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Supply chain optimization of forest-based biomass for gasification considering uncertainties Ahmadvand, Sahar
Abstract
Producing energy from forest-based biomass could aid the transitions in energy and forest sectors to replace fossil fuels; reduce emissions and wastes; and diversify product portfolios and revenue streams. Optimizing the economic and environmental performance of biomass supply chains can help realize these benefits. Besides optimizing the supply chain, investigating other factors, e.g., government incentives and carbon and energy pricing, which contribute to success or failure of forest-based biomass projects, is beneficial. The supply chain of forest-based biomass includes different activities that are cost- and emission-intensive and involve uncertainties. Unlike the majority of studies on forest-based biomass supply chain planning that focused on long-term and deterministic optimization, this dissertation aims to optimize the supply chain of syngas production at tactical level considering uncertainties. Thus, a multi-period bi-objective robust optimization model is developed and applied to the case of a British Columbia Kraft pulp mill that would produce syngas to fuel their lime kiln. The objectives are to minimize costs and emissions while optimizing the monthly biomass procurement, storage, and preprocessing decisions. Robust optimization with an adjustable budget of uncertainty is used to model the uncertainties in biomass supply and cost. Robust Pareto-optimal solutions are obtained that demonstrate a trade-off between objectives. The cost and emissions of robust solutions are on average 68% and 41% higher than those of the deterministic solutions. However, unlike the robust solution, the deterministic solution becomes infeasible in 98% of simulated future scenarios. Besides logistics costs, other factors (e.g., capital investment, government funding, fuel prices, and carbon tax) determine the financial viability of biomass projects. A previous techno-economic feasibility study for the same case revealed that despite a short payback period and positive net present value, the syngas price and carbon tax would result in negative annual cashflows halfway through project’s lifespan. Thus, the pulp mill would be reluctant to invest in this project despite all its potential, especially emission savings. To improve the financial attractiveness of this project for the pulp mill, an optimization model is developed that shows an optimal syngas price of 27 $/GJ, increasing by 0.49¢ annually, would make all cashflows positive.
Item Metadata
Title |
Supply chain optimization of forest-based biomass for gasification considering uncertainties
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Creator | |
Supervisor | |
Publisher |
University of British Columbia
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Date Issued |
2023
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Description |
Producing energy from forest-based biomass could aid the transitions in energy and forest sectors to replace fossil fuels; reduce emissions and wastes; and diversify product portfolios and revenue streams. Optimizing the economic and environmental performance of biomass supply chains can help realize these benefits. Besides optimizing the supply chain, investigating other factors, e.g., government incentives and carbon and energy pricing, which contribute to success or failure of forest-based biomass projects, is beneficial.
The supply chain of forest-based biomass includes different activities that are cost- and emission-intensive and involve uncertainties. Unlike the majority of studies on forest-based biomass supply chain planning that focused on long-term and deterministic optimization, this dissertation aims to optimize the supply chain of syngas production at tactical level considering uncertainties. Thus, a multi-period bi-objective robust optimization model is developed and applied to the case of a British Columbia Kraft pulp mill that would produce syngas to fuel their lime kiln.
The objectives are to minimize costs and emissions while optimizing the monthly biomass procurement, storage, and preprocessing decisions. Robust optimization with an adjustable budget of uncertainty is used to model the uncertainties in biomass supply and cost. Robust Pareto-optimal solutions are obtained that demonstrate a trade-off between objectives. The cost and emissions of robust solutions are on average 68% and 41% higher than those of the deterministic solutions. However, unlike the robust solution, the deterministic solution becomes infeasible in 98% of simulated future scenarios.
Besides logistics costs, other factors (e.g., capital investment, government funding, fuel prices, and carbon tax) determine the financial viability of biomass projects. A previous techno-economic feasibility study for the same case revealed that despite a short payback period and positive net present value, the syngas price and carbon tax would result in negative annual cashflows halfway through project’s lifespan. Thus, the pulp mill would be reluctant to invest in this project despite all its potential, especially emission savings. To improve the financial attractiveness of this project for the pulp mill, an optimization model is developed that shows an optimal syngas price of 27 $/GJ, increasing by 0.49¢ annually, would make all cashflows positive.
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Genre | |
Type | |
Language |
eng
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Date Available |
2023-08-15
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0435209
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2023-11
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Campus | |
Scholarly Level |
Graduate
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Rights URI | |
Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International