Allocation of Power Quality Monitors by Genetic Algorithms and Fuzzy Sets Theory

The aim of this article is to present the application of Genetic Algorithms (GA's) and Fuzzy Mathematical Programming in the design of Voltage Sag and Swell monitoring systems for power transmission networks. The proposed methodology uses the simulations 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 (number of monitors and buses where they are supposed to be installed) are assessed through GA's. Two different GA modeling 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. The evaluation of the methodology performance for the IEEE 30- buses network is presented, and a comparison between the results achieved and the results from a similar work in the same field is carried out.

[1]  Carlos César Barioni de Oliveira,et al.  Fuzzy decision model for the reconfiguration of distribution networks using genetic algorithms , 1999 .

[2]  Math Bollen,et al.  Stochastic prediction of voltage sags in a large transmission system , 1998, 1998 IEEE Industrial and Commercial Power Systems Technical Conference. Conference Record. Papers Presented at the 1998 Annual Meeting (Cat. No.98CH36202).

[3]  Math Bollen,et al.  Optimal dips monitoring program for characterization of transmission system , 2003, 2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491).

[4]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[5]  R. Romero,et al.  Optimal Capacitor Placement in Radial Distribution Networks , 2001, IEEE Power Engineering Review.

[6]  Math Bollen,et al.  Understanding Power Quality Problems: Voltage Sags and Interruptions , 1999 .

[7]  Math Bollen,et al.  Stochastical and statistical assessment of voltage dips , 1998 .