A load model for EV parking lots

In the next years, electric mobility will be one of the issues electric utilities will have to face. The detailed modeling of the electric load generated by the presence of Electric Vehicles, EV, parking lots will be essential to simulate the different working conditions of new distribution systems. Also the detailed modeling will allow to deduce technical and economical aspects, allowing Distribution Systems Operators to devise the right incentives for EV customers. Such as, or maybe more than, residential loading the EV loading is strongly variable because it is connected to the human behavior, the modeling thus has to include stochastic terms. Moreover, to get realistic load profile for electric mobility, it is essential to consider the social and economical aspects connected to the market penetration of the different models of EVs [1]. This implies the recourse to a Montecarlo approach for simulating the EV load profile. Costs of different types EVs will be a crucial aspect ruling this phenomenon. Habits of the typical customer of each of the considered models will in turn affect recharge start time. In this paper, based on realistic data available from studies carried out in the field, a load model for electrical vehicles parking lots is detailed. The parking lot can be composed by different types of vehicles and namely: FEV (Full Electric Vehicles,), PHEV (Partially Hybrid Electric Vehicle), EREV (Extended Range Electric Vehicles). The model of each type of vehicle is characterized by a driving range and a battery size. Moreover batteries are modeled using the Peukert’s law for lead acid batteries, which is typically not considered in statistical modeling. Moreover the use of the vehicle (domestic, professional) influences the distance covered each day and thus the State of Charge of the vehicle when it is connected to the recharge station. In the paper, the probabilistic model used to simulate a generic EV parking lot impact on a distribution grid is outlined; it considers also smart and unmanaged charging modes.