A dominance based rough set classification system for fault diagnosis in electrical smart grid environments

Nowadays, power grid monitoring systems are shifting towards more disseminating and distributive operations. The diagnosis of faults using knowledge discovery techniques has become an essential component of the process, accounting to the challenges faced by the electrical power monitoring systems. The system’s operators employ various energy management techniques which play important roles in the overall management, reliability and operational sustainability of smart grid utilities. Sometimes, these systems are disrupted by events like a short circuit in the system or any external incursion that could pose a threat to the public safety as well as to the critical infrastructure of the grid. This paper aims at providing a robust system for fault diagnosis using the status of an intelligent electronic device and circuit breakers which can be tripped by any kind of fault. To protect the system from vulnerabilities and different kinds of faults, a multilayered fault estimation classifier, based on the Dominance based rough set is proposed. This technique provides an effective solution to the system’s operator for the proper diagnosis of the faults and intrusions by classifying the state of the system. In addition to this, the operator can take preventative measures to protect the system from further damage.