Expected power loss calculation including protection failures using importance sampling and SOM

Protection failures are rare events, which may result in cascading outages in power systems. Importance sampling is one of the "variance reduction" techniques for rare event simulation in reliability studies. However, in certain reliability analyses applications, importance sampling method reveals some disadvantages, which can be overcome by the introduction of SOM (self organizing map). This paper demonstrates the application of combination of importance sampling and SOM in power system reliability analysis considering protection failures. Both importance sampling and SOM techniques are embedded into non-sequential Monte Carlo simulation implementing the stochastic properties of contingencies, protective response and protection system failures. This newly developed methodology can be called "importance sampling + SOM" based Monte Carlo simulation scheme, which can deal with reliability analysis with rare events efficiently. The IEEE RTS system is used as the test system to demonstrate the performance of this approach.