Research
I study how low-carbon transitions move from end-use demand and technology pathways, through spatial infrastructure and supply chains, to hourly power-system operation and resilience.
Research programme
The programme follows decisions from changing end uses to the infrastructure that serves them, then tests how those choices perform within an hourly power system.
01
Demand, mobility, and technology pathways
I examine how evolving mobility demand, shared autonomous mobility, vehicle technologies, and fleet turnover reshape energy use, emissions, material requirements, and retired-battery availability.
02
Production, conversion, transport, and spatial coordination
I model where hydrogen and hydrogen-derived fuels could be produced, converted, and moved to demand centers such as ports and airports, while keeping resource, cost, and network constraints explicit.
03
Hourly operations, flexibility, and climate stress
I evaluate how EV charging, smart charging, vehicle-to-grid operation, electrolysis, and extreme-weather conditions interact with generation, storage, transmission, and system adequacy.
In progress
Ongoing questions are described without reporting results that have not yet entered the public research record.
Working paper
How do historically grounded extreme-weather events alter operational stress in a future power system, and when can smart charging or vehicle-to-grid operation provide credible resilience value?
Methods: Climate-stress event construction · fixed-capacity system replay · PyPSA-China
Research in progress
Where should hydrogen, ammonia, methanol, and sustainable-aviation-fuel equivalents be produced, and how should strategic transport infrastructure evolve as demand changes across China?
Methods: GIS · multi-period mixed-integer optimization · techno-economic analysis
Model development
How should photovoltaic generation and battery storage be sized across heterogeneous public charging stations, and how do economic and lifecycle-emissions objectives change the preferred deployment strategy?
Methods: Station-level data · capacity sizing · lifecycle and techno-economic assessment
Method development
How can national and provincial transition scenarios be translated into spatially and temporally explicit power-system inputs without losing traceability across model boundaries?
Methods: China TIMES · PyPSA-China · Python-based scenario interfaces and quality assurance
Models and methods
Specific platforms are listed as research tools, not as stand-alone claims of expertise.
China TIMES 2.0 and China TIMES-30PE
National and provincial pathways, technology change, and cross-sector interactions.
PyPSA-China
Hourly system operation, investment, flexibility, and regional coordination.
GIS and network optimization
Node-level demand and supply, transport links, candidate corridors, and regional heterogeneity.
Linear and mixed-integer optimization
Technology choice, capacity planning, logistics, and operational constraints.
Python, GAMS, and reproducible scenario workflows
Data preparation, model orchestration, quality assurance, analysis, and visualization.
I use models as structured ways to connect evidence across scales—from national transition pathways and provincial infrastructure to charging operations and technology choices. The emphasis is on explicit boundaries, traceable data, reproducible scenario comparisons, and conclusions that remain meaningful under uncertainty.