Hybrid optimization-simulation for integrated planning of bioenergy and biofuel supply chains

Shaghaygh Akhtari and Taraneh Sowlati

Applied Energy, 2020, vol. 259, issue C

Abstract: Traditionally, biomass supply chain planning has been done hierarchically at the strategic, tactical, and operational levels. Hierarchical planning might result in inconsistent or infeasible solutions at lower planning levels because short-term variations, e.g., those in biomass supply and demand, are not considered in long-term plans. To address this issue, an integrated strategic, tactical, and operational plan is developed in this paper in to consider the variations and details of lower planning levels. The integrated plan is developed as a hybrid model based on the recursive optimization-simulation approach. The optimization model integrates the strategic and tactical plans, while the simulation model incorporates the variations at the operational level. A procedure is developed to adjust the plans according to the variations in the model parameters using a feedback mechanism between the operational and the strategic/tactical level plans. The hybrid model is applied to a case study in British Columbia, Canada. The results show that the operational level variations and constraints could affect the long-term investment decisions and their profitability. For the given case study, the operational level variations decreased the estimated net present value by 21% due to the higher demand for logging residues. However, compared with the initial solution considered in the hybrid model, the final solution has a 17% higher net present value. The final design from the hybrid model suggests small-scale bioenergy and biofuel conversion facilities rather than large-scale ones as their demand for biomass could be met using more sawmill residues and less roadside logging residues.

Keywords: Biofuel; Bioenergy; Integrated planning; Simulation; Optimization; Hybrid modeling; Variations (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (10)

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DOI: 10.1016/j.apenergy.2019.114124

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