Power allocation to a network of charging stations based on network tomography monitoring

There is a strong push to increase the electrification of the transportation sector, in order to reduce emissions and dependence on fossil fuels. However, a key component would be the deployment of a network of charging stations, so as to alleviate range-anxiety for electric vehicle drivers. On the other hand, power allocation from the grid to such a network needs to be carefully designed so as to avoid spikes that could lead to grid instability. In this paper, we examine a network of charging stations equipped with an energy storage device. We also introduce a monitoring scheme, which coupled with network tomography techniques estimates online from limited measurements vehicle traffic intensity rates and adjust power to the stations accordingly. Of note, the required communications and computational cost are minimal compared to schemes that engage the drivers of the vehicles. The proposed allocation scheme is illustrated through a simulation study, whose key parameters are calibrated from a real data set of bus movements in the Seattle area. The results indicate that the scheme is promising and offers significant gains in performance.