Title :
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
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;
Conference_Titel :
Electrical Engineering (ICEE), 2014 22nd Iranian Conference on
Conference_Location :
Tehran
DOI :
10.1109/IranianCEE.2014.6999606
