Vol. 66 No. 4 (2011):
Special section

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

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  • Iacopo Bernetti,
  • Christian Ciampi,
  • Sandro Sacchelli
Iacopo Bernetti
Department of Agricultural and Forest economics, engineering, Sciences and Technologies - University of Florence, P.le delle Cascine 18, 50144 Florence, Italy
Christian Ciampi
Department of Agricultural and Forest economics, engineering, Sciences and Technologies - University of Florence, P.le delle Cascine 18, 50144 Florence, Italy
Sandro Sacchelli
Department of Agricultural and Forest economics, engineering, Sciences and Technologies - University of Florence, P.le delle Cascine 18, 50144 Florence, Italy
DOI: https://doi.org/10.4129/ifm.2011.4.06

Published 2011-08-30

Keywords

  • carbon footprint,
  • biomass,
  • MILP,
  • fuzzy MADM,
  • regionalization

Copyright (c) 2011 Italian Journal of Forest and Mountain Environments

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Abstract

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 geo-referenced Mixed Integer Linear Programming model based on resource-supply-demand structure for carbon-minimization energy planning has been applied.

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