Optimisation of bioenergy supply chains

This thesis aims to address the optimal strategic design of bioenergy supply chains and provide insight into the future implications of these systems. Among the bioenergy supply chains, biomass-to-biofuel (as the main focus), biomass-to-bioelectricity and biomass-to-hydrogen routes are studied within the context of this thesis. To solve these problems, mathematical programming, especially mixed integer linear programming (MILP), models and solution approaches are developed. Regarding the biofuel supply chains, deterministic, spatially-explicit, static optimisation models are developed first based on single economic objective considering first and hybrid generation systems. A “neighbourhood” flow approach is also proposed for the solution of these models. This approach provides significant computational savings when compared to similar models in literature. The single objective modelling framework is then extended to a multi-objective optimisation model which considers economic and environmental objectives simultaneously. The multi-objective model can provide insight into the trade-offs between the two conflicting objectives. Finally, the single objective static model is further developed into deterministic and stochastic multi-period modelling frameworks to incorporate temporal effects such as change of demand and biomass availability with time as well as uncertainty related to different aspects such as biomass availability. Regarding the bioelectricity supply chains, a deterministic, spatially-explicit, static, multi-objective mathematical programming model is developed based on mixed integer nonlinear optimisation. This considers electricity generation through biomass enhanced carbon capture and storage (BECCS) systems. The model aims to address issues such as carbon tax levels required to incentivise decarbonisation in the power sector as well as the potential impacts of biomass availability and commodity (carbon and coal) prices. The biomass-to-hydrogen route is considered as one of the possible conversion pathways within a deterministic, spatially-explicit, multi-period model developed for the optimal strategic design of future hydrogen supply chains. A two-step hierarchical solution approach is also proposed to increase computational efficiency during the solution of the large scale problem. The model results provide insight into the optimal evolution of a hydrogen supply chain through time.