Planning and developing the future Smart City is becoming mandatory due to the need of moving forward to a more sustainable society. To foster this transition an accurate simulation of energy production from renewable sources, such as Photovoltaic Panels (PV), is necessary to evaluate the impact on the grid. In this paper, we present a distributed infrastructure that simulates the PV production and evaluates the integration of such systems in the grid considering data provided by smart-meters. The proposed solution is able to model the behaviour of PV systems solution exploiting GIS representation of rooftops and real meteorological data. Finally, such information is used to feed a real-time distribution network simulator.

PVInGrid: A Distributed Infrastructure for evaluating the integration of Photovoltaic systems in Smart Grid / Bottaccioli, Lorenzo; Macii, Enrico; Patti, Edoardo; Estebsari, Abouzar; Pons, Enrico; Acquaviva, Andrea. - ELETTRONICO. - 499:(2017), pp. 316-324. (Intervento presentato al convegno 8th Advanced Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS 2017) tenutosi a Caprica (Lisbon), Portugal nel 03-05 May 2017) [10.1007/978-3-319-56077-9_31].

PVInGrid: A Distributed Infrastructure for evaluating the integration of Photovoltaic systems in Smart Grid

BOTTACCIOLI, LORENZO;MACII, Enrico;PATTI, EDOARDO;ESTEBSARI, ABOUZAR;PONS, ENRICO;ACQUAVIVA, ANDREA
2017

Abstract

Planning and developing the future Smart City is becoming mandatory due to the need of moving forward to a more sustainable society. To foster this transition an accurate simulation of energy production from renewable sources, such as Photovoltaic Panels (PV), is necessary to evaluate the impact on the grid. In this paper, we present a distributed infrastructure that simulates the PV production and evaluates the integration of such systems in the grid considering data provided by smart-meters. The proposed solution is able to model the behaviour of PV systems solution exploiting GIS representation of rooftops and real meteorological data. Finally, such information is used to feed a real-time distribution network simulator.
2017
978-331956076-2
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2669665