Based on Time Sequence of ARIMA Model in the Application of Short-Term Electricity Load Forecasting

Author

Wei, Li ; Zhen-gang, Zhang

Author_Institution

Dept. of Econ. & Manage., North China Electr. Power Univ., Baoding, China

fYear

2009

fDate

28-29 Dec. 2009

Firstpage

11

Lastpage

14

Abstract

Short-term electricity load is effected by various factors, It has the certain difficulty to make prediction accurate, but we can improve prediction precise by continuously optimizing forecasting methods. This paper carried out the combination of ARIMA several methods based on the idea of time sequence, to avoid deficiencies in various aspects, perfect forecasting methods, make ARIMA model can conduct electricity short-term load forecasting better.

Keywords

autoregressive moving average processes; load forecasting; ARIMA model; electricity short-term load forecasting; perfect forecasting method; prediction precision; short-term electricity load forecasting; time sequence; Autoregressive processes; Conference management; Economic forecasting; Energy management; Load forecasting; Power generation economics; Predictive models; Random processes; Testing; Time series analysis; ARIMA; Short-term Electricity Load Forecasting; Test; Time Sequence;

fLanguage

English

Publisher

ieee

Conference_Titel

Research Challenges in Computer Science, 2009. ICRCCS '09. International Conference on

Conference_Location

Shanghai

Print_ISBN

978-0-7695-3927-0

Electronic_ISBN

978-1-4244-5410-5

Type

conf

DOI

10.1109/ICRCCS.2009.12

Filename

5401272