IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v203y2017icp26-40.html
   My bibliography  Save this article

A cyberGIS approach to uncertainty and sensitivity analysis in biomass supply chain optimization

Author

Listed:
  • Hu, Hao
  • Lin, Tao
  • Wang, Shaowen
  • Rodriguez, Luis F.

Abstract

Decision making in biomass supply chain management is subject to uncertainties in a number of factors such as biomass yield, procurement prices, market demands, transportation costs, and processing technologies. To better understand such uncertainties requires statistical analysis and data-intensive computing enabled by cyberGIS (aka geographic information science and systems based on advanced cyberinfrastructure and e-science). Therefore, we have developed a cyberGIS approach to optimize biomass supply chains under uncertainties. Our approach (1) designs optimal biomass supply chains from regional to national scale with flexible spatial selection of study areas; (2) performs uncertainty and sensitivity analysis to quantify how various sources of uncertainty in the biomass supply chain contribute to the variation of optimal results; and (3) provides users with online geodesign features. This approach has been implemented as a decision support system through integration of data management, mathematical modeling, uncertainty and sensitivity analysis, scenario analysis, and result representation and visualization. An optimization modeling analysis of 7000 scenarios using Monte Carlo methods has been conducted to quantify the uncertainty and sensitivity impact of various input factors on ethanol production costs and optimal biomass supply chain configurations in Illinois, United States. The results from uncertainty analysis showed that the minimal ethanol production costs range from $2.30 to $3.43gal−1, considering uncertainties from biomass supply, transportation, and processing. The results of sensitivity analysis demonstrated that biomass-ethanol conversion rate was the most influential factor to ethanol production costs while the optimal biomass supply chain infrastructure was sensitive to changes in biomass yield, raw biomass transportation cost, and logistics loss rate. Leveraging high performance computing power through cutting-edge cyberGIS software, what-if scenario analysis has been evaluated to make decisions in case of unexpected events occurring in the supply chain operations.

Suggested Citation

  • Hu, Hao & Lin, Tao & Wang, Shaowen & Rodriguez, Luis F., 2017. "A cyberGIS approach to uncertainty and sensitivity analysis in biomass supply chain optimization," Applied Energy, Elsevier, vol. 203(C), pages 26-40.
    • Handle: RePEc:eee:appene:v:203:y:2017:i:c:p:26-40
    DOI: 10.1016/j.apenergy.2017.03.107
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261917303525
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2017.03.107?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Srirangan, Kajan & Akawi, Lamees & Moo-Young, Murray & Chou, C. Perry, 2012. "Towards sustainable production of clean energy carriers from biomass resources," Applied Energy, Elsevier, vol. 100(C), pages 172-186.
    2. Jonker, J.G.G. & Junginger, H.M. & Verstegen, J.A. & Lin, T. & Rodríguez, L.F. & Ting, K.C. & Faaij, A.P.C. & van der Hilst, F., 2016. "Supply chain optimization of sugarcane first generation and eucalyptus second generation ethanol production in Brazil," Applied Energy, Elsevier, vol. 173(C), pages 494-510.
    3. Höhn, J. & Lehtonen, E. & Rasi, S. & Rintala, J., 2014. "A Geographical Information System (GIS) based methodology for determination of potential biomasses and sites for biogas plants in southern Finland," Applied Energy, Elsevier, vol. 113(C), pages 1-10.
    4. Frombo, Francesco & Minciardi, Riccardo & Robba, Michela & Sacile, Roberto, 2009. "A decision support system for planning biomass-based energy production," Energy, Elsevier, vol. 34(3), pages 362-369.
    5. Parker, Nathan & Fan, Yueyue & Ogden, Joan, 2010. "From waste to hydrogen: An optimal design of energy production and distribution network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(4), pages 534-545, July.
    6. Zhang, Jun & Osmani, Atif & Awudu, Iddrisu & Gonela, Vinay, 2013. "An integrated optimization model for switchgrass-based bioethanol supply chain," Applied Energy, Elsevier, vol. 102(C), pages 1205-1217.
    7. Sharma, B. & Ingalls, R.G. & Jones, C.L. & Khanchi, A., 2013. "Biomass supply chain design and analysis: Basis, overview, modeling, challenges, and future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 608-627.
    8. Balat, Mustafa & Balat, Havva, 2009. "Recent trends in global production and utilization of bio-ethanol fuel," Applied Energy, Elsevier, vol. 86(11), pages 2273-2282, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bernardine Chigozie Chidozie & Ana Luísa Ramos & José Vasconcelos Ferreira & Luís Pinto Ferreira, 2023. "Residual Agroforestry Biomass Supply Chain Simulation Insights and Directions: A Systematic Literature Review," Sustainability, MDPI, vol. 15(13), pages 1-16, June.
    2. Luo, Li & O'Hehir, Jim & Regan, Courtney M. & Meng, Li & Connor, Jeffery D. & Chow, Christopher W.K., 2021. "An integrated strategic and tactical optimization model for forest supply chain planning," Forest Policy and Economics, Elsevier, vol. 131(C).
    3. De Laporte, Aaron V. & Ripplinger, David G., 2019. "The effects of site selection, opportunity costs and transportation costs on bioethanol production," Renewable Energy, Elsevier, vol. 131(C), pages 73-82.
    4. Kang, Yating & Yang, Qing & Bartocci, Pietro & Wei, Hongjian & Liu, Sylvia Shuhan & Wu, Zhujuan & Zhou, Hewen & Yang, Haiping & Fantozzi, Francesco & Chen, Hanping, 2020. "Bioenergy in China: Evaluation of domestic biomass resources and the associated greenhouse gas mitigation potentials," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
    5. Olli-Jussi Korpinen & Mika Aalto & Raghu KC & Timo Tokola & Tapio Ranta, 2023. "Utilisation of Spatial Data in Energy Biomass Supply Chain Research—A Review," Energies, MDPI, vol. 16(2), pages 1-23, January.
    6. Lim, Chun Hsion & Lam, Hon Loong & Ng, Wendy Pei Qin, 2018. "A novel HAZOP approach for literature review on biomass supply chain optimisation model," Energy, Elsevier, vol. 146(C), pages 13-25.
    7. Cooper, Nathanial & Panteli, Anna & Shah, Nilay, 2019. "Linear estimators of biomass yield maps for improved biomass supply chain optimisation," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    8. Biljana Kulisic & Bruno Gagnon & Jörg Schweinle & Sam Van Holsbeeck & Mark Brown & Jurica Simurina & Ioannis Dimitriou & Heather McDonald, 2021. "The Contributions of Biomass Supply for Bioenergy in the Post-COVID-19 Recovery," Energies, MDPI, vol. 14(24), pages 1-31, December.
    9. Ng, Rex T.L. & Maravelias, Christos T., 2017. "Economic and energetic analysis of biofuel supply chains," Applied Energy, Elsevier, vol. 205(C), pages 1571-1582.
    10. Lo, Shirleen Lee Yuen & How, Bing Shen & Leong, Wei Dong & Teng, Sin Yong & Rhamdhani, Muhammad Akbar & Sunarso, Jaka, 2021. "Techno-economic analysis for biomass supply chain: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    11. Yazan, Devrim Murat & Fraccascia, Luca & Mes, Martijn & Zijm, Henk, 2018. "Cooperation in manure-based biogas production networks: An agent-based modeling approach," Applied Energy, Elsevier, vol. 212(C), pages 820-833.
    12. Awasthi, Mukesh Kumar & Sarsaiya, Surendra & Patel, Anil & Juneja, Ankita & Singh, Rajendra Prasad & Yan, Binghua & Awasthi, Sanjeev Kumar & Jain, Archana & Liu, Tao & Duan, Yumin & Pandey, Ashok & Zh, 2020. "Refining biomass residues for sustainable energy and bio-products: An assessment of technology, its importance, and strategic applications in circular bio-economy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
    13. Guo, Changqiang & Hu, Hao & Wang, Shaowen & Rodriguez, Luis F. & Ting, K.C. & Lin, Tao, 2022. "Multiperiod stochastic programming for biomass supply chain design under spatiotemporal variability of feedstock supply," Renewable Energy, Elsevier, vol. 186(C), pages 378-393.
    14. Schipfer, Fabian & Kranzl, Lukas, 2019. "Techno-economic evaluation of biomass-to-end-use chains based on densified bioenergy carriers (dBECs)," Applied Energy, Elsevier, vol. 239(C), pages 715-724.
    15. Akhtari, Shaghaygh & Sowlati, Taraneh, 2020. "Hybrid optimization-simulation for integrated planning of bioenergy and biofuel supply chains," Applied Energy, Elsevier, vol. 259(C).
    16. Senocak, Ahmet Alp & Guner Goren, Hacer, 2023. "Three-phase artificial intelligence-geographic information systems-based biomass network design approach: A case study in Denizli," Applied Energy, Elsevier, vol. 343(C).
    17. Carta, José A. & Díaz, Santiago & Castañeda, Alberto, 2020. "A global sensitivity analysis method applied to wind farm power output estimation models," Applied Energy, Elsevier, vol. 280(C).
    18. Ng, Rex T.L. & Kurniawan, Daniel & Wang, Hua & Mariska, Brian & Wu, Wenzhao & Maravelias, Christos T., 2018. "Integrated framework for designing spatially explicit biofuel supply chains," Applied Energy, Elsevier, vol. 216(C), pages 116-131.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ghadge, Abhijeet & van der Werf, Sjoerd & Er Kara, Merve & Goswami, Mohit & Kumar, Pankaj & Bourlakis, Michael, 2020. "Modelling the impact of climate change risk on bioethanol supply chains," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    2. Shu, Kesheng & Schneider, Uwe A. & Scheffran, Jürgen, 2017. "Optimizing the bioenergy industry infrastructure: Transportation networks and bioenergy plant locations," Applied Energy, Elsevier, vol. 192(C), pages 247-261.
    3. Ba, Birome Holo & Prins, Christian & Prodhon, Caroline, 2016. "Models for optimization and performance evaluation of biomass supply chains: An Operations Research perspective," Renewable Energy, Elsevier, vol. 87(P2), pages 977-989.
    4. Cambero, Claudia & Sowlati, Taraneh, 2014. "Assessment and optimization of forest biomass supply chains from economic, social and environmental perspectives – A review of literature," Renewable and Sustainable Energy Reviews, Elsevier, vol. 36(C), pages 62-73.
    5. Razm, Sobhan & Brahimi, Nadjib & Hammami, Ramzi & Dolgui, Alexandre, 2023. "A production planning model for biorefineries with biomass perishability and biofuel transformation," International Journal of Production Economics, Elsevier, vol. 258(C).
    6. Rendon-Sagardi, Miguel A. & Sanchez-Ramirez, Cuauhtemoc & Cortes-Robles, Guillermo & Alor-Hernandez, Giner & Cedillo-Campos, Miguel G., 2014. "Dynamic analysis of feasibility in ethanol supply chain for biofuel production in Mexico," Applied Energy, Elsevier, vol. 123(C), pages 358-367.
    7. Gilani, H. & Sahebi, H. & Oliveira, Fabricio, 2020. "Sustainable sugarcane-to-bioethanol supply chain network design: A robust possibilistic programming model," Applied Energy, Elsevier, vol. 278(C).
    8. Moraes, Bruna S. & Junqueira, Tassia L. & Pavanello, Lucas G. & Cavalett, Otávio & Mantelatto, Paulo E. & Bonomi, Antonio & Zaiat, Marcelo, 2014. "Anaerobic digestion of vinasse from sugarcane biorefineries in Brazil from energy, environmental, and economic perspectives: Profit or expense?," Applied Energy, Elsevier, vol. 113(C), pages 825-835.
    9. Jensen, Ida Græsted & Münster, Marie & Pisinger, David, 2017. "Optimizing the supply chain of biomass and biogas for a single plant considering mass and energy losses," European Journal of Operational Research, Elsevier, vol. 262(2), pages 744-758.
    10. Gital Durmaz, Yeşim & Bilgen, Bilge, 2020. "Multi-objective optimization of sustainable biomass supply chain network design," Applied Energy, Elsevier, vol. 272(C).
    11. Varrone, C. & Liberatore, R. & Crescenzi, T. & Izzo, G. & Wang, A., 2013. "The valorization of glycerol: Economic assessment of an innovative process for the bioconversion of crude glycerol into ethanol and hydrogen," Applied Energy, Elsevier, vol. 105(C), pages 349-357.
    12. Zhu, Shengdong & Luo, Fang & Huang, Wenjing & Huang, Wangxiang & Wu, Yuanxin, 2017. "Comparison of three fermentation strategies for alleviating the negative effect of the ionic liquid 1-ethyl-3-methylimidazolium acetate on lignocellulosic ethanol production," Applied Energy, Elsevier, vol. 197(C), pages 124-131.
    13. Malladi, Krishna Teja & Sowlati, Taraneh, 2018. "Biomass logistics: A review of important features, optimization modeling and the new trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 587-599.
    14. Gökhan Memişoğlu & Halit Üster, 2016. "Integrated Bioenergy Supply Chain Network Planning Problem," Transportation Science, INFORMS, vol. 50(1), pages 35-56, February.
    15. Debnath, Deepayan & Whistance, Jarrett & Thompson, Wyatt & Binfield, Julian, 2017. "Complement or substitute: Ethanol’s uncertain relationship with gasoline under alternative petroleum price and policy scenarios," Applied Energy, Elsevier, vol. 191(C), pages 385-397.
    16. Balaman, Şebnem Yılmaz & Selim, Hasan, 2014. "A network design model for biomass to energy supply chains with anaerobic digestion systems," Applied Energy, Elsevier, vol. 130(C), pages 289-304.
    17. Kheybari, Siamak & Kazemi, Mostafa & Rezaei, Jafar, 2019. "Bioethanol facility location selection using best-worst method," Applied Energy, Elsevier, vol. 242(C), pages 612-623.
    18. Sarker, Bhaba R. & Wu, Bingqing & Paudel, Krishna P., 2019. "Modeling and optimization of a supply chain of renewable biomass and biogas: Processing plant location," Applied Energy, Elsevier, vol. 239(C), pages 343-355.
    19. Patrizio, P. & Chinese, D., 2016. "The impact of regional factors and new bio-methane incentive schemes on the structure, profitability and CO2 balance of biogas plants in Italy," Renewable Energy, Elsevier, vol. 99(C), pages 573-583.
    20. Zetterholm, Jonas & Pettersson, Karin & Leduc, Sylvain & Mesfun, Sennai & Lundgren, Joakim & Wetterlund, Elisabeth, 2018. "Resource efficiency or economy of scale: Biorefinery supply chain configurations for co-gasification of black liquor and pyrolysis liquids," Applied Energy, Elsevier, vol. 230(C), pages 912-924.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:203:y:2017:i:c:p:26-40. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.