@inproceedings{9b7c95366ea34a758e3d8ab1240a5b3c,
title = "Deep-learning-based Fast System-level Harmonic Control Strategy for Multi-bus Voltages Detected APF in Distribution Systems",
abstract = "Conventional linearized-model-based system-level control strategy of active power filter (APF) has poor dynamic control performance when load changing happens. Therefore, a four-layer neural network is built to learn the convergence behavior of the linearized system-level harmonic mitigation model. Then, a deep-learning-based control strategy is proposed to achieve fast mitigation of multi-bus harmonic voltages by single APF. Finally, an eight-bus system with distributed harmonic loads is built in simulation. Simulation results proves the good dynamic performance of the proposed method. Moreover, compared with conventional implementation of deep learning method in system-level harmonic control, the proposed method benefits in lower data demand and simplified training process.",
keywords = "deep learning, harmonic, harmonics active filter, neural network, power quality",
author = "Zebin Yang and Hao Yi and Xian Wu and Fang Zhuo and Lingyu Zhu and Qing Wang",
note = "Publisher Copyright: {\textcopyright} 2023 EPE Association.; 25th European Conference on Power Electronics and Applications, EPE 2023 ECCE Europe ; Conference date: 04-09-2023 Through 08-09-2023",
year = "2023",
doi = "10.23919/EPE23ECCEEurope58414.2023.10264570",
language = "英语",
series = "2023 25th European Conference on Power Electronics and Applications, EPE 2023 ECCE Europe",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2023 25th European Conference on Power Electronics and Applications, EPE 2023 ECCE Europe",
}