Title :
The Application and Research of the PAR Approach in the Short Term Load Forecasting
Author :
Fan, Yu ; Min, Dong
Author_Institution :
Sch. of Comput. Sci. & Eng., Xi´´an Technol. Univ., Xi´´an, China
Abstract :
For load sequences changes run in cycle by days, weeks, and years, and the power load data are non-stationary, the periodic autoregressive (PAR) model is used to describe the periodic variations accurately of the power load and establish a short-term forecast of the prediction model. Compared with traditional time series, it is show that this way is more effective.
Keywords :
autoregressive processes; load forecasting; PAR approach; load sequences; periodic autoregressive model; periodic variations; power load; prediction model; short term load forecasting; time series; Industrial control; PAR model; Power load; Short-term forecast;
Conference_Titel :
Industrial Control and Electronics Engineering (ICICEE), 2012 International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4673-1450-3
DOI :
10.1109/ICICEE.2012.88
