In recent years

the implementation of wind power grid-connection policy and the increase of wind power penetration have played a positive role in energy conservation and emission reduction. However

due to the obvious uncertainty and correlation of wind power output

the economic dispatching of power system is also facing great challenges. In this paper

a novel Pair Copula method is applied to formulate the dependence of multiple wind farms. A large number of stochastic scenarios

in which the complicated dependence of multiple wind farms are considered

are generated to represent the uncertainties of wind power based on quasi-Monte Carlo (QMC) simulations. To solve the stochastic economic dispatching problem with wind power output

a risk constrained mean-variance (MV) model considering risk constraints is constructed. The MV model considers economic cost and economic risk under the uncertainties of wind power simultaneously

among which economic risk is calculated by means of least variance of fuel cost. In order to adapt to the actual scheduling situation

the probability density function (PDF) obtained for fuel cost is established

and a predefined level of confidence interval is proposed to improve the MV model. The effectiveness of the proposed pair copula method and the improved MV model are validated via numerical simulations with a modified IEEE 30-bus system.