Multi-period automated targeting and optimisation for net zero

Net-zero targets are not likely to be achievable without the use of negative emission technologies (NETs). Various energy planning tools rarely consider NETs for net-zero emissions planning. Marginal abatement cost (MAC) curves, which plot different emissions reduction options based on specific cost and cumulative emissions reduction, are popular tools for communication and decision support. However, this graphical approach is tedious and hard to use for the calculation of the total system cost. Hence, the automated marginal abatement cost (AMAC) method was recently developed to overcome the limitation of the graphical method. The AMAC was based on the MAC curve but implemented on an optimization platform, which allows it to set rigorous performance targets. In this work, the AMAC is extended for multi-period net-zero emissions planning. The methodology is illustrated with a case study of multiple fossil fuel power plants and two NETs (biochar and bioenergy with carbon capture and storage) with a three-decade planning horizon. In the baseline scenario, it is not possible to achieve net zero due to a deficit of 4.38 Mt CO₂/y of negative emissions. The rest of the scenarios achieved net-zero emissions during their target period. Targeting net-zero emissions in every period is at a higher risk of obtaining extreme values of the total system cost ($ 13,824–32,046 M) compared to targeting net-zero emissions only in the last period ($ 10,312–27,116 M). Multi-period decision support models are critical because of the dynamic nature of inputs needed to achieve net-zero emissions.