Reliability analysis of emergency and standby power systems

Different facilities have varying requirements for reliability of electric power supply. The reliability indices of an actual physical system can be estimated by collecting data on the occurrence of failures and the durations of repair. The Monte Carlo method mimics the failure and repair history of the components and the system by using the probability distributions of the component state durations. Statistics are then collected and indices estimated using statistical inference. There are two basic approaches for Monte Carlo simulation: (1) sequential simulation and (2) random sampling. The sequential simulation proceeds by generating a sequence of events using random numbers and probability distributions of random variables representing component state durations. In random sampling, states are drawn based on the probability distributions of component states and random numbers. Further, there are two methods for representing the passage of time in sequential simulation: (1) the fixed interval method, also called synchronous timing, and (2) the next event or asynchronous timing method. In the fixed interval method, time is advanced in steps of fixed length and the system state is updated. In the next event method, time is advanced to the occurrence of the next event. In actual implementations, it is likely that combinations of the timing controls may be used. The sampling method is generally faster than the sequential technique, but is suitable when component failures and repairs are independent. This article presents the sequential method for reliability analysis