In this paper,it aims to model wind speed time series at multiple *** five-parameter Johnson mdistribution is deployed to relate the wind speed at each site to a Gaussian time series,and the resultant-Z(t)dimensional ...
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In this paper,it aims to model wind speed time series at multiple *** five-parameter Johnson mdistribution is deployed to relate the wind speed at each site to a Gaussian time series,and the resultant-Z(t)dimensional Gaussian stochastic vector process is employed to model the temporal-spatial correlation of mwind speeds at different *** general,it is computationally tedious to obtain the autocorrelation functions Z(t)(ACFs)and cross-correlation functions(CCFs)of Z(t),which are different to those of wind speed times *** order to circumvent this correlation distortion problem,the rank ACF and rank CCF are introduced to Z(t)characterize the temporal-spatial correlation of wind speeds,whereby the ACFs and CCFs of can be analytically ***,Fourier transformation is implemented to establish the cross-spectral density matrix Z(t)mof,and an analytical approach is proposed to generate samples of wind speeds at different ***,simulation experiments are performed to check the proposed methods,and the results verify that the five-parameter Johnson distribution can accurately match distribution functions of wind speeds,and the spectral representation method can well reproduce the temporal-spatial correlation of wind speeds.
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