Biomass transport cost from field to conversion facility when biomass yield density and road network vary with transport radius

Applied Energy

Volumn 164, Issue , 2016, Pages 321-331

  Golecha, Rajdeep ^a   Gan, Jianbang ^b  

^a Texas A and M University ^*  (United States)

^b TEXAS A AND M UNIVERSITY   (United States)

Author keywords

Biomass availability; Simulation; Supply chain design; Transport Amplification Factor

Indexed keywords

BIOFUELS; COSTS; ROADS AND STREETS; SUPPLY CHAINS; TRANSPORTATION;

AMPLIFICATION FACTORS; BIOMASS AVAILABILITY; CONVERSION FACILITY; COST COMPETITIVENESS; INVESTMENT OPPORTUNITIES; SIMULATION; SUPPLY CHAIN DESIGN; THEORETICAL DERIVATIONS;

BIOMASS;

BIOENERGY; BIOFUEL; BIOMASS; COMPETITIVENESS; COST ANALYSIS; DESIGN; INVESTMENT; ROAD; ROAD TRANSPORT; SPATIAL DISTRIBUTION; TRANSPORTATION;

EID: 84951147558     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2015.11.070     Document Type: Article

References (25)

1. Hoogwijk M., Faaij A., van den Broek R., Berndes G., Gielen D., Turkenburg W. Exploration of the ranges of the global potential of biomass for energy. Biomass Bioenergy 2003, 25:119-133. 10.1016/S0961-9534(02)00191-5.
2. U.S. Energy Information Agency, International Energy Outlook 2013, Outlook 2013; 2013. 312. doi: EIA-0484(2013).
3. Perlack RD, Stokes BJ, Eaton LM, Turnhollow AF. U.S. Billion-Ton Update; 2011. https://bioenergykdf.net/.
4. West T, Dunphy-guzman K, Sun A, Malczynski L, Reichmuth D, Larson R, et al. Feasibility, economics, and environmental impact of producing 90billiongallons of ethanol per year by 2030 [GM Sandia Study Preprint 20090806].pdf; 2009. http://hitectransportation.org/news/2009/whitepaper_90BillionGallonBiofuel_SAND2009-3076J.pdf.
5. Maung T.A., Gustafson C.R., Saxowsky D.M., Nowatzki J., Miljkovic T., Ripplinger D. The logistics of supplying single vs. multi-crop cellulosic feedstocks to a biorefinery in southeast North Dakota. Appl Energy 2013, 109:229-238. 10.1016/j.apenergy.2013.04.003.
6. Leduc S., Lundgren J., Franklin O., Dotzauer E. Location of a biomass based methanol production plant: a dynamic problem in northern Sweden. Appl Energy 2010, 87:68-75. 10.1016/j.apenergy.2009.02.009.
7. Zhang F., Johnson D.M., Sutherland J.W. A GIS-based method for identifying the optimal location for a facility to convert forest biomass to biofuel. Biomass Bioenergy 2011, 35:3951-3961. 10.1016/j.biombioe.2011.06.006.
8. Kaundinya D.P., Balachandra P., Ravindranath N.H., Ashok V. A GIS (geographical information system)-based spatial data mining approach for optimal location and capacity planning of distributed biomass power generation facilities: a case study of Tumkur district, India. Energy 2013, 52:77-88. 10.1016/j.energy.2013.02.011.
9. Höhn J., Lehtonen E., Rasi S., Rintala J. A Geographical Information System (GIS) based methodology for determination of potential biomasses and sites for biogas plants in southern Finland. Appl Energy 2014, 113:1-10. 10.1016/j.apenergy.2013.07.005.
10. Sultana A., Kumar A. Development of tortuosity factor for assessment of lignocellulosic biomass delivery cost to a biorefinery. Appl Energy 2014, 119:288-295. 10.1016/j.apenergy.2013.12.036.
11. Overend R.P. The average haul distance and transportation work factors for biomass delivered to a central plant. Biomass 1982, 2:75-79.
12. Jenkins T.L., Sutherland J.W. A cost model for forest-based biofuel production and its application to optimal facility size determination. For Policy Econ 2014, 38:32-39. 10.1016/j.forpol.2013.08.004.
13. Wetterlund E., Leduc S., Dotzauer E., Kindermann G. Optimal localisation of biofuel production on a European scale. Energy 2012, 41:462-472. 10.1016/j.energy.2012.02.051.
14. Larson E.D., Marrison C.I. Economic scales for first-generation biomass-gasifier/gas turbine combined cycles fueled from energy plantations. J Eng Gas Turbines Power 1997, 119:285. 10.1115/1.2815572.
15. Sultana A., Kumar A. Optimal configuration and combination of multiple lignocellulosic biomass feedstocks delivery to a biorefinery. Bioresour Technol 2011, 102:9947-9956. 10.1016/j.biortech.2011.07.119.
16. Wright M., Brown R.C. Establishing the optimal sizes of different kinds of biorefineries. Biofuels Bioprod. Biorefining. 2007, 1:191-200. 10.1002/bbb.25.
17. Gan J., Smith C.T. Optimal plant size and feedstock supply radius: a modeling approach to minimize bioenergy production costs. Biomass Bioenergy 2011, 35:3350-3359. 10.1016/j.biombioe.2010.08.062.
18. Leboreiro J., Hilaly A.K. Biomass transportation model and optimum plant size for the production of ethanol. Bioresour Technol 2011, 102:2712-2723. 10.1016/j.biortech.2010.10.144.
19. Nguyen M.H., Prince R.G.H. A simple rule for bioenergy conversion plant size optimisation: bioethanol from sugar cane and sweet sorghum. Biomass Bioenergy 1996, 361-365. 10.1016/0961-9534(96)00003-7.
20. Walla C., Schneeberger W. The optimal size for biogas plants. Biomass Bioenergy 2008, 32:551-557. 10.1016/j.biombioe.2007.11.009.
21. Fridley J.D. Resource availability dominates and alters the relationship between species diversity and ecosystem productivity in experimental plant communities. Oecologia 2002, 132:271-277. 10.1007/s00442-002-0965-x.
22. Cohena M.A., Tan C.O. A polynomial approximation for arbitrary functions. Appl Math Lett 2012, 25:1947-1952. 10.1016/j.aml.2012.03.007.
23. Khan I.R., Ohba R. Taylor series based finite difference approximations of higher-degree derivatives. J Comput Appl Math 2003, 154:115-124. 10.1016/S0377-0427(02)00816-6.
24. Li P., Jin F., Sun Q., Ma J. The application of second-order approximation of Taylor series in thickness shear vibration analysis of quartz crystal microbalances. Ultrasonics 2015, 58:96-103. 10.1016/j.ultras.2014.12.007.
25. Alfonso D., Perpiñá C., Pérez-Navarro A., Peñalvo E., Vargas C., Cárdenas R. Methodology for optimization of distributed biomass resources evaluation, management and final energy use. Biomass Bioenergy 2009, 33:1070-1079. 10.1016/j.biombioe.2009.04.002.