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Different Regional Scenarios of Renewable Energies Analyzed with the Use of Analytic Network Process

Elena Comino
Dipartimenti di Ingegneria del Territorio dell’Ambiente e delle Geotecnologie – Politecnico di Torino, Torino, Italy

Vincenzo Riggio
Dipartimenti di Ingegneria del Territorio dell’Ambiente e delle Geotecnologie – Politecnico di Torino, Torino, Italy

Maurizio Rosso
Dipartimento di idraulica, trasporti e infrastrutture civili – Politecnico di Torino, Torino, Italy

Ladda ner artikelhttp://dx.doi.org/10.3384/ecp110573460

Ingår i: World Renewable Energy Congress - Sweden; 8-13 May; 2011; Linköping; Sweden

Linköping Electronic Conference Proceedings 57:59, s. 3460-3467

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Publicerad: 2011-11-03

ISBN: 978-91-7393-070-3

ISSN: 1650-3686 (tryckt), 1650-3740 (online)

Abstract

In March 2007 Europe Union fixed strong environmental objectives for all its members; and for the 2020 it will be required a reduction of 20% of energy consumption; a 20% quota of energy consumption obtained by renewables and a 20% reduction of greenhouse gases. The Piedmont Region administration lunched a roadmap either for the industrial side that for the civil one; but our Region has several territory scenario strongly linked with the geomorphology and many technical solutions can’t be used as a standard. With this work our aim is to make a comparison of the most used renewables technology in our territory like biomass; hydroelectric and photovoltaic with a multi-criteria analysis. The paper shows the application of Analytic Network Process (ANP); a multi-criteria technique; according to complex network; in order to select the most sustainable solution for the different scenario. The models enable all the elements of the decision process to be considered; namely technological factors; environmental aspects; economic costs and social impacts; and to compare them to find the best alternative. All the data used in the model are taken from public sources and the required elaboration were self-made.

Nyckelord

Multi-criteria analysis; Renewable energy; Analytic Network Process

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