Stochastic approach using Petri nets for maintenance optimization in Belgian power systems

In this paper, we propose a Petri net-based stochastic model for the simulation and evaluation of complex maintenance activities for the Belgian power system. The main objective of this modeling approach is to develop a decision-aiding tool in order to improve the maintenance and renewal decisions in terms of their consequences on the total maintenance costs and on the global performance of the power system. The model takes into account the different constraints influencing the maintenance and renewal policies. A single component, presenting two failure modes and periodically inspected and maintained according to its degradation level, is investigated first, before studying a system corresponding to a simplified feeder. A Petri net-based Monte Carlo simulation of these two cases is performed in order to estimate the costs entailed by several possible maintenance policies.