Spatial Approach of Artificial Neural Network for Solar Radiation Forecasting: Modeling Issues. (18th February 2015)

• Record Type: Journal Article
• Authors: Kashyap, Yashwant; Bansal, Ankit; Sao, Anil K.
• Other Names: Bandara Jayasundera M. S. Academic Editor.
• Is Part Of: Journal of solar energy. Volume 2015(2015)
• Publication Date: 2015-02-18
• Subjects: Solar energy -- Periodicals; 621.4705
• DOI: 10.1155/2015/410684
• Languages: English
• ISSNs: 2356-7635

Abstract

Abstract : Design of neural networks architecture has been done on setting up the number of neurons, delays, and activation functions. The expected model was initiated and tested with Indian solar horizontal irradiation (GHI) metrological data. The results are assessed using the effect of different statistical errors. The effort is made to verify simulation capability of ANN architecture accurately, on hourly radiation data. ANN model is a well-organized technique to estimate the radiation using different meteorological database. In this paper, we have used nine spatial neighbour locations and 10 years of data for assessment of neural network. Hence, overall 90 different inputs are compared, on customized ANN model. Results show the flexibility with respect to spatial orientation of model inputs.