Related Experiment Video
Updated: Jul 6, 2026
11:31
Continuously-stirred Anaerobic Digester to Convert Organic Wastes into Biogas: System Setup and Basic Operation
Published on: July 13, 2012
34.3K
Modeling and Simulation of Biogas Production in Full Scale with Time Series Analysis.
Celina Dittmer1, Johannes Krümpel1, Andreas Lemmer1
1State Institute of Agricultural Engineering and Bioenergy, University of Hohenheim, Garbenstrasse 9, 70599 Stuttgart, Germany.
Microorganisms
|February 10, 2021
Summary
This study presents a new biogas production simulation model using time series analysis. It accurately predicts biogas output based on historical data, enabling demand-driven biogas production.
Area of Science:
- Biotechnology
- Chemical Engineering
- Environmental Science
Background:
- Biogas production requires proactive feeding management for demand-driven output.
- Existing models like Anaerobic Digestion Model No. 1 (ADM1) are complex and parameter-dependent.
- Lack of reliable monitoring hinders ADM1 parameter adjustment in full-scale plants.
Purpose of the Study:
- To develop a simplified simulation model for biogas production.
- To enable proactive feeding management in biogas plants.
- To overcome limitations of complex models in real-world applications.
Main Methods:
- Utilized time series analysis based on historical biogas production and substrate supply data.
- Developed a model independent of individual substrate differentiation.
- Evaluated model performance using 366 simulations with a 48-hour horizon across two digesters.
Main Results:
- Achieved a mean absolute percentage error (MAPE) of 14-18% in biogas production prediction.
- Demonstrated the model's self-learning and adaptive capabilities.
- Confirmed model applicability regardless of substrate composition.
Conclusions:
- The developed time series model offers a practical approach for demand-driven biogas production.
- The model's adaptability makes it suitable for various full-scale biogas plant applications.
- Simplified simulation enhances operational efficiency and proactive management in biogas facilities.
