An AI Agent for Techno-Economic Analysis of Anaerobic Co-Digestion in Renewable Energy Applications

Ruixi Gao, Das Li and Duo Zhang ()
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Ruixi Gao: INVESTAI LIMITED, Bristol BS16 7GQ, UK
Das Li: INVESTAI LIMITED, Bristol BS16 7GQ, UK
Duo Zhang: INVESTAI LIMITED, Bristol BS16 7GQ, UK

Energies, 2025, vol. 18, issue 21, 1-26

Abstract: The global transition to renewable energy has intensified the focus on anaerobic digestion (AD) as a sustainable solution for organic waste management and biogas production. This study presents a comprehensive techno-economic analysis (TEA) of AD systems integrated with carbon capture and digestate treatment technologies, evaluated across four distinct operational scenarios. The research leverages an innovative AI-agent framework to streamline TEA, enabling stakeholders to conduct sophisticated analyses without specialized expertise. Key findings reveal that feedstock composition significantly impacts biogas yields, with maize and rye blends (mix2) outperforming maize-dominated mixes (mix1), achieving higher biogas production (26,029 m 3 /y vs. 23,182 m 3 /y). Membrane-based CO 2 separation and liquefaction technologies demonstrated superior economic viability compared to cryogenic methods, yielding lower energy consumption (2400 MWh/y vs. 3000 MWh/y) and higher net revenues (GBP 4.0 million/y vs. GBP 3.5 million/y). Financial metrics further underscored the advantages of membrane-based systems, with the mix2 configuration achieving a net present value (NPV) of GBP 19 million and an internal rate of return (IRR) of 36%, alongside a shorter payback period (3 years). Sensitivity analysis highlighted natural gas prices and tax rates as critical determinants of economic performance, while water costs had negligible impact. The study also evaluated digestate treatment methods, finding that base-case separation outperformed torrefaction in financial returns.

Keywords: AI-agent; anaerobic digestion (AD); techno-economic analysis (TEA) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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