Hourly Wind Speed Prediction using ARMA Model and Artificial Neural Networks

محورهای موضوعی : مهندسی هوشمند برق

Farzaneh Tatari ¹ (Electrical Engineering Department, Semnan University, Semnan, Iran)
Majid Mazouchi ² (Electrical Engineering Department, Ferdowsi University, Mashhad, Iran)

تاریخ دریافت : 1396/09/28 تاریخ پذیرش : 1396/10/20 تاریخ انتشار : 1396/06/10

کلید واژه: Artificial Neural Network (ANN), Adaptive linear element (ADALINE), Auto-regressive moving average (ARMA), Multilayer Perceptron (MLP), Radial basis function (RBF), Wind speed forecasting,

چکیده مقاله :

In this paper, a comparison study is presented on artificial intelligence and time series models in 1-hour-ahead wind speed forecasting. Three types of typical neural networks, namely adaptive linear element, multilayer perceptrons, and radial basis function, and ARMA time series model are investigated. The wind speed data used are the hourly mean wind speed data collected at Binalood site in Iran. Simulation results indicate the ability of the proposed methods in 1-hour-ahead wind speed forecasting in Binalood of Iran.