A review of combined approaches for prediction of short-term wind speed and power A. Tascikaraoglu n , M. Uzunoglu Department of Electrical Engineering, Yildiz Technical University, Istanbul 34220, Turkey article info Article history: Received 19 May 2013 Received in revised form 7 February 2014 Accepted 12 March 2014 Keywords: Forecasting methods Combined prediction Hybrid prediction Wind speed Wind power abstract With the continuous increase of wind power penetration in power systems, the problems caused by the volatile nature of wind speed and its occurrence in the system operations such as scheduling and dispatching have drawn attention of system operators, utilities and researchers towards the state-of-the- art wind speed and power forecasting methods. These methods have the required capability of reducing the influence of the intermittent wind power on system operations as well as of harvesting the wind energy effectively. In this context, combining different methodologies in order to circumvent the challenging model selection and take advantage of the unique strength of plausible models have recently emerged as a promising research area. Therefore, a comprehensive research about the combined models is called on for how these models are constructed and affect the forecasting performance. Aiming to fill the mentioned research gap, this paper outlines the combined forecasting approaches and presents an up-to date annotated bibliography of the wind forecasting literature. Furthermore, the paper also points out the possible further research directions of combined techniques so as to help the researchers in the field develop more effective wind speed and power forecasting methods. & 2014 Elsevier Ltd. All rights reserved. Contents 1. Introduction ........................................................................................................ 243 2. Classification and overview of wind forecasting methods .................................................................... 244 3. Combined wind forecasting methods .................................................................................... 246 3.1. Weighting-based combined approaches ............................................................................ 246 3.2. Other combined approaches ..................................................................................... 248 3.2.1. Combined approaches including data pre-processing techniques ................................................. 248 3.2.2. Combined approaches including parameter selection and optimization techniques .................................. 250 3.2.3. Combined approaches including error processing techniques .................................................... 251 4. Discussion and prospects ............................................................................................. 251 5. Conclusions ........................................................................................................ 252 Acknowledgment ....................................................................................................... 252 References ............................................................................................................. 252 1. Introduction Wind energy is of vital importance among the low-carbon energy technologies, which has the potential to achieve sustainable energy supply and constitutes a keystone component for micro-grids in a way towards the smart grid infrastructure. However, stochastic and intermittent wind power generation poses a number of challenges to the large scale penetration of wind power. These wind-related uncertainties can put the system reliability and power quality at risk with the increasing penetration of wind power and thus, the main grid integration issues such as balance management and reserve capacities can come into question [1–3]. Reducing the need for Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/rser Renewable and Sustainable Energy Reviews http://dx.doi.org/10.1016/j.rser.2014.03.033 1364-0321/& 2014 Elsevier Ltd. All rights reserved. n Corresponding author. Tel.: þ90 2123835866; fax: þ90 212 383 5858. E-mail addresses: atasci@yildiz.edu.tr, akintasci@gmail.com (A. Tascikaraoglu). Renewable and Sustainable Energy Reviews 34 (2014) 243–254