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Solar power forecasting modeling using soft computing approach
- 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.
- Subjects :
- Soft computing
Engineering
business.industry
Context (language use)
Solar energy
Grid
Solar power forecasting
Renewable energy
Physics::Space Physics
Electronic engineering
Grid-connected photovoltaic power system
Astrophysics::Solar and Stellar Astrophysics
Astrophysics::Earth and Planetary Astrophysics
business
Solar power
Subjects
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