Back to Search Start Over

Solar power forecasting modeling using soft computing approach

Authors :
Vikas Pratap Singh
Devendra K. Chaturvedi
Kumar Vaibhav
Source :
2012 Nirma University International Conference on Engineering (NUiCONE).
Publication Year :
2012
Publisher :
IEEE, 2012.

Abstract

In last few years, Renewable Energy is introduced as a alternative source of energy. Especially in Indian context solar Energy is an important issue and unlimited source of energy. However, solar radiation is varies with time and geographical locations and meteorological conditions. In this paper, artificial neural network and generalized neural network are used as a powerful tool for Renewable Energy Forecasting. With the help of metrological data such as wind velocity, solar irradiation, and temperature as input to the model we can predict the changes in generated solar power, which is very useful for integration of solar power into grid. In this paper these soft computing techniques are able to prediction the solar power generation accurately and fast compare to conventional methods of forecasting.

Details

Database :
OpenAIRE
Journal :
2012 Nirma University International Conference on Engineering (NUiCONE)
Accession number :
edsair.doi...........53385b095116060dfb262d6955371de6
Full Text :
https://doi.org/10.1109/nuicone.2012.6493268