Probabilistic active distribution network equivalence with correlated uncertain injections for grid analysis

Abstract

Equivalent modelling for active distribution networks (ADNs) is essential for improving the efficiency of analysing transmission networks. Current equivalent modelling methods for ADNs neglect the probabilistic characteristics of renewable energy sources (RESs) and loads. To address this issue, this study proposes a probabilistic equivalent modelling method (PEMM) for ADNs considering the uncertainty of RESs and loads. The uncertainty of the RESs and loads is transferred to the equivalent boundary bus injection using the properties of cumulant and power transfer matrices. The PEMM is extended to incorporate the correlations of RESs through an orthogonal transformation. A sampling method using the Gaussian copula function is employed to generate the correlated samples and the joint cumulants, providing the input data for the PEMM. The comparative results of the case studies on two different test systems demonstrate the effectiveness of the PEMM. The equivalent model developed in this study is a practical solution for analysing the transmission network efficiently and taking the uncertainty of RESs and loads in the ADNs into account simultaneously.