Intelligent Expert System for Power Quality Improvement Under Distorted and Unbalanced Conditions in Three-Phase AC Microgrids
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Data
2018-11-01
Autores
Moreira, Alexandre C.
Paredes, Helmo K. M. [UNESP]
Souza, Wesley A. de
Marafao, Fernando P. [UNESP]
Silva, Luiz C. P. da
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Ieee-inst Electrical Electronics Engineers Inc
Resumo
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.
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Palavras-chave
Conservative power theory, distributed generation, expert system, k-NN classifier, harmonics, microgrid, power factor, reactive power, unbalance loads
Como citar
Ieee Transactions On Smart Grid. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 9, n. 6, p. 6951-6960, 2018.