This research aims to understanding the fundamental principles of brain-like bio-inspired computational intelligence (CI). We are particularly interested in: bio-inspired learning mechanisms, deep learning, reinforcement learning, adaptive/approximate dynamic programming, fuzzy logic, artificial neural networks, and data-driven modeling and control mechanisms. This research will advance the fundamental scientific foundations of general-purpose intelligence and develop innovative techniques to bring such a level of intelligence closer to reality across a wide variety of important applications, such as cyber-physical energy systems, smart grids, robotics, and sensor networks.
Smart Grid Control and Optimization:
With the continuous significant increase of energy demand and environment issues, the development of a smart electric power grid has become a critical research topic worldwide. Among many efforts toward this objective, computational intelligence (CI) research could provide key technical innovations to help the society to accomplish the essential energy objectives. We have been focused on a few aspects of the intelligent energy and power systems, including: (i) Development of adaptive and intelligent control and optimization methods for power grid based on adaptive dynamic programming (ADP), particle swarm optimization (PSO), deep learning (DL) and other CI techniques; (ii) Distributed energy systems, such as energy storage-based control, smart home energy management, DFIG-based wind farm control, HVDC transmission, and FACTS control; (iii) Agent-based sensing, learning, optimization, and prediction for power grid, such as isolated or networked microgrid; and (iv) power grid data analysis and signal processing, such as phase measurement unit (PMU)-based control and monitoring for resilient electrical power grid.
Smart Grid Cyber-Physical Security:
The security, reliability and resiliency of electric power grid have drawn significantly increasing attentions from academy, industry, and government after several large-scale blackouts (e.g., North American blackout in 2003, South American blackout in 2009, and the India blackout in 2012) and cyber penetrations of the power grid (e.g., Ukraine power grid cyber attack in 2015). The objectives of this research are to advance methods of vulnerability analysis and to develop innovative responses to maintain the integrity of power grids under complex attacks, from both cyber and physical perspectives. Examples of research including multi-contingency screening and analysis, cascading outage modeling, false data injection attack detection, and proactive defense design.