A new computational modelling technique could help maximize the economic return on anaerobic digestion systems and other farm-based sustainable energy projects.
Anaerobic digestion is a natural process that uses microorganisms to break down biodegradable material, such as livestock manure, municipal wastewater solids and food waste, in the absence of oxygen. The methane extracted by the digestor could be used to power homes, while the organic fertilizer produced could be used to grow new crops.
“The renewable fuel generates economic premiums that provide an added revenue stream to poultry farms which increases economic sustainability,” Mahmoud Sharara, lead author of a paper on the work and an assistant professor of biological and agricultural engineering at North Carolina State University, said.
“More and more, environmentally sustainable technologies, like anaerobic digestion, are receiving payments and incentives to make them economically attractive and help align environmental and economic sustainability. This provides poultry facilities with more options to increase production sustainability.”
However, farm-based sustainability programs can be costly to implement and the profitability of a particular project can be difficult to product.
Accounting for uncertainty
In tests published in the journal Waste Management, the model accurately predicted where a sustainable energy project should be located, what its capacity should be and how large a geographic area it should serve in order to maximize the economic return. It can account for several factors, including the size, location and species of animals raised on a farm.
The computational model even accounts for uncertainty. For example, because the future sales price of electricity is unpredictable, the model uses historical data and market forecasts to estimate a price range.
The research team designed the model to simulate variations in uncertainty for different site locations, generating data that tells users which combinations of factors generates the largest profit.
“At the moment, the model can only be used on machines with access to optimization solvers, but we are pursuing a distributable version, or alternatively available as a web-based tool, to make it accessible to more users,” Sharara added.
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