DocumentCode
2672560
Title
Allocation of Power Quality Monitors by Genetic Algorithms and Fuzzy Sets Theory
Author
Almeida, Carlos F. M. ; Kagan, Nelson
Author_Institution
Enerq-Center for Regul. & Power Quality Studies, Univ. of Sao Paulo, Sao Paulo, Brazil
fYear
2009
fDate
8-12 Nov. 2009
Firstpage
1
Lastpage
6
Abstract
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.
Keywords
fuzzy set theory; genetic algorithms; power supply quality; power system measurement; IEEE 30 buses network; binary vectors; fuzzy sets theory; genetic algorithms; power quality monitors; power transmission networks; voltage sag monitoring; voltage swell monitoring; Algorithm design and analysis; Fuzzy set theory; Fuzzy systems; Genetic algorithms; Mathematical programming; Monitoring; Power quality; Power system modeling; Power system simulation; Voltage fluctuations;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent System Applications to Power Systems, 2009. ISAP '09. 15th International Conference on
Conference_Location
Curitiba
Print_ISBN
978-1-4244-5097-8
Electronic_ISBN
978-1-4244-5098-5
Type
conf
DOI
10.1109/ISAP.2009.5352942
Filename
5352942
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