(511a) Optimal Risk-Transfer Strategies for Chemical Plant Decarbonization Using a MILP Framework

Previous research on investment timing for decarbonization strategies in chemical plants has shown that uncertainties in emerging green energy markets—ranging from grid decarbonization to the deployment of hydrogen pipelines and electrolyser technologies—profoundly affect investment decisions and timing. In today’s era of energy and financial crises, risk aversion compels many plants to continue operating legacy, high-emission systems, resulting in increased lifetime CO₂ emissions. Even though a fully optimized decarbonization strategy might theoretically yield lower overall costs, its uncertain nature prevents operators from choosing it in practice.

To overcome this, we introduce a Mixed Integer Linear Programming (MILP) framework that models a decarbonized energy system for a chemical plant and optimizes a portfolio of risk-transfer contracts—including instruments such as contracts for differences, long-term firm agreements, interruptible contracts, and agreements to buy or sell carbon credits—to mitigate both financial and operational uncertainties. Our model incorporates scenario analysis that examines the effects of diverse carbon policies—such as emissions trading schemes (ETS), carbon border adjustment mechanisms (CBAM), —as well as market dynamics, including fluctuations in the costs of carbon credits and green fuels such as green electricity, hydrogen, and biomass. The model captures feedback effects where widespread decarbonization alters market equilibria and shifts price-making versus price-taking dynamics.

Results demonstrate that risk-transfer measures increase the overall cost structure; however, this additional expense is a necessary trade-off that significantly reduces exposure to price shocks and encourages earlier decarbonization, reducing lifetime CO₂ emissions by over 30%, in what would otherwise be a delayed investment. This framework provides insights into the enablers of sustainable energy technologies and the reconfiguration of supply chains for feedstocks and end-products, supporting the systematic design, analysis, and optimization of future low-carbon energy systems and sustainable supply chains in the chemical sector.