Challenges (Oct 2022)
Efficient Methane Production from Anaerobic Digestion of Cow Dung: An Optimization Approach
Abstract
In the context of addressing the global challenge of facilitating a decision-making process based on methane production using a predictive model, the study seeks to evaluate the performance of a biogas digester in varying operating conditions for optimization purposes. One of the techniques for doing this is the application of constrained linear least-square optimization. This has been employed to optimize the input parameter with the corresponding measured desired response. The developed model was built from 430 measured data set points of all the predictors over an 18-day monitoring period with an interval of 30 min. The result showed that the difference between the optimized model and the general model output for methane production in the biogas digester was less than 4%. Hence, the performance of the model demonstrated a strong validity as the determination coefficient (R2) between the modeled, and optimized output was 0.968 for the volume of methane produced in the biogas digester. The obtained determination coefficient of the developed and optimized model suggests that the modeled value of the methane fits well with the measured value of methane for validation. Thus, from the test dataset, the optimized and modeled methane volume was reported as 28%. In this scenario, under the various operational parameters, an increase of 26.5% in methane was obtained when comparing the maximum volume of methane from the optimization process with the maximum methane volume (54.5%) produced in the real biogas digester. Interestingly, the biogas digester produced a maximum methane yield of 0.24 m3 and a methane composition of 60%. Evidently, methane yield was influenced by temperature as well as other meteorological factors in the developed model hence, these factors should be widely considered for sustainable biogas production.
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