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Fuzzy-based self-tuning model predictive direct power control of grid-connected multilevel converters | IEEE Conference Publication | IEEE Xplore

Fuzzy-based self-tuning model predictive direct power control of grid-connected multilevel converters


Abstract:

This paper proposes a self-tuning model predictive direct power control (MPDPC) strategy for power flow control and power quality improvement in grid-connected power conv...Show More

Abstract:

This paper proposes a self-tuning model predictive direct power control (MPDPC) strategy for power flow control and power quality improvement in grid-connected power converters. At each sampling instant, a fuzzy logic controller is used to determine online the best weighting factor values for a given operating point. These values are then used to solve the multi-objective optimal control problem associated to the MPDPC. The optimal solution that minimizes the multi-objective cost function is chosen as the input (power switch state). The proposed method is examined through a case study and verified numerically via MAT LAB SIMULINK. A comparative study is conducted to demonstrate the effective performance of this approach. As a result of the proposed weighting factor online tuning, an improved performance in terms of total harmonic distortion and average switching frequency is attained when compared with fixed weighting factors.
Date of Conference: 11-14 August 2017
Date Added to IEEE Xplore: 05 October 2017
ISBN Information:
Conference Location: Sydney, NSW, Australia

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