Abstract: As one of the core equipment of power system, power transformer has great fault influence and complex fault causes. In order to ensure the safe and stable operation of power system, its operation state must be monitored and judged. With the increasing maturity of the Internet industry and the continuous development of sensor technology, the emergence of smart grid has contributed to the realization of intelligent transformer on-line monitoring, condition evaluation and fault diagnosis. This paper studies the deep primary and secondary fusion transformer based on the Internet of Things technology, summarizes the development status of intelligent transformer and its existing problems on the basis of relevant literature, and proposes the optimization technology of deep primary and secondary fusion transformer based on the Internet of Things technology to solve its existing problems, and conducts related experiments and fault detection research on the proposed technology. The experimental results show that this optimization technology has good feasibility, good self-state evaluation and fault diagnosis functions. The deep primary and secondary fusion based on the Internet of Things technology proposed in this study can increase the reliability monitoring of intelligent transformer operation, provide a strong technical guarantee for the normal operation of distribution network, and also provide important technical support for the next research of distribution network technology.

Xiaohua Zhang, Yuping Wu, Jianjun Chen, Jie Dong and Yu Yue, “Deep Primary and Secondary Fusion Transformer Based on Internet of Things Technology” International Journal of Advanced Computer Science and Applications(IJACSA), 13(12), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0131282

@article{Zhang2022,
title = {Deep Primary and Secondary Fusion Transformer Based on Internet of Things Technology},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0131282},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0131282},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {12},
author = {Xiaohua Zhang and Yuping Wu and Jianjun Chen and Jie Dong and Yu Yue}
}