Modelling Correlated Forecast Error for Wind Power in Probabilistic Load Flow
The deepening penetration of wind power has brought about increasing uncertainty in power grid. In system operation, this uncertainty is mainly attributed to forecast uncertainty, which remains a challenging issue in uncertainty analysis. In this paper, a statistical model based on the mixed skewed distribution is developed to provide a perfect fitting for the conditional wind power forecast error in a single wind farm. The dependence structure of forecast error for multiple wind farms is obtained by pair-copula method, which takes mutual dependence of two arbitrary wind farms into account. The case study on a realistic transmission network in China is presented and different modelling schemes are compared to demonstrate the effectiveness of the proposed model in the application of probabilistic load flow.
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