Research

My research focuses on fostering an efficient, sustainable, and resilient clean energy transition to mitigate climate change through a combination of modeling, simulation, and quantitative analysis approaches. This work goes beyond considering the power system in isolation and explores the dynamics and feedbacks between multiple interconnected systems such as water resources. Another focus of my research is to develop adaptive control strategies for complex dynamic systems while incorporating multiple conflicting objectives from different stakeholders by employing the state-of-art data-driven optimal learning techniques.

Current Research Directions

1. Decarbonization with Multi-Sector Modeling under Long-term Climate Change Scenarios Modeling multi-sector dynamics and feedback to study the interactions between multi-sector systems under alternative realizations of long-term climate scenarios to (a) identify potential failure modes of the current climate-energy plans and (b) explore feasible solutions to foster decarbonize multi-sectors collectively
2. Resource Adequacy Analysis for CLCPA climate-energy policy Evaluated the operational feasibility of the NYS climate-energy policy with high spatial-temporal resolution modeling and pinpointed bottlenecks with renewable energy integration and transmission line expansion
3. Power System Modeling and Analysis Developed an open-source representation for the NYS grid with publicly available data and validated the model for power flow and optimal power flow analysis with official data
4. Weather Data Assisted Microgrids Energy Management Designed multi-objective reinforcement learning framework taking advantage of local weather data to find adaptive control strategies for microgrid energy management under multiple conflicting objectives; tested the framework on the Cornell campus microgrid with improvements for all objectives considered
5. Marginal Emission Rate Prediction Creating comprehensive models to represent the wholesale market clearing process and identifying the marginal resources analytically and numerically to assist the development of future carbon markets
6. Co-optimization of Transmission and Distribution Systems Implementing a bi-level optimization framework to collaboratively operate the transmission and distribution systems with real-world test cases and examining alternative market mechanisms to incentivize demand side response