Royal DSM is a global science-based company active in Life Sciences and Materials Sciences. In the Joint Venture POET-DSM Advanced Biofuels, DSM supported delivering the first commercial scale demonstration of cellulosic bio-ethanol production technology. In this presentation it will be shown how DSM, with its advanced cellulosic enzyme and yeast technology, continues the efforts to fulfill the promise to deliver a cost competitive bio-ethanol technology.
DSM’s involvement in bio-ethanol production process is reflected in enzyme production and use in hydrolysis, and yeast propagation and use in ethanol fermentation. Breakthroughs in this area by DSM that helped in ethanol cost reduction are the development of robust thermo-stable, acid-tolerant enzyme cocktails for lignocellulosic hydrolyzate production and advanced yeast strains with the ability to ferment both C6 and C5 sugars in ethanol production. DSM yeast performance has been confirmed on demo and commercial scale. DSM’s strategy is to license enzyme on-site manufacturing technology that provides advantages of using local C-sources, reducing costs of stabilization and transportation, and offering integration with the overall ethanol production. With integration of on-site enzyme and yeast production in the ethanol production plant, the need arose for an integral process view, with an overall process optimization rather than optimization of single technologies. This challenge was answered by developing an Integral Process and Cost Model (IPCM) which integrated R&D knowledge available in different teams into a structure for integral scenario evaluation. IPCM follows the standard approach to Process Design and Techno-Economic Assessment; inputs collected from the research teams are fed into the mass balance used further on in Capital Investment (CAPEX) and Operational Cost (OPEX) estimation. This process requires harmonization between the teams and IPCM brings the structure making the exchange and alignment more efficient. In order to make a structure dedicated to each process step and generate sufficient degrees of freedom for testing different parameters, the model is structured to follow cellulosic ethanol production steps. Various integral process scenarios can be constructed by selecting options for each process step, such as pretreatment conditions, residence time of steps, enzyme dosage, to name a few. CAPEX estimation is a connection point with the Engineering input where practical knowledge based on years of industrial experience support realistic view on the estimates. Finally, OPEX and CAPEX costs are used in the estimates of various profitability parameters, e.g. the ethanol costprice. These results are used for benefit estimation of different process improvement options as input to R&D teams and better understanding of the sensitivities in ethanol production process.
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