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Optimal control strategy of voltage source converter-based high-voltage direct current under unbalanced grid voltage conditions

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      Abstract

      This study presents an optimisation control strategy for the power control of voltage source converter-based high-voltage direct current transmission under unbalanced grid voltage conditions. To facilitate simple implementation and flexible operation, the current references are derived and synthesised into one generalised equation that introduces two individually adaptable parameters. The two parameters can be adapted to eliminate the oscillations of instantaneous active and reactive power, as well as the currents at the grid side under unbalanced grid voltage conditions. The optimisation method based on particle swarm optimisation algorithm is presented to determine the two parameters. The simulation is conducted with PSCAD/EMTDC. The results show that the proposed strategy is effective and feasible.

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      Most cited references 19

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      Flexible Active Power Control of Distributed Power Generation Systems During Grid Faults

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        Regulation of a PWM rectifier in the unbalanced network state using a generalized model

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          Dual current control scheme for PWM converter under unbalanced input voltage conditions

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            Author and article information

            Affiliations
            College of Energy and Electrical Engineering, Hohai University , Nanjing, People's Republic of China
            Contributors
            Journal
            IET-GTD
            IET Generation, Transmission & Distribution
            IET Gener. Transm. Distrib.
            The Institution of Engineering and Technology
            1751-8687
            1751-8695
            4 February 2016
            : 10
            : 2
            : 444-451
            10.1049/iet-gtd.2015.0749 IET-GTD.2015.0749 GTD.2015.0749.R1

            This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)

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            Funding
            Funded by: National Key Basic Research Program of China
            Award ID: 2013CB228204
            Funded by: National Natural Science Foundation of China
            Award ID: 51137002
            Categories
            Research Articles

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