Li, S and Fu, X and Alonso, E and Fairbank, M and Wunsch, DC (2016) Neural-network based vector control of VSCHVDC transmission systems. In: International Conference on Renewable Energy Research and Applications (ICRERA), 2015, 2015-11-22 - 2015-11-25.
Li, S and Fu, X and Alonso, E and Fairbank, M and Wunsch, DC (2016) Neural-network based vector control of VSCHVDC transmission systems. In: International Conference on Renewable Energy Research and Applications (ICRERA), 2015, 2015-11-22 - 2015-11-25.
Li, S and Fu, X and Alonso, E and Fairbank, M and Wunsch, DC (2016) Neural-network based vector control of VSCHVDC transmission systems. In: International Conference on Renewable Energy Research and Applications (ICRERA), 2015, 2015-11-22 - 2015-11-25.
Abstract
The application of high-voltage dc (HVDC) using voltage-source converters (VSC) has surged recently in electric power transmission and distribution systems. An optimal vector control of a VSC-HVDC system which uses an artificial neural network to implement an approximate dynamic programming algorithm and is trained with Levenberg-Marquardt is introduced in this paper. The proposed neural network vector control algorithm is analyzed in comparison with standard vector control methods for various HVDC control requirements, including dc voltage, active and reactive power control, and ac system voltage support. Assessment of the resulting closed-loop control shows that the neural network vector control approach has superior performance and works efficiently within and beyond the constraints of the HVDC system, for instance, converter rated power and saturation of PWM modulation.
Item Type: | Conference or Workshop Item (Paper) |
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Additional Information: | Notes: |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 12 Dec 2016 21:46 |
Last Modified: | 24 Oct 2024 23:02 |
URI: | http://repository.essex.ac.uk/id/eprint/18485 |