ERI: Towards Dynamic Life Cycle Assessment of Renewable Energy Hub Systems

Life cycle assessment (LCA) is a methodology that evaluates the environmental impact of a product or system over its lifetime. The existing methodology is not well-suited for systems whose characteristics vary in time, which are called dynamic systems. This project will combine LCA with models of dynamic systems to improve predictions of environmental impact. The project will use renewable energy hubs, a timely and economically important application, as a prototype to demonstrate new computational methods for analyzing environmental impacts of complex dynamic systems. The project will build a data exchange interface connecting LCA with other modeling environments. It will provide an environmental tool to determine the quantity and quality of energy used by these systems over time. It will also provide a teaching method to promote critical thinking about complex systems connected with the environment. Results from the project will help evaluate and minimize the environmental impact of energy technologies that affect the lives of millions of people every day.

To advance dynamic life cycle assessment and close a modeling gap in multi-energy systems, this project will integrate life cycle analysis and system dynamic modeling in a bidirectional co-simulation framework. This will enable an accurate, numerically efficient, and accessible evaluation of environmental impacts of renewable energy hub systems. The research team will first develop a flexible data exchange platform based on the Functional Mockup Interface and interconnect Brightway and Modelica environments. For the demonstration, the team will investigate the accuracy and numerical performance of energy- and exergy-based functional units for life cycle assessment of renewable energy hubs. An interactive web module will be developed and deployed for understanding complex energy systems and the environment. The module will be evaluated for student cognitive and affective learning outcomes. The project will advance computational methods for studying environmental impacts of complex dynamical systems with tangible results in energy applications. Additionally, this project will provide publicly available open-source software and educational modules for undergraduate students. The module will be integrated into a core undergraduate course in Civil and Environmental Engineering at the University of Vermont.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Award Number: 2501735
Principal Investigator: Kathryn Hinkelman
Funds Obligated: $200,000
State: VT