Adapting the experience curve for estimating biorefinery cost

Canadian Pulp and Paper (P&P) sector is struggling with financial difficulties. This is due to decreases in demand for their traditional products, increasing energy prices and increased competition from low-cost countries. Biorefinery integration into this sector can bring competetiveness by diversifiying products portfolio and revenue sources.;There are some uncertainties in integration of emerging biorefineries into P&P sector, such as first implementation costs and long-term competitiveness. On the other hand stage of development (laboratory, pilot or demonstration scales) of a biorefinery affects level of these uncertainties. This in turn makes comparison of biorefineries options more challenging. Poor cost estimation of biorefineries affect the quality of decision made about commercialization. Moreover In order for a pulp mill to make well-informed decisions, it is necessary to forecast commercial costs.;The objective of this thesis is to propose a model inspired by experience curve approach to evaluate costs of emerging biorefinery technologies before and after commercialization. The model is applied in lignin-based case studies considering retrofit biorefinery implementation into a Kraft P&P mill.;The methodology to accomplish the objective of this thesis consists of: (1) Reviewing literatures on (a) Early cost estimate analysis; (b) Experience curves of energy technologies; (c) Forest biorefineries; (2) Proposing a model to underline factors impacting costs before and after commercialization; (3) Application of model into two retrofit lignin-based biorefinery case studies: (a) Large Block Analysis (LBA) on the case studies; (b) Evaluating the identified factors before and after commercialization; (c) Operating the experience curve model based on gathered data from previous steps.;Fundamental factors that affect costs before and after commercialization of emerging biorefineries are identified. Then a new of experience curve based on these factors is proposed. The factors affecting the first commercial cost are: (1) New technology; (2) Appreciation for and level of design engineering; (3) Appreciation for risk associated with integration and scale up; (4) Optimism bias of the technology and project developers.;The factors affecting the post commercial costs are: (1) Economies-of-scale; (2) Process operation optimization due to learning; (3) Process design optimization and less conservatism in design due to learning; (4) Process improvement with new technology additions post-implementation.;The two lignin-based biorefinery case studies for application of this model were; solvent pulping and lignin precipitation processes. For the first commercial scale, both case studies showed cost underestimation; solvent pulping process by 200 ($ per ton of PF resin precursor) and lignin precipitation by 100 ($ per ton of PF resin precursor).;At post commercial scales, costs of both case studies were reduced; solvent pulping with progress ratio of 77% and lignin precipitation with progress ratio of 96%.;Application of this model can bring critical information about costs of biorefinery technologies in pre and post commercial scales for decision-making processes such as Multi Criteria Decision Making (MCDM). Fore example based on the achieved results, it can be understood that in short term of business strategy lignin precipitation process with less cost per ton of lignin precursor is more promising. On the other hand in long-term business strategy when demand and market of lignin products such as PF resin precursor are developed, solvent pulping process is more beneficial. This is mainly due to three factors: (1) More opportunities for cost reduction at commercial scales; (2) More quantity; (3) Better quality of lignin.;Future work includes application of this model to more case studies to enhance its understanding. Furthermore suitable criteria based on achieved information from this model should be defined for decision-makings techniques. This will help to validate further the importance of this provided information.