The aim of this article is to present the application of Genetic Algorithms (GAs) and Fuzzy Mathematical Programming in the design of voltage sag and swell monitoring systems for power transmission networks. The proposed methodology uses the simulation of different types of short-circuit in many different points of the power system, in order to characterize the system behavior towards the occurrence of voltage sags and swells. Then, different configurations for the monitoring system, i.e. number of monitors and buses where they are supposed to be installed, are assessed through GAs. Two different GA codifications are presented, namely one based on binary vectors, for the decision over the installation of a monitor in a specific bus of the power system and another based on integer vectors, in order to indicate in which buses the monitors should be installed. A comparison between the two models is presented. The evaluation of the methodology performance is determined for a real 154 bus transmission network. The methodology is also applied for the IEEE 30 bus network, in order to allow its comparison with a previous research work.
optimal power quality meters allocation; power quality monitoring; voltage sags and swells; genetic algorithms; fuzzy sets theory
