82
Views
0
CrossRef citations to date
0
Altmetric
Review Article

How can mathematical models help in the biogas generation process?

ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 1588-1605 | Received 01 Oct 2023, Accepted 18 Dec 2023, Published online: 11 Jan 2024

References

  • Abilmazhinov, Y., K. Shakerkhan, V. Meshechkin, Y. Shayakhmetov, N. Nurgaliyev, and A. Suychinov. 2023. Mathematical modeling for evaluating the sustainability of biogas generation through anaerobic digestion of livestock waste. Sustainability 15 (7):5707. doi:10.3390/su15075707.
  • Afonso, M. H. F. 2011. Como construir conhecimento sobre o tema de pesquisa? Aplicação do processo Proknow-C na busca de literatura sobre avaliação do desenvolvimento sustentável. Revista de Gestão Social e Ambiental 5 (2):47–62. doi:10.24857/rgsa.v5i2.424.
  • Akbaş, H., B. Bilgen, and A. M. Turhan. 2015. An integrated prediction and optimization model of biogas production system at a wastewater treatment facility. Bioresource Technology 196:566–76. doi:10.1016/j.biortech.2015.08.017.
  • Aria, M. and C. Cuccurullo. 2017. Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics 11 (4):959–75. doi:10.1016/j.joi.2017.08.007.
  • Auburger, S., A. Jacobs, B. Märländer, and E. Bahrs. 2016. Economic optimization of feedstock mix for energy production with biogas technology in Germany with a special focus on sugar beets - effects on greenhouse gas emissions and energy balances. Renewable Energy 89:1–11. doi:10.1016/j.renene.2015.11.042.
  • Auburger, S., E. Petig, and E. Bahrs. 2017. Assessment of grassland as biogas feedstock in terms of production costs and greenhouse gas emissions in exemplary federal states of Germany. Biomass and Bioenergy 101:44–52. doi:10.1016/j.biombioe.2017.03.008.
  • Axaopoulos, P., P. Panagakis, A. Tsavdaris, and D. Georgakakis. 2001. Simulation and experimental performance of a solar heated anaerobic digester. Solar Energy 70 (2):155–64. doi:10.1016/S0038-092X(00)00130-4.
  • Balaman, T. Y., and H. Selim. 2014. A network design model for biomass to energy supply chains with anaerobic digestion systems. Applied Energy 130:289–304. doi:10.1016/j.apenergy.2014.05.043.
  • Barampouti, E. M. P., S. T. Mai, and A. G. Vlyssides. 2005. Dynamic modeling of biogas production in an UASB reactor for potato processing wastewater treatment. Journal of Chemical Engineering 106 (1):53–58. doi:10.1016/j.cej.2004.06.010.
  • Biswas, J., R. Chowdhury, and P. Bhattacharya. 2007. Mathematical modeling for the prediction of biogas generation characteristics of an anaerobic digester based on food/vegetable residues. Biomass and Bioenergy 31 (1):80–86. doi:10.1016/j.biombioe.2006.06.013.
  • Chinese, D., P. Patrizio, and G. Nardin. 2014. Effects of changes in Italian bioenergy promotion schemes for agricultural biogas projects: Insights from a regional optimization model. Energy Policy 75:189–205. doi:10.1016/j.enpol.2014.09.014.
  • Daiem, M. M. A., A. Hatata, O. H. Galal, N. Said, and D. Ahmed. 2021. Prediction of biogas production from anaerobic co-digestion of waste activated sludge and wheat straw using two-dimensional mathematical models and an artificial neural network. Renewable Energy 178:226–40. doi:10.1016/j.renene.2021.06.050.
  • de Jesus, R. H. G., J. T. de Souza, F. N. Puglieri, C. M. Piekarski, and A. C. de Francisco. 2021. Biodigester location problems, its economic–environmental–social aspects and techniques: Areas yet to be explored. Energy Reports 7:3998–4008. doi:10.1016/j.egyr.2021.06.090.
  • Díaz-Trujillo, L. A., L. F. Fuentes-Cortés, and F. Nápoles-Rivera. 2020. Economic and environmental optimization for a biogas supply chain: A CVaR approach applied to uncertainty of biomass and biogas demand. Computers and Chemical Engineering 141:107018. doi:10.1016/j.compchemeng.2020.107018.
  • Díaz-Trujillo, L. A., and F. Nápoles-Rivera. 2019. Optimization of biogas supply chain in Mexico considering economic and environmental aspects. Renewable Energy 139:1227–1240. doi:10.1016/j.renene.2019.03.027.
  • Di Trapani, D., G. Mannina, S. Nicosia, and G. Viviani. 2018. Biogas from municipal solid waste landfills: A simplified mathematical model. Water Science & Technology 77 (10):2426–35. doi:10.2166/wst.2018.193.
  • Drobež, R., Z. N. Pintarič, B. Pahor, and Z. Kravanja. 2009. MINLP synthesis of processes for the production of biogas from organic and animal waste. Chemical and Biochemical Engineering Quarterly 23 (4):455–59. https://www.scopus.com/inward/record.uri?eid=2-s2.0-74549210171&partnerID=40&md5=8200893226a31a887ee38a3e11bab1a5.
  • Drobež, R., Z. N. Pintarič, B. Pahor, and Z. Kravanja. 2011. Simultaneous heat integration and the synthesis of biogas processes from animal waste. Asia-Pacific Journal of Chemical Engineering 6 (5):734–49. doi:10.1002/apj.504.
  • Durmaz, Y. G., and B. Bilgen. 2020. Multi-objective optimization of sustainable biomass supply chain network design. Applied Energy 272:115259. doi:10.1016/j.apenergy.2020.115259.
  • Egieya, J. M., L. Čuček, K. Zirngast, A. J. Isafiade, B. Pahor, and Z. Kravanja. 2019. Synthesis of biogas supply networks using various biomass and manure types. Computers & Chemical Engineering 122:129–51. doi:10.1016/j.compchemeng.2018.06.022.
  • Fitamo, T., A. Boldrin, G. Dorini, K. Boe, I. Angelidaki, and C. Scheutz. 2016. Optimising the anaerobic co-digestion of urban organic waste using dynamic bioconversion mathematical modelling. Water Research 106:283–94. doi:10.1016/j.watres.2016.09.043.
  • Galvagno, A., V. Chiodo, F. Urbani, and F. Freni. 2013. Biogas as hydrogen source for fuel cell applications. International Journal of Hydrogen Energy 38 (10):3913–20. doi:10.1016/j.ijhydene.2013.01.083.
  • Gautam, P., S. N. Upadhyay, and S. K. Dubey. 2020. Bio-methanol as a renewable fuel from waste biomass: Current trends and future perspective. Fuel 273:117783. doi:10.1016/j.fuel.2020.117783.
  • Goodman, L. A. 1961. Snowball sampling. Annals of Mathematical Statistics 32 (1):148–170. doi:10.1214/aoms/1177705148.
  • Grillo, H., M. M. E. Alemany, and A. Ortiz. 2016. A review of mathematical models for supporting the order promising process under lack of homogeneity in product and other sources of uncertainty. Computers & Industrial Engineering 91:239–61. doi:10.1016/j.cie.2015.11.013.
  • Havrysh, V., V. Nitsenko, Y. Bilan, and D. Streimikiene. 2019. Assessment of optimal location for a centralized biogas upgrading facility. Energy & Environment 30 (3):462–80. doi:10.1177/0958305X18793110.
  • Hochloff, P., and M. Braun. 2014. Optimizing biogas plants with excess power unit and storage capacity in electricity and control reserve markets. Biomass and Bioenergy 65:125–35. doi:10.1016/j.biombioe.2013.12.012.
  • IEA. (2020). Outlook for biogas and biomethane: Prospects for organic growth. https://iea.blob.core.windows.net/assets/03aeb10c-c38c-4d10-bcec-de92e9ab815f/Outlook_for_biogas_and_biomethane.pdf
  • Karschin, I., and J. Geldermann. 2015. Efficient cogeneration and district heating systems in bioenergy villages: An optimization approach. Journal of Cleaner Production 104:305–14. doi:10.1016/j.jclepro.2015.03.086.
  • Kegl, T., and A. K. Kralj. 2020. Multi-objective optimization of anaerobic digestion process using a gradient-based algorithm. Energy Conversion and Management 226:226. doi:10.1016/j.enconman.2020.113560.
  • Kegl, T., and A. K. Kralj. 2022. An enhanced anaerobic digestion biomodel calibrated by parameters optimization based on measured biogas plant data. Fuel 312:312. doi:10.1016/j.fuel.2021.122984.
  • Khishtandar, S. 2019. Simulation based evolutionary algorithms for fuzzy chance-constrained biogas supply chain design. Applied Energy 236:183–95. doi:10.1016/j.apenergy.2018.11.092.
  • Laing, H., C. O’Malley, A. Browne, T. Rutherford, T. Baines, A. Moore, K. Black, and M. J. Willis. 2022. Optimisation of energy usage and carbon emissions monitoring using MILP for an advanced anaerobic digester plant. Energy 256:124577. doi:10.1016/j.energy.2022.124577.
  • Lauer, M., J. K. Hansen, P. Lamers, and D. Thrän. 2018. Making money from waste: The economic viability of producing biogas and biomethane in the Idaho dairy industry. Applied Energy 222:621–36. doi:10.1016/j.apenergy.2018.04.026.
  • Lauer, M., and D. Thrän. 2018. Flexible biogas in future energy systems—sleeping beauty for a cheaper power generation. Energies 11 (4):761. doi:10.3390/en11040761.
  • Liu, Y., T. Huang, D. Peng, J. Huang, C. Maurer, and M. Kranert. 2021. Optimizing the co-digestion supply chain of sewage sludge and food waste by the demand oriented biogas supplying mechanism. Waste Management and Research 39 (2):302–13. doi:10.1177/0734242X20953491.
  • Lobato, L. C. S., C. A. L. Chernicharo, and C. L. Souza. 2012. Estimates of methane loss and energy recovery potential in anaerobic reactors treating domestic wastewater. Water Science and Technology 66 (12):2745–53. doi:10.2166/wst.2012.514.
  • Lohani, S. P., S. Shakya, P. Gurung, B. Dhungana, D. Paudel, and B. Mainali. 2021. Anaerobic co-digestion of food waste, poultry litter and sewage sludge: Seasonal performance under ambient condition and model evaluation. Energy Sources Part A: Recovery, Utilization, and Environmental Effects 1–16. doi:10.1080/15567036.2021.1887976.
  • Lovato, G., M. Alvarado-Morales, A. Kovalovszki, M. Peprah, P. G. Kougias, J. A. D. Rodrigues, and I. Angelidaki. 2017. In-situ biogas upgrading process: Modeling and simulations aspects. Bioresource Technology 245:332–41. doi:10.1016/j.biortech.2017.08.181.
  • Luo, T., J. Pan, L. Fu, Z. Mei, C. Kong, and H. Huang. 2017. Reducing biogas emissions from village-scale plant with optimal floating-drum biogas storage tank and operation parameters. Applied Energy 208:312–18. doi:10.1016/j.apenergy.2017.10.036.
  • Lyng, K.-A., M. Bjerkestrand, A. E. Stensgård, P. Callewaert, and O. J. Hanssen. 2018. Optimising anaerobic digestion of manure resources at a regional level. Sustainability 10 (1). doi:10.3390/su10010286.
  • Mayerle, S. F., and J. de Figueiredo. 2016. Designing optimal supply chains for anaerobic bio-digestion/energy generation complexes with distributed small farm feedstock sourcing. Renewable Energy 90:46–54. doi:10.1016/j.renene.2015.12.022.
  • Misrol, M. A., S. R. W. Alwi, J. S. Lim, and Z. A. Manan. 2022. Biogas production from multiple feedstock at the district-level centralized facility for multiple end-use options: A case study in Johor Bahru, Malaysia. Clean Technologies and Environmental Policy 24 (1):315–32. doi:10.1007/s10098-021-02140-w.
  • Moher, D., A. Liberati, J. Tetzlaff, D. G. Altman, and Prisma Group. 2010. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. International Journal of Surgery 8 (5):336–41. doi:10.1016/j.ijsu.2010.02.007.
  • Muha, I., B. Linke, and G. Wittum. 2015. A dynamic model for calculating methane emissions from digestate based on co-digestion of animal manure and biogas crops in full scale German biogas plants. Bioresource Technology 178:350–58. doi:10.1016/j.biortech.2014.08.060.
  • Mula, J., D. Peidro, M. Díaz-Madroñero, and E. Vicens. 2010. Mathematical programming models for supply chain production and transport planning. European Journal of Operational Research 204 (3):377–90. doi:10.1016/j.ejor.2009.09.008.
  • Murillo-Alvarado, P. E., and J. M. Ponce-Ortega. 2022. An optimization approach to increase the human development index through a biogas supply chain in a developing region. Renewable Energy 190:347–57. doi:10.1016/j.renene.2022.02.076.
  • Nightingale, J. M., and G. Marshall. 2013. Reprint of “citation analysis as a measure of article quality, journal influence and individual researcher performance”. Nurse Education in Practice 13 (5):429–436. doi:10.1016/j.nepr.2013.02.005.
  • Nixon, J. D. 2016. Designing and optimising anaerobic digestion systems: A multi objective non-linear goal programming approach. Energy 114:814–22. doi:10.1016/j.energy.2016.08.053.
  • Obileke, K., S. Mamphweli, E. L. Meyer, G. Makaka, and N. Nwokolo. 2021. Development of a mathematical model and validation for methane production using cow dung as substrate in the underground biogas digester. Processes 9 (4):643. doi:10.3390/pr9040643.
  • Okushima, S. 2024. Measuring energy sufficiency: A state of being neither in energy poverty nor energy extravagance. Applied Energy 354:122161. doi:10.1016/j.apenergy.2023.122161.
  • Pagani, R., J. Kovaleski, and L. Resende. 2015. Methodi Ordinatio: A proposed methodology to select and rank relevant scientific papers encompassing the impact factor, number of citation, and year of publication. Scientometrics 105 (3):2109–35. doi:10.1007/s11192-015-1744-x.
  • Patrizio, P., and D. Chinese. 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 99:573–83. doi:10.1016/j.renene.2016.07.047.
  • Patrizio, P., S. Leduc, D. Chinese, E. Dotzauer, and F. Kraxner. 2015. Biomethane as transport fuel – a comparison with other biogas utilization pathways in northern Italy. Applied Energy 157:25–34. doi:10.1016/j.apenergy.2015.07.074.
  • Patrizio, P., S. Leduc, D. Chinese, and F. Kraxner. 2017. Internalizing the external costs of biogas supply chains in the Italian energy sector. Energy 125:85–96. doi:10.1016/j.energy.2017.01.033.
  • Poma, P., M. Usca, M. Polanco, T. Toulkeridis, and C. Mestanza-Ramón. 2021. Estimation of biogas generated in two landfills in south-central ecuador. Atmosphere 12 (10):1365. doi:10.3390/atmos12101365.
  • Raheman, H. 2002. A mathematical model for fixed dome type biogas plant. Energy 83 (JUN):10–15. https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036624946&partnerID=40&md5=329713dd7c3169075477b232af7077ca.
  • Rahimi, T., R. Babazadeh, and A. Doniavi. 2021. Designing and planning the animal waste-to-energy supply chains: A case study. Renewable Energy Focus 39:37–48. doi:10.1016/j.ref.2021.07.004.
  • Rosa, A. P., L. C. S. Lobato, and C. A. L. Chernicharo. 2020. Mathematical model to predict the energy potential of UASB-based sewage treatment plants. Brazilian Journal of Chemical Engineering 37 (1):73–87. doi:10.1007/s43153-020-00012-2.
  • Salvador, R., M. V. Barros, J. G. D. P. D. Rosário, C. M. Piekarski, L. M. da Luz, and A. C. de Francisco. 2019. Life cycle assessment of electricity from biogas: A systematic literature review. Environmental Progress & Sustainable Energy 38 (4). doi:10.1002/ep.13133.
  • Samer, M. 2010. A software program for planning and designing biogas plants. Transactions of the ASABE 53 (4):1277–85. https://www.scopus.com/inward/record.uri?eid=2-s2.0-77956457953&partnerID=40&md5=40ef8a641f16d5922fc069ee3270e65c.
  • Samer, M., K. Helmy, S. Morsy, T. Assal, Y. Amin, S. Mohamed, M. Maihoob, M. Khalil, I. Fouda, and A. Abdou. 2019. Cellphone application for computing biogas, methane and electrical energy production from different agricultural wastes. Computers and Electronics in Agriculture 163:163. doi:10.1016/j.compag.2019.104873.
  • Sarker, B. R., B. Wu, and K. P. Paudel. 2018. Optimal number and location of storage hubs and biogas production reactors in farmlands with allocation of multiple feedstocks. Applied Mathematical Modelling 55:447–65. doi:10.1016/j.apm.2017.11.010.
  • Sarker, B. R., B. Wu, and K. P. Paudel. 2019. Modeling and optimization of a supply chain of renewable biomass and biogas: Processing plant location. Applied Energy 239:343–55. doi:10.1016/j.apenergy.2019.01.216.
  • Sharara, M. A., M. Y. Owusu-Twum, T. M. Runge, and R. Larson. 2020. Planning methodology for anaerobic digestion systems on animal production facilities under uncertainty. Waste Management 104:262–69. doi:10.1016/j.wasman.2020.01.028.
  • Silva, S., L. Alçada-Almeida, and L. C. Dias. 2017. Multiobjective programming for sizing and locating biogas plants: A model and an application in a region of Portugal. Computers and Operations Research 83:189–98. doi:10.1016/j.cor.2017.02.016.
  • Silva, T. P., M. de Oliveira, J. M. M. Mourão, A. dos Santos, and E. L. Pereira. 2023. Monte Carlo-based model for estimating methane generation potential and electric energy recovery in swine wastewater treated in UASB systems. Journal of Water Process Engineering 51:103399. doi:10.1016/j.jwpe.2022.103399.
  • Silva-Gonzalez, J. A., I. O. H.-D. Lira, N. Balagurusamy, B. Juárez-López, G. A. Ruiz-Santoyo, A. Rodríguez-Martínez, A. Rodriguez-Martinez, G. A. Ruiz-Santoyo, B. Juarez-Lopez, N. Balagurusamy, et al. 2021. Design of a centralized bioenergy unit at Comarca Lagunera, Mexico: Modeling strategy to optimize bioenergy production and reduce methane emissions. Processes 9 (8):1350. doi:10.3390/pr9081350.
  • Singh, P. P., B. S. Ghuman, and N. S. Grewal. 1998. Computer model for performance prediction and optimization of unheated biogas plant. Energy Conversion and Management 39 (1–2):51–63. doi:10.1016/s0196-8904(96)00177-x.
  • Stuermer, B., E. Schmid, and M. W. Eder. 2011. Impacts of biogas plant performance factors on total substrate costs. Biomass & bioenergy 35 (4):1552–60. doi:10.1016/j.biombioe.2010.12.030.
  • Tampio, E., F. Pettersson, S. Rasi, and M. Tuomaala. 2022. Application of mathematical optimization to exploit regional nutrient recycling potential of biogas plant digestate. Waste Management 149:105–13. doi:10.1016/j.wasman.2022.06.013.
  • Uhlemair, H., I. Karschin, and J. Geldermann. 2014. Optimizing the production and distribution system of bioenergy villages. International Journal of Production Economics 147 (PART A):62–72. doi:10.1016/j.ijpe.2012.10.003.
  • Van Eck, N. J. and L. Waltman. 2010. Software survey: VOS viewer, a computer program for bibliometric mapping. Scientometrics 84 (2):523–38. doi:10.1007/s11192-009-0146-3.
  • Wang, D., Q. Duan, Y. Li, X. Tian, and S. Rahman. 2017. Simulation of a solar-biogas hybrid energy system for heating, fuel supply, and power generation. International Journal of Energy Research 41 (13):1914–31. doi:10.1002/er.3754.
  • Wattanasilp, C., R. Songprakorp, A. Nopharatana, and C. Khompatraporn. 2021. Techno-cost-benefit analysis of biogas production from industrial cassava starch wastewater in Thailand for optimal utilization with energy storage. Energies 14 (2):416. doi:10.3390/en14020416.
  • Wu, B., B. R. Sarker, and K. P. Paudel. 2015. Sustainable energy from biomass: Biomethane manufacturing plant location and distribution problem. Applied Energy 158:597–608. doi:10.1016/j.apenergy.2015.08.080.
  • Younessi, H. S., S. Bahramara, F. Adabi, and H. Golpîra. 2023. Modeling the optimal sizing problem of the biogas-based electrical generator in a livestock farm considering a gas storage tank and the anaerobic digester process under the uncertainty of cow dung. Energy 270:126876. doi:10.1016/j.energy.2023.126876.
  • Zirngast, K., L. Čuček, Ž. Zore, Z. Kravanja, and Z. N. Pintarič. 2019. Synthesis of flexible supply networks under uncertainty applied to biogas production. Computers & Chemical Engineering 129:106503. doi:10.1016/j.compchemeng.2019.06.028.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.