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贺兴 Xing HE
贺兴 Xing HE
Dirección de correo verificada de sjtu.edu.cn
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Año
A big data architecture design for smart grids based on random matrix theory
X He, Q Ai, RC Qiu, W Huang, L Piao, H Liu
IEEE transactions on smart Grid 8 (2), 674-686, 2017
3582017
An accurate and real-time method of self-blast glass insulator location based on faster R-CNN and U-net with aerial images
Z Ling, D Zhang, RC Qiu, Z Jin, Y Zhang, X He, H Liu
CSEE Journal of Power and Energy Systems 5 (4), 474-482, 2019
124*2019
A correlation analysis method for power systems based on random matrix theory
X Xu, X He, Q Ai, RC Qiu
IEEE Transactions on Smart Grid 8 (4), 1811-1820, 2017
1172017
数字孪生在电力系统应用中的机遇和挑战
贺兴, 艾芊, 朱天怡, 邱才明, 张东霞
电网技术 44 (6), 2009-2019, 2020
78*2020
The impact of large-scale distributed generation on power grid and microgrids
Q Ai, X Wang, X He
Renewable Energy 62, 417-423, 2014
672014
基于机会约束规划的虚拟电厂调度风险分析
范松丽, 艾芊, 贺兴
中国电机工程学报 35 (16), 4025-4034, 2015
66*2015
A novel data-driven situation awareness approach for future grids—Using large random matrices for big data modeling
X He, L Chu, RC Qiu, Q Ai, Z Ling
IEEE Access 6, 13855-13865, 2018
642018
Designing for situation awareness of future power grids: An indicator system based on linear eigenvalue statistics of large random matrices
X He, RC Qiu, Q Ai, L Chu, X Xu, Z Ling
IEEE Access 4, 3557-3568, 2016
642016
Invisible units detection and estimation based on random matrix theory
X He, L Chu, RC Qiu, Q Ai, Z Ling, J Zhang
IEEE Transactions on Power Systems 35 (3), 1846-1855, 2020
60*2020
Spatio-temporal correlation analysis of online monitoring data for anomaly detection and location in distribution networks
X Shi, R Qiu, Z Ling, F Yang, H Yang, X He
IEEE Transactions on Smart Grid 11 (2), 995-1006, 2020
572020
Research on dynamic load modelling based on power quality monitoring system
RF Yuan, Q Ai, X He
IET Generation, Transmission & Distribution 7 (1), 46-51, 2013
452013
Massive streaming PMU data modelling and analytics in smart grid state evaluation based on multiple high-dimensional covariance test
L Chu, R Qiu, X He, Z Ling, Y Liu
IEEE Transactions on Big Data 4 (1), 55-64, 2017
432017
基于深度学习的输电线路故障类型辨识
徐舒玮, 邱才明, 张东霞, 贺兴, 储磊, 杨浩森
中国电机工程学报 39 (1), 65-74, 2019
38*2019
基于数字孪生驱动的智慧微电网多智能体协调优化控制策略
高扬, 贺兴, 艾芊
电网技术 45 (7), 2483-2491, 2021
32*2021
Preliminary exploration on digital twin for power systems: Challenges, framework, and applications
X He, Q Ai, RC Qiu, D Zhang
arXiv preprint arXiv:1909.06977, 2019
322019
基于数据驱动的用电行为分析方法及应用综述
朱天怡, 艾芊, 贺兴, 李昭昱, 孙东磊, 李雪亮
电网技术 44 (9), 3497-3507, 2020
28*2020
A new approach of exploiting self-adjoint matrix polynomials of large random matrices for anomaly detection and fault location
Z Ling, RC Qiu, X He, L Chu
IEEE Transactions on Big Data 7 (3), 548-558, 2019
282019
提高电网输电能力技术概述与展望
艾芊, 杨曦, 贺兴
中国电机工程学报 33 (28), 34-40, 2013
26*2013
Unsupervised feature learning for online voltage stability evaluation and monitoring based on variational autoencoder
H Yang, RC Qiu, X Shi, X He
Electric Power Systems Research 182, 106253, 2020
252020
Early anomaly detection and localisation in distribution network: A data‐driven approach
X Shi, R Qiu, X He, Z Ling, H Yang, L Chu
IET Generation, Transmission & Distribution 14 (18), 3814-3825, 2020
24*2020
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