Table of Contents
Journal of Wind Energy
Volume 2014, Article ID 683939, 9 pages
Research Article

A New Hybrid Forecasting Strategy Applied to Mean Hourly Wind Speed Time Series

1Department of Organic Greenhouse Crops and Floriculture, School of Agricultural Technology, Antikalamos, 24100 Kalamata, Greece
2Department of Electrical and Electronic Engineering Educators, School of Pedagogical and Technological Education (ASPETE), N. Heraklion, 14121 Athens, Greece
3School of Engineering, University of Greenwich, Medway Campus, Pembroke Building, Central Avenue, Chatham Maritime, Kent ME4 4TB, UK

Received 19 March 2014; Accepted 14 May 2014; Published 12 June 2014

Academic Editor: Adrian Ilinca

Copyright © 2014 Stylianos Sp. Pappas et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


An alternative electric power source, such as wind power, has to be both reliable and autonomous. An accurate wind speed forecasting method plays the key role in achieving the aforementioned properties and also is a valuable tool in overcoming a variety of economic and technical problems connected to wind power production. The method proposed is based on the reformulation of the problem in the standard state space form and on implementing a bank of Kalman filters (KF), each fitting an ARMA model of different order. The proposed method is to be applied to a greenhouse unit which incorporates an automatized use of renewable energy sources including wind speed power.