Monte Carlo simulation applied to support risk-based decision making in electricity distribution networks

Risk management, as a decision-making process, is a key enabler in successful asset management for asset intensive industries such as electricity network companies. With the introduction of PAS55 and more recently the ISO55000 for asset management, there is an increasing need for probabilistic risk modelling tools. In this paper the methodology of Monte Carlo Simulation (MCS) has been adopted and the potential utilization of this for risk-based asset management decision-making purposes has been investigated for a Dutch Distribution System Operator (DSO), Stedin. Several case studies with the focus on the prediction of customer interruptions in the electrical distribution networks are performed with the main focus on medium voltage (MV) cables and cable joint failures. The MCS is performed for 12 MV radial feeder systems. For each cable section and cable joint separate failure distribution models have been used to characterize the failure behavior on the basis of historical data and statistical life data analysis. This information is used as input for the MCS. On the whole, it can be concluded that all historical actual occurred outages for these 12 feeder systems were possible outcomes from the MCS simulations. This implies that the amount of customer outages could have been predicted through the MCS. Therefore, on the basis of this work, the utilization of MCS for risk based decision-making for DSOs as part of their asset management system is recommended.