Wind Profile Prediction Using Linear Markov Chains: A Linear Algebra Approach

To predict the future wind speed and wind direction is of relevance to the wind industry to maximize the power generation. In this regards, this article describes a methodology for the construction of predictive models based on linear Markov chains under linear algebra point of view. The model analy...

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Bibliographic Details
Published in:Revista IEEE América Latina 2018-02, Vol.16 (2), p.536-541
Main Authors: Garcia-Planas, Maria Isabel, Gongadze, Tornike
Format: Article
Language:eng ; spa
Subjects:
eigenvalues
Eigenvectors
Electric power generation
Espais vectorials
IEEE transactions
Linear algebra
Markov analysis
Markov Chains
Markov processes
Markov, Processos de
Matemàtiques i estadística
Mathematical model
MATLAB
Prediction models
Silicon
stationary distribution
Wind direction
Wind forecasting
Wind speed
Àrees temàtiques de la UPC
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Description
Summary:To predict the future wind speed and wind direction is of relevance to the wind industry to maximize the power generation. In this regards, this article describes a methodology for the construction of predictive models based on linear Markov chains under linear algebra point of view. The model analyzes the direction and speed of the wind obtained from a meteorological station. This Model allows making a precise study of wind direction and speeding data; figure out the stability, the most common direction or speed, its behaviour depending on the hours or seasons.
ISSN:1548-0992
1548-0992
DOI:10.1109/TLA.2018.8327410