Modern active distribution networks make use of intelligent switching actions to restore supply to end users after faults. This complicates the reliability analysis of such networks, as the number of possible switching actions grows exponentially with network size. This paper proposes an approximate reliability analysis method where switching actions are modelled implicitly. It can be used graphically as a model reduction method, and
simulated using time-sequential or state sampling Monte Carlo
methods. The method is illustrated on a simple distribution
network, and reliability indices are reported both as averages and
distributions. Large speedups result from the use of biased non-sequential Monte Carlo sampling–a method that is hard to combine with explicit switch
ing models.