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Zhaocai Liu is a data science researcher and transportation system scientist with the Computational Science Center at NREL. He has strong technical background and experience in transportation network modeling, transportation infrastructure planning, and planning and operation of electrified and automated transportation systems. At NREL, Zhaocai Liu has been leveraging NREL’s high-performance computing (HPC) system to enable large-scale data analysis, simulation, and optimization for electrified transportation systems. He has contributed to many projects funded by federal or local government agencies and industry organizations. Liu actively collaborates with NREL colleagues, university collaborators, and industrial partners on brainstorming new research ideas and developing research proposals. 

He has published 24 peer-reviewed journal papers (with 1000+ citations) in top journals, including Applied Energy, Transportation Research Part B/C/D/E, Energy, Sustainable Cities and Society, among others. He has served as an Associate Editor for IEEE IAS Transportation Systems Committee since January 2023.

Zhaocai Liu got his bachelor’s and master’s degree in transportation engineering from Southeast University in China, and obtained his Ph.D. in Civil and Environmental Engineering from Utah State University in 2019. He was awarded one of the College of Engineering Outstanding Ph.D. Scholars at Utah State University in 2019, and won the Ellis L. Mathes Scholarship from ITE Intermountain Section.

Transportation network modeling 
 
Sustainable transportation systems with electric and autonomous vehicles 
 
Stochastic programming and robust optimization 
 
Simulation-based optimization for transportation system planning and operation 
 
Scalable algorithms for planning and operation of large transportation systems 
 
Joint optimization of the planning and operation of coupled transportation and power systems

Professional Research at NREL

Leading the EV charging demand analysis task for the DOE Office of Electricity funded project: Valuing V2X for Customer and Grid Resilience

Leading the EV charging demand analysis task for the Xcel Energy-funded project: Colorado Residential Resiliency and Managed Charging

Analyzing LDV and M/HD electric vehicle charging demand in the future for the DOE-funded Project: EVs@Scale FUSE (Flexible charging to Unify the grid and transportation Sectors for EVs at scale)

Energy consumption estimation/prediction of electric buses and optimization model implementation and solution algorithm design to support electric transit bus system planning and operation

Training energy consumption prediction models for heavy duty trucks and analyzing the energy saving potential for heavy duty trucks to take more energy efficient routes instead of the shortest time paths

Developing a scalable and efficient data processing pipeline to extract key vehicle driving features from a huge connected-vehicle trajectory data

Ground transportation infrastructure planning and shuttle bus system analysis for the Dallas/Fort Worth International Airport for the DOE-funded project: ATHENA (Advanced Transportation Hub Efficiency using Novel Analysis)