UBC Theses and Dissertations
Value chain optimization of a forest biomass power plant considering uncertainties Shabani, Nazanin
Mathematical modeling has been employed to improve the cost competitiveness of forest bioenergy supply chains. Most of the studies done in this area are at the strategic level, focus on one part of the supply chain and ignore uncertainties. The objective of this thesis is to optimize the value generated in a forest biomass power plant at the tactical level considering uncertainties. To achieve this, first the supply chain configuration of a power plant is presented and a nonlinear model is developed and solved to maximize its overall value. The model considers procurement, storage, production and ash management in an integrated framework and is applied to a real case study in Canada. The optimum solution forecasts $1.74M lower procurement cost compared to the actual cost of the power plant. Sensitivity analysis and Monte Carlo simulation are performed to identify important uncertain parameters and evaluate their impacts on the solution. The model is reformulated into a linear programming model to facilitate incorporating uncertainty in the decision making process. To include uncertainty in the biomass availability, biomass quality and both of them simultaneously, a two-stage stochastic programming model, a robust optimization model and a hybrid stochastic programming-robust optimization model are developed, respectively. The results show that including uncertainty in the optimization model provides a solution which is feasible for all realization of uncertain parameters within the defined scenario sets or uncertainty ranges, with a lower profit compared to the deterministic model. Including uncertainty in biomass availability using the stochastic model decreases the profit by $0.2M. In the robust optimization model, there is a trade-off between the profit and the selected range of biomass quality. Profit decreases by up to $3.67M when there are ±13% variation in moisture content and ±5% change in higher heating value. The hybrid model takes advantage of both modeling approaches and balances the profit and model tractability. With the cost of only $30,000, an implementable solution is provided by the hybrid model with unique first stage decision variables. These models could help managers of a biomass power plant to achieve higher profit by better managing their supply chains.
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Attribution-NonCommercial-NoDerivs 2.5 Canada