Intelligent Expert System for Power Quality Improvement Under Distorted and Unbalanced Conditions in Three-Phase AC Microgrids

This paper presents an expert system (ES) based on decoupled power/current decomposition and the {k} -nearest neighbor pattern recognition method to identify and choose the correct mitigation solution for power quality improvement in three-phase ac microgrids under non-sinusoidal current and voltag...

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Bibliographic Details
Published in:IEEE transactions on smart grid 2018-11, Vol.9 (6), p.6951-6960
Main Authors: Moreira, Alexandre C., Paredes, Helmo K. M., de Souza, Wesley A., Marafao, Fernando P., da Silva, Luiz C. P.
Format: Article
Language:English
Subjects:
Alternating current
Capacitors
Conservative power theory
Distributed generation
Electric power grids
expert system
Expert systems
Harmonic analysis
harmonics
k-NN classifier
microgrid
Microgrids
Pattern recognition
power factor
Power harmonic filters
Power quality
Reactive power
Robustness (mathematics)
unbalance loads
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Description
Summary:This paper presents an expert system (ES) based on decoupled power/current decomposition and the {k} -nearest neighbor pattern recognition method to identify and choose the correct mitigation solution for power quality improvement in three-phase ac microgrids under non-sinusoidal current and voltage operations. By using power/current terms, load conformity factors and a {k} -nearest neighbor classifier, the proposed ES achieved 99.98% classification accuracy. Simulation studies were carried out in a PSCAD/EMTDC environment, where the IEEE 13-bus feeder test system was in a grid connected microgrid mode. The obtained results indicate that the proposed ES is robust and able to easily select an appropriate/adequate compensation solution.
ISSN:1949-3053
1949-3061
DOI:10.1109/TSG.2017.2771146