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Introducing a stochastic decision support tool for anaerobic digestion projects

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Blog picture: Introducing a stochastic decision support tool for anaerobic digestion projects

Anaerobic digestion (AD) is a process by which micro-organisms break down biodegradable material in the absence of oxygen, leading to the production of biogas and bio-fertilisers. AD technologies convert the methane in biogas into (renewable) electricity and heat energy with a low carbon footprint.

To further its goal towards a low carbon economy and to keep its commitment to renewable energy targets, the UK and its devolved parliaments have introduced a number of policies designed to incentivise investments in AD projects. Among these are policies aimed at enhancing AD economics (e.g. feed-in-tariffs, renewable heat incentives, renewable obligation certificates, levy exemption certificates, etc.); and policies aimed at channelling the potential of biodegradable waste for low carbon renewable energy production (e.g. landfill ban for biodegradable waste, ban on macerators, legislation requiring separate food waste collections, etc.). Together, these policies have created opportunities for the AD industry in the UK which has experienced substantial growth over the past decade, from under 20 AD plants in 2006 to over 120 in 2016.

In March last year, my colleagues and I initiated a research project to examine the economics of an AD plant on The James Hutton Institute’s Hartwood farm. My role in the project was to develop the economic model to that goal. In the first instance, I looked at the bespoke freely available decision support tools for AD economics and was disappointed to find that there were few solutions available and all had important limitations. In particular, all of the ones I found used a deterministic approach in line with most studies on AD economics. The problem with a deterministic approach however is that it typically uses a single value for particular inputs whereas we know that in the real world key values can fluctuate. For example, according to researchers Philip Lusk and Andrew Wiselogel,methane content in biogas from AD processes can vary between 55% and 80%. A stochastic approach can take this into account by allowing multiple simulated cases of a single AD project to be calibrated. Different values based on a probability distribution of the values in the range can then be considered making the analysis more useful to potential investors and policymakers.

I thought a gap existed to introduce a robust and freely accessible stochastic AD decision support tool for farmers, private firms, academics and policy makers to guide investment decisions for AD projects and/or explore policy options for the industry. With funding from the Macaulay Development Trust, I set out to develop SADEAT (Stochastic Anaerobic Digestion Economic Assessment Tool). SADEAT is not another simple spreadsheet tool. I wrote it using MATLAB software, utilising an advanced user friendly interface. Underlying SADEAT are 4 economic models, each outputting an indicator of the economics of a user specified AD project. The four indicators are (1) net present value, (2) modified internal rate of return, (3) breakeven electricity price and (4) breakeven heat price. SADEAT is freely available here and is compatible for installation on Windows computers (see the associated SADEAT user guide for further details; also see a dedicated James Hutton Institute page for SADEAT here).  It is available under the GNU General Public Licence so please be aware of the terms.

Every effort has been made to ensure that SADEAT is user-friendly and free of errors. However, if you have suggestions about how SADEAT may be improved, or if you have found a bug, then please contact me at yakubu.abdul-salam@hutton.ac.ukor yaksamash@hotmail.com.  Inclusion of the effects of rents from greenhouse gas credits and/or sale of bio-fertilisers in the economics of AD projects are the subject of current work for incorporation in future versions of SADEAT so please watch out.

Disclaimer: The views expressed in this blog post are the views of the author(s), and not an official position of the institute or funder.

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Printed from /blogs/introducing-stochastic-decision-support-tool-anaerobic-digestion-projects on 28/02/24 08:08:53 PM

The James Hutton Research Institute is the result of the merger in April 2011 of MLURI and SCRI. This merger formed a new powerhouse for research into food, land use, and climate change.