Comparing probabilistic load flow methods in dealing with uncertainties at TSO/DSO interface

摘要

Increasing decentralized and renewable power production, which is mainly installed in distribution networks, makes planning of the transmission network more challenging. The application of probabilistic power flow methods provides additional information that can be used to predict future power flows in networks with a high share of decentralized and renewable generation. This paper compares numerical and analytical probabilistic power flow approaches focusing on the trade-off between computational time and information gain. It is shown that for the 6-bus Roy Billinton Test System, using normally distributed random variables, the analytical method is a suitable alternative to the numerical method. Reducing computational effort while retaining considerable accuracy. This makes analytical probabilistic power flow an interesting method for studying networks with a high share of decentralized and renewable generation.