(128e) Multi-Level Life Cycle Analysis Tool for Sustainable Energy Systems Modeling
- Conference: AIChE Annual Meeting
- Year: 2019
- Proceeding: 2019 AIChE Annual Meeting
- Group: Sustainable Engineering Forum
- Time: Monday, November 11, 2019 - 2:10pm-2:35pm
The tool is built as a MATLAB app that encapsulates MATLAB models, databases, and integrated process simulations. A modular framework constitutes the underlying analytical engine that covers all the life stages of major energy conversion pathways. The current version of the tool contains more than 900 individual pathways, which are responsible for ~80% of US greenhouse gas (GHG) emissions. For the greenhouse gas emission hot spots, such as power plants and some chemical conversion pathways, detailed process simulation capabilities have been incorporated for in-depth analysis. In addition to performing pathway-level life cycle analysis (LCA), a central aspect of this analytical framework is the ability to assess key systems interactions and couplings. The system-level analysis is enabled by the embedded power systems and vehicle fleet models that captures market dynamics and explore dynamics of technology adoption and usage. By executing the analysis using a modular framework we can establish a basis for the accurate assessment of the life cycle implications arising from complex system-level restructuring.
The presentation will focus on the overview of the tool, the modeling approach as well as the results of case studies investigating electric power system. We will demonstrate how the changes in the operational variability of natural-gas fired power plants impacts the system-wide emissions. Specifically, the operation of NG power plants in the evolving power system significantly reduces plant performance and increases the emissions footprint of NG power generation. The results of extensive analysis of power plant dispatch profiles and detailed life cycle analysis of the US power grid using high resolution plant level simulation models and incorporation of publicly available US-wide generation and emissions data will be presented.