The solar energy source is characterized by unpredictability and an intermittent behaviour which must be faced using accurate forecasting tools. In the present paper an optimization algorithm is used to assess the possible impact of the vehicle to grid (V2G) technology to minimize solar photovoltaic (PV) uncertainties due to forecasting inaccuracies. In particular, forecasted values from the PVGIS database are compared with actual measurements from the Savona Campus facility and the exploitation of the V2G technology to mitigate discrepancies between the two datasets is investigated. Results show the impact of the initial state of charge (SOC) of the electrical vehicles (EVs) at the beginning of the day on the capability of balancing either the overestimation or the underestimation of the PV production. Moreover, a great influence is given by the number of involved EVs and the charging/discharging power limits of the charging stations.
Scheda prodotto non validato
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo
|Titolo:||V2G technology to mitigate PV uncertainties|
|Data di pubblicazione:||2020|
|Appare nelle tipologie:||04.01 - Contributo in atti di convegno|