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The outputs of this part include the expected wind power generation trajectory of each wind farm, the joint cumulative distribution function (JCDF) of the forecast errors, and the corresponding multi- dimensional scenarios.

3) Quality evaluation of multi-dimensional scenarios.

Multi-dimensional scenarios can be generated from the JCDF of the random variables.

Open image in new window Fig. 13 Generated multi-dimensional scenarios.

Step 3: Generate V groups of multi-dimensional scenarios of wind power generation.

It is seen that without the scaling factor, the MUSCL scheme may not necessarily be monotonic in multi-dimensional scenarios.

The forecast result is the possible trajectories of the outputs of the wind farms which are referred to as the multi-dimensional scenarios.

Therefore, the multi-dimensional scenarios of wind power generation are produced with respect to the spot forecast result, PDF of the spot forecast error, and the Gaussian copula.

A set of 50 multi-dimensional scenarios corresponding to the predicted PDF and the estimated Gaussian copula is depicted in Fig. 13.

Energy score (ES), which is a multivariate verification tool for the forecasted scenarios, is applied to evaluate the quality of the generated multi-dimensional scenarios [27].

A multi-dimensional scenario forecast approach is proposed in this paper.