Publication History View all
- SourceAvailable from: Haythem Ghazouani
- [Show abstract] [Hide abstract]
ABSTRACT: a b s t r a c t In this paper, an adaptive model for predicting hourly global, diffuse and direct solar irradiance is described. A dataset of measured air temperature, relative humidity, direct, diffuse and global horizontal irradiance for Jeddah site (Saudi Arabia) were used in this study. Several combinations have been pro-posed, and the best performance is obtained by using sunshine duration, air temperature and relative humidity as inputs of the developed adaptive a-model. A good agreement between measured and pre-dicted data is obtained. In fact, the correlation coefficient is more than 97% and the mean bias error is less than 0.8. A comparison between a Feed-Forward Neural Network (FFNN) and the adaptive proposed model is presented in order to demonstrate his performance.Energy Conversion and Management 01/2010; 51(4). DOI:10.1016/j.enconman.2009.10.034
- Ecole Nationale des Sciences de l'Informatique, 01/2010, Degree: PhD
Information provided on this web page is aggregated encyclopedic and bibliographical information relating to the named institution. Information provided is not approved by the institution itself. The institution’s logo (and/or other graphical identification, such as a coat of arms) is used only to identify the institution in a nominal way. Under certain jurisdictions it may be property of the institution.
Rg score distribution
No data available.