Voltage THD Analysis Using Knowledge Discovery in Databases With a Decision Tree Classifier | Zendy

Edson Farias de Oliveira | Zendy; Maria Emilia de Lima Tostes | Zendy; Carlos Alberto Oliveira de Freitas | Zendy; Jandecy Cabral Leite | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Voltage THD Analysis Using Knowledge Discovery in Databases With a Decision Tree Classifier

Author(s) -

Edson Farias de Oliveira,

Maria Emilia de Lima Tostes,

Carlos Alberto Oliveira de Freitas,

Jandecy Cabral Leite

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2017.2778028

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

Industrial production has evolved significantly over the last decade. For this reason, it is necessary to obtain mathematical and computational tools that enable power systems engineers to make decisions that reduce harmonic distortions in accordance with international standards. This paper presents a total harmonic distortion (THD) assessment based on full knowledge discovery in databases (KDD) using power quality (PQ) standards and computational intelligence tools. The materials and methods of THD assessment consist of load and layout analysis; choice and installation of PQ analyzers; and the application of the full KDD process, including collection, selection, cleaning, integration, transformation and reduction, mining, interpretation, and evaluation of the data. This research methodology was used in an electrical and electronic industry; the results obtained have characteristics that can be used as a reference for other types of analyses. The results indicate that these methods can be applied to several industrial applications such as: 1) the description of the complete KDD process for THD assessment of the point of common coupling; 2) simultaneous collection using five PQ analyzers at several points in the electrical network; and (3) the use of a decision tree classifier.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research