Title :
Photovoltaic power forecasting methods in smart power grid
Author :
Harendra Kumar Yadav;Yash Pal;M.M. Tripathi
Author_Institution :
School of Renewable Energy and Efficiency, NIT Kurukshetra Haryana, India
Abstract :
Due to increasing global warming and depletion of conventional resources it is important to think of new types of energy sources to have clean and sufficient energy for sustainable growth. Photovoltaic (PV) power generation is playing important role in minimizing the shortage of power demand and providing clean energy to smart power grid. PV energy is growing and getting connected in distributed manner to the smart power grid. Forecasting of PV generation would play a vital role in the interconnection of the PV generators to smart power grid as this is intermittent in nature, depend on weather conditions and distributed throughout the grid. A comprehensive review of the PV forecasting methods in terms of their performances has been done in this paper. This paper presents a broad spectrum of the issues related to forecasting of PV generation at centralized as well as distributed level and also discusses its importance in smart power grid.
Keywords :
"Forecasting","Predictive models","Power generation","Meteorology","Data models","Artificial neural networks","Statistical analysis"
Conference_Titel :
India Conference (INDICON), 2015 Annual IEEE
Electronic_ISBN :
2325-9418
DOI :
10.1109/INDICON.2015.7443522