A hybrid model for wind power prediction composed of ANN and imperialist competitive algorithm (ICA)

Author

Gazafroudi, Amin Shokri ; Bigdeli, Nooshin ; Ramandi, Mostafa Yousefi ; Afshar, Karim

Author_Institution

Dept. of Electr. Eng., Imam Khomeini Int. Univ., Qazvin, Iran

fYear

2014

fDate

20-22 May 2014

Firstpage

562

Lastpage

567

Abstract

Rapid growth of wind power generation in addition to its high penetration in electrical power systems has brought wind power prediction into play. Wind power is a complex signal for modeling and forecasting. In this paper, wind power prediction model based on neural network and imperialist competitive algorithm (ICA) is presented to forecast wind power generation of wind farm of Alberta. Finally, the results of the proposed model and the neural networks trained by PSO and GA are compared with each other.

Keywords

genetic algorithms; load forecasting; neural nets; particle swarm optimisation; power engineering computing; wind power; ANN; GA; ICA; PSO; artificial neural network; electrical power system; imperialist competitive algorithm; wind farm; wind power generation; wind power prediction; Artificial neural networks; Correlation; Predictive models; Wind forecasting; Wind power generation; Wind speed; artificial neural network; correlation analysis; imperialist competitive algorithm (ICA); wind power forecasting;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Engineering (ICEE), 2014 22nd Iranian Conference on

Conference_Location

Tehran

Type

conf

DOI

10.1109/IranianCEE.2014.6999606

Filename

6999606