MODELING OF SOLAR RADIATION WITH A NEURAL NETWORK

• Main Authors: VALENTIN STOYANOV, IVAYLO STOYANOV, TEODOR ILIEV
• Format: Article
• Language: English
• Published: Alma Mater Publishing House "Vasile Alecsandri" University of Bacau 2018-09-01
• Series: Journal of Engineering Studies and Research
• Subjects: modeling; solar radiation; neural network
• Online Access: http://www.jesr.ub.ro/1/article/view/55

Modeling of solar radiation with neural network could be used for real-time calculations of the radiation on tilted surfaces with different orientations. In the artificial neural network (ANN), latitude, day of the year, slope, surface azimuth and average daily radiation on horizontal surface are inputs, and average daily radiation on tilted surface of definite orientation is output. The possible ANN structure, the size of training data set, the number of hidden neurons, and the type of training algorithms were analyzed in order to identify the most appropriate model. The same ANN structure was trained and tested using data generated from the Klein and Theilacker model and long-term measurements. Reasonable accuracy was obtained for all predictions for practical need.