Electric Power ›› 2013, Vol. 46 ›› Issue (10): 111-114.DOI: 10.11930/j.issn.1004-9649.2013.10.111.3

• Power Planning • Previous Articles     Next Articles

Data Preprocessing for Grey Model of Medium-Long Term Load Forecasting

ZHENG Ya-nan1, 2, SHAN Bao-guo1, GU Yu-gui1, LI Geng-yin2   

  1. 1. State Grid Energy Research Institute, Beijing 100052, China; 2. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
  • Received:2013-05-28 Online:2013-10-23 Published:2015-12-10

Abstract: The medium-long term power load forecasting is fundamental to system regulation, power plant and network construction and demand side management. Based on the conventional medium-long term grey forecasting model, the moving average, transformation of power functions and the expected impacts are introduced to improve the data preprocessing of the traditional grey model. It is the first time that the expected impact adjustment component is applied to power load forecasting. Through deeper mining and sufficient utilization of information, the prediction accuracy can be improved. The methods for evaluating the fitting and prediction accuracy of the model quantitatively are also introduced. At last, based on the power loads in China between 1999 and 2011, the fitting and prediction accuracy of the improved methods are compared in two scenes. And, the power loads of 2012 and 2013 are also predicted with the improved methods.

Key words: grey model, smoothing, expected influence, fitting accuracy, prediction accuracy

CLC Number: