Copula Based Dependent Discrete Convolution for Power System Uncertainty Analysis

Discrete convolution (DC) is a generally accepted approach for the probabilistic analysis such as reliability assessment and probabilistic load flow. However, it has a strong precondition that the stochastic variables being convolved must be independent, which may not be fully satisfied in all cases. Using copula functions, this letter derives the formulation of DC for dependent variables. The performance of the proposed dependent discrete convolution (DDC) is illustrated using reliability assessment involving wind power. The result shows that the DDC inherits the efficient and reliable performance of DC, indicating a promising potential for practical applications.