P-graph and Monte Carlo simulation approach to planning carbon management networks

- A hybrid P-graph and Monte Carlo approach is proposed for planning carbon management networks.
- P-graph methodology is applied for synthesis of optimal and near-optimal networks.
- Monte Carlo simulation is applied to gauge robustness of alternative networks.
- Two case studies are used to illustrate the approach.

A P-graph and Monte Carlo simulation approach to planning carbon management networks is proposed. These networks are generalized systems for minimizing emissions of CO2. Application of the P-graph framework to such problems has the added advantage of being able to rigorously identify both optimal and near-optimal solutions, which is a feature that is useful for practical decision-making; Monte Carlo simulation can then be used to evaluate the robustness of a network to variations in system parameters. Two literature case studies are used to demonstrate this methodology. The first example is a carbon-constrained energy sector planning problem, while the second example is a CO2 capture and storage planning problem. In both cases, it is demonstrated that multiple solutions generated using P-graph methodology allow identification of robust, near-optimal carbon management networks.