In this paper, a methodology is proposed to evaluate the impact on the Italian electric power system deriving from the increasing adoption of Battery Electric Vehicles (BEVs). To this purpose, a case study that involves the Lombardy region in a 2030 scenario is analyzed. To accurately estimate travel habits within the region, datasets publicly available were used, complementing them with suitable energetic models of BEVs. Detailed data about the journeys traveled by commuters in the region, distinguished by reason to move and modes of transport, were provided in input to an online routing machine to extract significant information about the vehicle’s instantaneous speed, length, and duration of each trip. This allowed for an accurate assessment of the energy and power requirements of private electric mobility in a 2030 scenario. The quantities in output to the analysis can be effectively used by transmission and distribution network operators to identify the issues that could arise on the grid due to increased demand related to electric vehicles. In addition, these analyses can support the proper design and planning of all the reinforcement actions needed on the electrical grid to improve its capability to supply the energy and power required during the charging processes.
IMPACT OF GREEN MOBILITY ON THE ELECTRIC POWER SYSTEM: A NUMERICAL ANALYSIS IN A 2030 SCENARIO
Falabretti D.;Gulotta F.;
2025-01-01
Abstract
In this paper, a methodology is proposed to evaluate the impact on the Italian electric power system deriving from the increasing adoption of Battery Electric Vehicles (BEVs). To this purpose, a case study that involves the Lombardy region in a 2030 scenario is analyzed. To accurately estimate travel habits within the region, datasets publicly available were used, complementing them with suitable energetic models of BEVs. Detailed data about the journeys traveled by commuters in the region, distinguished by reason to move and modes of transport, were provided in input to an online routing machine to extract significant information about the vehicle’s instantaneous speed, length, and duration of each trip. This allowed for an accurate assessment of the energy and power requirements of private electric mobility in a 2030 scenario. The quantities in output to the analysis can be effectively used by transmission and distribution network operators to identify the issues that could arise on the grid due to increased demand related to electric vehicles. In addition, these analyses can support the proper design and planning of all the reinforcement actions needed on the electrical grid to improve its capability to supply the energy and power required during the charging processes.| File | Dimensione | Formato | |
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