Kinetic modeling and optimization of biogas production from maize silage for sustainable energy systems

 Kinetic Modeling and Optimization of Biogas Production from Maize Silage: Paving the Way for Sustainable Energy Systems

The global push towards clean and sustainable energy sources has intensified interest in biogas as a renewable alternative to fossil fuels. One promising substrate for biogas production is maize silage, a readily available agricultural resource rich in biodegradable organic matter. To maximize the efficiency and scalability of biogas systems, researchers have turned to kinetic modeling and optimization techniques.

Kinetic models such as the first-order kinetics, modified Gompertz model, and ADM1 (Anaerobic Digestion Model No.1) are widely used to predict the biogas yield and understand the dynamic behavior of the digestion process. These models help identify rate-limiting steps, optimal retention times, and the influence of process parameters like temperature, pH, and substrate concentration.

Optimization through response surface methodology (RSM), genetic algorithms (GA), or artificial neural networks (ANN) further enhances process performance. These techniques support the development of automated and adaptive control systems, ensuring maximum methane production while minimizing energy input and system costs.

Utilizing maize silage in biogas systems not only addresses agricultural waste management but also contributes to the circular bioeconomy, GHG reduction, and energy independence. By integrating kinetic modeling and optimization, we take a significant step toward a greener, more resilient energy future.

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