Feedstock Contract Considerations for a Piedmont Biorefinery
Abstract
:1. Introduction
2. Review of Literature
3. Objectives
4. Materials and Methods
- All producers within the reference radius must have the same opportunity for profit. A producer located 50 km from the biorefinery must not be disadvantaged relative to a producer located 5 km from the biorefinery. We argue that the highway hauling cost must be borne by the biorefinery, thus transportation is not part of the feedstock contract.
- The feedstock contract must compensate for storage losses. Significant storage will be required to meet a biorefinery’s supply needs. Distributed, satellite storage locations (SSLs), stationed within a defined distance to the production field, would benefit the biorefinery by facilitating biomass collection and delivery scheduling. However, the SSLs will need to be filled and emptied at various times over the course of a year, and a producer whose feedstock is stored 6 months before shipment will incur a higher storage loss than a producer whose biomass is shipped shortly after harvest.
- Harvest over three months, with storage and delivery for year-round operation.
- Harvest over six months, with storage and delivery for year-round operation.
- Harvest over six months, with a relatively short (maximum of 3 months) storage and delivery for 6-month operation. The remaining 6 months of biorefining operations would be supplied with another feedstock. (In the Southeast, this may be some type of woody feedstock).
4.1. Length of Harvest Window Cost Factors
- Size/Cost of Storage—e.g., does storage have to be provided for an 11 month-supply (1-month harvest window) or a 6-month supply (6-month harvest window)?
- Biomass Losses—in-field losses incurred because of delayed harvest, machinery-related harvest losses, and losses in transport and storage.
- Fertilizer Cost—greater fertilizer costs for stand maintenance occur if the crop is harvested before senescence, because nutrient translocation into the root system is reduced, which increases removal of nutrients (which must be replaced).
- Harvest Cost—higher annual use hours of harvest equipment reduce USD/h ownership cost, and thus reduces USD/Mg harvest cost.
4.2. Analysis for Comparison of Three Harvest Window Scenarios
4.2.1. Definition of Parameters
- Biorefinery design capacity: Simulations were preformed based on plant capacities of 0.5, 1, and 2 bale/min for a biorefinery operating 24/7, 48 wk/y. (Results are given on the basis of USD/Mg-annual-capacity; thus, biorefinery size does not impact the interpretation of results).
- The round baler will create 5 × 4 bales {5 ft diameter × 4 ft wide (1.5 m × 1.2 m) round bales}. Average bale weight is 400 kg at 15% MC (wb). As a reference point, the annual biorefinery capacity consuming 1 bale/min for 24/7 operation, 48 wk/y is {400 (60) (24) (7) (48)}/1000 = 193,536 Mg.
- Average productivity across all balers employed for the harvest, and over all hours these balers work, is taken to be 8.2 Mg/h. This represents a conservative estimate for the region, and accounts for available production areas, which typically comprise small irregular-shaped fields over rolling terrain. Thus, field size, shape, and topography reduce equipment productivity, and operating time is lost when the balers must travel between multiple relatively small fields.
- Average base yield across the entire production area is 6.7 Mg/ha. Although yields greater than 13.4 Mg/ha have been obtained in research plots [55], such estimates typically do not provide an accurate estimate of yields achieved with field-scale equipment. As well, biomass feedstock operations likely will compete with existing uses of marginal land and the poorest quality fields. Previous, regionally appropriate research under such conditions [50] suggests 6.7 Mg/ha is a sufficiently conservative yield estimate. On that basis, the production area required to supply a bale-a-min biorefinery is 28,790 ha, or 3.7% of the land area within a 50-km radius.
- Average maintenance fertilizer cost is defined for this study by using an estimate of 7 g of nitrogen per kg of biomass. If nitrogen cost is 1.54 USD/kg, then this is about 72 USD/ha cost to replace harvested nitrogen and does not include cost of other nutrients.
- Biomass in round bales, placed in single-layer ambient storage at an SSL, is valued at a baseline cost of 77 USD/Mg. This estimate is used for calculating lost revenue adjustments for harvest and storage losses.
- The SSL is a graded and graveled surface. In this study, the cost to own and maintain an SSL is assigned to be 1.47 USD/m2 (see Appendix A).
4.2.2. Baler Cost
- Certain farmers, or full-time contract harvesters, will enter agreements with their neighbors to harvest their biomass and accumulate an economic production unit. These farmers will own and operate one or more SSLs.
- Brokers will contract for farmers to harvest (using their own equipment) and deliver biomass to an SSL owned and operated by the broker.
- Scenario 1 = 2.51 USD/Mg;
- Scenarios 2 and 3 = 2.24 USD/Mg.
4.2.3. Fertilizer Cost
4.2.4. Harvest Losses
4.2.5. Storage Losses
4.3. Computation Procedure
4.4. Considerations for Individual Feedstock Contracts
- Fertilizer adjustment—A fertilizer adjustment was defined with the cost for a November (i = 3) harvest as the base. This means that a September and October harvest will receive a positive adjustment, a November harvest a zero adjustment, and December, January, and February harvests receive a negative adjustment.
- 2.
- The adjustment paid to growers who harvest after September (and thus incur a harvest loss) is calculated as follows:
Typical Feedstock Contracts with Adjustments
5. Results and Discussion
5.1. Inventory
5.2. Storage Cost
- Three-month harvest: 5.27 USD/Mg;
- Six-month harvest: 3.52 USD/Mg;
- Six-month harvest, six-month campaign: 1.64 USD/Mg.
5.3. Harvest and Storage Losses
5.4. Cost of Losses
5.5. Fertilizer Cost
5.6. Baler Cost
- Scenario 1 = 2.51 USD/Mg;
- Scenarios 2 and 3 = 2.24 USD/Mg.
5.7. Comparison of Total Cost for Three Scenarios
6. Discussion
6.1. Comparison of Feedstock Contract Payments—Biorefinery
6.2. Comparison of Feedstock Contract Payments—Feedstock Contractors
7. Conclusions
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
Appendix A. Annual Cost to Build and Maintain SSL
- Construction Cost: 34,110 USD;
- Design life: 10 y, n =10;
- Interest rate: 6.25%, r = 0.0625;
- Insurance rate: $0.80/$100 value/y.
References
- USDOE (U.S. Dept. Energy). U.S. Billion-Ton Update: Biomass Supply for a Bioenergy and Bioproducts Industry; Oak Ridge National Laboratory: Oak Ridge, TN, USA, 2011; 227p.
- Sands, R.D.; Malcolm, S.A.; Suttles, S.A.; Marshall, E. Dedicated Energy Crops and Competition for Agricultural Land; United States Department of Agriculture: Washigton, DC, USA, 2017. Available online: https://www.ers.usda.gov/webdocs/publications/81903/err-223.pdf?v=2442.6 (accessed on 3 November 2020).
- Zilberman, D. Indirect land use change: Much ado about (almost) nothing. GCB Bioenergy 2017, 9, 485–488. [Google Scholar] [CrossRef] [Green Version]
- Swenson, D. Most of America’s rural areas are doomed to decline. The Conversation. 7 May 2019. Available online: https://theconversation.com/most-of-americas-rural-areas-are-doomed-to-decline-115343 (accessed on 3 November 2020).
- Porter, E. The Hard Truths of Trying to ‘Save’ the Rural Economy. The New York Times, 14 December 2018. Available online: https://www.nytimes.com/interactive/2018/12/14/opinion/rural-america-trump-decline.html (accessed on 3 November 2020).
- USDA-ERS (U.S. Department of Agriculture—Economic Research Service). Rural Employment and Unemployment. Available online: https://www.ers.usda.gov/topics/rural-economy-population/employment-education/rural-employment-and-unemployment (accessed on 3 November 2020).
- Rajagopal, D.; Sexton, S.; Roland-Holst, D.; Zilberman, D. Challenge of biofuel: Filling the tank without emptying the stomach? Environ. Res. Lett. 2007, 2, 044004. [Google Scholar] [CrossRef]
- Fewell, J.E.; Bergtold, J.S.; Williams, J.R. Farmers’ willingness to contract switchgrass as a cellulosic bioenergy crop in Kansas. Energy Econ. 2016, 55, 292–302. [Google Scholar] [CrossRef] [Green Version]
- Pannell, D.J.; Marshall, G.R.; Barr, N.; Curtis, A.; Vanclay, F.; Wilkinson, R. Understanding and promoting adoption of conservation practices by rural landholders. Aust. J. Exp. Agric. 2006, 46, 1407–1424. [Google Scholar] [CrossRef] [Green Version]
- Dicks, M.R.; Campiche, J.; Ugarte, D.D.L.T.; Hellwinckel, C.; Bryant, H.L.; Richardson, J.W. Land Use Implications of Expanding Biofuel Demand. J. Agric. Appl. Econ. 2009, 41, 435–453. [Google Scholar] [CrossRef] [Green Version]
- Walsh, M.E.; Ugarte, D.G.D.L.T.; Shapouri, H.; Slinsky, S.P. Bioenergy Crop Production in the United States: Potential Quantities, Land Use Changes, and Economic Impacts on the Agricultural Sector. Environ. Resour. Econ. 2003, 24, 313–333. [Google Scholar] [CrossRef]
- Altman, I.; Bergtold, J.; Sanders, D.; Johnson, T. Willingness to supply biomass for bioenergy production: A random parameter truncated analysis. Energy Econ. 2015, 47, 1–10. [Google Scholar] [CrossRef]
- Altman, I.J.; Boessen, C.R.; Sanders, D.R. Contracting for biomass: Supply chain strategies for renewable energy. J. ASFMRA 2008. Available online: www.jstor.org/stable/jasfmra.2008.1 (accessed on 11 November 2020). [CrossRef]
- Altman, I.J.; Sanders, D.R.; Boessen, C.R. Applying transaction cost economics: A note on biomass supply chains. J. Agric. Bus. 2007, 25, 107–114. [Google Scholar]
- Altman, I.J.; Johnson, T.G.; Moon, W. Organization preferences and producer characteristics in biomass supply chains. J. Agric. Bus. 2010, 28, 151–162. [Google Scholar]
- Epplin, F.M.; Clark, C.D.; Roberts, R.K.; Hwang, S. Challenges to the Development of a Dedicated Energy Crop. Am. J. Agric. Econ. 2007, 89, 1296–1302. [Google Scholar] [CrossRef]
- Giannoccaro, G.; de Gennaro, B.C.; De Meo, E.; Prosperi, M. Assessing farmer’s willingness to supply biomass as energy feedstock: Cereal straw Apulia (Italy). Energy Econ. 2017, 61, 179–185. [Google Scholar] [CrossRef]
- Gong, H.; Zhang, Y.; Li, J. Coordination mechanism by option contract in the biomass supply chain organized by “Company and Farmer. In Proceedings of the IEEE International Conference on Automation and Logistics, Hong Kong & Macau, China, 16–20 August 2010; pp. 71–75. [Google Scholar]
- Larson, J.A.; English, B.C.; Lambert, L. Economic Analysis of the Conditions for Which Farmers Will Supply Biomass Feedstocks for Energy Production; Agricultural Marketing Resource Center: Ames, IA, USA, 2007; Available online: http://www.agmrc.org/media/cms/2007UTennProjDeliverable_9BDDFC4C2F4E5.pdf (accessed on 11 November 2020).
- Stricker, J.A.; Segrest, S.A.; Rockwood, D.L.; Prine, G.M. Model fuel contract—Co-firing biomass with coal. In Proceedings of the 59th Annual Meeting, Tallahassee, FL, USA, 20–22 September 2000; Available online: http://sfrc.ufl.edu/facultysites/rockwood/trees/Biomass%20Contract.pdf (accessed on 11 December 2020).
- Wilhelm, W.W.; Johnson, J.M.; Hatfield, M.L.; Voorhees, W.B.; Linden, D.R. Crop and soil productivity response to corn residue removal: A literature review. Agron. J. 2004, 96, 1–17. [Google Scholar] [CrossRef]
- Yu, X.; Zhang, W.-G.; Liu, Y.-J.; Xing, Y.; Wei-Guo, Z.; Yong-Jun, L. Coordination Mechanism for Contract Farming Supply Chain with Government Option Premium Subsidies. Asia Pac. J. Oper. Res. 2019, 36. [Google Scholar] [CrossRef]
- Caldas, M.M.; Bergtold, J.S.; Peterson, J.M.; Graves, R.W.; Earnhart, D.; Gong, S.; Lauer, B.; Brown, J.C. Factors affecting farmers’ willingness to grow alternative biofuel feedstocks across Kansas. Biomass Bioenergy 2014, 66, 223–231. [Google Scholar] [CrossRef]
- Sun, F.; Sarin, S.C.; Cundiff, J.S.; Sert, I.O. Design of cost-effective sorghum biomass feedstock logistics-A comparison of different systems. Biomass Bioenergy 2020, 143, 105823. [Google Scholar] [CrossRef]
- Malladi, K.T.; Sowlati, T. Biomass logistics: A review of important features, optimization modeling and the new trends. Renew. Sustain. Energy Rev. 2018, 94, 587–599. [Google Scholar] [CrossRef]
- Aguayo, M.M.; Sarin, S.C.; Cundiff, J.S.; Comer, K.; Clark, T. A corn-stover harvest scheduling problem arising in cellulosic ethanol production. Biomass Bioenergy 2017, 107, 102–112. [Google Scholar] [CrossRef]
- Gonzales, D.S.; Searcy, S. GIS-based allocation of herbaceous biomass in biorefineries and depots. Biomass Bioenergy 2017, 97, 1–10. [Google Scholar] [CrossRef] [Green Version]
- Marufuzzaman, M.; Ekşioğlu, S.D. Designing a Reliable and Dynamic Multimodal Transportation Network for Biofuel Supply Chains. Transp. Sci. 2017, 51, 494–517. [Google Scholar] [CrossRef]
- Gautam, S.; Lebel, L.; Carle, M.-A. Supply chain model to assess the feasibility of incorporating a terminal between forests and biorefineries. Appl. Energy 2017, 198, 377–384. [Google Scholar] [CrossRef]
- Lin, T.; Rodríguez, L.F.; Davis, S.C.; Khanna, M.; Shastri, Y.; Grift, T.; Long, S.; Ting, K.C. Biomass feedstock preprocessing and long-distance transportation logistics. GCB Bioenergy 2015, 8, 160–170. [Google Scholar] [CrossRef]
- Zamora-Cristales, R.; Sessions, J.; Boston, K.; Murphy, G. Economic Optimization of Forest Biomass Processing and Transport in the Pacific Northwest USA. For. Sci. 2015, 61, 220–234. [Google Scholar] [CrossRef]
- De Meyer, A.; Cattrysse, D.; Rasinmäki, J.; Van Orshoven, J. Methods to optimise the design and management of biomass-for-bioenergy supply chains: A review. Renew. Sustain. Energy Rev. 2014, 31, 657–670. [Google Scholar] [CrossRef] [Green Version]
- De Meyer, A.; Cattrysse, D.; Van Orshoven, J. A generic mathematical model to optimise strategic and tactical decisions in biomass-based supply chains (OPTIMASS). Eur. J. Oper. Res. 2015, 245, 247–264. [Google Scholar] [CrossRef] [Green Version]
- Griffith, A.P.; Haque, M.; Epplin, F.M. Cost to produce and deliver cellulosic feedstock to a biorefinery: Switchgrass and forage sorghum. Appl. Energy 2014, 127, 44–54. [Google Scholar] [CrossRef]
- Roni, S.; Eksioglu, S.D.; Searcy, E.; Jha, K. A supply chain network design model for biomass co-firing in coal-fired power plants. Transp. Res. Part E Logist. Transp. Rev. 2014, 61, 115–134. [Google Scholar] [CrossRef]
- Shastri, Y.; Hansen, A.C.; Rodriguez, L.F.; Ting, K. Engineering and Science of Biomass Feedstock Production and Provision; Springer: New York, NY, USA, 2014. [Google Scholar]
- Lin, T.; Rodríguez, L.F.; Shastri, Y.; Hansen, A.C.; Ting, K. GIS-enabled biomass-ethanol supply chain optimization: Model development and Miscanthus application. Biofuels Bioprod. Biorefining 2013, 7, 314–333. [Google Scholar] [CrossRef]
- Lin, T.; Rodríguez, L.F.; Shastri, Y.; Hansen, A.C.; Ting, K.C. Integrated strategic and tactical biomass–biofuel supply chain optimization. Bioresour. Technol. 2014, 156, 256–266. [Google Scholar] [CrossRef]
- Lin, T.; Wang, S.; Rodríguez, L.F.; Hu, H.; Liu, Y.Y. CyberGIS-enabled decision support platform for biomass supply chain optimization. Environ. Model. Softw. 2015, 70, 138–148. [Google Scholar] [CrossRef] [Green Version]
- Grisso, R.; McCullough, D.; Cundiff, J.S.; Judd, J.D. Harvest schedule to fill storage for year-round delivery of grasses to biorefinery. Biomass Bioenergy 2013, 55, 331–338. [Google Scholar] [CrossRef]
- Miao, Z.; Shastri, Y.; Grift, T.E.; Hansen, A.C.; Ting, K. Lignocellulosic biomass feedstock transportation alternatives, logistics, equipment configurations, and modeling. Biofuels Bioprod. Biorefining 2012, 6, 351–362. [Google Scholar] [CrossRef]
- Miao, Z.; Grift, T.; Hansen, A.C.; Ting, K. An overview of lignocellulosic biomass feedstock harvest, processing and supply for biofuel production. Biofuels 2013, 4, 5–8. [Google Scholar] [CrossRef] [Green Version]
- An, H.; Searcy, S.W. Economic and energy evaluation of a logistics system based on biomass modules. Biomass Bioenergy 2012, 46, 190–202. [Google Scholar] [CrossRef]
- Zhu, X.; Li, X.; Yao, Q.; Chen, Y. Challenges and models in supporting logistics system design for dedicated-biomass-based bioenergy industry. Bioresour. Technol. 2011, 102, 1344–1351. [Google Scholar] [CrossRef]
- Bai, Y.; Hwang, T.; Kang, S.; Ouyang, Y. Biofuel refinery location and supply chain planning under traffic congestion. Transp. Res. Part B Methodol. 2011, 45, 162–175. [Google Scholar] [CrossRef]
- Parrish, D.J.; Fike, J.H. The Biology and Agronomy of Switchgrass for Biofuels. Crit. Rev. Plant Sci. 2005, 24, 423–459. [Google Scholar] [CrossRef]
- Fike, J.H.; Parrish, D.J.; Alwang, J.; Cundiff, J.S. Challenges for deploying dedicated, large-scale, bioenergy systems in the USA. CAB Rev. Perspect. Agri. Vet. Sci. Nutr. Nat. Res. 2007, 64, 1–28. [Google Scholar] [CrossRef] [Green Version]
- Cundiff, J.S.; Fike, J.H.; Parrish, D.J.; Alwang, J. Logistic Constraints in Developing Dedicated Large-Scale Bioenergy Systems in the Southeastern United States. J. Environ. Eng. 2009, 135, 1086–1096. [Google Scholar] [CrossRef]
- Fike, J.H.; Pease, J.W.; Owens, V.; Farris, R.L.; Hansen, J.L.; Heaton, E.A.; Hong, C.O.; Mayton, H.S.; Mitchell, R.B.; Viands, D.R. Switchgrass nitrogen response and estimated production costs on diverse sites. GCB Bioenergy 2017, 9, 1526–1542. [Google Scholar] [CrossRef]
- Fike, J.H.; Parrish, D.J.; Wolf, D.D.; Balasko, J.A.; Green, J.T.; Rasnake, M.; Reynolds, J.H. Long-term yield potential of switchgrass-for-biofuel systems. Biomass Bioenergy 2006, 30, 198–206. [Google Scholar] [CrossRef]
- Hong, C.O.; Owens, V.; Bransby, D.; Farris, R.; Fike, J.; Heaton, E.; Kim, S.; Mayton, H.; Mitchell, R.; Viands, D. Switchgrass Response to Nitrogen Fertilizer Across Diverse Environments in the USA: A Regional Feedstock Partnership Report. BioEnergy Res. 2014, 7, 777–788. [Google Scholar] [CrossRef]
- Owens, V.; Viands, D.; Mayton, H.; Fike, J.H.; Farris, R.L.; Heaton, E.; Bransby, D.; Hong, C.O. Nitrogen use in switchgrass grown for bioenergy across the USA. Biomass Bioenergy 2013, 58, 286–293. [Google Scholar] [CrossRef]
- Liu, X.-J.A.; Fike, J.H.; Galbraith, J.M.; Fike, W.B. Switchgrass Response to Cutting Frequency and Biosolids Amendment: Biomass Yield, Feedstock Quality, and Theoretical Ethanol Yield. BioEnergy Res. 2014, 7, 1191–1200. [Google Scholar] [CrossRef]
- Grisso, R.D.; Webb, E.G. Determining Available Workdays for Biomass Logistics: Proposed method. Technical Manuscript ORNL/TM-2012/260; 37831–6283; Oak Rideg National Laboratory: Oak Ridge, TN, USA, 2012; 30p.
- Fike, J.H.; Parrish, D.J.; Wolf, D.D.; Balasko, J.A.; Green, J.T.; Rasnake, M.; Reynolds, J.H. Switchgrass production for the upper southeastern USA: Influence of cultivar and cutting frequency on biomass yields. Biomass Bioenergy 2006, 30, 207–213. [Google Scholar] [CrossRef]
- ASABE. ASAE Standards, EP496.3, FEB 2006 (R2015) Cor. 1, Agricultural Machinery Management; American Society of Agricultural and Biological Engineers: St. Joseph, MI, USA, 2015. [Google Scholar]
- Cundiff, J.S.; Marsh, L.S. Harvest and storage costs for bales of switchgrass in the southeastern United States. Bioresour. Technol. 1996, 56, 95–101. [Google Scholar] [CrossRef]
- Mooney, D.F.; Larson, J.A.; English, B.; Tyler, D.D. Effect of dry matter loss on profitability of outdoor storage of switchgrass. Biomass Bioenergy 2012, 44, 33–41. [Google Scholar] [CrossRef]
- Grisso, R.; Cundiff, J.S.; Comer, K. Multi-Bale Handling Unit for Efficient Logistics. AgriEngineering 2020, 2, 336–349. [Google Scholar] [CrossRef]
- Gordian. RSMeans Data from Gordian. Construction Publishers & Consultants, 1099 Hingham St., Suite 201, Rockland, MA 02370. Available online: https://www.rsmeans.com/ (accessed on 12 November 2020).
Harvest Month | Probable Workday | Scenario 1 | Scenarios 2 and 3 |
---|---|---|---|
Hours (Total) | (% Annual Total) | (% Annual Total) | |
1 (September) | 196 | 37.2 | 27.3 |
2 (October) | 185 | 35.1 | 25.7 |
3 (November) | 146 | 27.7 | 20.3 |
4 (December) | 66 | 9.1 | |
5 (January) | 63 | 8.8 | |
6 (February) | 63 | 8.8 |
Percentage | Size of | Number of | Area | Percentage of |
---|---|---|---|---|
of Contracts | Contract (ha) | Contracts | (ha) | Total Area |
41 | 40 | 108 | 4320 | 15 |
42 | 123 | 110 | 13,530 | 47 |
17 | 243 | 45 | 10,940 | 38 |
100 | 263 | 28,790 | 100 |
Harvest Window | Harvest Loss | Required Production Area (ha) | Percent in 50- km Radius | Achieved Average Yield (Mg/ha) |
---|---|---|---|---|
3-month | Low | 30,421 | 3.9 | 6.36 |
(Scenario 1) | High | 32,134 | 4.1 | 6.02 |
6-month | Low | 31,636 | 4.0 | 6.12 |
(Scenario 2) | High | 35,849 | 4.6 | 5.40 |
6-month | Low | 15,818 | 2.0 | 6.12 |
(Scenario 3) | High | 17,925 | 2.3 | 5.40 |
(a) | |||
Harvest | Shipped Direct | Placed in Storage | Total |
Month | (Mg) | (Mg) | (Mg) |
1 (September) | 16,131 | 55,862 | 71,993 |
2 (October) | 16,131 | 51,821 | 67,952 |
3 (November) | 16,131 | 37,496 | 53,627 |
Total | 48,393 | 145,179 | 193,572 |
(b) | |||
Harvest | Shipped Direct | Placed in Storage | Total |
Month | (Mg) | (Mg) | (Mg) |
1 (September) | 16,131 | 36,637 | 52,768 |
2 (October) | 16,131 | 33,676 | 49,807 |
3 (November) | 16,131 | 23,176 | 39,307 |
4 (December) | 16,131 | 1638 | 17,769 |
5 (January) | 16,131 | 830 | 16,961 |
6 (February) | 16,131 | 830 | 16,961 |
Total | 96,786 | 96,786 | 193,572 |
(c) | |||
Harvest | Shipped Direct | Placed in Storage | Total |
Month | (Mg) | (Mg) | (Mg) |
1 (September) | 16,131 | 10,255 | 26,386 |
2 (October) | 16,131 | 8772 | 24,903 |
3 (November) | 16,131 | 3522 | 19,653 |
4 (December) | 8884 | 0 | 8884 |
5 (January) | 8481 | 0 | 8481 |
6 (February) | 8481 | 0 | 8481 |
Total | 74,239 | 22,550 | 96,788 |
(a) | |||
Loss Curves | Harvest Losses | Storage Losses | Total |
Low | 5.15 | 2.56 | 7.71 |
High | 9.62 | 4.76 | 14.38 |
(b) | |||
Loss Curves | Harvest Losses | Storage Losses | Total |
Low | 8.48 | 2.22 | 10.70 |
High | 16.89 | 3.86 | 20.75 |
(c) | |||
Loss Curves | Harvest Losses | Storage Losses | Total |
Low | 8.48 | 0.35 | 8.83 |
High | 16.89 | 0.81 | 17.70 |
(a) | |||
Loss Curves | Harvest Losses | Storage Losses | Total |
Low | 4.37 | 2.12 | 6.49 |
High | 8.96 | 3.92 | 12.88 |
(b) | |||
Loss Curves | Harvest Losses | Storage Losses | Total |
Low | 7.63 | 1.82 | 9.45 |
High | 18.92 | 3.37 | 22.29 |
(c) | |||
Loss Curves | Harvest Losses | Storage Losses | Total |
Low | 7.63 | 0.28 | 7.91 |
High | 18.92 | 0.65 | 19.57 |
Field | 3-Month | 6-Month | 6-Month |
---|---|---|---|
Productivity | (Scenario 1) | (Scenario 2) | (Scenario 3) |
Low | 14.26 | 12.95 | 12.95 |
High | 19.39 | 17.77 | 17.77 |
Scenario 1 | ||||||
Total Cost (USD/Mg) | 5.27 | + 8.29 | + 14.26 | + 2.51 | = | 30.33 |
% of Total Cost | 17 | + 28 | + 47 | + 8 | = | 100% |
Scenario 2 | ||||||
Total Cost (USD/Mg) | 3.52 | + 11.00 | + 12.95 | + 2.24 | = | 29.71 |
% of Total Cost | 11 | + 37 | + 44 | + 8 | = | 100% |
Scenario 3 | ||||||
Total Cost (USD/Mg) | 1.64 | + 8.28 | + 12.95 | + 2.24 | = | 25.11 |
% of Total Cost | 6 | + 33 | + 52 | + 9 | = | 100% |
Harvest Loss | 3-Month (Scenario 1) | 6-Month (Scenario 2) | 6-Month (Scenario 3) |
---|---|---|---|
Low | 93.79 | 93.32 | 87.92 |
High | 98.95 | 104.93 | 99.00 |
Harvest Loss | 3-Month (Scenario 1) | 6-Month (Scenario 2) | 6-Month (Scenario 3) |
---|---|---|---|
Low | 94.66 | 93.49 | 88.09 |
High | 99.82 | 104.95 | 99.02 |
Harvest | Feedstock Contract | Feedstock Contract |
---|---|---|
Month | (USD/ha) | (USD/Mg) |
1 (September) | 566.81 | 84.30 |
2 (October) | 540.61 | 85.54 |
3 (November) | 518.91 | 86.72 |
4 (December) | 506.51 | 88.63 |
5 (January) | 496.11 | 89.98 |
6 (February) | 487.21 | 90.58 |
Harvest | Storage Loss Adjustment | Feedstock Contract | Total Payment |
---|---|---|---|
Month | Equation (11) (USD/ Mg) | (USD/Mg at SSL) | (USD/Mg at Biorefinery) |
1 (September) | 5.44 | 84.30 | 89.74 |
2 (October) | 6.55 | 85.54 | 92.08 |
3 (November) | 7.26 | 86.72 | 93.98 |
4 (December) | 7.58 | 88.63 | 96.21 |
5 (January) | 7.25 | 89.98 | 97.23 |
6 (February) | 6.61 | 90.58 | 97.19 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Cundiff, J.; Grisso, R.“.; Fike, J. Feedstock Contract Considerations for a Piedmont Biorefinery. AgriEngineering 2020, 2, 607-630. https://doi.org/10.3390/agriengineering2040041
Cundiff J, Grisso R“, Fike J. Feedstock Contract Considerations for a Piedmont Biorefinery. AgriEngineering. 2020; 2(4):607-630. https://doi.org/10.3390/agriengineering2040041
Chicago/Turabian StyleCundiff, John, Robert “Bobby” Grisso, and John Fike. 2020. "Feedstock Contract Considerations for a Piedmont Biorefinery" AgriEngineering 2, no. 4: 607-630. https://doi.org/10.3390/agriengineering2040041
APA StyleCundiff, J., Grisso, R. “., & Fike, J. (2020). Feedstock Contract Considerations for a Piedmont Biorefinery. AgriEngineering, 2(4), 607-630. https://doi.org/10.3390/agriengineering2040041