FORECASTING MODELING AND SIMULATION ANALYSIS OF A POWER SYSTEM IN CHINA, BASED ON A CLASS OF SEMI-PARAMETRIC REGRESSION APPROACH

Authors

  • Xiaojia Wang China Key Laboratory of Process Optimization and Intelligent Decision-Making, School of Management, HeFei University of Technology, Hefei, Anhui, China
  • Zhiqiang Chen China Key Laboratory of Process Optimization and Intelligent Decision-Making, School of Management, HeFei University of Technology, Hefei, Anhui, China
  • Shanlin Yang China Key Laboratory of Process Optimization and Intelligent Decision-Making, School of Management, HeFei University of Technology, Hefei, Anhui, China

DOI:

https://doi.org/10.7166/23-3-518

Abstract

Forecasting electricity consumption is one of the most important challenges in electricity system planning. This paper presents an improved semi-parametric regression model using the Student distribution function of residual to replace the nonparametric component of the traditional semi-parametric model, thus eliminating the effects of the residual disturbance term. Compared with general linear models, the models make statistical inferences and can automatically regulate the boundary effect, which gives the forecast result a higher accuracy. A case study using data from China is presented to demonstrate the effectiveness of the approach.

Downloads

Download data is not yet available.

Downloads

Published

2012-12-03

How to Cite

Wang, X., Chen, Z., & Yang, S. (2012). FORECASTING MODELING AND SIMULATION ANALYSIS OF A POWER SYSTEM IN CHINA, BASED ON A CLASS OF SEMI-PARAMETRIC REGRESSION APPROACH. The South African Journal of Industrial Engineering, 23(3), 154–168. https://doi.org/10.7166/23-3-518

Issue

Section

General Articles