TY - JOUR
T1 - Solar Radiation Measurement Using Raspberry Pi and Its Modelling Using Artificial Neural Networks
AU - Priya, Selvanathan Shanmuga
AU - Freudenberg, Norman Carl
AU - Borkataky, Arunabh
PY - 2016/10/3
Y1 - 2016/10/3
N2 - The advent of solar energy as the best alternative to traditional energy sources has led to an extensive study on the measurement and prediction of solar radiation. Devices such as pyranometer, pyrrheliometer, global UV radiometer are used for the measurement of solar radiation. The solar radiation measuring instruments available at Innovation Center, MIT Manipal were integrated with a Raspberry Pi to allow remote access to the data through the university Local Area Network. The connections of the data loggers and the Raspberry Pi were enclosed in a plastic box to prevent damage from the rainfall and humidity in Manipal. The solar radiation data was used to validate an Artificial Neural Network model which was developed using various meterological data from 2011-2015.
AB - The advent of solar energy as the best alternative to traditional energy sources has led to an extensive study on the measurement and prediction of solar radiation. Devices such as pyranometer, pyrrheliometer, global UV radiometer are used for the measurement of solar radiation. The solar radiation measuring instruments available at Innovation Center, MIT Manipal were integrated with a Raspberry Pi to allow remote access to the data through the university Local Area Network. The connections of the data loggers and the Raspberry Pi were enclosed in a plastic box to prevent damage from the rainfall and humidity in Manipal. The solar radiation data was used to validate an Artificial Neural Network model which was developed using various meterological data from 2011-2015.
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U2 - 10.1051/matecconf/20167706011
DO - 10.1051/matecconf/20167706011
M3 - Article
AN - SCOPUS:84994051907
SN - 2261-236X
VL - 77
JO - MATEC Web of Conferences
JF - MATEC Web of Conferences
M1 - 06011
ER -