Abstract
Nowadays trends pay attention to used renewable energy sources, e.g. wind – wind energy or sun irradiance – solar energy, as a source of electrical power. This kind of energy sources are very unstable and inconstancy (nonstationary) over the time. The proper and accurate wind speed or sun irradiance prediction is necessary to control the power grid. This paper presents short time wind prediction algorithm with genetic column subset selection problem. It uses multiple weather data sources, genetics algorithm for features selection, and the prediction is done by a neural network. The genetic algorithm chooses the most important features for the prediction algorithm.
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Acknowledgment
This work was supported by the Czech Science Foundation under the grant no. GACR GJ16-25694Y and in part by Grant of SGS No. SP2017/85 VŠB - Technical University of Ostrava, Czech Republic.
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Prilepok, M. (2018). Wind Speed Prediction with Genetic Algorithm. In: Barolli, L., Woungang, I., Hussain, O. (eds) Advances in Intelligent Networking and Collaborative Systems. INCoS 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 8. Springer, Cham. https://doi.org/10.1007/978-3-319-65636-6_29
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DOI: https://doi.org/10.1007/978-3-319-65636-6_29
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