A generalized MILP framework for plant-level decarbonization

Energy-intensive plants must navigate technology, fuel-price, and policy uncertainty when selecting least-cost decarbonization pathways. We develop a two-stage mixed-integer linear programming (MILP) framework for industrial decarbonization planning that co-optimizes multi-technology capacity expansion and commissioning schedules with hourly site-energy dispatch, while explicitly modeling emissions-allowance procurement and intertemporal banking under an emissions trading system (ETS). The formulation combines multi-decadal investment decisions to hourly operations; includes an allowance-accounting module for ETS-consistent compliance cost calculation with banking; represents correlated trajectories for grid-carbon intensity, fuel and electricity prices, and ETS design; and incorporates time-varying technology costs for electrification, hydrogen, carbon capture and storage (CCS), and bio-energy. We demonstrate the framework on a UK epoxy-resin facility (2025–2055) under five market–policy scenarios to illustrate how scenario-driven stress-testing alters technology choice and timing. Results show that electrification is least-cost/lowest-emissions only if grid intensity falls below 50 g CO kWh−1 by 2035; a slower trajectory increases cumulative emissions by up to 745 kt CO2. A carbon-price corridor alone is insufficient to close the green-fuel cost premium, motivating long-dated hedging instruments (e.g., power purchase agreements and forward/swap positions) to reduce exposure to price volatility. Allowing credit banking enables additional cost-effective abatement (up to 110 kt CO2) by valuing early over-compliance, whereas prohibiting banking increases compliance cost and weakens the cost–emissions trade-off. Overall, the framework provides a practical, scenario-driven tool for regulators and operators to evaluate robust industrial decarbonization pathways.