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

• Autor(a) principal: Moreira, Alexandre C.
• Data de Publicação: 2018
• Outros Autores: Paredes, Helmo K. M. [UNESP], Souza, Wesley A. de, Marafao, Fernando P. [UNESP], Silva, Luiz C. P. da
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1109/TSG.2017.2771146; http://hdl.handle.net/11449/186518
• topic: Conservative power theory; distributed generation; expert system; k-NN classifier; harmonics; microgrid; power factor; reactive power; unbalance loads

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.