Intelligent Expert System for Power Quality Improvement Under Distorted and Unbalanced Conditions in Three-Phase AC Microgrids
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Ieee-inst Electrical Electronics Engineers Inc
Institute of Electrical and Electronics Engineers (IEEE)
Institute of Electrical and Electronics Engineers (IEEE)
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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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Ieee Transactions On Smart Grid. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 9, n. 6, p. 6951-6960, 2018.
