H
Hung Duc Nguyen
Researcher at Australian Maritime College
Publications - 71
Citations - 717
Hung Duc Nguyen is an academic researcher from Australian Maritime College. The author has contributed to research in topics: Control theory & Remotely operated underwater vehicle. The author has an hindex of 11, co-authored 67 publications receiving 466 citations. Previous affiliations of Hung Duc Nguyen include University of Tasmania.
Papers
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A hybrid energy management and battery size optimization for standalone microgrids: a case study for Flinders Island, Australia
Kutaiba S. El-Bidairi,Hung Duc Nguyen,Shantha Gamini Jayasinghe,Thair S. Mahmoud,Irene Penesis +4 more
TL;DR: The results show that the intelligent online multi-objective energy management strategy is capable of managing a smooth power flow with the same optimal configuration in the isolated microgrid, minimising the fossil fuel utilisation and reducing the CO2 emission level.
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Optimal sizing of Battery Energy Storage Systems for dynamic frequency control in an islanded microgrid: A case study of Flinders Island, Australia
Kutaiba S. El-Bidairi,Hung Duc Nguyen,Thair S. Mahmoud,Shantha Gamini Jayasinghe,Josep M. Guerrero +4 more
TL;DR: An approach for finding the optimum BESS size for an islanded microgrid power system is proposed based on an existing case study, under which the most severe contingencies of generation loss and load loss have been accounted for, as well as different levels of penetration of renewable energy sources.
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Grey Wolf Optimization-Based Optimum Energy-Management and Battery-Sizing Method for Grid-Connected Microgrids
Kutaiba Sabah Nimma,Monaaf D.A. Al-Falahi,Hung Duc Nguyen,Shantha Gamini Jayasinghe,Thair S. Mahmoud,Michael Negnevitsky +5 more
TL;DR: In this article, the grey wolf optimization (GWO) technique was used to meet the requirements of intelligent energy management and battery sizing in the microgrid to ensure the optimal use of the renewable sources and reduce conventional fuel utilization in such complex systems.
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Unscented Kalman Filter trained neural networks based rudder roll stabilization system for ship in waves
TL;DR: In this article, a rudder roll stabilization system based on Radial Basis Function Neural Network (RBFNN) control algorithm for ship advancing in the seaway only through rudder actions is proposed.
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Experimental Study of Command Governor Adaptive Control for Unmanned Underwater Vehicles
TL;DR: Experimental results showed that CGAC performs better than standard MRAC and thus is a promising solution for future underwater vehicle applications.