Name
AI-driven optimisation of anaerobic digestion: enhancing efficiency, feedstock strategy, and system integration
Description
Artificial intelligence (AI) and digitalisation are rapidly transforming anaerobic digestion (AD) from a reactive process into an optimised, integrated energy system. This presentation demonstrates how AI-driven tools are enhancing operational efficiency, enabling strategic co-digestion, and supporting system-level integration across the biogas value chain.
Drawing on research from the University of Surrey AI4AD EPSRC research group and commercial deployment through BiofuelAI, the session will show how real-time process optimisation improves plant stability and performance, while predictive feedstock selection and blending maximise biogas yields. Beyond the plant, AI enables forecasting of production and demand, supporting smart grid integration and load balancing across distributed assets.
A key focus is the role of digital platforms in enabling vertical integration—from feedstock supply through to fuel end-use—improving coordination, visibility, and value capture across the entire system.
Case studies will highlight measurable improvements in operational efficiency, yield consistency, and decision-making. The presentation will demonstrate how these approaches are enabling more resilient, flexible, and commercially viable biogas systems, positioning AD as a core component of the future renewable energy landscape.
Authors
Alan Beesley, Biofuel Ai ltd, UK
Michael Short and Ruosi Zhang, University of Surrey, UK
Benaissa Dekhici and Rohit Murali, Biofuel AI, UK
Michael Short and Ruosi Zhang, University of Surrey, UK
Benaissa Dekhici and Rohit Murali, Biofuel AI, UK