A powerful technique used for power system composite reliability evaluation is Monte Carlo Simulation (MCS). There are two approaches to MCS in this context: non-sequential MCS, in which the system states are randomly sampled, and sequential MCS, in which the chronological behaviour of the system is simulated by sampling sequences of system states for several time periods. The sequential MCS approach can provide information that the non-sequential can not, but requires higher computational effort and is more sequentially constrained. This paper presents a parallel methodology for composite reliability evaluation using sequential MCS on three different computer platforms: a scalable distributed memory parallel computer IBM RS/6000 SP with 10 processors, a network of workstations (NOW) composed of 8 IBM RS/6000 43P workstations and a cluster of PCs composed of 8 Pentium III 500MHz personal microcomputers. The results obtained in tests with actual power system models show considerable reduction of the simulation time, with high speedup and good efficiency.
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