TY - GEN
T1 - Artificial Intelligence-Aided Optimization Strategy for Three-Level DAB Converters Modulated with Five DoFs
AU - Feng, Zhichen
AU - Wen, Huiqing
AU - Han, Xu
AU - Wang, Gunagyu
AU - Zhu, Yinxiao
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The three-level dual-active-bridge (DAB) converter presents several benefits, including enhanced control flexibility and the ability to use power switches with lower voltage ratings compared to traditional two-level DAB converters. To improve transmission efficiency, an optimization approach based on deep reinforcement learning (DRL) has been proposed, leveraging the five degrees of freedom (5- DoFs) control method. This approach applies the deep deterministic policy gradient (DDPG) algorithm to minimize power losses and determine optimal control strategies. The trained DDPG agent functions as a predictor, facilitating appropriate control actions under varying operational conditions. The main goal is to maximize efficiency by minimizing power losses. With the proposed strategy, the conversion efficiency is well improved, and the effectiveness is verified by experiment results under various conditions.
AB - The three-level dual-active-bridge (DAB) converter presents several benefits, including enhanced control flexibility and the ability to use power switches with lower voltage ratings compared to traditional two-level DAB converters. To improve transmission efficiency, an optimization approach based on deep reinforcement learning (DRL) has been proposed, leveraging the five degrees of freedom (5- DoFs) control method. This approach applies the deep deterministic policy gradient (DDPG) algorithm to minimize power losses and determine optimal control strategies. The trained DDPG agent functions as a predictor, facilitating appropriate control actions under varying operational conditions. The main goal is to maximize efficiency by minimizing power losses. With the proposed strategy, the conversion efficiency is well improved, and the effectiveness is verified by experiment results under various conditions.
KW - conversion efficiency
KW - deep reinforcement learning (DRL)
KW - degree-of-freedom
KW - Dual-Active-Bridge (DAB)
UR - http://www.scopus.com/inward/record.url?scp=85217160337&partnerID=8YFLogxK
U2 - 10.1109/ICRERA62673.2024.10815185
DO - 10.1109/ICRERA62673.2024.10815185
M3 - Conference Proceeding
AN - SCOPUS:85217160337
T3 - 13th International Conference on Renewable Energy Research and Applications, ICRERA 2024
SP - 1457
EP - 1462
BT - 13th International Conference on Renewable Energy Research and Applications, ICRERA 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th International Conference on Renewable Energy Research and Applications, ICRERA 2024
Y2 - 9 November 2024 through 13 November 2024
ER -
