(580c) New Short-Cut Tools for Early-Stage Investment Evaluation of Biorefineries

Tsagkari, M., Arkema France
Couturier, J. L., Arkema France
Kokossis, A. C., National Technical University of Athens
Dubois, J. L., Arkema France

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)


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).