Time Decomposition for Diagnosis of Discrete Event

Research on future energy systems shows that an electricity network is often tolerant to failures but may collapse after encountering a certain number of failures that take place within a short period of time. The smart grid is the upcoming generation of electricity networks. Challenges faced in the smart grid include prompt, reliable, and informative alarm processing to detect the points of failure. Another aspect is inferring the root cause for failures. Being able to accurately and promptly determine the fault occurrences allows rapid intervention, which leads to faster restoration and lower vulnerability to multiple faults. This work focuses on systems modeled by a Discrete Event System (DES). A DES is a system model representing state dynamics in a discrete manner [Cassandras and Lafortune, 2008]. DES provides a common modeling framework for diagnosis problems retaining the properties with a discrete nature.