A novel multi-dimensional scenario forecast approach which can capture the dynamic temporal-spatial interdependence relation among the outputs of multiple wind farms is *** the proposed approach,support vector machine...
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A novel multi-dimensional scenario forecast approach which can capture the dynamic temporal-spatial interdependence relation among the outputs of multiple wind farms is *** the proposed approach,support vector machine(SVM)is applied for the spot forecast of wind power *** probability density function(PDF)of the SVM forecast error is predicted by sparse Bayesian learning(SBL),and the spot forecast result is corrected according to the error expectation *** copula function is estimated using a Gaussian copula-based dynamic conditional correlation matrix regression(DCCMR)model to describe the correlation among the *** the multidimensional scenario is generated with respect to the estimated marginal distributions and the copula *** results on three adjacent wind farms illustrate the effectiveness of the proposed approach.
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