Biogas Production Modelling Based on a Semi-Continuous Feeding Operation in a Municipal Wastewater Treatment Plant

Anaerobic digestion is a common method for treating sewage sludge in municipal wastewater treatment plants (WWTPs). However, modelling this process can be very challenging due to the complexity of biochemical reactions. This paper presents a novel methodology that estimates biogas production from sewage sludge by considering the semi-continuous sludge-feeding process of the digester. In most WWTPs, the sewage sludge treatment operates in a dynamic process; therefore, using a time-dependent tool that represents this dynamic process is essential for accurately representing biogas production. The biogas production results from the proposed model are compared against the historical data for a large-scale WWTP located in Sydney, Australia. The proposed model shows great accuracy and follows the historical data trend very precisely. The average biogas production based on historical data for 2020, 2021, and 2022 was 37,337 m3/d, 31,695 m3/d, and 23,350 m3/d, whereas for the proposed model, it was 37,960 m3/d, 30,465 m3/d, and 23,080 m3/d. Over the three-year period, the average biogas production was 30,794 m3/d for historical data and 30,503 m3/d for the proposed model, which shows a great level of accuracy (R2 of 0.85 and average error of 4.64%) on the results of the proposed model and WWTP historical data.

Authors

Institutions

Publication Details

Journal
Energies
Published
2025-02-22
DOI
https://doi.org/10.3390/en18051065
Citations
5
Primary Topic
Wastewater Treatment and Nitrogen Removal
Type
article
Field-Weighted Citation Impact
2.52

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Biogas Production Modelling Based on a Semi-Continuous Feeding Operation in a Municipal Wastewater Treatment Plant

Gregory Appleby, Derick Lima, Li Li
5 citations
Energies
Wastewater Treatment and Nitrogen Removal
2.52
article

Biogas Production Modelling Based on a Semi-Continuous Feeding Operation in a Municipal Wastewater Treatment Plant

Gregory Appleby, Derick Lima, Li Li
article en
5 citations

Abstract

Anaerobic digestion is a common method for treating sewage sludge in municipal wastewater treatment plants (WWTPs). However, modelling this process can be very challenging due to the complexity of biochemical reactions. This paper presents a novel methodology that estimates biogas production from sewage sludge by considering the semi-continuous sludge-feeding process of the digester. In most WWTPs, the sewage sludge treatment operates in a dynamic process; therefore, using a time-dependent tool that represents this dynamic process is essential for accurately representing biogas production. The biogas production results from the proposed model are compared against the historical data for a large-scale WWTP located in Sydney, Australia. The proposed model shows great accuracy and follows the historical data trend very precisely. The average biogas production based on historical data for 2020, 2021, and 2022 was 37,337 m3/d, 31,695 m3/d, and 23,350 m3/d, whereas for the proposed model, it was 37,960 m3/d, 30,465 m3/d, and 23,080 m3/d. Over the three-year period, the average biogas production was 30,794 m3/d for historical data and 30,503 m3/d for the proposed model, which shows a great level of accuracy (R2 of 0.85 and average error of 4.64%) on the results of the proposed model and WWTP historical data.

EnergiesVol. 18(5)
University of Technology Sydney (AU), Sydney Water (AU)
University of Technology Sydney
Openalex Percentile: Top 12%
Wastewater Treatment and Nitrogen Removal
2.52
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.