Data modelling tool for ALG-AD

A challenge when adopting new technology is being able to visualise the results expected and predict outcomes to justify the investment.

The ALG-AD team are working on a number of tools to help AD managers to make those difficult decisions around whether or not to implement ALG-AD on their sites.

This will include a data modelling tool which will take defined parameters such as geographical location, digestate properties (in terms of nitrogen and phosphorous), type of reactor system and algal strain information, and from this will predict biomass production.

The teams are now validating modelling predictions against actual data and working with colleagues to refine the model so it best reflects the needs of AD stakeholders.  “We are validating with a complex mine of information, gathered over months, and even years, and so the aim is for predicted biomass production from the model to accurately reflect results gathered over the course of the project,” said Claudio Fuentes Grünewald from Swansea University leading on the algal cultivation work-package.  

“Stakeholders are very interested in the technology, but the first questions are always around how much biomass can be grown, and how much will it be worth” said Nina Bailet from AC3A, leading on the long term rollout work-package within ALG-AD.

“This tool will allow us to answer such questions, and give stakeholders some real data to help them put together the business case for ALG-AD investment”

When considered with all the other Decision Support Tool (DST) information, being developed by Birmingham City University (BCU), it is hoped that stakeholders will be able to get enough information to implement this exciting technology.


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