# Impact of the Integration of the Electric Vehicle on Low-Voltage Rural Networks
## 3 Methodology
### Definition of Scenarios  
The network described in Section 3.1 corresponds to the current situation of the grid, which has been called \"Scenario 0\". As the work aims to study the effects of the integration of EVs in the grid, the expectations regarding the number of electric vehicles and chargers in the region have been considered to define what has been called \"Scenario 1\".  
In Spain, on 3 November 2020, the Council of Ministers approved the 'Estrategia a Largo Plazo para una Economia Espanola Moderna, Competitiva y Ambientalmente Neutral en 2050' (ELP 2050), a document that outlines the roadmap to achieve climate neutrality by 2050. The ELP 2050 guides in attaining the proposed objectives specified for each decade in the 'Plan National Integrado de Energa y Clima' (PNIEC) [17]. PNIEC aims at achieving electrification (100%) in the road transport sector by 2050 and sets a goal for Spain to deploy 5.5 million electric vehicles (EV) by 2030. According to the 2022 report of the Spanish Association of Automobile and Truck Manufacters (ANFAC) [60], the Spanish fleet totaled over 30.2 million vehicles, of which 25.6 million were passenger cars, accounting for approximately 84.8%. Extrapolating vehicle registration data from the historical series provided by ANFAC, it can be considered that by 2030, there will be around 32.8 million vehicles, with 27.7 million being passenger cars. According to this proportion, of the 5.5 million electric vehicles projected by the PNIEC for 2030, slightly more than 4.2 million will be passenger cars, representing (15.2%) of the total passenger cars. Using the statistical data from the Spanish National Institute of Statistics (INE), Spain is expected to have around 50.5 million inhabitants in 2030, resulting in a passenger car motorization rate of nearly 550 cars per 1000 inhabitants. Based on an analysis of the town's characteristics, including its average size and a stable population of 1200 inhabitants, the number of vehicles in the area is expected to mirror the national average. By 2030, it is projected that there will be approximately 660 vehicles, of which 100 are estimated to be electric. These projections rely on assumptions of demographic stability and do not encompass possible changes in transportation patterns or social dynamics. According to INE data, about 26%of the vehicles in the Aragon region are parked on the street. Consequently, only 74% of the vehicles would have access to private charging facilities at their residences. Given that not all cars require daily charging, and according to the experience of the distribution company, which provided the network data, we have assumed that only 75% of the drivers available to charge at home do so regularly, so only 56 vehicles will require daily charging upon returning home.  
The charging profiles of electric vehicles have been chosen considering only weekdays for the sake of simplicity. The profiles have been defined considering different charge starting times and charging states. The starting times range between 18:30 and 20:00, as they are the typical arrival times at homes in Spain. Regarding the charging states, five different load profiles have been defined for 65%, 56%, 47%, 39% and 29% of the maximum load when the charge starts. Each vehicle connected to a charging point has been randomly assigned one of these five charging states. Figure 2b shows the used charging profiles.  
Once the two base scenarios, Scenario 0 without EVs and Scenario 1 with EVs, are analyzed, three solutions are proposed to mitigate the effects of the penetration of the EVs in the grid. They are defined as Scenarios 2, 3 and 4. Scenario 3 includes a control system for EV charging based on a threshold for the maximum voltage drops allowed in the grid. In Scenario 2, a 4-branch D-FACTS is connected to the grid for current balancing. Finally, Scenario 5 combines both solutions, D-STATCOM and the controlled charging system.