Short-Term Power Load Forecasting Method Based on Improved Exponential Smoothing Grey Model

Author:

Mi Jianwei12ORCID,Fan Libin12,Duan Xuechao12ORCID,Qiu Yuanying12ORCID

Affiliation:

1. School of Mechano-Electronic Engineering, Xidian University, Xi’an 710071, China

2. Key Laboratory of Electronic Equipment Structure Design, Ministry of Education, Xidian University, No. 2 South Taibai Road, Xi’an 710071, China

Abstract

In order to improve the prediction accuracy, this paper proposes a short-term power load forecasting method based on the improved exponential smoothing grey model. It firstly determines the main factor affecting the power load using the grey correlation analysis. It then conducts power load forecasting using the improved multivariable grey model. The improved prediction model firstly carries out the smoothing processing of the original power load data using the first exponential smoothing method. Secondly, the grey prediction model with an optimized background value is established using the smoothed sequence which agrees with the exponential trend. Finally, the inverse exponential smoothing method is employed to restore the predicted value. The first exponential smoothing model uses the 0.618 method to search for the optimal smooth coefficient. The prediction model can take the effects of the influencing factors on the power load into consideration. The simulated results show that the proposed prediction algorithm has a satisfactory prediction effect and meets the requirements of short-term power load forecasting. This research not only further improves the accuracy and reliability of short-term power load forecasting but also extends the application scope of the grey prediction model and shortens the search interval.

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

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