Analysis of wind power output characteristics and output prediction

Abstract

Abstract A fuzzy clustering method and a prediction correction method based on the Copula function are used to establish an analytical model of wind power generation output characteristics. It also predicts the expected and corrected values of its power generation to alleviate the pressure on the grid caused by the high proportion of random new energy sources connected to the grid. Based on the natural properties of wind, a new characteristic index based on the traditional load characteristic index and the new energy output curve is proposed to quantify and evaluate the characteristics of new energy power generation. The results show that the method proposed in this paper can effectively reduce the influence of climate change on output prediction; in comparison to the traditional index, the new index is more refined and instructive.