A5101456102- Smart Grid Security and Resilience
- Smart Grid and Power Systems
- Rock Mechanics and Modeling
- Cellular Mechanics and Interactions
- Discourse Analysis in Language Studies
- Smart Grid Energy Management
- Coal Properties and Utilization
- Microstructure and Mechanical Properties of Steels
- Fatigue and fracture mechanics
- Network Security and Intrusion Detection
- Particle accelerators and beam dynamics
- Advanced Surface Polishing Techniques
- Advanced Algorithms and Applications
- Drilling and Well Engineering
- EFL/ESL Teaching and Learning
- Advanced Measurement and Metrology Techniques
- Energy Load and Power Forecasting
- Welding Techniques and Residual Stresses
- Image Processing and 3D Reconstruction
- Advanced machining processes and optimization
- Advanced Neural Network Applications
- Landslides and related hazards
- Pluripotent Stem Cells Research
- 3D Printing in Biomedical Research
- Geotechnical and Geomechanical Engineering
State Key Laboratory of Industrial Control Technology
2023-2024
Shaoxing University
2024
Northeast Electric Power University
2012
Institute of Zoology
2008
Kopin Corporation (United States)
2005
Beijing Polytechnic
2003
Beijing University of Technology
2003
Smart grid is confronted with cyberattacks due to the increasing dependence on cyberspace. False data injection attacks (FDIAs) represent a major type of that cannot be detected by traditional bad detection (BDD). The majority existing researches focus how detect FDIAs, while little attention has been paid obtaining exact attack locations, which are crucial for deploying countermeasures in time. In this paper, we propose neural network-based approach online localizing FDIAs AC power systems....
In the electricity market, fluctuations in real-time prices are unstable, and changes short-term load determined by many factors. By studying timing of charging discharging, as well economic benefits energy storage process participating power this paper takes scheduling merely one factor affecting load, which affects time series along with time-of-use price, holidays, temperature. A deep learning network is used to predict a convolutional neural (CNN) extract features, long memory (LSTM)...