Title :
Forecast of Power Generation for Grid-Connected Photovoltaic System Based on Knowledge Representation of Rough Sets
Author :
Li, Ying-zi ; Nie, Ru-qing ; Niu, Jin-cang
Author_Institution :
Coll. of Inf. & Electr. Eng., Beijing Univ. of Civil Eng. & Archit., Beijing, China
Abstract :
A grid-connected PV system characteristics and operation laws has been analysis, which is based on the 5.6kW grid-connected PV system in Beijing Institute of Architectural Engineering. Considering the environmental factors, the forecasting model of grid-connected PV system based on rough set theory was established. Compared the forecasting result with acture operation results of the weekly, monthly, seasonal and annual generation, it shows that former is more correct and accuracy. So the research proved that the forecasting model of rough set is practical.
Keywords :
environmental factors; load forecasting; photovoltaic power systems; power grids; Beijing Institute of Architectural Engineering; annual generation; environmental factors; grid-connected PV system; grid-connected photovoltaic system; knowledge representation; monthly generation; power 5.6 kW; power generation forecast; rough sets; seasonal generation; weeky generation; Environmental factors; Knowledge based systems; Photovoltaic systems; Predictive models; Rough sets; Weather forecasting;
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2012 Asia-Pacific
Conference_Location :
Shanghai
Print_ISBN :
978-1-4577-0545-8
DOI :
10.1109/APPEEC.2012.6307183
