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• W42508739 abstract "Supervisory Control and Data Acquisition (SCADA) systems are fundamental tools for quick fault diagnosis and efficient restoration of power systems. When multiple faults, or malfunctions of protection devices occur in the system, the SCADA system issues many alarm signals rapidly and relays these to the control center. The original cause and location of the fault can be difficult to determine for operators under stress without assistance from a computer aided decision support system. In cases of power system disturbances, network operators in the control center must use their judgement and experience to determine the possible faulty elements as the first step in the restoration procedures. If a breaker or its associated relays fail to operate, the fault is removed by backup protection. In such cases, the outage area can be large and it is then difficult for the network operators to estimate the fault location. Multiple faults, events and actions may eventually take place with many breakers being tripped within a short time. In these circumstances, many alarms need to be analysed by the operators to ensure that the most appropriate actions are taken [1]. Therefore, it is essential to develop software tools to assist in these situations." @default.
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• W42508739 date "2008-12-23" @default.
• W42508739 modified "2023-09-25" @default.
• W42508739 title "Developing a Knowledge-Based System Using Rough Set Theory and Genetic Algorithms for Substation Fault Diagnosis" @default.
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• W42508739 doi "https://doi.org/10.1007/978-3-540-89921-1_11" @default.
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