CLASSIFICATION OF POWER QUALITY CONSIDERING VOLTAGE SAGS IN DISTRIBUTION SYSTEMS USING KDD PROCESS
AUTOR(ES)
Góes, Anderson Roges Teixeira, Steiner, Maria Teresinha Arns, Peniche, Rodrigo Antonio
FONTE
Pesqui. Oper.
DATA DE PUBLICAÇÃO
2015-08
RESUMO
In this paper, we propose a methodology to classify Power Quality (PQ) in distribution systems based on voltage sags. The methodology uses the KDD process (Knowledge Discovery in Databases) in order to establish a quality level to be printed in labels. The methodology was applied to feeders on a substation located in Curitiba, Paraná, Brazil, considering attributes such as sag length (remnant voltage), duration and frequency (number of occurrences on a given period of time). On the Data Mining Stage (the main stage on KDD Process), three different techniques were used, in a comparative way, for pattern recognition, in order to achieve the quality classification for the feeders: Artificial Neural Networks (ANN); Support Vector Machines (SVM) and Genetic Algorithms (GA). By printing a label with quality level information, utilities companies (power concessionaires) can get better organized for mitigation procedures by establishing clear targets. Moreover, the same way costumers already receive information regarding PQ based on interruptions, they will also be able to receive information based on voltage sags.
Documentos Relacionados
- Detecção e classificação de VTCDs em sistemas de distribuição de energia elétrica usando redes neurais artificiais.
- Methodology for monitoring voltage SAGs and SWELLs in power systems.
- A robustez de um sistema de distribuição e a alocação de medidores de qualidade da energia elétrica frente aos afundamentos de tensão
- Optimal operation of basic voltage control equipment on power distribution systems
- Conversores de freqüencia VSI-PWM submetidos a afundamentos temporários de tensão ("voltage sags")