Title :
A novel ARX-based multi-scale spatio-temporal solar power forecast model
Author :
Yang, Chen ; Xie, Le
Author_Institution :
Dept. of Electr. & Comput. Eng., Texas A&M Univ., College Station, TX, USA
Abstract :
In this paper an autoregressive with exogenous input (ARX) based spatio-temporal solar forecast model is proposed. Compared with conventional temporal-only autoregressive models, the proposed formulation takes into account both spatial and temporal solar power correlations. The overall root mean squared error (RMSE) percentage can be reduced by 12.72% using spatio-temporal solar forecast compared with persistence forecast model for hour ahead intervals.
Keywords :
autoregressive processes; correlation methods; load forecasting; photovoltaic power systems; spatiotemporal phenomena; ARX-based multiscale spatiotemporal solar power forecast model; RMSE percentage; autoregressive with exogenous input; hour ahead intervals; root mean squared error percentage; spatial solar power correlation; temporal solar power correlation; Accuracy; Clouds; Computational modeling; Correlation; Data models; Predictive models; Weather forecasting; Solar irradiance; Solar power forecast; Spatial correlation; Spatio-temporal;
Conference_Titel :
North American Power Symposium (NAPS), 2012
Conference_Location :
Champaign, IL
Print_ISBN :
978-1-4673-2306-2
Electronic_ISBN :
978-1-4673-2307-9
DOI :
10.1109/NAPS.2012.6336383
