Recently, there has been a growing interest in the development of cost‐effective technologies for the production of biofuels. A common approach to biofuel research is to invent or improve a biochemical or thermochemical conversion step. Subsequently, other conversion and separation steps are added to form a complete biorefinery flowsheet. Because this approach is structured around a specific conversion step, it may limit the possibilities of configuring optimal and innovative biorefineries. This article proposes a novel and systematic two‐stage approach to the synthesis and optimization of biorefinery configurations, given available feedstocks and desired products. In the synthesis stage, a systems‐based approach is developed to create a methodical way for synthesizing integrated biorefineries. This method is referred to as “forward‐backward” approach. It involves forward synthesis of biomass to possible intermediates and reverse synthesis starting with the desired products and identifying necessary species and pathways leading to them. In the optimization stage, Bellman's principle of optimality is applied to decompose the optimization problem into subproblems in which an optimal policy of available technologies is determined for every conversion step. An optimization formulation is utilized to determine the optimal configuration based on screening and connecting the optimal policies and generating the biorefinery flowsheet. A case study of alcohol‐producing pathways from lignocellulosic biomass is solved to demonstrate the merits of the proposed approach. © 2011 American Institute of Chemical Engineers AIChE J, 2012

MixAlco is a robust process that converts biomass to fuels and chemicals. A key feature of the MixAlco process is the fermentation, which employs a mixed culture of acid-forming microorganisms to convert biomass components (carbohydrates, proteins, and fats) to carboxylate salts. Subsequently, these intermediate salts are chemically converted to hydrocarbon fuels (gasoline, jet fuel, and diesel). This work focuses on process synthesis, simulation, integration, and cost estimation of the MixAlco process. For the base-case capacity of 40 dry tonne feedstock per hour, the total capital investment is US $5.54/annual gallon of hydrocarbon fuels (US $3.79/annual gallon of ethanol equivalent), and the minimum selling price [with 10% return on investment (ROI), internal hydrogen production, and US $60/tonne biomass] is US $2.56/gal hydrocarbon, which is equivalent to US $1.75/gal ethanol. If plant capacity is increased to 400 tph, the minimum selling price of biomass-derived hydrocarbon fuels is US $1.76/gal hydrocarbon (US $1.20/gal ethanol equivalent), which can compete without subsidies with petroleum-derived hydrocarbons when crude oil sells for about US $65/bbl. At 40 tph, using the average tipping fee for municipal solid waste (US $45/dry tonne) and current price of external hydrogen (US $1/kg), the minimum selling price is only US $1.24/gal hydrocarbon (US $0.85/gal ethanol equivalent).

The pooling problem is an important optimization problem that is encountered in process operation and scheduling. Because of the presence of bilinear terms, the traditional formulation is nonconvex. Consequently, there is a need to develop computationally efficient and easy-to-implement global-optimization techniques. In this paper, a new approach is proposed based on three concepts: linearization by discretizing nonlinear variables, preprocessing using implicit enumeration of the discretization to form a convex-hull which limits the size of the search space, and application of integer cuts to ensure compatibility between the original problem and the discretized formulation. The continuous quality variables contributing to the bilinear terms are first discretized. The discretized problem is a mixed integer linear program (MILP) which is globally solvable in a computationally effective manner using the branch and bound method. The merits of the proposed approach are illustrated with case studies from literature and comparison with published results.

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