others. 关键词：Forecasting linear neural networks with tapped delay time series wavelet transform wind power

相关文献

参考文献（51）
引证文献（9）
耦合文献（4）

参考文献(51)

引证文献(9)

耦合文献(4)

互联网出版许可证新出网证(渝)字10号全国400电话 - 免长途话费

Wind Power Forecasting Using Wavelet Transforms and Neural Networks with Tapped Delay

参考文献(51)

引证文献(9)

耦合文献(4)

用户提示