Anaerobic Digestion and Biogas Potential: Simulation of Lab and Industrial-Scale Processes

Article, Other literature type OPEN
Ihsan Hamawand ; Craig Baillie (2015)
  • Publisher: MDPI AG
  • Journal: Energies, volume 8, issue 1 1, pages 1-21 (issn: 1996-1073)
  • Related identifiers: doi: 10.3390/en8010454
  • Subject: wastewater | BioWin | meat industry | simulation | biogas | anaerobic digestion (AD) | Technology | T | wastewater; anaerobic digestion (AD); biogas; BioWin; meat industry; simulation
    • jel: jel:Q0 | jel:Q | jel:Q4 | jel:Q47 | jel:Q49 | jel:Q48 | jel:Q43 | jel:Q42 | jel:Q41 | jel:Q40

In this study, a simulation was carried out using BioWin 3.1 to test the capability of the software to predict the biogas potential for two different anaerobic systems. The two scenarios included: (1) a laboratory-scale batch reactor; and (2) an industrial-scale anaerobic continuous lagoon digester. The measured data related to the operating conditions, the reactor design parameters and the chemical properties of influent wastewater were entered into BioWin. A sensitivity analysis was carried out to identify the sensitivity of the most important default parameters in the software’s models. BioWin was then calibrated by matching the predicted data with measured data and used to simulate other parameters that were unmeasured or deemed uncertain. In addition, statistical analyses were carried out using evaluation indices, such as the coefficient of determination ( R -squared), the correlation coefficient ( r ) and its significance ( p -value), the general standard deviation ( SD ) and the Willmott index of agreement, to evaluate the agreement between the software prediction and the measured data. The results have shown that after calibration, BioWin can be used reliably to simulate both small-scale batch reactors and industrial-scale digesters with a mean absolute percentage error (MAPE) of less than 10% and very good values of the indexes. Furthermore, by changing the default parameters in BioWin, which is a way of calibrating the models in the software, as well, this may provide information about the performance of the digester. Furthermore, the results of this study showed there may be an over estimation for biogas generated from industrial-scale digesters. More sophisticated analytical devices may be required for reliable measurements of biogas quality and quantity.
  • References (31)
    31 references, page 1 of 4

    1. Igoni, A.H.; Ayotamuno, M.J.; Eze, C.L.; Ogaji, S.O.T.; Probert, S.D. Designs of anaerobic 2.

    digesters for producing biogas from municipal solid-waste. Appl. Energy 2008, 85, 430-438.

    Bruni, E.; Jensen, A.P.; Pedersen, E.S.; Angelidaki, I. Anaerobic digestion of maize focusing on variety, harvest time and pretreatment. Appl. Energy 2010, 87, 2212-2217.

    Renew. Sustain. Energy Rev. 2013, 22, 550-560.

    7. McCabe, B.; Hamawand, I.; Baillie, C. Investigating wastewater modelling as a tool to predict anaerobic decomposition and biogas yield of abattoir effluent. J. Environ. Chem. Eng. 2013, 1, 1375-1379.

    8. McCabe, B.; Hamawand, I.; Peter, H.; Baillie, C.; Yusaf, T. A case study for biogas generation from covered anaerobic ponds treating abattoir wastewater: Investigation of pond performance and potential biogas production. Appl. Energy 2014, 114, 798-808.

    9. Petruy, R.; Lettinga, G. Digestion of a milk-fat emulsion. Bioresour. Technol. 1997, 61, 141-149.

    10. Green, J. Effluent Treatment Ponds; CSIRO Meat Research Laboratoy: Melbourne, Australia, 1990.

    11. UNSW-CRC for Waste Management & Pollution Control. Treatment of Abattoir Wastewater Using a Covered Anaerobic Lagoon; Meat &Livestock Australia Limited MLA: Sydney, Australia, 1998.

    12. Lidholm, O.; Ossiansson, E. Modeling Anaerobic Digestion-Validation and Calibration of the Siegrist Model with Uncertainty and Sensitivity Analysis. Master's Thesis, Lunds University, Lund, Sweden, 2008.

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