Areas of Research
- Artificial Intelligence
- Power Electronics Systems
- Power Systems
- Renewable Energy Systems
- Smart Grid
His current research interests include renewable energy systems, power electronics, power systems, electric machines and drives, and applications of artificial intelligence and machine learning in power and energy systems.
From 1995 to 1999, Dr. Li involved into the research areas of renewable energies, neural networks, and applications of massively parallel processing.
Research Specialties
- Renewable Energy Systems
- Power Electronics, Electric Machines and Drives, Power Systems
- Artificial Intelligence and Neural Networks
- Modeling, Analysis, and Control of Dynamic Systems
- Smart Homes and Buildings
- Massively Parallel Processing Applications
- Software Engineering
- Measurements and Instrumentation
Research Areas
- Intelligent grids and systems
- Renewable Energy Systems
- Power Electronics
- Electric Machines and Drives
- Parallel Computing Applications
- Information Technology in Higher Education
Research Areas
- Intelligent grids and systems
- Intelligent control in power engineering applications
- Artificial neural networks for prediction and forecast of renewable energy generation.
- Neural network architecture, training algorithms, and comparisons of neural networks with traditional AI models.
- Renewable Energy and Distributed Generation
- Explore interoperability characteristics of typical renewable energy sources and energy storage systems
- Develop and model renewable energy sources and systems by adopting advanced computational strategies over the state-of-the-art cyberinfrastructure
- Design and analyze renewable energy conversion systems
- Investigate economics for grid integration of the different renewable sources by considering smart grid and smart metering technologies.
- Power Electronics and Power Quality
- Power electronic applications, such as renewable energy, distributed generation, and energy storage systems
- Power electronic circuits and systems
- Harmonic sources
- AC traction system harmonic process simulation
- Harmonic load flow and penetration in electric power systems
- Dynamic harmonic filtering and compensation.
- Electric machines and Drives in traction
- Artificial neural network vector control for high performance ac drives in traction systems
- Coordinated control and energy management systems in electric vehicles and electric trains
- Dynamic process simulation and analysis of electric vehicles and electric trains
- Dynamic process simulation of AC traction power systems in electrified railways
- Parallel Computing Applications and Implementations
- Converting sequential computer programs to parallel programs
- Development of parallel algorithms suitable for parallel computing on clusters and supercomputers
- Massively parallel processing applied for neural network training
- FPGA based parallel hardware implementations
- Information Technology for Higher Education
