Forced outages information treatment system and cause identification based on mobile computing and neural networks

The use of outage management systems is becoming vital for distribution utilities in the new paradigm of power systems competition and deregulation. These efforts include fuzzy logic, expert systems, heuristic applications and neural networks. These techniques allow to process and validate real-time data in order to feed a database for statistic analysis. This paper presents a computational system for forced outage event acquisition, validation and cause identification based on mobile computing and neural networks. The system is divided into two modules: one to collect and validate, based on mobile computing, forced-outage event data information (conditions in the surrounding environments) at local; and an other one to identify and classify the forced-outage caused using artificial neural networks (ANN).