Minimizing carbon footprint of biomass energy supply chain in the Province of Florence

• Authors: Iacopo Bernetti , Christian Ciampi , Sandro Sacchelli
• Languages of publication: EN

Abstracts

EN

The paper presents an approach for optimal planning of biomass energy system based on carbon footprint minimization. A geographical spatial demand driven approach is applied to assess the feasible ways for transferring energy from renewable sources to district heating plants in the Province of Florence (Italy). The proposed approach has been developed on three levels. In the first one, the Province of Florence is partitioned into a number of Regional Energy Cluster (REC) using a multidimensional algorithm of regionalization called SKATER. The variables used in SKATER model are related in order to realize sustainable policy for forest and agriculture biomass productions. In the second step a geographical fuzzy multiple attribute decision making model was applied to the selection of biomass district heating localization. Finally, in the third step a georeferenced Mixed Integer Linear Programming model based on resourcesupply- demand structure for carbon-minimization energy planning has been applied.

Keywords

EN

carbon footprint; biomass; MILP; fuzzy MADM; regionalization; spatial analysis; GIS

• Publisher: Katedra Ekonometrii i Statystyki, Szkoła Główna Gospodarstwa Wiejskiego w Warszawie
• Journal: Metody Ilościowe w Badaniach Ekonomicznych
• Year: 2010
• Volume: 11
• Issue: 1
• Pages: 24-36

Dates

published

2010

Contributors

author

Iacopo Bernetti

• Department of Agricultural and Forest Economics, Engineering, Sciences and Technologies – University of Florence, Italy

author

Christian Ciampi

• Department of Agricultural and Forest Economics, Engineering, Sciences and Technologies – University of Florence, Italy

author

Sandro Sacchelli

• Department of Agricultural and Forest Economics, Engineering, Sciences and Technologies – University of Florence, Italy

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