## 3 Results
#### 3.1.2 Light-Duty Vehicle Transport Sector  
The electrification of the entire LDV fleet through BEVs would result in remarkable changes of the total grid demand (power and profile), as Figure 5a depicts. The expected charging profile in the island, in which overnight charging events prevail over daily and/or opportunistic ones, does modify the grid valley period, increasing the demand from approximately 400 to 600 MW. The average contribution of dispatchable sources (mainly gas turbines fuelled with H\({}_{2}\)) during the overnight period is 12%, which means that a considerable amount of the LDV transportation demand would be covered through the Power-to-H\({}_{2}\)-to-Power path. Although this route would enable zero CO\({}_{2}\) tailpipe  
Figure 4: Operation of the decarbonised grid system response with no transport demand considered: representative week with large (**a**,**c**,**e**) and limited (**b**,**d**,**f**) WE resources. limited by grid/vehicle connection capacity. A value of 351 MW was employed, assuming that 2 kW of charging infrastructure was available per vehicle (the current ratio in Europe is 1 kW/vehicle) [66]. EnergyPLAN allows power injection from vehicles to replace conventional generation if enough energy is available in batteries. The amount of power is, again, capped by the grid/vehicle connection capacity. Table 7 summarises the input parameters employed to simulate the smart charging functionality in EnergyPLAN. Figure 5b,c exemplify the operation of the G2V/V2G functionality and the resulting load profile derived from its potential deployment. In the events of large RE generation (first three days), the grid enables significant charging (G2V) loads, increasing the direct contribution of RE to cover the vehicle demand, reducing the energy spilled and the grid stress at peak hours. The bidirectional power flow can also be observed in those days, with electrical vehicles providing power to the grid while they are parked (V2G) at night-time. The opposite behaviour can be observed in the next three days, with limited RE generation and, therefore, G2V capacity practically restricted to cover the daily vehicle demand. As the reader can expect, the power-generation structure that provided the annual results previously shown in Table 6 is insufficient to cope with the additional LDV fleet demand. Further contribution of dispatchable sources (H\({}_{2}\) turbines) will be required, which means more H\({}_{2}\) production requirements and, therefore, more electricity to feed the electrolysers. This behaviour turns into a snowball effect, preventing both sectors to meet the goals of decarbonisation with an autonomous energy supply. In order to provide an estimation of the additional resources required to cope with the demand, the RE power and energy storage capacities were increased based on the following criteria:  
1. For the sake of consistency with local government planning, the PV/WE ratio was kept constant. 2. Due to space constraints, the on-shore WE capacity was capped at 1700 MW, as previous reports suggest [46]. 3. User-based EES was increased according to PV self-consumption growth. 4. Large-scale EES limits were set to 5.2 GWh, based on the estimations carried out by the local government [44]. 5. A maximum curtailment level of 30% was considered to set the distributed EES capacity growth. Table 8 includes the RE structure evolution required to extend the decarbonisation and autonomous supply targets to the LDV sector. An additional 1400 MW of RE capacity will be required (33% increase) to support a fully electric LDV fleet. To put these figure into context, the required additional capacity exceeds 3.9 times the current RE installed in the island. The deployment of additional capacity of non-dispatchable energy sources brings along new requirements for EES capacity, as Table 8 illustrate. Simulation results point out that 1 GWh of EES, located at user and distributed levels, must be installed to avoid excessive curtailment levels.