Modelling the impact of future uncertainty in energy prices on aluminium decarbonization pathways
Secondary aluminium production facilities typically consume 700-1,000 kWh of natural gas and 200-400 kWh of electricity per tonne of rolled sheets. To achieve environmental targets, the aluminium industry is exploring decarbonization strategies, including biomass gasification, carbon abatement and utilization, powerto-gas, direct electrification, and waste heat recovery, among others. While most of these technologies have lifetimes of a couple of decades, decisions on their installation must be made today. Biomass, electricity, and natural gas costs can be subject to unpredictable market variations, whereas carbon prices are related to environmental regulations and future market situations. Therefore, current decarbonization decisions must account for uncertainty in future energy prices. This study presents a systemic approach to incorporate energy price fluctuations into decarbonization planning for secondary aluminium production. A mixed integer linear programming (MILP) approach is used to generate a list of feasible system configurations under 4,000 combinations of energy prices and carbon taxes. Next, Monte Carlo simulations are applied to predict energy price trends and assess the resilience of favourable scenarios, from the MILP approach, under ''stochastic'' or ''crisis'' circumstances. Results show that decarbonization pathways are less costly than fossil CO2-emitting configurations in 50% of the price combinations. Among these decarbonization configurations, the pathway combining electricity and biomass is the most economical. However, its likelihood of outperforming the natural gas-driven baseline over a 25-year lifetime is estimated at 22%-37% under stochastic energy price profiles. Finally, resource diversification, such as biomass utilization, reduces risk during economic crises by 6% compared to complete electrification.
1-s2.0-S0196890425011033-main.pdf
Main Document
Published version
openaccess
CC BY
4.05 MB
Adobe PDF
61554f42ad0e49c9b7aa5131d5138a32