T. Hossain, L. Toba
Idaho National Laboratory,
United States
Keywords: synthetic graphite, supply chain, optimization, site suitability
Summary:
The graphite demand in the USA is increasing significantly due to the growing demand for lithium-ion batteries used in electric vehicles (EVs) and energy storage systems. Currently, ~81 % of the total graphite demand comes from synthetic sources produced using petroleum and the remaining accounts for natural graphite imports. About 65% of the synthetic graphite is produced domestically while the rest comes from international imports. With a compound annual growth rate (CAGR) of 4.7% for U.S. synthetic graphite demand, a total of 179,000 metric tons (mton) of synthetic graphite will be required within the next 10 years. Production of graphite is also a highly GHG emitting process based on petroleum sources with emissions ranging from 4.9 to 20.6 tons of CO2 per ton of synthetic graphite. To reduce the import reliance for meeting the growing demand and to improve the environmental footprint of graphite production, it is essential to incorporate secondary sources into the graphite production system in the US. Our analysis is focused on supply chain assessment of producing synthetic graphite from woody biomass and polyethylene (PE) waste as feedstock materials. One of the major objectives of the supply chain assessment is to understand how the secondary sources can help increase graphite production, decreasing the dependency on imports as well as production from petroleum. We developed a two-step modeling approach using site suitability modeling and optimization modeling to identify the optimal site locations and capacity for battery grade synthetic graphite production sites. In the first step, we developed a site suitability model to determine the most suitable graphite production sitings, outputting candidate locations. These locations are then, in the second step, inputted in the optimization model for optimal site selection. The suitability model determines the most suitable sites based on six criteria, 1) Woody biomass availability, 2) PE waste availability, 3) Population density, 4) Road network, 5) Labor wages, and 6) Existing location for the synthetic graphite and battery anode manufacturers site. The optimization model uses a mixed integer linear programming (MILP) approach to minimize the supply chain costs and GHG emission of the system. System level GHG emissions (CO2) include emission from processing woody biomass and PE waste, transportation of raw materials from collection site to production site and graphitization GHG. The system level costs include material cost, energy cost, capital cost, labor cost, operational cost, and transportation cost. The analysis was conducted on a county level. For analysis, we assumed a scenario with 40% of the synthetic graphite coming from current petroleum sources and the remaining being derived from biomass and waste materials. Results from scenarios show improvement in costs and CO2 emissions, compared to current production with petroleum coke as feedstock.