Multi-wind Farm Output Scenario Generation Method Based on Copula Function

In the case of large-scale wind power connected to the power system, because wind power is unstable, uncontrollable, and random, it is important to obtain their change laws and generate scenarios. Aiming at the difficulty of generating scenarios for multiple wind farms and the poor effect of scenario generation, this paper proposes a scenario generation method based on copula function and kernel density estimation method. This method can take into account both time correlation and spatial correlation for better power system scheduling and planning. In order to verify the accuracy and effectiveness of this method, this paper takes the output of actual wind farms in a region of a certain province, China as a sample, and generates a large number of spatially and temporally correlated wind power output scenarios. These generated scenarios better reflect the correlation between the output of multiple wind farms. This paper also validates the superiority of the proposed method by using several assessment methods.