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The use of Markov chains in forecasting wind speed: Matlab source code and applied case study

Ionuţ Alexandru Petre (), Mihai Rebenciuc () and Ștefan Cristian Ciucu ()
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Ionuţ Alexandru Petre: The Bucharest University of Economics Studies
Mihai Rebenciuc: University Politehnica of Bucharest
Ștefan Cristian Ciucu: The Bucharest University of Economics Studies

Computational Methods in Social Sciences (CMSS), 2016, vol. 4, issue 2, 44-53

Abstract: The ability to predict the wind speed has an important role for renewable energy industry which relies on wind speed forecasts in order to calculate the power a wind farm can produce in an area. There are several well-known methods to predict wind speed, but in this paper we focus on short-term wind forecasting using Markov chains. Often gaps can be found in the time series of the wind speed measurements and repeating the measurements is usually not a valid option. In this study it is shown that using Markov chains these gaps from the time series can be filled (they can be generated in an efficient way), but only when the missing data is for a short period of time. Also, the developed Matlab programms that are used in the case study, are included in the paper beeing presented and commented by the authors. In the case study data from a wind farm in Italy is used. The available data are as average wind speed at an interval of 10 minutes in the time period 11/23/2005 - 4/27/2006., pages 44-53

Keywords: Markov chain; wind speed; Matlab; Chapman-Kolmogorov; forecast (search for similar items in EconPapers)
Date: 2016
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