Forecasting and Modelling of Solar Radiation for Photovoltaic (PV) Systems
Ines Sansa and
Najiba Mrabet Bellaaj
A chapter in Solar Radiation - Measurement, Modeling and Forecasting Techniques for Photovoltaic Solar Energy Applications from IntechOpen
Abstract:
Solar radiation is characterized by its fluctuation because it depends to different factors such as the day hour, the speed wind, the cloud cover and some other weather conditions. Certainly, this fluctuation can affect the PV power production and then its integration on the electrical micro grid. An accurate forecasting of solar radiation is so important to avoid these problems. In this chapter, the solar radiation is treated as time series and it is predicted using the Auto Regressive and Moving Average (ARMA) model. Based on the solar radiation forecasting results, the photovoltaic (PV) power is then forecasted. The choice of ARMA model has been carried out in order to exploit its own strength. This model is characterized by its flexibility and its ability to extract the useful statistical properties, for time series predictions, it is among the most used models. In this work, ARMA model is used to forecast the solar radiation one year in advance considering the weekly radiation averages. Simulation results have proven the effectiveness of ARMA model to forecast the small solar radiation fluctuations.
Keywords: solar radiation; PV power; forecasting; ARMA; fluctuation (search for similar items in EconPapers)
JEL-codes: Q20 Q40 (search for similar items in EconPapers)
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.intechopen.com/chapters/78152 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ito:pchaps:223462
DOI: 10.5772/intechopen.99499
Access Statistics for this chapter
More chapters in Chapters from IntechOpen
Bibliographic data for series maintained by Slobodan Momcilovic ().