Title :
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
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;
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
DOI :
10.1109/ICRCCS.2009.12
