Dr. Guo will present two of his work on renewable generator planning and EV charging incentive design considering transportationa and power interdependency at INFORMs 2019 in Seattle.
Dr. Zhaomiao (Walter) Guo leads INfrastructure Systems with Proactive, Intelligence, and Resilience Enhancement (INSPIRE) Lab* at the University of Central Florida. Dr.Guo is currently an Assistant Professor in the Department of Civil, Environmental, and Construction Engineering and hold a joint appointemnt with the Resilient, Intelligent and Sustainable Energy Systems(RISES) Cluster. Dr. Guo’s research centers around modeling and computational strategies for intelligent and resilient critical infrastructure systems, with applications in transportation and energy systems. His research was/is supported by government agencies, auto manufacturers and leading power suppliers.
*Multiple fully funded Ph.D. positions in INSPIRE lab for Spring/Fall 2020. The research areas broadly relate to network modeling and optimization, with applications in smart city, cyber-physical systems, and transportation & power system interactions. The candidates are expected to have a strong background in operations research, data science and/or computer science. Experiences in transportation and/or power system are preferred. If interested, please send your resume to Dr. Guo at guo@ucf.edu.
PhD in Transportation Engineering, 2016
University of California Davis
MSc in Agricultural and Resource Economics, 2015
University of California Davis
MSc in Transportation Engineering, 2011
University of California Berkeley
BSc in Civil Engineering, 2010
Tsinghua University
Asterisks indicate an author is/was a graduate (*) or undergraduate (**) researcher in INSPIRE Lab.
Due to an increasing connectivity, interdependence, and complexity of infrastructure systems, an analytical model may not be feasible to reflect the interactions within/between systems. As an alternative, agent-base modeling is found to be effective to capture complicated agent interactions and visualize system dynamics, especially with increasing data availability. This project develops an agent-base modeling platform to capture the interactions between key decision makers in transportation and power systems, including drivers, households and infrastructure investors, and simulate their decision making over both short-term and long-term horizon. This platform has broad applications in the study of EV charging, ride-sharing and power-transportation interdependency.
Cascading failures have become one of the biggest challenges for increasingly connected infrastructure systems, such as power network. This project investigates effective and robust planning and operation strategies for power system considering the possibility of cascading failures.
Charging infrastructure is a critical element for the success of transportation electrification. But charging infrastructure is not developed by a single central planner. This project investigates the potential evolvement of PEV charging infrastructure in a competitive market.
Data has arguably become one of the most powerful tools to understand system in a timely fashion. In transportation, multiple data sources (e.g. social media, transaction, economics, sensors, etc.) have become readily available. This project collects and analyzes large-scale transportation data, including vehicle market value, on-demand transportaiton service, travel survey, and charging data.
Power and transportation networks have various similarity and interdependency. This project looks at different linkages between these two critical infrastructure systems, including methodological and functional aspects
Visiting Scholar
Graduate Researcher
Undergraduate Researcher
Undergraduate Researcher
Dr. Guo will present two of his work on renewable generator planning and EV charging incentive design considering transportationa and power interdependency at INFORMs 2019 in Seattle.
New publication in value of autonomous electric vehicles on power distribution network operation considering dynamic distribution network reconfiguration, travel behaviors, and existence of renewable energy. Access Link
Dr. Guo will have two presentations at IISE Annual Conference 2019 in Orlando, FL. He will present his work on Competitive Intermediate Facility Location Problems under Traffic Equilibrium on May. 19, 2019, and his work on Interdependence between Transportation and Power Systems, beyond Electric Vehicles on May. 20, 2019.
Dr. Guo will present his work on a stochastic general equilibrium approach on market-based facility infrastructure development on Mar. 22, 2019 at USF.