Probabilistic Energy Management Strategy for EV Charging Stations Using Randomized Algorithms

Electric vehicle charging stations (EVCSs) come along with great challenges for the power grid due to their highly uncertain load characteristic. This is particularly the case for charging stations located in nonresidential areas, such as commercial centers, company sites, or car-rental stations. For a safe and sustainable operation of the power grid, distribution system operators require reliable load forecasts of such charging stations. In this brief, a robust EVCS management strategy is proposed, which provides a day-ahead upper limit profile of the EVCS's power consumption. In real time, this upper limit profile is strictly respected while guaranteeing-at a configurable probability-the Quality of Service. The strategy is based on randomized algorithms and relies on a statistic occupancy model of the EVCS while not requiring any online forecasts of each EVs' arrival and departure schedules. In a case study based on statistic data, which has been provided by the Euref Campus in Berlin, the feasibility and relevance of the proposed approach are demonstrated.