Implementing Intelligent Techniques for the Advanced Alarm Processing

Abstract

A major power system disturbance could trigger hundreds and sometimes thousands of individual alarms and events. A better and simpler description of the problems affecting the power system is an urgent need for the operators. The task of an Intelligent Alarm Processor (IAP) is to analyze thousands of alarm messages and extract the information that explains causeeffect sequences associated with the network events. In this sense, Fuzzy Reasoning Petri-nets is a very powerful intelligent technique to deal with the complexities of the power system fault and alarm processing. A graphical FRPN model is build in this paper based on the optimal structure and uses fuzzy logic parameters to effectively tackle the uncertainties. Case studies are presented to demonstrate the capability of the IAP under real fault scenarios.

Binary integer programming applied to fault section estimation in power systems

“…Recently, many Metaheuristics inspired by various natural processes have been developed and applied to solve the FSE problem [6]. An immune system was proposed in [7] to fault location, which logical relations of expected and actual status of protective devices are considered in an unconstrained binary programming model.…”