Research Interests
Resilience of cyber-physical systems
Electricity distribution network management
Distributed Energy Resources (DERs) management and grid integration
Predictive modeling and energy systems optimization
Power grid situational awareness
Central and local energy markets
Recent Activities (details coming soon)
(1) Advanced DMS, DERMS, Aggregators and DERs
(2) Holistic cyber-security solutions for distribution grid
(3) Tariff design for distribution systems
(4) Synthetic time series generation of DER power and electric load profiles
(5) Application of machine learning in voltage management of distribution grid
(6) Real-time flexibility assessment of Behind-the-meter DERs and its implementation in HELICS platform
(7) Resilience of interdependent gas-electric system
Projects
DOE-CEDS project, "Next-generation attack resilient electricity distribution systems", 2019-present
DOE-CEDS project, "Secure Evolvable Energy Delivery Systems (SEEDS)", 2016-2018
NSF project, "Cyber-innovation for Sustainability Science and Engineering (CyberSEES)", 2014-2016
NSF project, "Computing and Communication Foundations", 2013-2014
Research Tools
Linear and non-linear optimization, machine learning including deep learning, statistical estimation and detection theory, stochastic optimal control and dynamic programming, reinforcement learning, time series models, probability and statistics
Computer Skills
Programming: Python (including Numpy, Scipy, Pandas, Scikit-learn, Tensorflow, Pytorch, RestAPI), MATLAB, SQL, Github, Amazon Web Services
Optimization: Pyomo, Gurobi, CPLEX, CVXpy
Power system simulation: MATPOWER, OpenDSS
Others: Jupyter Notebook, Microsoft Office, Latex
Certificates (MOOC): Machine Learning (deeplearning.ai, 2017), Deep Learning Specialization (deeplearning.ai, 2018), Generative Adversarial Networks (deeplearning.ai, 2020), Machine Learning Implementation (deeplearning.ai, 2020), MLops (deeplearning.ai, 2021)