Multiple Wind Farms Power Generation Scenario Generation and Reduction Based on Multivariate Copula Function and Greedy Strategy

Large scale access integration of wind power generation brings great challenges to power system. Scenario generation and reduction are the basis for power system security assessment. Existing scenario generation methods cannot characterize spatial correlation of multiple wind power accurately and existing scenario reduction methods have low efficiency. For the shortcomings of current studies, a scenario generation method based on multivariate copula function is proposed to accurately characterize the correlation of multiple wind farms power. And a scenario reduction method based on greed strategy and K-means algorithm is proposed to improve the computational efficiency. Finally, taking two geographically similar wind farms in a China province as an example, the effectiveness of the proposed method is verified.