Black-start value considering wind power uncertainty based on KL divergence

Abstract

With the aggravation of global energy shortage, it is imperative for new energy to be connected in a high proportion in the power system. In the context of a new power system, the high proportion of wind power access brings greater challenges to the recovery process after a major power failure. Therefore, it is of great significance to study wind power uncertainty processing methods for evaluating the impact of wind power black start value. Due to the correlation between multiple wind farms, Copula theory was first used to analyze, and Latin hypercube sampling was used to get the typical wind speed scenarios with correlation, and then the synchronous back-substitution method was used to subdue the typical scenarios. On this basis, the fuzzy set based on KL divergence was established to obtain the wind power output sequence. Then, the risk value theory was introduced to establish the wind power black start value model considering the extreme output of wind power. Finally, IEEE 39-bus system with wind farms was given to verify the effectiveness of the proposed method. The applicability of wind power black-start value is improved.