Study on the Monthly Power Load Forecasting Performance Based on regARIMA Model

doi:10.11930/j.issn.1004-9649.201704041

Electric Power ›› 2018, Vol. 51 ›› Issue (5): 166-171.DOI: 10.11930/j.issn.1004-9649.201704041

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Study on the Monthly Power Load Forecasting Performance Based on regARIMA Model

SU Zhenyu^1,2, LONG Yong¹, ZHAO Liyan³

1. School of Economics and Business Administration, Chongqing University, Chongqing 400030, China;
2. Gansu Electric Power Training Center, Lanzhou 730070, China;
3. Gansu Electric Power Research Institute, Lanzhou 730070, China

Received:2017-04-11 Revised:2018-02-10 Online:2018-05-05 Published:2018-05-07
Supported by:
This work is supported by National Social Science Fund(No.14AZD130).

Abstract

Abstract: In order to explore the impact of outliers on the monthly power load forecasting performance, a seasonal ARIMA model considering the impact of outliers (regARIMA) is established. The actual monthly power load data series of 5 provinces recorded from January 1999 to December 2017 are used to verify the accuracy of power load forecasting. The empirical results show that the forecasting error of the regARIMA model considering the outliers impact is significantly reduced within samples for last 3 years. The forecasting accuracy of the regARIMA out of samples for 12 steps ahead is also improved to some extent.

Key words: monthly power load, power load forecasting, outliers, regARIMA model

CLC Number:

TM715

SU Zhenyu, LONG Yong, ZHAO Liyan. Study on the Monthly Power Load Forecasting Performance Based on regARIMA Model[J]. Electric Power, 2018, 51(5): 166-171.

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https://www.electricpower.com.cn/EN/Y2018/V51/I5/166

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Study on the Monthly Power Load Forecasting Performance Based on regARIMA Model

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