460997 New Short-Cut Tools for Early-Stage Investment Evaluation of Biorefineries

Wednesday, November 16, 2016: 3:59 PM
Carmel I (Hotel Nikko San Francisco)
Mirela Tsagkari1,2, Jean-Luc Couturier1, Antonis C. Kokossis2 and Jean-Luc Dubois1, (1)CRRA, Arkema, Pierre-BĂ©nite, France, (2)School of Chemical Engineering, National Technical University of Athens, Athens, Greece

New short-cut tools for early-stage investment evaluation of biorefineries

Biorefineries offer a promising alternative to fossil-based processing industries and have met rapid development during the last years.  Biorefinery processes employ state-of-the-art technologies and thus, represent high risk business decisions. Researchers undertaking the development of a biorefinery, often have to estimate capital and manufacturing costs based on minimum information, in order to decide wisely on project continuity and justify further funding for their research. Most R&D engineers rely on literature information to estimate the costs as historical cost data are proprietary information and are seldom announced. They also draw on various costing techniques and heuristics, which were developed for the needs of the petrochemical and the Oil & Gas Industry and require high level of process detail, which is not available at the early-stages of process conception.

We have evaluated some of these methods with means of both deterministic and statistical comparison from reported literature estimates and commercial biorefineries’ cost data. As the majority were published during the 1970’s-80’s and were derived from petrochemical processes, they do not account for the technological progress often met within the state-of-the-art biorefinery processes and report discrepancies in their results. Fig. 1 illustrates the aforementioned discrepancies for dry corn mill ethanol biorefineries. We have been collecting capital cost data for commercial corn-to-ethanol plants (marked as circles). Only three out of the six cost methods fall within the 90% Confidence Intervals of the best regression line (marked as triangles), while the capital estimation reported in literature reference greatly underestimates the plant’s final cost (marked as x). Our work reports similar figures for chemical and thermochemical biorefineries, as well CITATION Tsa16 \l 2057  [1].

Therefore, we decided to attempt new capital and manufacturing cost estimation methods to meet the needs of non-experienced cost estimators which undertake the design of first-of-a-kind biorefineries: the methods require information available at the start of the process conception. The first capital cost estimation method proposes new investment factors that draw on historical investment costs along with probabilistic estimation of the total investment. The second capital cost estimation method proposes cost estimation relationships for chemical, biochemical and thermochemical biorefineries, as well as simple techniques to define the uncertainty of the estimate. Finally, we have developed a new rapid manufacturing cost estimation methodology with uncertainty: it relies on factors requiring minimal user input, i.e. raw materials cost calculation, for determining the net production cost of the process, employing probabilistic means of determination.

Fig. 1. Dry corn mill bioethanol production plants Investment Costs (M$, 2011,US) vs Plant Capacity (kt/yr)


The European Commission is gratefully acknowledged for funding the Renewable Systems Engineering project (RENESENG - FP7 Marie Curie project).



M. Tsagkari, J.-L. Couturier, A. Kokossis and J.-L. Dubois, "Early-stage capital cost estimation of biorefinery processes: a comparative study of heuristic techniques," ChemSusChem, 2016 (under review).

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See more of this Session: Design of Integrated Biorefineries I
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