This paper presents a new method for the planning of photovoltaic systems in the early architectural design. The method finds capacity and position of a photovoltaic system over the envelope of a building by means of optimization. The input consists in: geometry of the building, surrounding shadings, local weather, hourly electric demand, unitary costs of the system and benefits for the production of electricity (sold or self-consumed). In the input there are known values (e.g. PV installation costs [€/kWp] or present costs for the electricity [€/kWh]) and unknown ones (e.g. degradation rate [%/year], maintenance costs [€/kWp year] or discount rate [%/year]). The optimization is performed using the expected value out of a set of parametric scenarios generated by the unknown input values. The results show that, if capacity and position of the system are tailored on its aggregated electric demand, a large penetration of photovoltaic electricity is profitable at current prices without incentives or valorization from the grid. The optimization performed with an arbitrary set of electric storages shows how the presence of storage fosters a higher optimal capacity for the PV system. This method has the potential to hugely expand the installation of urban photovoltaic.

New method for the early design of BIPV with electric storage: a case study in northern Italy

G. Salvalai;ALBATICI, ROSSANO;
2019-01-01

Abstract

This paper presents a new method for the planning of photovoltaic systems in the early architectural design. The method finds capacity and position of a photovoltaic system over the envelope of a building by means of optimization. The input consists in: geometry of the building, surrounding shadings, local weather, hourly electric demand, unitary costs of the system and benefits for the production of electricity (sold or self-consumed). In the input there are known values (e.g. PV installation costs [€/kWp] or present costs for the electricity [€/kWh]) and unknown ones (e.g. degradation rate [%/year], maintenance costs [€/kWp year] or discount rate [%/year]). The optimization is performed using the expected value out of a set of parametric scenarios generated by the unknown input values. The results show that, if capacity and position of the system are tailored on its aggregated electric demand, a large penetration of photovoltaic electricity is profitable at current prices without incentives or valorization from the grid. The optimization performed with an arbitrary set of electric storages shows how the presence of storage fosters a higher optimal capacity for the PV system. This method has the potential to hugely expand the installation of urban photovoltaic.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1075703
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