Charging optimization for electric vehicles in large Park & Ride areas

Smart mobility can be achieved through the logistic and energy optimization of multimodal transportation systems where electric vehicles (EVs) play an important role. Suitable locations to realize this integration are suburbs of metropolitan areas of large cities where Park & Ride (P&R) facilities permit public transport connections with private mobility. The paper presents the application of a linear programming optimization algorithm to a P&R equipped with charging stations. The initial state of charge of every EV and the park occupancy have been randomly selected according to real mobility scenarios. Thus, the effectiveness of the algorithm has been tested comparing the obtained optimal load profile of the P&R facility with the non-optimal one. It has been proved that the maximum power requested by the P&R can be dramatically reduced by optimizing the recharge. This leads to a downsizing of the distribution devices (e.g., power transformer) and a significant increase in efficiency.