Hourly Wind Speed Prediction using ARMA Model and Artificial Neural Networks

International Journal of Smart Electrical Engineering

مقاله 4، دوره 06، شماره 03، آذر 2017، صفحه 101-107   

نوع مقاله: Research Paper

نویسندگان

Farzaneh Tatari^{* 1}؛ Majid Mazouchi²

¹Electrical Engineering Department, Semnan University, Semnan, Iran

²Electrical Engineering Department, Ferdowsi University, Mashhad, Iran

چکیده

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.

کلیدواژه‌ها

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