This work presents an integrated method for the optimisation of a regional wood-energy supply network. The model is based on a scalar system that comprises a demand point (district heating plants (DHP)) and bio-energy sources (supply basin (SB)), each of which is related to a biomass terminal. The objective of optimisation is based on both technical-logistics and environmental parameters. An SB is defined by the anisotropic weighted Voronoi tessellation methodology. The parameters are then aggregated to a multi-objective analysis that includes the optimisation of variables and compromise programming approach. Results permit the identification of the best supply chain organisation and the determination of the agro-forest energy districts where rural policy and intervention could be applied. The model was tested in the province of Florence (central Italy) to depict efficient scenarios for the fuelling of DHPs.
Optimisation of the regional energy supply network: a multi-objective analysis in the province of Florence (Italy) / Bernetti I.; Sacchelli S.; Alampi Sottini V.; Marinelli N.; Marone E.; Menghini S.. - In: INTERNATIONAL JOURNAL OF SUSTAINABLE ENERGY. - ISSN 1478-646X. - ELETTRONICO. - 33:(2014), pp. 1076-1089. [10.1080/14786451.2013.811412]
Optimisation of the regional energy supply network: a multi-objective analysis in the province of Florence (Italy)
BERNETTI, IACOPO;SACCHELLI, SANDRO;ALAMPI SOTTINI, VERONICA;MARINELLI, NICOLA;MARONE, ENRICO;MENGHINI, SILVIO
2014
Abstract
This work presents an integrated method for the optimisation of a regional wood-energy supply network. The model is based on a scalar system that comprises a demand point (district heating plants (DHP)) and bio-energy sources (supply basin (SB)), each of which is related to a biomass terminal. The objective of optimisation is based on both technical-logistics and environmental parameters. An SB is defined by the anisotropic weighted Voronoi tessellation methodology. The parameters are then aggregated to a multi-objective analysis that includes the optimisation of variables and compromise programming approach. Results permit the identification of the best supply chain organisation and the determination of the agro-forest energy districts where rural policy and intervention could be applied. The model was tested in the province of Florence (central Italy) to depict efficient scenarios for the fuelling of DHPs.File | Dimensione | Formato | |
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