Abstract
Over the past six years, biogas production in Italy has experienced an economic boom: investments of more than 4.5 billion euros and production of about 2 billion normal m2 of natural gas equivalent. By contrast, biomethane production in Italy is not widespread. This limited spread substantially results from the lack of effective government incentives for biomethane production. In the near future, the Italian government is expected to fix new feed-in tariff (FIT) schemes for energy production from renewable energy sources (RES). In this context, it is fundamental for the policy maker to determine whether it will be preferable to introduce more generous FITs to support biogas production for electric-power generation or biomethane production through biogas upgrading. In this paper, we propose a multicriteria decision model to support the policy maker in the definition of sustainable development policies for biogas and biomethane production. Specifically we provide an Analytic Hierarchy Process (AHP) model to multicriteria prioritization of incentives paid to biogas versus biomethane. In accord with group decision-making approaches, we selected a pool of experts that structured the decision problem and disaggregated it into a hierarchy by identifying quantitative and qualitative criteria and subcriteria to evaluate each technology. The model results reveal that biomethane production plants are preferred to biogas production plants, independently of their size, whereas larger biomethane installations are ranked higher than smaller ones. Under stringent public budget constraints, it might be de facto inefficient and not cost-effective to introduce incentive mechanisms for biogas-production plants.
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Banzato, D., Canesi, R., D’Alpaos, C. (2018). Biogas and Biomethane Technologies: An AHP Model to Support the Policy Maker in Incentive Design in Italy. In: Bisello, A., Vettorato, D., Laconte, P., Costa, S. (eds) Smart and Sustainable Planning for Cities and Regions. SSPCR 2017. Green Energy and Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-75774-2_22
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