Title :
Wind resource analysis and characterization with Markov’s-transition matrices
Author_Institution :
Dept. of Electr. & Computering Eng., Univ. of the West Indies, St. Augustine
Abstract :
Wind resource analysis and characterization is a key ingredient in the planning and operation of wind farms. The most popular method to perform it is based on the generation of histograms showing the frequency of occurrence of the wind speed and their approximation with probability density functions (PDF). This paper presents the mathematical bases and examples of application of two statistical methods using a matrix based representation. The main advantage of this representation is that allows the preservation of information related to the temporal patterns of the wind speed time series and the results are shown. Further studies are being carried out to use these matrixes to reconstruct and forecast the wind speed.
Keywords :
Markov processes; matrix algebra; power generation planning; probability; wind power plants; Markov processes; matrix based representation; probability density functions; statistical methods; time series; wind farm planning; wind resource analysis; wind resource characterization; wind speed forecast; Frequency; Histograms; Neural networks; Probability density function; Statistical analysis; Time series analysis; Wind energy; Wind farms; Wind forecasting; Wind speed; Markov process; Wind energy; proability functions; statistical methods; wind resource; wind speed;
Conference_Titel :
Transmission and Distribution Conference and Exposition: Latin America, 2008 IEEE/PES
Conference_Location :
Bogota
Print_ISBN :
978-1-4244-2217-3
Electronic_ISBN :
978-1-4244-2218-0
DOI :
10.1109/TDC-LA.2008.4641731
