Dynamic State Estimation of New Energy Power Systems Considering Multi-Level False Data Identification Based on LSTM-CNN

Dynamic State Estimation of New Energy Power Systems Considering Multi-Level False Data Identification Based on LSTM-CNN

With the increase of new energy integration, it is difficult to identify the measured data and false data in power system when they are mixed into cyber network. If false data with error information is utilized in the power system state estimation, the accuracy of state estimation will be reduced. T...

Full description

Bibliographic Details
Main Authors: Zhengnan Gao, Shubo Hu, Hui Sun, Jinsong Liu, Yuanqing Zhi, Jun Li
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
New energy power system
false data identification
dynamic state estimation
long-short term memory neural network (LSTM)
convolution neural network (CNN)
Online Access:https://ieeexplore.ieee.org/document/9580888/

Internet

https://ieeexplore.ieee.org/document/9580888/

Similar Items