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Long Term Load Forecasting and Recommendations for China Based on Support Vector Regression

Authors :
Shijie Ye
Guangfu Zhu
Zhi Xiao
Source :
Energy and Power Engineering. :380-385
Publication Year :
2012
Publisher :
Scientific Research Publishing, Inc., 2012.

Abstract

Long-term load forecasting (LTLF) is a challenging task because of the complex relationships between load and factors affecting load. However, it is crucial for the economic growth of fast developing countries like China as the growth rate of gross domestic product (GDP) is expected to be 7.5%, according to China’s 11th Five-Year Plan (2006-2010). In this paper, LTLF with an economic factor, GDP, is implemented. A support vector regression (SVR) is applied as the training algorithm to obtain the nonlinear relationship between load and the economic factor GDP to improve the accuracy of forecasting.

Details

ISSN :
19473818 and 1949243X
Database :
OpenAIRE
Journal :
Energy and Power Engineering
Accession number :
edsair.doi...........a87d955e34428716ce43ba7266d653a3
Full Text :
https://doi.org/10.4236/epe.2012.45050