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S15: Renewable resources use for energy production

Page: Main.S15 - Last Modified : Sun, 29 Jun 08

Main.S15 History

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Giulia Fiorese, Politecnico di Milano, Dept. of Electronics and Information, Milan, Italy
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Giorgio Guariso - EMS, Politecnico di Milano, Department of Electronics and Information, Milan, Italy
Riccardo Minciardi - Department of Communication, Computer and System Sciences, University of Genova, Italy; CIMA, Interuniversity Center of Research in Environmental Monitoring, Savona, Italy
Roberto Sacile - Department of Communication, Computer and System Sciences, University of Genova, Italy; CIMA, Interuniversity Center of Research in Environmental Monitoring, Savona, Italy
Michela Robba - Department of Communication, Computer and System Sciences, University of Genova, Italy; CIMA, Interuniversity Center of Research in Environmental Monitoring, Savona, Italy (contact: michela.robba@unige.it)
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Giorgio Guariso, Politecnico di Milano, Dept. of Electronics and Information, Milan, Italy
Riccardo Minciardi, Dept. of Communication, Computer and System Sciences, University of Genova, Italy; CIMA, Interuniversity Center of Research in Environmental Monitoring, Savona, Italy
Roberto Sacile, Dept. of Communication, Computer and System Sciences, University of Genova, Italy; CIMA, Interuniversity Center of Research in Environmental Monitoring, Savona, Italy
Michela Robba, Dept. of Communication, Computer and System Sciences, University of Genova, Italy; CIMA, Interuniversity Center of Research in Environmental Monitoring, Savona, Italy (contact: michela.robba@unige.it)
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Giorgio Guariso - EMS, Politecnico di Milano, Department of Electronics and Information, Milan, Italy (contact: michela.robba@unige.it)
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Giorgio Guariso - EMS, Politecnico di Milano, Department of Electronics and Information, Milan, Italy
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Michela Robba - Department of Communication, Computer and System Sciences, University of Genova, Italy; CIMA, Interuniversity Center of Research in Environmental Monitoring, Savona, Italy

Description

Renewable energy sources (RES) play a key role in the current European Union (EU) strategies to mitigate the impacts of global warming. Their exploitation is important for the attainment of different goals like the reduction of greenhouse gas emission, the partial replacement of fossil fuels, the reduction of external energies supply, and the respect of the obligations assumed in the Kyoto Conference of (1997). Biomass exploitation for energy production requires the effective design, planning and management of the related biomass supply-chain (BSC), including the optimization of the logistics operations, the ability to combine economically appealing and environmentally sustainable strategies, as well as the participation in the decisions of the key actors and stakeholders of the territory. EDSS are considered since years to be effective tools for the environmental planning and management of natural resources (Matthies et al., 2007; Soncini-Sessa et al., 2003; Rizzoli and Young, 1997). In the recent literature, they have been applied to renewable energies problems, and in particular biomass use as well as the optimization of the overall supply chain. Noon (1996), for instance, proposed a GIS-based EDSS to assist the Tennessee Valley Authority in estimating the costs for supplying wood fuel to its 12 coal-fired power plants, to analyze efficiently the transportation network and estimate distances and costs. A GIS-based EDSS to estimate the power production potential of agricultural residues was developed by Voivontas et al (2001). That analysis handled all possible restrictions and identified candidate power plants using an iterative procedure that locates bioenergy units and establishes the required cultivated area for biomass collection. Electricity production cost constituted the criterion for the identification of the sites where biomass potential can be economically exploited. As regards decision models, Nagel (2000) presented a methodology to allow biomass management for energy supply at a regional level. This methodology, which was tested in the German state of Brandenburg, dealt with many aspects like the dimensions and typology of heating plants, the sensitivity of the decision with respect to fuel costs, and the reduction of carbon emissions. More recently, another GIS-based EDSS for forest biomass exploitation at regional level has been presented by Freppaz et al. (2004). The aim of the proposed session is to focus on the state-of-the-art specific models and methods in the field of renewable energy.

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Michela Robba - Department of Communication, Computer and System Sciences, University of Genova, Italy; CIMA, Interuniversity Center of Research in Environmental Monitoring, Savona, Italy (contact: michela.robba@unige.it)
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Description

Renewable energy sources (RES) play a key role in the current European Union (EU) strategies to mitigate the impacts of global warming. Their exploitation is important for the attainment of different goals like the reduction of greenhouse gas emission, the partial replacement of fossil fuels, the reduction of external energies supply, and the respect of the obligations assumed in the Kyoto Conference of (1997). Biomass exploitation for energy production requires the effective design, planning and management of the related biomass supply-chain (BSC), including the optimization of the logistics operations, the ability to combine economically appealing and environmentally sustainable strategies, as well as the participation in the decisions of the key actors and stakeholders of the territory. EDSS are considered since years to be effective tools for the environmental planning and management of natural resources (Matthies et al., 2007; Soncini-Sessa et al., 2003; Rizzoli and Young, 1997). In the recent literature, they have been applied to renewable energies problems, and in particular biomass use as well as the optimization of the overall supply chain. Noon (1996), for instance, proposed a GIS-based EDSS to assist the Tennessee Valley Authority in estimating the costs for supplying wood fuel to its 12 coal-fired power plants, to analyze efficiently the transportation network and estimate distances and costs. A GIS-based EDSS to estimate the power production potential of agricultural residues was developed by Voivontas et al (2001). That analysis handled all possible restrictions and identified candidate power plants using an iterative procedure that locates bioenergy units and establishes the required cultivated area for biomass collection. Electricity production cost constituted the criterion for the identification of the sites where biomass potential can be economically exploited. As regards decision models, Nagel (2000) presented a methodology to allow biomass management for energy supply at a regional level. This methodology, which was tested in the German state of Brandenburg, dealt with many aspects like the dimensions and typology of heating plants, the sensitivity of the decision with respect to fuel costs, and the reduction of carbon emissions. More recently, another GIS-based EDSS for forest biomass exploitation at regional level has been presented by Freppaz et al. (2004). The aim of the proposed session is to focus on the state-of-the-art specific models and methods in the field of renewable energy.

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