Decision Support System for Anaerobic Digestion Optimal Feeding and Localization
Tagliabue, Alberto
Colombo, Simone
Manenti, Flavio
Bozzano, Giulia Luisa
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How to Cite

Tagliabue A., Colombo S., Manenti F., Bozzano G.L., 2021, Decision Support System for Anaerobic Digestion Optimal Feeding and Localization, Chemical Engineering Transactions, 86, 49-54.
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Abstract

In Italy, the extension and widespread cultural diversification find a strong ally in the energy of agricultural, zootechnical, and agro-industrial matrices through Anaerobic Digestion and in particular in "Co-digestion", a technique based on the joint use of different biomass which allows achieving higher energy yields respect to the simple digestion. To date, this technology is exploited to treat mainly zootechnical waste and energy crops, and in many agricultural cases this is an obligatory choice, as the availability of residual biomass is modest and it is composed almost exclusively by wastewater; therefore a not negligible extension of the company / extra-company Utilised Agricultural Area (UAA) for dedicated cultivation is often needed to improve yield and make the digestion economically sustainable.
In this context, the use of agro-industrial residues available in primary processing industries operating at "zero km" to the digestion plant would help the entire supply chain both from an economic, energetic and environmental point of view, as the energy content of by-products is often comparable or higher to that of energy crops.
The objective of this work is focused on the development of a decision support tool aimed at technical assistance for the installation of small, medium, and large-scale biogas plants. Efficient sizing, logistics, and operation of waste recovery plants require continuous and consistent waste feedstock supply. For this purpose, the strategic choice of the feed is provided through an optimization analysis based on the availability of residual biomass on a selectable territory; this allows to size the plant and locates it geographically exploiting a “Facility Location Problem “ approach and GIS technologies. The economic assessment of the technical optimal solution is made available to the user through the forecast of cash flows, taking into account both CapEx and Opex of the process. This analysis is then supported by the evaluation of Pay Back Time (PBT), Net Present Value (NPV), and other economic parameters. Moreover, national incentives have been taken into account in the evaluation.
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