A Markov Model Based Algorithm for Calculating Mean Downtimes of Distribution Feeders

Distribution utilities compute several reliability indices to assess the reliability performance of power systems. In reliability-based planning, these indices are computed using reliability planning models. Such models require failure rates and mean downtimes of distribution feeders as inputs. At present, there is a lack of models for calculating operational mean downtimes of distribution feeders. This paper proposes a Markov model which represents failures in a feeder and operations circumstances in fault recovery. This proposed model can efficiently calculate the operational mean downtime of a feeder, using analytical equations. An algorithm and a graphical user interface are also developed based on the proposed model, in order to integrate the proposed model with software tools. Two case studies are conducted on two selected feeders, using actual data obtained from failure and repair histories and experts' opinion. Results of case studies show the applicability of our proposed Markov model-based algorithm to calculate mean downtimes of distribution feeders. The Markov model is validated by comparing results provided by the proposed algorithm with the results obtained using Monte Carlo simulation. The proposed Markov model-based algorithm would be very useful for utilities to calculate operational mean downtimes required for reliability-based planning models.