Abstract
Energy efficiency measures in buildings can provide for a significant reduction of greenhouse gas (GHG) emissions. A sustainable design and planning of technologies for energy production should be based on economic and environmental criteria. Life Cycle Assessment (LCA) is used to quantify the environmental impacts over the whole cycle of life of production plants. Optimization models can support decisions that minimize costs and negative impacts. In this work, a multi-objective decision problem is formalized that takes into account LCA calculations and that minimizes costs and GHG emissions for general buildings. A decision support system (DSS) is applied to a real case study in the Northern Italy, highlighting the advantage provided by the installation of renewable energy. Moreover, a comparison among different optimal and non optimal solution was carried out to demonstrate the effectiveness of the proposed DSS.
Highlights
The overall increment in wellbeing and the increasing use of technology are leading western countries to an expansion in terms of energy demand and production [1]
Each of the previously discussed technologies has been analyzed from a life cycle costing (LCC) perspective, in order to assess the financial burden during the life cycle of each one of them
The results highlighted by the two different optimization runs suggest similar choices of technologies that use renewable resources
Summary
The overall increment in wellbeing and the increasing use of technology are leading western countries to an expansion in terms of energy demand and production [1]. The cost scaling law, reported in Equation (1) [42] is used to scale the considered process for the considered turbine life cycle. This method has already been used by other studies [43] to scale the inventory data from a bigger turbine to a desired size: C2 “ C1 ˆ p X2 b q X1 (1). Ecoinvent 2.2 database [38], even if an update of the energy mix has been applied, taking into account data from Terna, for 2013 (Terna is the company that manages the Italian electric network [47]).
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