Area of research
Electrical and Electronic Engineering · Control and Systems Engineering
Research interest
Research interests include Computer science, Artificial intelligence, Electric power system, Deep learning, Mathematical optimization, and Renewable energy.
Artificial intelligence-based methods for renewable power system operation
PMU Measurements-Based Short-Term Voltage Stability Assessment of Power Systems via Deep Transfer Learning
Control-Oriented Extraction and Prediction of Key Performance Features Affecting Performance Variability of Solid Oxide Fuel Cell System
Dense Skip Attention Based Deep Learning for Day-Ahead Electricity Price Forecasting
Cooperative game consistency optimal strategy of multi-microgrid system considering flexible load
Robust and Resilient Distributed Optimal Frequency Control for Microgrids Against Cyber Attacks
Deep Learning Based Densely Connected Network for Load Forecasting
Coordinated Scheduling for Improving Uncertain Wind Power Adsorption in Electric Vehicles—Wind Integrated Power Systems by Multiobjective Optimization Approach
Adjustable Uncertainty Set Constrained Unit Commitment With Operation Risk Reduced Through Demand Response
An Interactive Decision-Making Model Based on Energy and Reserve for Electric Vehicles and Power Grid Using Generalized Stackelberg Game