  The correlations of multiple renewable power plants (RPPs) should be fully
considered in the power system with very high penetration renewable power
integration. This paper models the uncertainties, spatial correlation of
multiple RPPs based on Copula theory and actual probability historical
histograms by one-dimension distributions for economic dispatch (ED) problem.
An efficient dynamic renewable power scenario generation method based on Gibbs
sampling is proposed to generate renewable power scenarios considering the
uncertainties, spatial correlation and variability (temporal correlation) of
multiple RPPs, in which the sampling space complexity do not increase with the
number of RPPs. Distribution-based and scenario-based methods are proposed and
compared to solve the real-time ED problem with multiple RPPs. Results show
that the proposed dynamic scenario generation method is much more consist with
the actual renewable power. The proposed ED methods show better understanding
for the uncertainties, spatial and temporal correlations of renewable power and
more economical compared with the traditional ones.
