[1] Chen W J, Zhao G L. Key technologies and equipment of new power system with new energy as the main body [J]. Global Energy Internet, 2022, 5(1): 1. (in Chinese)
[2] 贾玉强. 基于深度学习的序列和空间数据压缩技术研究[D]. 哈尔滨工业大学, 2021.

Jia Y Q. Research on sequence and spatial data compression technology based on deep learning[D]. Harbin: Harbin Institute of Technology, 2021. (in Chinese)
[3] Chen S W, Gao C Y, Hu C. Adaptive waveform data compression based on similarity segmentation and resampling [J]. Journal of Electronic Measurement and Instrumentation, 2019, 33(4): 178-185. (in Chinese)
[4] Wang Y Z, Sun L Q. Application of data compression technology in ship power monitoring system [J]. Journal of Shanghai Institute of Ship Transportation Science, 2020, 43(1): 55-60. (in Chinese) doi:  10.3969/j.issn.1674-5949.2020.01.010
[5] Unterweger A, Engel D. Resumable load data compression in smart grids [J]. IEEE Transactions on Smart Grid, 2015, 6(2): 919-929. doi:  10.1109/TSG.2014.2364686
[6] Chen Y, Wang Y L. Lossless data compression scheme of intelligent distribution network monitoring system [J]. Guangdong Electric Power, 2021, 34(5): 90-98. (in Chinese)
[7] Zhao H S, Feng J H, Ma L B. Data compression of distribution network infrared image monitoring based on tensor Tucker decomposition [J]. Power System Technology, 2021, 45(4): 1632-1639. (in Chinese)
[8] 叶佳翔. 基于压缩感知的电力系统图像采集与重建研究[D]. 湖北工业大学, 2020.

Ye J X. Research on image acquisition and reconstruction of power system based on compressed sensing[D]. Wuhan: Hubei University of Technology, 2020. (in Chinese)
[9] 赵洪山, 刘秉聪, 王龄婕, 等. 基于压缩感知的电力设备红外图像盲超分辨率方法[J/OL]. 电网技术: 1-12

Zhao H S, Liu B C, Wang L J, et al. Blind super resolution method for infrared images of power equipment based on compressed sensing[J/OL]. Power System Technology, (2022-01-12) [2022-01-24]. (in Chinese)
[10] Zhao H H, Jiang Y, Lin R, et al. Research on acceleration and compression of transmission line inspection image detection model [J]. Guangdong Electric Power, 2020, 33(9): 123-128. (in Chinese)
[11] 王正辉. 深度学习框架下电气设备图像压缩感知与重建研究[D]. 湖北工业大学, 2021.

Wang Z H. Research on compressed sensing and reconstruction of electrical equipment images under the framework of deep learning[D]. Wuhan: Hubei University of Technology, 2021. (in Chinese)
[12] Peng J S, Sun L X, Wang L, et al. ED-YOLO electric power inspection UAV obstacle avoidance target detection algorithm based on model compression [J]. Journal of Instrumentation, 2021, 42(10): 161-170. (in Chinese)
[13] Tang N Y, Cai L, Zhu T, et al. Construction of image recognition model for power equipment based on deep learning [J]. Automation and Instrumentation, 2020(12): 54-57. (in Chinese)
[14] 吴毓峰, 李富盛, 余涛, 等. 基于残差双重注意机制网络的电力数据压缩与高精度重建[J/OL]. 电网技术: 1-15[2022-01-24]

Wu Y F, Li F S, Yu T, et al. Power data compression and high-precision reconstruction based on residual dual attention mechanism network[J/OL]. Power System Technology, (2022-1-15)[2022-01-24]. (in Chinese)
[15] Zhang S Q, Yang F B, Wang X X. Ghost imaging optimization method based on autoencoding neural network [J]. Electronic Measurement Technology, 2021, 44(21): 77-83. (in Chinese)