LOAD CURVE ESTIMATE FOR ELECTRIC VEHICLE CHARGING INFRASTRUCTURE: A MULTIDISCIPLINARY MODEL
The vehicle electrification is a contemporary phenomenon and means gradually replacing the motor source of the most diverse modes of transport. However, the high cost of electric vehicles (EVs) compared to conventional combustion vehicles, in addition to the lack of charging infrastructure, are impeding factors. Furthermore, despite the many advantages, high EV penetration causes problems in the power distribution network: it worsens quality indices, causes voltage fluctuations, increases harmonic distortion, among others. However, it is in the context of planning the distribution system that the contribution of this thesis is located. Faced with the inevitable, it is necessary to consider the possibility of high simultaneity in the use of the charging infrastructure, which may result in the need for reinforcements in the network. If, on the one hand, there are barriers to the diffusion of EVs, on the other hand, due to the presence of charging stations, their geographic location and the amount of energy withdrawn from the electrical grid, they also pose challenges for planners. EV loading features a peculiar type of load with unique behavior and still unknown to planners. Measurement campaigns are not possible in this case, as the fleet and charging infrastructure are not yet consolidated. For this reason, it is extremely difficult to predict the behavior of demand at a time when penetration is still low or non-existent in many places, with little or no measurement available. Thus, this thesis aims to contribute in this area, proposing a model that estimates demand curves for the charging infrastructure and identifies, graphically and spatially, any needs for reinforcements in the electrical network, showing the periods of peak demand throughout a typical day.