Early‐Stage Capital Cost Estimation of Biorefinery Processes: A Comparative Study of Heuristic Techniques

Abstract Biorefineries offer a promising alternative to fossil‐based processing industries and have undergone rapid development in recent years. Limited financial resources and stringent company budgets necessitate quick capital estimation of pioneering biorefinery projects at the early stages of their conception to screen process alternatives, decide on project viability, and allocate resources to the most promising cases. Biorefineries are capital‐intensive projects that involve state‐of‐the‐art technologies for which there is no prior experience or sufficient historical data. This work reviews existing rapid cost estimation practices, which can be used by researchers with no previous cost estimating experience. It also comprises a comparative study of six cost methods on three well‐documented biorefinery processes to evaluate their accuracy and precision. The results illustrate discrepancies among the methods because their extrapolation on biorefinery data often violates inherent assumptions. This study recommends the most appropriate rapid cost methods and urges the development of an improved early‐stage capital cost estimation tool suitable for biorefinery processes.

[1]  D. R. Raman,et al.  Development and validation of a technoeconomic analysis tool for early-stage evaluation of bio-based chemical production processes. , 2013, Bioresource technology.

[2]  Zacharias B. Maroulis,et al.  Food Plant Economics , 2007 .

[3]  J. H. Taylor.  The 'process step scoring' method for making quick capital estimates , 1977 .

[4]  J. Kwiatkowski,et al.  Modeling the process and costs of fuel ethanol production by the corn dry-grind process , 2006 .

[5]  Prasant Kumar Rout,et al.  Production of first and second generation biofuels: A comprehensive review , 2010 .

[6]  John Cran.  EPE plant cost indices , 1979 .

[7]  Krist V. Gernaey,et al.  Uncertainties in Early-Stage Capital Cost Estimation of Process Design – A Case Study on Biorefinery Design , 2015, Front. Energy Res..

[8]  James Riley Couper,et al.  Process Engineering Economics , 2003 .

[9]  David A. Swenson,et al.  An Exploration of Green Job Policies, Theoretical Underpinnings, Measurement Approaches, and Job Growth Expectations , 2011 .

[10]  Ray Sinnott,et al.  Chemical Engineering Design , 2007 .

[11]  Christopher W. Myers,et al.  Understanding cost growth and performance shortfalls in pioneer process plants , 1981 .

[12]  Elnaz Shahbazali.  Biorefinery: from biomass to chemicals and fuels , 2013 .

[13]  R. Lathe.  Phd by thesis , 1988, Nature.

[14]  A. M. Gerrard.  Guide to Capital Cost Estimating , 2000 .

[15]  Kenneth A. Kobe,et al.  Process engineering economics , 1956 .

[16]  Tristan R. Brown.  A critical analysis of thermochemical cellulosic biorefinery capital cost estimates , 2015 .

[17]  Zacharias B. Maroulis,et al.  Cost data analysis for the food industry , 2005 .

[18]  A. V. Bridgwater.  Development of a location index , 1976 .

[19]  R. K. Sinnott,et al.  An introduction to chemical engineering design , 1983 .

[20]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[21]  Paul W. Gallagher,et al.  Plant size: Capital cost relationships in the dry mill ethanol industry , 2005 .

[22]  M. Schenkel,et al.  Charles University in Prague Faculty of Mathematics and Physics , 2013 .

[23]  A. McAloon,et al.  A process model to estimate biodiesel production costs. , 2006, Bioresource technology.

[24]  D. J. Brennan,et al.  New Factors for Capital Cost Estimation in Evolving Process Designs , 2002 .

[25]  Om Prakash Kharbanda,et al.  Capital cost estimating for the process industries , 1989 .

[26]  Ken Black,et al.  Business Statistics: Contemporary Decision Making , 1994 .

[27]  Jean-Paul Lange,et al.  Fuels and Chemicals Manufacturing; Guidelines for Understanding and Minimizing the Production Costs , 2001 .

[28]  H. von Blottnitz,et al.  Cost analyses and predictions for a fuel ethanol plant in a rural and landlocked African country: Lang factor approach , 2009 .