A novel method based on Weibull distribution for short-term wind speed prediction Orhan Kaplan * , Murat Temiz Gazi University, Department of Electrical & Electronic Engineering, Ankara, Turkey article info Article history: Received 15 November 2016 Received in revised form 20 February 2017 Accepted 2 March 2017 Available online xxx Keywords: Weibull distribution Wind energy Stochastic processes Correction algorithm for wind speed prediction abstract Wind speed prediction (WSP) is essential in order to predict and analyze efficiency and performance of wind-based electricity generation systems. More accurate WSP may pro- vide better opportunities to design and build more efficient and robust wind energy sys- tems. Precious short-term prediction is difficult to achieve; therefore several methods have been developed so far. We notice that the statistics of the alterations, which occur between sequential values of the predicted wind speed data, may differ significantly from observed wind statistics. In this study, we investigate these alterations and compare them and, accordingly, propose a novel method based on Weibull and Gaussian probability distri- bution functions (PDF) for short-term WSP. The proposed method stands on an algorithm, which examines comparison of the statistical features of the observed and generated wind speed in order to achieve more accurate estimation. We have examined this method on the wind speed data set observed and recorded in Ankara in 2013 and in 2014. The obtained results show that the new algorithm provides better wind speed prediction with an enhanced wind speed model. © 2017 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved. Introduction Due to having limited fossil fuel reserves and their detri- mental effects on the nature, sustainable energy sources have become more important solutions for electricity generation. Smart grid and microgrid concepts, which are being enhanced with each passing day, provide efficient usage of the renew- able energy sources for electrical energy production. Addi- tionally, the integration of the renewable energy plants into main is expected to be more secure and safe with these con- cepts [1]. Briefly, a microgrid which is described as local and small energy plants may include solar panels, wind turbines, fuel cells, batteries diesel generators and other small power energy generators and they can be built in residential areas or close to these areas when possible [2]. Microgrids may contribute to reducing transmission losses, enhancing effi- ciency and reliability of the system and better-quality inte- gration of renewable energy into main electrical grid [3]. Because of the advantages of the renewable energy, there is an increasing trend in renewable energy and microgrids in- vestments and research. Wind, which is one of the most essential renewable sources, has high energy potential without resulting in air or soil pollution and it is expected to play a more important role in the future energy networks. Recent developments in power electronics and material sci- ence fields have enabled companies to build cheaper, safer and more efficient wind energy conversion systems (e.g. lighter materials, more efficient semiconductor components) to satisfy the increasing clean energy demands [4]. According * Corresponding author. E-mail addresses: okaplan@gazi.edu.tr (O. Kaplan), mutemiz@gmail.com (M. Temiz). Available online at www.sciencedirect.com ScienceDirect journal homepage: www.elsevier.com/locate/he international journal of hydrogen energy xxx (2017) 1 e8 http://dx.doi.org/10.1016/j.ijhydene.2017.03.006 0360-3199/© 2017 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved. Please cite this article in press as: Kaplan O, Temiz M, A novel method based on Weibull distribution for short-term wind speed pre- diction, International Journal of Hydrogen Energy (2017), http://dx.doi.org/10.1016/j.ijhydene.2017.03.006