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Reactive power minimization of dual active bridge DC/DC converter with triple phase shift control using neural network.

Harrye, Yasen A.; Ahmed, Khaled H.; Aboushady, Ahmed A.

Authors

Yasen A. Harrye

Khaled H. Ahmed

Ahmed A. Aboushady



Abstract

Reactive power flow increases dual active bridge (DAB) converter RMS current leading to an increase in conduction losses especially in high power applications. This paper proposes a new optimized triple phase shift (TPS) switching algorithm that minimizes the total reactive power of the converter. The algorithm iteratively searches for TPS control variables that satisfy the desired active power flow while selecting the operating mode with minimum reactive power consumption. This is valid for the whole range of converter operation. The iterative algorithm is run offline for the entire active power range (-1pu to 1pu) and the resulting data is used to train an open loop artificial neural network controller to reduce computational time and memory allocation necessary to store the data generated. To validate the accuracy of the proposed controller, a 500-MW 300kV/100kV DAB model is simulated in Matlab/Simulink, as a potential application for DAB in DC grids.

Start Date Oct 19, 2014
Publication Date Jan 22, 2015
Publisher Institute of Electrical and Electronics Engineers
Pages 566-571
Institution Citation HARRYE, Y.A., AHMED, K.H. and ABOUSHADY, A.A. 2014. Reactive power minimization of dual active bridge DC/DC converter with triple phase shift control using neural network. In Proceedings of the 3rd International conference on renewable energy research and applications (ICRERA 2014), 19-22 October 2014, Milwakuee, USA. Piscataway: IEEE [online], pages 566-571. Available from: https://doi.org/10.1109/ICRERA.2014.7016448
DOI https://doi.org/10.1109/ICRERA.2014.7016448
Keywords DCDC converter; Dual active bridge (DAB) converter; Neural network (NN) controller; Reactive power; Triple phase shift (TPS)

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