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

Shijie Ye, Guangfu Zhu, Zhi Xiao

School of Economics and Business Administration, Chongqing City Management College, Chongqing, China.

DOI: 10.4236/epe.2012.45050                

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.

Keywords

Long Term Load Forecasting; Support Vector Regression; China

Conflicts of Interest

The authors declare no conflicts of interest.

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