Energy and Power Engineering

Volume 4, Issue 5 (September 2012)

ISSN Print: 1949-243X   ISSN Online: 1947-3818

Google-based Impact Factor: 0.66  Citations  

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

HTML  Download Download as PDF (Size: 257KB)  PP. 380-385  
DOI: 10.4236/epe.2012.45050    4,414 Downloads   7,155 Views  Citations

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.

Share and Cite:

S. Ye, G. Zhu and Z. Xiao, "Long Term Load Forecasting and Recommendations for China Based on Support Vector Regression," Energy and Power Engineering, Vol. 4 No. 5, 2012, pp. 380-385. doi: 10.4236/epe.2012.45050.

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